title_s
stringlengths 2
79
| title_dl
stringlengths 0
200
| source_url
stringlengths 13
64
| authors
listlengths 0
10
| snippet_s
stringlengths 0
291
| text
stringlengths 21
100k
| date
timestamp[ns]date 1926-02-14 00:00:00
2030-07-14 00:00:00
| publish_date_dl
stringlengths 0
10
| url
stringlengths 15
590
| matches
listlengths 1
278
|
|---|---|---|---|---|---|---|---|---|---|
CCM TRAININGS - Newmark J-School
|
Newmark J-School
|
https://www.journalism.cuny.edu
|
[
"Newmark J-School"
] |
If you have any suggestions for trainings, please let us know at [email protected]. ... AI for SEO can dramatically increase your visibility, grow ...
|
Whether you're a newsroom of one or part of a larger ethnic media collective, learning to leverage AI for SEO can dramatically increase your visibility, grow your audience, and ensure your brand ranks in search. With shrinking newsrooms and rising automation, mastering AI-driven SEO is no longer optional — it's essential for survival and growth.
| 2025-06-25T00:00:00 |
https://www.journalism.cuny.edu/centers/center-community-media/ccm-trainings/
|
[
{
"date": "2025/06/25",
"position": 82,
"query": "AI journalism"
}
] |
|
AI layoffs pose risk: Build strength, not weakness
|
AI layoffs pose risk: Build strength, not weakness
|
https://hrzone.com
|
[
"Quentin Millington",
"Read More Quentin Millington",
"Susan Bright",
"Kate Palmer",
"Becky Norman",
"Paul O Donnell"
] |
Here, Quentin Millington of Marble Brook considers four ways leaders can ensure artificial intelligence strengthens – rather than weakens – their team's value.
|
Let us resist scaremongering and the bashing of company executives. Of the 40 to 55,000 job losses planned for the decade and announced by former BT Group chief Philip Jansen in 2023, the roll-out of Full Fibre accounted for over half. Some 10,000 layoffs were to come from digitisation and automation.
Still, the claim made to the Financial Times earlier this month by Jansen’s successor Allison Kirkby, that advances in artificial intelligence (AI) might by 2030 allow the telecoms giant to be “even smaller”, gives pause for thought.
Kirkby’s view that the group’s original ambitions “did not reflect the full potential of AI” shows how the technology is disrupting operations across the sector. Her words also raise general questions about how AI is recasting the lives of employees, customer experiences and society at large.
AI is no panacea
Thinking about the redundancies that AI is now causing across many industries, what is the full potential of AI? Many corporate decision-makers remain unsure.
Research by Orgvue suggests that over half of companies that fired people in favour of AI now regret the decision. Gartner predicts that by 2027 many businesses will shelve their plans to reduce customer-facing teams given how ‘agent-less’ staffing initiatives have failed to meet expectations.
Whilst Silicon Valley bullies, blackmails and bribes the world to jump on its bandwagon of artificial intelligence, executive teams are discovering – many to their cost and embarrassment – that AI is no panacea for the challenges of good performance.
The value that employees bring is complex and not easily quantified.
Four practical ways to make sense of AI
How, then, can organisations avoid the pitfalls of hasty implementation and instead make the technology work for them and their stakeholders?
1. Clarify your vision of ‘good’
Without doubt, AI is a force for disruptive change. Whilst we know what we are moving away from – our present circumstances – how clear are we on what we are moving toward? When not guided by a coherent vision of the future, AI strategies will be rudderless, ineffective or downright harmful.
A first step is to describe what ‘good’ looks like, by stating what your AI ambitions mean, in truth, for the workplace, employees’ jobs and lives, customers, and wider society. It is also important to explain what will be lost as the future unfolds. If diverse stakeholders cannot agree that your picture is enriching, then the plans may be unsound.
2. Think value, not cost
Silicon Valley’s AI discourse is dominated by the rhetoric of efficiency, speed and cost. But such strategies rarely yield long-term advantage. Worse, powered by AI, the relentless drive for efficiency risks creating workplaces, businesses and whole societies stripped of richness and meaning: few people want to be surrounded by bots.
Spreadsheets will always favour AI over human resources, so cost metrics skew the conversation. Instead, explore how AI both adds to, and subtracts from, value the business exists to create.
Trade-offs are a factor in this decision-making process: to illustrate, redundancies ease the financials yet mean a loss for individuals, their families and society. Where is the gain for such stakeholders that offsets a firm’s “opportunity” to be smaller?
3. Automate tasks, don’t replace people
The value that employees bring is complex and not easily quantified. Consider, for example, the hotel doorman, whose role is not simply to open doors but to champion the human experiences that guests appreciate; this ‘invisible’ responsibility secures rack rates and repeat custom.
Competitors can replicate the work of your bots and, unlike the contributions of human employees, AI outputs bring neither meaning nor stickiness to relationships with customers and employees. As such, questions about replacing jobs likely miss hidden value and are almost certainly premature.
Ask colleagues and customers, rather, what tasks they find tedious and would like to automate. This helps secure buy-in and reveals practical ways forward.
The world cannot cherry-pick the upside of cost-efficiency and neglect AI’s impact on employees.
4. Let your AI strategy evolve
Decisions made about AI today will not suffice for the long term: workplaces are complex, roles evolve, people grow, markets shift and appetites change. Technology also advances at pace. We cannot know, as Kirkby intimates, the full potential – or, let us add, the full harm – of AI.
Small steps reveal the surest path to beneficial use of new technology. Again, involve stakeholders in a dialogue, not a one-off research exercise, about how automation may be used to augment value.
The important thing during early disruption is to turn the corner, as we call it, and give everyone a more assured view of the future, which is as yet unknown. Learn from experience as you go along.
Call for leadership strength
The world cannot cherry-pick the upside of cost-efficiency and neglect AI’s impact on employees, customers or (especially for large firms) society. Thoughtful executive teams will bring intelligence, empathy and care to think through consequences, relate to people and make sound choices.
A friend of mine who runs technology for a global bank last week said, “Most AI strategies are confidently designed on a spreadsheet, and that’s a disaster for everyone”. No one can make full sense of AI in the areas above, for definitive answers are impossible. What matters is that we ask the right questions.
And as the world grapples with this complex yet vital reality, I wish for Kirkby – and her peers across global industry – imagination, courage and, not least, luck, as they shoulder the burden to create value from AI.
| 2025-06-25T00:00:00 |
2025/06/25
|
https://hrzone.com/ai-layoffs-pose-risk-build-strength-not-weakness/
|
[
{
"date": "2025/06/25",
"position": 34,
"query": "AI layoffs"
}
] |
ChatGPT use among Americans roughly doubled since 2023
|
34% of U.S. adults have used ChatGPT, about double the share in 2023
|
https://www.pewresearch.org
|
[
"Olivia Sidoti",
"Colleen Mcclain",
".Wp-Block-Prc-Block-Bylines-Display Background Inherit Box-Sizing Inherit Color Inherit Color Var --Wp--Preset--Color--Text-Color",
"Font-Family Var --Wp--Preset--Font-Family--Sans-Serif",
"Font-Size Font-Weight Gap Important Line-Height",
"Margin-Bottom Text-Transform Uppercase .Wp-Block-Prc-Block-Bylines-Display A Text-Decoration None Important .Wp-Block-Prc-Block-Bylines-Display A Hover Text-Decoration Underline Important .Wp-Block-Prc-Block-Bylines-Display .Prc-Platform-Staff-Bylines__Separator Margin-Left",
".Wp-Block-Prc-Block-Bylines-Query Background Inherit Color Inherit"
] |
In two years, the share of employed adults who say they use ChatGPT for work has risen by 20 percentage points to 28%. That includes an 8-point increase since ...
|
The share of Americans who have used ChatGPT, an AI chatbot released in November 2022, has roughly doubled since summer 2023. Today, 34% of U.S. adults say they have ever used ChatGPT, according to a Pew Research Center survey. That includes a 58% majority of adults under 30.
Still, 66% of Americans have not used the chatbot, including 20% who say they’ve heard nothing about it.
Below, we explore the following questions:
How we did this Pew Research Center conducted this analysis to understand Americans’ use of ChatGPT. For this analysis, we surveyed 5,123 U.S. adults from Feb. 24 to March 2, 2025. Everyone who took part in this survey is a member of the Center’s American Trends Panel (ATP), a group of people recruited through national, random sampling of residential addresses who have agreed to take surveys regularly. This kind of recruitment gives nearly all U.S. adults a chance of selection. Interviews were conducted either online or by telephone with a live interviewer. The survey is weighted to be representative of the U.S. adult population by gender, race, ethnicity, partisan affiliation, education and other factors. Read more about the ATP’s methodology. Here are the questions used for this analysis, the topline and the survey methodology.
Who has used ChatGPT?
Use of ChatGPT is up across age groups and education levels, but some groups remain more likely than others to have used it.
Differences by age
As in previous years, young adults stand out in their ChatGPT use. Today, 58% of adults under 30 say they have used it, up from 43% in 2024 and 33% in 2023. While use is rising in older age groups as well, they remain less likely to have used ChatGPT:
41% of adults ages 30 to 49 have used it.
25% of those 50 to 64 say the same.
10% of those 65 and older report ever using ChatGPT.
Differences by education
Adults with higher levels of formal education are more likely than those with less education to have used ChatGPT. About half of those with a bachelor’s degree only (51%) or a postgraduate degree (52%) say they have used ChatGPT, compared with smaller shares of those with some college experience (33%) or a high school degree or less education (18%).
How have Americans used ChatGPT?
Since March 2023, we’ve also asked about three ways people might use ChatGPT: for work, to learn something new or for entertainment. We see growth in all three areas.
In two years, the share of employed adults who say they use ChatGPT for work has risen by 20 percentage points to 28%. That includes an 8-point increase since last year.
Other Center research shows workers have mixed feelings about its use and expect it to have a major impact on jobs.
Looking at other use cases for ChatGPT among U.S. adults overall:
26% have used it for learning, up from 8% in March 2023.
up from 8% in March 2023. 22% have used it for entertainment, up from 11%.
Differences by age
Use of ChatGPT for these reasons has risen since March 2023 across age groups. But younger adults are more likely than older adults to use ChatGPT in these ways. For example, 38% of employed adults ages 18 to 29 say they have used ChatGPT on the job. This compares with:
30% of those ages 30 to 49
18% of those 50 and older
Some 46% of all adults under 30 have used it to learn something new. And 42% have used it for entertainment.
Still, some older adults have used ChatGPT in these ways. About three-in-ten adults ages 30 to 49 say they’ve ever used the chatbot for learning and entertainment. The share of adults 50 or older who say the same drops further.
Differences by education
Adults with higher levels of formal education also stand out in using ChatGPT at work. Some 45% of employed adults with a postgraduate degree say they have used it this way, compared with:
36% of those with a bachelor’s degree
25% of those with some college experience
17% of those with a high school education or less
Among all U.S. adults, those with a bachelor’s degree only (34%) or a postgraduate degree (39%) are the most likely to use the chatbot for learning.
How aware are Americans of ChatGPT?
Awareness of ChatGPT has risen over time: When we first asked about it in March 2023, 58% said they had heard at least a little about it. Now, most Americans – 79% – have heard at least a little about it, including 34% who have heard a lot about it.
Differences by age
Majorities of adults of all ages have heard about the chatbot. But adults under 30 stand out for hearing a lot about it – 53% say this, compared with 15% of those 65 and older.
Differences by education
Regardless of education level, majorities of adults have heard at least a little about ChatGPT. But about half of adults with a postgraduate degree say they’ve heard a lot about it. That compares with 19% of those with a high school degree or less education.
Note: This is an update of a post originally published on March 26, 2024. Here are the questions used for this analysis, the topline and the survey methodology.
| 2025-06-25T00:00:00 |
2025/06/25
|
https://www.pewresearch.org/short-reads/2025/06/25/34-of-us-adults-have-used-chatgpt-about-double-the-share-in-2023/
|
[
{
"date": "2025/06/25",
"position": 1,
"query": "ChatGPT employment impact"
}
] |
White‑Collar Job Losses Rise, But Don't Blame ChatGPT
|
White‑Collar Job Losses Rise, But Don’t Blame ChatGPT
|
https://www.aol.com
|
[
"Aol Staff",
"Joe Riley",
"June",
"At Am"
] |
Employees that take advantage of the latest AI tools reported a 40% boost in their productivity, according to a new report from freelancing platform Upwork. C- ...
|
Over the last year, it's been hard to open a news app or scroll social media without seeing some headline claiming artificial intelligence is gunning for your job. If you've been laid off from a desk job recently—or know someone who has—it's easy to jump to conclusions. But while AI is certainly reshaping workplaces, the real reasons behind the white-collar job cuts of 2024 and 2025 have more to do with corporate strategy, economic tightening, and good old-fashioned belt-tightening than a chatbot coming for your paycheck.
After all, ChatGPT did not tell your boss to fire you. It didn't push the layoff button or delete your role from the org chart. What's really happening is more complicated and a lot more human.
The Layoff Landscape: It's Not Just Tech
Image via Unsplash/Greg Bulla
White-collar job cuts aren't isolated to Silicon Valley, although big tech has definitely been setting the tone. Microsoft, Google, Amazon, and Meta all made headlines this year for laying off thousands of employees, many of them in high-paying roles like software development, sales, human resources, and even middle management. But they weren't the only ones. Corporations across industries, from media to finance to FMCG, followed suit, often without much public explanation.
According to the U.S. Bureau of Labor Statistics, professional and business services, a sector that typically houses white-collar jobs, saw a dip in hiring activity in both 2024 and early 2025. In May alone, the sector reported a -0.4% decline in job growth. Meanwhile, fields like healthcare and construction saw solid gains, with healthcare alone adding 62,000 jobs.
So while some corners of the job market are humming along, the corporate cubicle crowd is feeling the pinch.
What's Actually Behind the Layoffs
For now, economists who study labor trends aren't placing the blame squarely on AI. Cory Stahle, an economist with job search site Indeed, put it plainly: "This is more of an economic story and less of an AI disruption story, at least so far." Alí Bustamante, from the Roosevelt Institute, agreed, noting that job creation in white-collar roles has been slowing down for years, long before ChatGPT became a household name.
In other words, the slowdown was already in motion. What we're seeing now is a mix of companies adjusting to post-pandemic growth bubbles, trying to cut costs after overhiring in 2021 and 2022, and responding to investor pressure.
The Middle Manager Problem
One of the more visible targets of recent layoffs is middle management. A trend that started quietly in 2023 has picked up steam. Meta CEO Mark Zuckerberg even commented on it directly, saying he didn't want "managers managing managers managing managers." At companies like Microsoft, Salesforce, and Amazon, mid-level leaders have been quietly thinned out, many replaced by smaller, more autonomous teams with flatter reporting structures.
Data from McKinsey shows that nearly half of middle managers spend less than 25% of their time actually managing people. The rest is tied up in reporting, meetings, and process-heavy tasks that aren't as essential in a streamlined setup. This has made them an easy target during restructuring, and not because AI is writing their performance reviews.
Yes, AI Is In the Room—But It's Not Running It
Image via Freepik/rawpixel.com
That's not to say AI hasn't played a role at all. It's just not the boogeyman it's made out to be. Companies like Amazon and Klarna have been vocal about how they're using generative AI to increase efficiency, and in some cases, reduce headcount. Amazon CEO Andy Jassy has spoken about using smaller teams powered by AI tools. Klarna's CEO noted that their company has trimmed its workforce by 40%, thanks in part to AI adoption.
AI tools can now handle tasks like data entry, initial drafts of written content, and basic customer support responses. That's a big help for teams stretched thin. Still, these tools don't manage projects, build trust with clients, or set strategy. They help with the grunt work, not the big picture.
A 2024 report from Indeed backs this up. Researchers found that out of more than 2,800 unique job skills analyzed, fewer than 1% were considered "very likely" to be fully replaced by generative AI. Over two-thirds of those skills were labeled "very unlikely" or "unlikely" to be automated anytime soon.
Specialization, Not Automation, Is the Bigger Deal
A lesser-discussed reason behind the white-collar crunch is the growing emphasis on specialization. Job postings increasingly call for experience with specific tools, niche certifications, or expertise in emerging fields like AI ethics or data science.
The hiring slowdown is also about roles sitting unfilled because companies don't want to train up generalists anymore. As one tech recruiter bluntly put it, "Nobody wants to hire someone they have to train for six months." This shift means many well-qualified workers are now competing for fewer jobs that require much narrower skill sets.
While some firms are still shelling out massive salaries to lure elite candidates—like Meta, which offers multimillion-dollar packages to AI researchers—those roles are the exception, not the rule. For the average corporate employee, the path forward looks a lot more competitive.
There's also a psychological shift happening behind the scenes. Post-pandemic optimism gave way to a more cautious mindset as interest rates rose and market growth slowed. Companies that once prioritized "growth at all costs" are now pivoting to efficiency and profitability.
That means fewer new roles, slower hiring, and yes, some job cuts that would've been unthinkable just a couple of years ago.
So, What Now?
If you're sitting in a white-collar job that feels suddenly less stable, you're not imagining things. But you're also not being replaced by a chatbot. The current wave of job losses stems from a tangle of economic caution, company restructuring, and a shift toward specialized hiring.
In fact, generative AI tools like ChatGPT are still limited by what they don't know. They can summarize, automate, and suggest, but they can't replace decision-making, emotional intelligence, or original thought. Not yet—and possibly not for a long time.
If anything, the real challenge might be adjusting to the pace of change in corporate culture and keeping your skills fresh enough to ride it out.
| 2025-06-25T00:00:00 |
https://www.aol.com/white-collar-job-losses-rise-130048679.html
|
[
{
"date": "2025/06/25",
"position": 34,
"query": "ChatGPT employment impact"
}
] |
|
ChatGPT: Will AI Replace Lawyers?
|
Will ChatGPT Replace Lawyers?
|
https://www.clio.com
|
[
"Kate Rattray",
".Wp-Block-Co-Authors-Plus-Coauthors.Is-Layout-Flow",
"Class",
"Wp-Block-Co-Authors-Plus",
"Display Inline",
".Wp-Block-Co-Authors-Plus-Avatar",
"Where Img",
"Height Auto Max-Width",
"Vertical-Align Bottom .Wp-Block-Co-Authors-Plus-Coauthors.Is-Layout-Flow .Wp-Block-Co-Authors-Plus-Avatar",
"Vertical-Align Middle .Wp-Block-Co-Authors-Plus-Avatar Is .Alignleft .Alignright"
] |
... ChatGPT, to allow firms to perform tasks like high-level drafting work. With ... impact and overall volume of casework and revenue collection. In ...
|
5 minutes read
These days, news sites are flooded with articles about ChatGPT, the AI bot disrupting industries from programming to law.
And, with all the buzz, legal professionals and clients are asking: will AI replace lawyers? And how can lawyers use AI?
Below, we’ll introduce you to OpenAI—the artificial intelligence company that developed ChatGPT—along with the notorious chatbot and what its development means for the legal profession.
And, if you’re just diving into the world of legal AI, check out Clio Duo—Clio’s AI solution, designed specifically for law firms and built on our platform-wide principle of protecting sensitive legal data.
What is OpenAI?
OpenAI is an artificial intelligence (AI) research and development company creating “highly autonomous systems that outperform humans at most economically valuable work.” Tools like ChatGPT are free to use—though, on occasion demand may be too high for you to access it.
What is ChatGPT?
ChatGPT is an AI-powered chatbot from OpenAI that responds to open-ended text queries with paragraphs of text-written answers. It was trained through reinforcement learning from human feedback. During this process, human AI trainers would converse as a user and an AI assistant, then rank chatbot responses to teach the chatbot how to respond appropriately.
ChatGPT recently released ChatGPT 4o, which understands images, can browse the web, and speaks more languages. This model brings many of the paid capabilities to the free plan, which makes it an excellent opportunity to test out what’s possible without needing to pay. If you’re looking for additional capabilities, you can subscribe to ChatGPT Plus for $20 per month. ChatGPT Plus offers priority access even when demand is high, faster response times, and priority access to new features.
And, anticipation is rising for OpenAI’s upcoming model and the latest version of ChatGPT: ChatGPT-5. While OpenAI has not yet provided a release date, there is speculation that ChatGPT-5 will be released at the end of 2024.
How do you use ChatGPT?
ChatGPT is relatively simple to use—all you have to do is type in your request on the ChatGPT website or the WebChatGPT Chrome plugin. And if you’re working from your iPhone, you can access ChatGPT via the ChatGPT iOS app.
For instance, you can ask the tool to write a poem, answer a question in Shakespearean English, or solve complex math problems.
From there, you’ll get a unique, surprisingly accurate answer on the same website.
How Lawyers Use ChatGPT
ChatGPT has transitioned from its initial research phase to being deployed in various applications and platforms, advancements and improvements are always ongoing. This leaves legal professionals naturally asking: how can lawyers use ChatGPT?
While AI might not imminently replace lawyers, there’s no doubt that ChatGPT presents opportunities for law firms. From creating legal marketing content to drafting legal documents with the right prompts, the benefits of automating your legal writing with AI seem endless.
What’s more, law firm’s are already attempting to leverage ChatGPT technology to support legal clients. Take, for example, Harvey AI—an AI tool designed specifically for legal work that is already showing promising results. With these developments, it’s clear that AI has a role to play in the legal system—though what role that is exactly remains to be seen.
In fact, according to our latest Legal Trends Report, the legal industry is increasingly adopting a variety of AI-powered technology to enhance efficiency and accuracy, with the top solutions being generic non-legal AI tools, such as ChatGPT, to allow firms to perform tasks like high-level drafting work.
With Clio Duo, instantly access information from case files, draft client communications, extract key details from documents, get smart recommendations on where to prioritize your time, receive suggestions for unlogged work, and more to improve your firm’s productivity and efficiency–check out the AI powers of Clio Duo today!
Challenges ChatGPT poses for lawyers
Beyond technical limitations, like using electronic devices in the courtroom, ChatGPT faces additional hurdles in the legal sphere.
For one, this technology is still in development. And, as eerily accurate as its responses may be, ChatGPT is not a human lawyer.
Nor, it’s not always accurate—users have reported receiving incorrect information from the chatbot-in-training. ChatGPT only has access to information up to early 2022, which is partially responsible for inaccuracies. But competitors that crawl the web in real-time, like Google Bard, also risk pulling inaccurate information published online.
Lacking the nuance necessary to create consistently accurate responses, let alone complex legal arguments, it’s safe to say that—at this stage, at least—ChatGPT is not in a position to replace lawyers.
Additionally, a lawyer’s ethical obligations will always take precedence over convenience.
Not only are there ethical considerations in using AI to argue your cases for you, but issues of security, client privacy, and privilege can also arise through the transmission of data between your firm and ChatGPT. As the chatbot stores personal and conversation data, lawyers must familiarize themselves with ChatGPT’s Privacy Policy and Terms of Use before using the service.
Embracing technology—responsibly—in your law firm
While we’ve highlighted some of the ethical hurdles of how lawyers can use ChatGPT in their law firm, we also know that enthusiastic adoption of technology positively affects a law firm’s business performance. As uncovered in our Legal Trends Report research, the adoption of multiple technologies has a compounding effect on business performance both in terms of impact and overall volume of casework and revenue collection.
In essence, adopting technologies that streamline routine legal tasks, save time, and help you to imprint your expertise on tasks that matter most is a win for any law firm. But it’s critical to assess and implement technology responsibly to ensure you’re meeting your ethical obligations and protecting your client’s interests.
One way to get started is by completing Clio’s legal AI training course—a free, self-paced program designed to help legal professionals adopt AI tools effectively and ethically.
Will AI replace lawyers? Final thoughts
Only time will tell what role AI tools like ChatGPT may—or may not—play in the legal profession.
Still, one thing’s for certain: adopting technology responsibly can help save time managing your law firm and has a measurable impact on law firm performance.
While AI tools like ChatGPT have the potential to change the way lawyers work, that doesn’t mean that it will replace them. Lawyers may harness AI as a tool to help them work faster and more effectively—but they’ll still ultimately be responsible for completing legal work and practicing law. With AI, tasks like e-discovery, drafting legal documents, and conducting due diligence can become less time-consuming, which can, in turn, free up lawyers time to focus on legal work that requires a human touch.
Consider, too, the role that legal-specific AI tools can play in ensuring that your law firm can responsibly adopt AI technology. For example, Clio Duo, our AI solution, can help law firms harness the power of AI while protecting sensitive client data and adhering to the highest security standards. Book your free demo of Clio Duo today.
Share article
| 2023-01-31T00:00:00 |
2023/01/31
|
https://www.clio.com/blog/chat-gpt-lawyers/
|
[
{
"date": "2025/06/25",
"position": 100,
"query": "ChatGPT employment impact"
}
] |
The Batch | DeepLearning.AI | AI News & Insights
|
AI News & Insights
|
https://www.deeplearning.ai
|
[] |
The Batch AI News and Insights: AI's ability to make tasks not just cheaper, but also faster, is underrated in its importance in creating business value.
|
Jun 18, 2025
Apple Sharpens Its GenAI Profile, Hollywood Joins Copyright Fight, OpenAI Ups Reasoning Quotient, LLM Rights Historical Wrongs
The Batch AI News and Insights: One of the most effective things the U.S. or any other nation can do to ensure its competitiveness in AI is to welcome high-skilled immigration and international students who have the potential to become high-skilled.
| 2025-06-25T00:00:00 |
https://www.deeplearning.ai/the-batch/
|
[
{
"date": "2025/06/25",
"position": 82,
"query": "artificial intelligence journalism"
}
] |
|
Informatica CEO: How to future-proof your career in the age ...
|
Informatica CEO: How to future-proof your career in the age of AI
|
https://fortune.com
|
[
"Amit Walia"
] |
Employees need to raise their AI IQ and exercise more left-brain thinking, says Amit Walia, to survive workplace upheaval.
|
There’s a lively debate underway about the impact artificial intelligence will have on the workplace, from worries about a “job apocalypse” at one extreme to a shorter workweek at the other. It’s too early to know how it will play out, but one thing is clear: AI will require most everyone to learn new skills—and quickly.
Retraining, reskilling, upskilling, and AI-aware professional development are the new norm in many jobs, from entry-level to senior executives. Maybe I shouldn’t say “new norm” because workers have been down this career path many times before. When telephone operators were displaced by switching systems 100 years ago, they branched into new areas like directory assistance and customer service. Similar transitions happened in printing plants, branch banks, and elsewhere as new technologies transformed the workplace.
What is new is the dizzying pace of change with AI and the sense that this time the stakes are higher. So don’t be surprised by it; be ready.
Nurture the technologist within
A good starting point for many people is to raise their AI IQ by getting hands-on experience with generative-AI tools like ChatGPT, Gemini, Claude, or Perplexity. I recently tinkered with text-to-image creation, and I’ve experimented with using gen AI as a personal coach. Once we’ve chalked up these types of rudimentary learnings, the next steps into things like agentic AI will feel more familiar.
Another suggestion: Try to foresee where and how AI will impact your profession and industry. Design and content creation are already in the throes of AI disruption. Customer support is another major area of activity. Likewise in manufacturing, financial services, and health care. The more we can anticipate these AI-driven changes, the better prepared we can be.
Today’s college graduates may feel especially vulnerable, having spent the past few years learning a vocation only to confront a topsy-turvy job market. One way to adapt is to embrace the principle of continuous learning. For Gen Z, who are digital natives, that may mean becoming early adopters of AI technologies, which can give them an edge.
Of course, the challenge of AI readiness isn’t limited to entry-level positions. Across the board, skills for “AI-exposed” jobs are changing 66% faster than other jobs, according to PwC. So even experienced workers and managers need to think about ways to advance their AI know-how. And here’s an upside: AI-powered jobs pay more.
Bite-sized learning breaks
How do people stay sharp in the AI-driven workplace? Don’t underestimate the power of left-brain thinking. Valuable skills include data fluency, AI literacy, complex problem solving, and critical thinking, according to Harvard University’s Division of Continuing Education.
AI certifications can be a way to come up to speed on complex technologies such as APIs, machine learning, language models, and frameworks. However, not everyone has the time or budget for these programs. Harvard recommends self-directed development through online learning, project-based learning, and even “micro-learning” with bite-sized content during breaks or between tasks.
At Informatica, we’re doing everything we can to help employees quickly ascend the AI learning curve. Our IT organization developed an AI literacy class that has been widely attended. That’s given us a common vocabulary, so terms like LangChain (an open-source framework), retrieval augmented generation (RAG), and vectors (an emerging data type) are more widely understood across teams and departments.
We also created an AI Center of Excellence to establish best practices and synergies across departments and ensure that legal, privacy, and security issues are top of mind for everyone.
Human skills still matter
As these first-hand experiences show, AI learning and skills development happen best when employees take some of the responsibility on themselves, yet within an organizational culture that values, encourages, and provides career-building opportunities.
This imperative—for both individual and business development—is here and now. LinkedIn, based on analysis of its members, determined that 70% of the skills in most jobs will change by 2030, driven by AI.
That doesn’t mean we all need advanced degrees in AI. LinkedIn also found that “human skills”—things like curiosity, creativity, communication, and courage—may matter the most in today’s workplace.
Frankly, that’s wonderful to see because it signals that the future of work will be an eclectic mix of human skills and AI skills. So, while it’s important to recognize that we must raise our AI proficiencies, it’s equally vital that we bring our best versions of ourselves to work every day.
The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.
Read more:
| 2025-06-25T00:00:00 |
2025/06/25
|
https://fortune.com/2025/06/25/careers-ai-future-work/
|
[
{
"date": "2025/06/25",
"position": 40,
"query": "future of work AI"
}
] |
US Robot Density in Car Industry Ranks 7th Worldwide
|
US Robot Density in Car Industry Ranks 7th Worldwide
|
https://ifr.org
|
[
"Ifr International Federation Of Robotics"
] |
Automation allows manufacturers to nearshore production without sacrificing cost efficiency. 5 – Robots Addressing Labor Shortage. The global manufacturing ...
|
The World Robotics 2021 Industrial Robots report shows a record of 3 million industrial robots operating in factories around the world – an increase of 10%. Sales of new robots grew slightly at 0.5% despite the global pandemic, with 384,000 units shipped globally in 2020. This trend was dominated by the positive market developments in China, compensating the contractions of other markets. This is the third most successful year in history for the robotics industry, following 2018 and 2017.
“The economies in North America, Asia and Europe did not experience their Covid-19 low point at the same time,” says Milton Guerry, President of the International Federation of Robotics. “Order intake and production in the Chinese manufacturing industry began surging in the second quarter of 2020. The North American economy started to recover in the second half of 2020, and Europe followed suit a little later.”
“Global robot installations are expected to rebound strongly and grow by 13% to 435,000 units in 2021, thus exceeding the record level achieved in 2018,” reports Milton Guerry. “Installations in North America are expected to increase by 17% to almost 43,000 units. Installations in Europe are expected to grow by 8% to almost 73,000 units. Robot installations in Asia are expected to exceed the 300,000-unit mark and add 15% to the previous year’s result. Almost all Southeast Asian markets are expected to grow by double-digit rates in 2021.”
Asia, Europe and the Americas - overview
Asia remains the world’s largest market for industrial robots. 71% of all newly deployed robots in 2020 were installed in Asia (2019: 67%). Installations for the region´s largest adopter China grew strongly by 20% with 168,400 units shipped. This is the highest value ever recorded for a single country. The operational stock reached 943,223 units (+21%). The 1-million-unit mark will be broken in 2021. This high growth rate indicates the rapid speed of robotization in China.
Annual shipments by country © World Robotics
Japan remained second to China as the largest market for industrial robots, though the Japanese economy was hit hard by the Covid-19 pandemic: Sales declined by 23% in 2020 with 38,653 units installed. This was the second year of decline following a peak value of 55,240 units in 2018. In contrast to China, demand from the electronics industry and the automotive industry in Japan was weak. Japan’s operational stock was 374,000 units (+5%) in 2020.
The outlook for the fiscal year 2021 is positive with an expected GDP growth rate of 3.7%. The Japanese robotics market is expected to grow by 7% in 2021 and continue to do so by 5% in 2022. Independent of the domestic market for robotics, the major export destinations will secure demand for Japanese robotics. Even though a major share of production today takes place directly in China, 36% of the Japanese exports of robotics and automation technology were destined for China. Another 22% of the exports were shipped to the United States.
The Republic of Korea was the fourth largest robot market in terms of annual installations, following Japan, China and the US. Robot installations decreased by 7% to 30,506 units in 2020. The operational stock of robots was computed at 342,983 units (+6%).
The export-oriented economy has coped with the pandemic remarkably well so far. In 2020, GDP was down by just 1%, and for 2021 and 2022 strong GDP growth of +4% and +3% is expected. The electronics industry and the semiconductor industry, in particular, are investing heavily. An investment support program launched in May 2021, will further boost investment in machinery and equipment. The demand for robots both from the electronics industry as well as from the automotive suppliers is expected to grow substantially by 11% in 2021 and by 8% annually on average in the next years following.
Europe
Industrial robot installations in Europe were down by 8% to 67,700 units in 2020. This was the second year of decline, following a peak of 75,560 units in 2018. Demand from the automotive industry dropped by another 20%, while demand from the general industry was up by 14%.
Germany, which belongs to the five major robot markets in the world (China, Japan, USA, Korea, Germany) had a share of 33% of the total installations in Europe. Italy followed with 13% and France with 8%.
The number of installed robots in Germany remained at about 22,300 units in 2020. This is the third highest installation count ever - a remarkable result given the pandemic situation that dominated 2020. The German robotics industry is recovering, driven by strong overseas business. Robot demand in Germany is expected to grow slowly, mainly supported by demand for low-cost robots in the general industry and outside of manufacturing.
In the United Kingdom, industrial robot installations were up by 8% to 2,205 units. The automotive industry rose by 16% to 875 units - representing 40% of the installations in the UK. The food and beverage industry almost doubled their installations from 155 units in 2019 to 304 units in 2020 (+96%). The food and beverage industry had a high share of foreign workers, often from Eastern Europe, is facing a massive labor shortage. With continued Covid-19-related travel restrictions as one reason and Brexit another, the demand for robots in the United Kingdom is expected to grow strongly at two-digit percentage rates in 2021 and 2022. [struggling to connect] The modernization of the UK manufacturing industry will be boosted by a massive tax incentive. The newly installed 2,205 units in the UK are about ten times less than the shipments in Germany (22,302 units), about four times less than in Italy (8,525 units) and less than half the number in France (5,368 units).
North America
The USA is the largest industrial robot user in the Americas, with a share of 79% of the region´s total installations. It is followed by Mexico with 9% and Canada with 7%.
New installations in the United States slowed down by 8% in 2020. This was the second year of decline following eight years of growth. While the automotive industry demanded substantially fewer robots in 2020 (10,494 units, -19%), installations in the electrical/electronics industry grew by 7% to 3,710 units. The operational stock in the United States increased by 6% CAGR since 2015.
The overall expectations for the North American market are very positive. A strong recovery is currently in progress and the return to pre-crisis levels of industrial robot installations can be expected for 2021. Robot installations are expected to grow by +17% in 2021. A post-crisis boom will create additional growth at low double-digit rates 2022 and beyond.
Shipments by industries © World Robotics
Outlook
The “boom after crisis” is expected to fade slightly in 2022 on a global scale. From 2021 to 2024, average annual growth rates in the medium single-digit range are expected. Minor contractions may occur as a statistical effect, ‘catch-up’ occurs in 2022 or 2023. If this anomaly takes place, it will not break the overall growth trend. The notable mark of 500,000 units installed per year worldwide is expected to be reached in 2024.
World Robotics 2021 edition
Orders for World Robotics 2021 Industrial Robots and Service Robots reports can be placed online. Further downloads on the content are available here.
Video
FACTS ABOUT ROBOTS on our YouTube channel.
Downloads
Graphs, presentations and press releases on the German, Japanese, Chinese, Korean, US, UK, Swedish and Spanish/Brazilian/Latin American market are available below. All graphs are also part of the presentations.
Press Contact
Carsten Heer
phone +49 (0) 40 822 44 284
E-Mail: [email protected]
#WorldRobotics
| 2025-06-25T00:00:00 |
https://ifr.org/news
|
[
{
"date": "2025/06/25",
"position": 82,
"query": "job automation statistics"
}
] |
|
How AI is being used in the hiring process, and how job seekers can ...
|
How AI is being used in the hiring process, and how job seekers can get their foot in the door
|
https://www.wxyz.com
|
[
"Jolie Sherman"
] |
(WXYZ) — It's safe to say Artificial Intelligence is changing the way we live our lives, including how we apply for jobs.
|
(WXYZ) — It's safe to say Artificial Intelligence is changing the way we live our lives, including how we apply for jobs. That's because it's become a tool to build resumes and screen applications, affecting both job seekers and employers.
Watch Jolie's full story in the video player below
How AI is being used in the hiring process, and how job seekers can get their foot in the door
Chelsea Jordan will be the first to tell you that finding a well-paying job in metro Detroit has been difficult.
WXYZ
"The job search has been going on for about a year," she told me.
The mother from Inkster says she's applied for at least 100 jobs in the last 12 months and wasn't getting any calls. But that changed once she started using Artificial Intelligence to enhance her resume.
"I'm getting more interviews now than I was before I was using AI," Chelsea said.
And she's not alone: a recent study conducted by the recruiting agency, Kelly Services, shows that out of a thousand job seekers in the U.S., nearly 80 percent are using AI in the application process. Most of the job seekers are using it to build resumes and find openings, while others are using it to write cover letters and prepare for interviews.
But it's not just job seekers using AI, hiring managers are using it, too.
That same study found that out of roughly 1,000 managers in the U.S., 66 percent say their company uses AI to screen applications.
WXYZ
"They want to use AI to get things faster, look at resumes faster, interview faster, but I still want to make the decision," said Mark Saltrelli.
Mark, the vice president of engineering and recruiting at Kelly Services, says at the end of the day you still need to make sure you are who you say you are and be able to talk about your experience.
"To really differentiate yourself, you still need that people aspect," Mark said. "You still need to validate that you've done the job well, and others can refer you into it."
But Chelsea says sometimes the hardest part is getting past those automated screenings.
"It was how I was formatting it, and the terminology I was using," Chelsea said. It looks good in general, but for this specific job, if it's going to get through to a person, it has to say specific words. I guess it just opened my eyes up to, for a lack of a better term, the job search can be a game that you have to play, and I think that AI has helped me do that."
Where Your Voice Matters
| 2025-06-26T00:00:00 |
2025/06/26
|
https://www.wxyz.com/news/voices/how-ai-is-being-used-in-the-hiring-process-and-how-job-seekers-can-get-their-foot-in-the-door
|
[
{
"date": "2025/06/26",
"position": 62,
"query": "artificial intelligence hiring"
},
{
"date": "2025/06/26",
"position": 82,
"query": "AI hiring"
},
{
"date": "2025/06/26",
"position": 81,
"query": "AI hiring"
},
{
"date": "2025/06/26",
"position": 81,
"query": "AI hiring"
},
{
"date": "2025/06/26",
"position": 79,
"query": "AI hiring"
},
{
"date": "2025/06/26",
"position": 89,
"query": "AI hiring"
},
{
"date": "2025/06/26",
"position": 82,
"query": "AI hiring"
},
{
"date": "2025/06/26",
"position": 81,
"query": "AI hiring"
},
{
"date": "2025/06/26",
"position": 82,
"query": "AI hiring"
},
{
"date": "2025/06/26",
"position": 83,
"query": "AI hiring"
},
{
"date": "2025/06/26",
"position": 82,
"query": "AI hiring"
},
{
"date": "2025/06/26",
"position": 19,
"query": "artificial intelligence hiring"
}
] |
AI in Healthcare Statistics: Market Insights & Growth - Binariks
|
AI in Healthcare Statistics: 20+ Key Facts for 2025-2029
|
https://binariks.com
|
[
"Business Director",
"Healthcare Industry"
] |
The global AI in the healthcare market was valued at .69 billion in 2024 and is expected to grow at a CAGR of 38.5% from 2023 to 2033. The ...
|
Artificial Intelligence has a great demand in the healthcare industry. For now, 94% of healthcare providers, life science companies, and tech vendors use AI in some capacity. This number is crucial proof to demonstrate the benefits of AI in healthcare and how significant it is for the industry.
However, there are still some issues that are slowing down the adoption of AI in healthcare. One of them is the lack of experienced specialists, leading to development delays, mistakes, increased costs in healthcare. Healthcare providers turn to tech companies for expertise in adopting AI, and naturally, demand for such expertise makes competition among the latter highly intensive.
AI healthcare market overview
The global AI in the healthcare market was valued at .69 billion in 2024 and is expected to grow at a CAGR of 38.5% from 2023 to 2033. The healthcare AI market is experiencing a remarkable and significant surge in its growth and acceptance. Here are some facts about AI in healthcare:
Healthcare is considered the second-largest industry for AI in 2024.
North America dominates the market, accounting for over 54% of revenue as of 2024.
The use of AI-powered medical imaging technologies is a significant trend among healthtech companies, with 76% of all AI-enabled medical devices authorized for sale in the US being those used in radiology.
Medical businesses continue to grow and expand, so mergers and acquisitions are becoming very common. Larger players are acquiring smaller companies to enhance their AI capabilities or extend their market coverage.
The integration of AI with complementary technologies like robotics or blockchain promotes precision medicine and transforms healthcare delivery.
Generative AI-powered virtual assistants and chatbots are in high demand, with 47% of healthcare organizations already using or planning to implement them. These AI solutions can automate up to 30% of patient interactions, significantly reducing providers' administrative workload.
Take your software to new heights with AI and ML services Read more
AI healthcare market segmentation: by application
By application of AI in healthcare, the top segments dominating are Robot-Assisted Surgery, Clinical Trials, and Connected Machines. Cybersecurity, Dosage Error Reduction, and Diagnostics are developing slower.
AI-powered robots make surgical procedures more precise. Complicated surgeries in cardiovascular or neurology need absolute accuracy, and AI robotics can ensure it. AI algorithms are also changing clinical trials processes. The power of rapid data analysis at every stage of clinical trials makes them more accurate, cost-effective, and patient-centric.
Besides, AI has a crucial role in using connected machines in healthcare. AI integrates data from IoT devices and sensors into a single healthcare system. This gives an opportunity to gather, exchange, and analyze huge amounts of data.
To understand which therapeutic areas have most AI support, let's take a look at the FDA-approved list of AI-enabled applications. For now, FDA approved a total of 950 medical devices using AI, and radiology has 76% of them. This report shows us that radiological imaging has become very promising and usable in practice.
All the applications mentioned above highlight how AI is rapidly advancing across multiple facets of healthcare, from operating rooms to patient monitoring and diagnostics. Let's explore how AI is transforming each of these areas in more detail:
Robot-assisted surgery
AI is now a standard in cardiovascular, neurological, and orthopedic surgery. It minimizes human error and ensures extreme precision.
There is a rising trend of AI-enabled robotic systems entering outpatient surgery centers, reducing recovery time and operational costs. 53% of EU healthcare organizations stated they plan to use medical robotics by the end of 2025.
Clinical trials
AI is revolutionizing how trials are designed and managed. It optimizes recruitment, data analysis, and adaptive protocols. In particular, it is increasingly used in decentralized trials with AI for remote patient participation and real-time analytics.
Connected machines
AI integrates data from ICU monitors, wearable tech, and in-home sensors to support early intervention. Next-generation AI systems are now enabling predictive hospital asset management to reduce ICU overloads. 72% of EU healthcare organizations plan to use AI for patient monitoring.
Diagnostics (imaging)
Diagnostics is the most established area of AI use in healthcare. AI helps interpret X-rays, CT scans, and MRIs more quickly and accurately.
Regulatory agencies have recently fast-tracked approvals for multimodal AI imaging tools that combine various scan types.
45% of Americans view GenAI as helpful in interpreting medical tests, X-rays, and other diagnostic images.
Dosage error reduction
AI tools aim to reduce prescribing mistakes through automated dose checks and alerts. Integration with clinical decision support systems (CDSS) is improving prescription safety in pilot programs.
Cybersecurity
AI monitors network traffic and detects anomalies to protect sensitive patient data. According to statistics of AI in healthcare, 83% of US consumers view AI's potential for error as a barrier, and 86% state they are concerned about transparency.
As of May 2025, the US Food and Drug Administration (FDA) has authorized 950 AI/ML-enabled medical devices for marketing in the US. This information is available on the FDA's official AI/ML-Enabled Medical Devices list .
Radiology continues to be the leading field, with a significant number of these devices designed to assist in imaging and diagnostic processes.
Looking ahead:
Radiology will stay at the forefront, especially with real-time, multimodal imaging tools.
AI in diagnostics beyond imaging (e.g., pathology, genomics) is set to grow at 35% CAGR over 5 years.
over 5 years. Operational AI will become standard for scheduling, inventory, and billing.
AI healthcare market segmentation: by technology
Based on components, the global AI in the healthcare market can be divided into software, hardware, and services. The software segment has the largest share and is expected to have the fastest growth.
This segment includes Machine Learning platforms, Natural Language Processing (NLP) and text analysis tools, Deep Learning Platforms, Computer Vision, Speech and Audio Recognition, Integrated Development environments (IDEs) and AI frameworks. Global trend of digital transformation , and capabilities of AI software solutions made it the leading component in healthcare.
Finally, based on technology, the AI healthcare market can be divided into Machine Learning, Natural Language Processing (NLP), Computer Vision , and Context-Aware Computing. Machine Learning is a leader now, but NLP has the potential to be the market leader in the future. The AI in healthcare statistics shows the demand for analyzing human language data will soon be more than for images and contextual information.
Will adopting GenAI mark the next chapter for your business? Download our free whitepaper now to find out. Get the guide
4 drivers affecting rise of AI in healthcare
The growing amount of medical data: According to the DATCON index, the healthcare data explosion will exceed 10 trillion gigabytes in 2025. Now AI algorithms can help operate it and give important insights. Emerging global issues: COVID-19 has become a litmus test for identifying problems in healthcare. Medical AI can enable healthcare providers to do more with less. Moreover, it can revolutionize AI and the healthcare market and pay more attention to prediction than treatment. Population aging: With the increase in life expectancy, people need more medical help and care. AI-enabled technologies can help people to live healthier and longer lives. Lack of medical staff: With a shortage of medical workers, the duties and burden on existing employees increase. That leads to mistakes and negatively affects performance and patient care. AI can help automate routine tasks and give new opportunities for treatment.
How to become FHIR-compliant A detailed approach to FHIR implementation Download whitepaper
Regional analysis
North America has a dominant position in the healthcare artificial intelligence market. Healthcare companies in the USA have great support from the government. Moreover, the public and private sectors have built a coordinated collaboration and managed to adopt AI technologies earlier.
The second-largest region in the AI healthcare market is Europe. Germany, the United Kingdom, France, Spain, Ireland, Switzerland, and Belgium are key players in life sciences. They are focusing on R&D activity and biotechnology drug discovery.
Asia-Pacific region is a quickly growing market and is expected to register a CAGR of 8.5% by 2028. Because of the rising geriatric population, medical tourism, and the growing research activities, Asian countries accelerated the adoption of medical AI.
The healthcare artificial intelligence market in South America is focusing on developing Remote Patient Monitoring (RPM) and telehealth. The Middle East and Africa will grow more slowly than other regions. Their focus is AI-based telehealth services and increasing collaborations between healthcare facilities.
Tech giants in a competitive landscape
Big tech giants have been accelerating their pursuit of the AI healthcare market for the last several years. They make collaborations, develop AI-powered solutions, and invest in AI startups intensively.
Google is building its life science brand and actively uses AI for its purpose. DeepMind, the artificial intelligence company owned by Google, is the key player in this market. Google focuses on AI pharmaceutical R&D, radiology, and imaging. Also, it is interested in healthcare search and unstructured data analysis.
is building its life science brand and actively uses AI for its purpose. DeepMind, the artificial intelligence company owned by Google, is the key player in this market. Google focuses on AI pharmaceutical R&D, radiology, and imaging. Also, it is interested in healthcare search and unstructured data analysis. Microsoft is a leader in health IT services. Azure Cloud is becoming the leading environment for enterprises' provider-focused software. Besides, Microsoft Corporation is competing to collect and sell medical data.
is a leader in health IT services. Azure Cloud is becoming the leading environment for enterprises' provider-focused software. Besides, Microsoft Corporation is competing to collect and sell medical data. Amazon has its HIPAA -appropriated cloud service for healthcare data processing. It is also focused on AI in precision medicine, medical supply chain, insurance, and care delivery.
has its HIPAA -appropriated cloud service for healthcare data processing. It is also focused on AI in precision medicine, medical supply chain, insurance, and care delivery. Apple holds the largest share of wearable devices. iPhone and Apple Watch are mainly used for gathering patients' data for further processing with AI. Besides, Apple's Health App offers a patient-doctor environment with multiple functions via iPhone.
Conclusion
Statistics demonstrate the growing use of artificial intelligence in healthcare. We observe remarkable results, including growing trust in medical providers for AI and increasing interest from investors in developing AI-enabled healthcare solutions.
It appears that we can expect significant advancements soon. Still, with a lack of skilled specialists and inefficient cooperation between the public and private sectors, the journey remains complex and requires the right expertise.
With over 60 healthcare projects, Binariks is the partner of choice for providers, payers, and innovators ready to make AI work in real healthcare settings. Our AI Center of Excellence gives you access to cross-functional experts and a proven, business-first approach, ensuring safe, compliant, and impactful solutions.
See how our clients benefit: explore our case studies and discover how we help you overcome barriers, unlock new value, and lead in digital health innovation. Ready to move from uncertainty to competitive advantage? Contact Binariks to unlock what's possible with AI in healthcare.
| 2025-06-26T00:00:00 |
https://binariks.com/blog/artificial-intelligence-ai-healthcare-market/
|
[
{
"date": "2025/06/26",
"position": 26,
"query": "AI healthcare"
},
{
"date": "2025/06/26",
"position": 26,
"query": "AI healthcare"
},
{
"date": "2025/06/26",
"position": 11,
"query": "AI healthcare"
},
{
"date": "2025/06/26",
"position": 12,
"query": "AI healthcare"
},
{
"date": "2025/06/26",
"position": 46,
"query": "AI healthcare"
},
{
"date": "2025/06/26",
"position": 63,
"query": "AI healthcare"
},
{
"date": "2025/06/26",
"position": 45,
"query": "AI healthcare"
},
{
"date": "2025/06/26",
"position": 46,
"query": "AI healthcare"
},
{
"date": "2025/06/26",
"position": 48,
"query": "AI healthcare"
},
{
"date": "2025/06/26",
"position": 44,
"query": "AI healthcare"
},
{
"date": "2025/06/26",
"position": 28,
"query": "AI healthcare"
},
{
"date": "2025/06/26",
"position": 28,
"query": "AI healthcare"
},
{
"date": "2025/06/26",
"position": 28,
"query": "AI healthcare"
}
] |
|
Unemployment among young college graduates outpaces overall ...
|
Unemployment among young college graduates outpaces overall US joblessness rate
|
https://www.kgw.com
|
[] |
The unemployment rate has stayed low mostly because layoffs are still relatively rare. The actual hiring rate — new hires as a percentage of all ...
|
For college graduates 22 to 27 years old, the unemployment rate was 5.8% in March — the highest, excluding the pandemic, since 2012.
WASHINGTON — While completing a master’s degree in data analysis, Palwasha Zahid moved from Dallas to a town near Silicon Valley. The location made it easy to visit the campuses of tech stalwarts such as Google, Apple, and Nvidia.
Zahid, 25, completed her studies in December, but so far she hasn't found a job in the industry that surrounds her.
“It stings a little bit,” she said. “I never imagined it would be this difficult just to get a foot in the door.”
Young people graduating from college this spring and summer are facing one of the toughest job markets in more than a decade. The unemployment rate for degree holders ages 22 to 27 has reached its highest level in a dozen years, excluding the coronavirus pandemic. Joblessness among that group is now higher than the overall unemployment rate, and the gap is larger than it has been in more than three decades.
The rise in unemployment has worried many economists as well as officials at the Federal Reserve because it could be an early sign of trouble for the economy. It suggests businesses are holding off on hiring new workers because of rampant uncertainty stemming from the Trump administration's tariff increases, which could slow growth.
“Young people are bearing the brunt of a lot of economic uncertainty,” Brad Hersbein, senior economist at the Upjohn Institute, a labor-focused think tank, said. “The people that you often are most hesitant in hiring when economic conditions are uncertain are entry-level positions.”
The growth of artificial intelligence may be playing an additional role by eating away at positions for beginners in white-collar professions such as information technology, finance, and law.
Higher unemployment for younger graduates has also renewed concerns about the value of a college degree. More workers than ever have a four-year degree, which makes it less of a distinguishing factor in job applications. Murat Tasci, an economist at JPMorgan, calculates that 45% of workers have a four-year degree, up from 26% in 1992.
While the difficulty of finding work has demoralized young people like Zahid, most economists argue that holding a college degree still offers clear lifetime benefits. Graduates earn higher pay and experience much less unemployment over their lifetimes.
The overall U.S. unemployment rate is a still-low 4.2%, and the government's monthly jobs reports show the economy is generating modest job gains. But the additional jobs are concentrated in health care, government, and restaurants and hotels. Job gains in professions with more college grads, such as information technology, legal services, and accounting have languished in the past 12 months.
The unemployment rate has stayed low mostly because layoffs are still relatively rare. The actual hiring rate — new hires as a percentage of all jobs — has fallen to 2014 levels, when the unemployment rate was much higher, at 6.2%. Economists call it a no-hire, no-fire economy.
For college graduates 22 to 27 years old, the unemployment rate was 5.8% in March — the highest, excluding the pandemic, since 2012, and far above the nationwide rate.
Lexie Lindo, 23, saw how reluctant companies were to hire while applying for more than 100 jobs last summer and fall after graduating from Clark Atlanta University with a business degree and 3.8 GPA. She had several summer internships in fields such as logistics and real estate while getting her degree, but no offer came.
“Nobody was taking interviews or responding back to any applications that I filled out,” Lindo, who is from Auburn, Georgia, said. "My resume is full, there’s no gaps or anything. Every summer I’m doing something. It’s just, ‘OK, so what else are you looking for?’”
She has returned to Clark for a master's program in supply chain studies and has an internship this summer at a Fortune 500 company in Austin, Texas. She's hopeful it will lead to a job next year.
Artificial intelligence could be a culprit, particularly in IT. Matthew Martin, senior U.S. economist at Oxford Economics, has calculated that employment for college graduates 28 and above in computer science and mathematical occupations has increased a slight 0.8% since 2022. For those ages 22 to 27, it has fallen 8%, according to Martin.
Company announcements have further fueled concerns. Tobi Lutke, CEO of online commerce software company Shopify, said in an April memo that before requesting new hires, “teams must demonstrate why they cannot get what they want done using AI.”
Last week, Amazon CEO Andy Jassy said AI would likely reduce the company's corporate workforce over the next few years.
“We will need fewer people doing some of the jobs that are being done today, and more people doing other types of jobs,” Jassy said in a message to employees. “We expect that this will reduce our total corporate workforce as we get efficiency gains from using AI extensively across the company.”
Zahid worries that AI is hurting her chances. She remembers seeing big billboard ads for AI at the San Francisco airport that asked, “Why hire a human when you could use AI?”
Still, many economists argue that blaming AI is premature. Most companies are in the early stages of adopting the technology.
Professional networking platform LinkedIn categorized occupations based on their exposure to AI and did not see big hiring differences between professions where AI was more prevalent and where it wasn't, said Kory Kantenga, the firm's head of economics for the Americas.
“We don’t see any broad-based evidence that AI is having a disproportionate impact in the labor market or even a disproportionate impact on younger workers versus older workers,” Kantenga said.
He added that the Federal Reserve's interest rate hikes have also slowed hiring in tech. Many IT firms expanded when the Fed pinned its short-term rate at nearly zero after the pandemic. In 2022, the Fed began cranking up rates to combat inflation, which made it harder to borrow and grow.
In fact, IT's hiring spree when rates were low — fueled by millions of Americans ramping up their online shopping and video conferencing — left many firms with too many workers, economists say.
Cory Stahle, an economist at the job-listings website Indeed, says postings for software development jobs, for example, have fallen 40% compared with four years ago. It's a sharp shift for students who began studying computer science when hiring was near its peak.
Zahid, who lives in Dublin, California, has experienced this whiplash firsthand. When she entered college in 2019, her father, who is a network engineer, encouraged her to study IT and said it would be easy for her to get a job in the field.
She initially studied psychology but decided she wanted something more hands-on and gravitated to data analysis. Her husband, 33, has a software development job, and friends of hers in IT received immediate job offers upon graduation a few years ago. Such rapid hiring seems to have disappeared now, she said.
She has her college diploma, but hasn't hung it up yet.
“I will put it up when I actually get a job, confirming that it was worth it all,” she said.
___
AP Writer Matt Sedensky in New York contributed to this report.
| 2025-06-26T00:00:00 |
2025/06/26
|
https://www.kgw.com/article/news/nation-world/unemployment-young-college-graduates-overall-joblessness-rate/507-6281513a-ee36-490e-bcf7-a6993fe4e204
|
[
{
"date": "2025/06/26",
"position": 82,
"query": "AI unemployment rate"
},
{
"date": "2025/06/26",
"position": 93,
"query": "AI unemployment rate"
}
] |
Engaging the workforce to develop AI governance
|
Engaging the workforce to develop AI governance
|
https://aicenterforgovernment.org
|
[
"Ai Center For Government",
"June"
] |
Agencies can deepen staff expertise by taking advantage of government-based AI courses, free AI Government Leadership Programs and custom ...
|
The Partnership for Public Service AI Center for Government™ champions pragmatic, people-centered approaches to building AI governance structures — and believes government agencies can design AI strategies to serve the public, satisfy employee need and enable smart, safe innovation.
1. Start with the mission
Agencies that treat AI as an operational, mission-delivery tool can focus their efforts to use AI to solve real problems and boost efficiency. When mission comes first, AI can effectively and appropriately support leadership, employees and the public.
2. Agency partnerships: Collaborate to innovate!
Government agencies with a broad range of internal offices and departmental missions can develop successful enterprise-wide AI governance practices by prioritizing engagement and participation. Through leadership convenings, workforce forums and communities of interest, for example, agencies can involve staff to ensure AI governance is fit-for-purpose across the organization.
3. AI literacy
AI training is key not only to deployment of AI, but also to AI strategy development. Agencies can deepen staff expertise by taking advantage of government-based AI courses, free AI Government Leadership Programs and custom internally-developed trainings. Employees can better contribute to strategy and implementation by understanding the tools.
4. Clear communication
During the AI governance (re)design process, agency leadership and AI strategy development teams can reduce friction and confusion by prioritizing clear, ongoing communication. Creating opportunity for employees to ask questions, surface concerns and share what doesn’t make sense will create a feedback loop that strengthens internal policy now and deployment later.
5. Manage change and make it stick
AI governance should be designed for impact and made to stick; it should be made to be part of the everyday workflow and implemented with change management principles in mind. Successful AI governance strategies are responsive and flexible enough to evolve with changing leadership, priorities or technology. Well-implemented plans keep the whole human and the whole organization in mind.
6. We can do this!
Through our touchpoints with governments across the country, we’ve seen that with the right balance of structure and flexibility, even large, complex agencies can build systems that are responsive, responsible and built to last.
It’s not about tech for tech’s sake. It’s about making government work better for everyone.
We’re here to help!
| 2025-06-26T00:00:00 |
2025/06/26
|
https://aicenterforgovernment.org/2025/06/26/engaging-the-workforce-to-develop-ai-governance/
|
[
{
"date": "2025/06/26",
"position": 93,
"query": "government AI workforce policy"
},
{
"date": "2025/06/26",
"position": 95,
"query": "government AI workforce policy"
},
{
"date": "2025/06/26",
"position": 79,
"query": "government AI workforce policy"
},
{
"date": "2025/06/26",
"position": 62,
"query": "government AI workforce policy"
},
{
"date": "2025/06/26",
"position": 77,
"query": "government AI workforce policy"
}
] |
AI & the retraining challenge - AI Policy Perspectives
|
AI & the retraining challenge
|
https://www.aipolicyperspectives.com
|
[
"Ai Policy Perspectives"
] |
However, in the US, where labor unionisation has been mostly declining, these latter technologies also widened income and, especially, wealth ...
|
In this essay, Julian Jacobs writes about the history of US public worker retraining programmes, their efficacy, and how they might fare as AI diffuses throughout the economy.
Source: Venus Krier
When asked to reflect on how AI may affect society, people frequently rate the loss of their job as their top concern. Such worries are not new. During the Industrial Revolution, the Luddites smashed textile machines and fought with mill owners, even if their demands were more nuanced than is often ascribed. At the turn of the 20th century, public administrators overseeing the US economy feared how new kinds of glassware and steel might impact workers.
Such fears are understandable. Jobs, particularly the skilled trades that are often most vulnerable to automation, can provide financial independence and feelings of status, purpose, and community. This is of course not true for all jobs, all the time. In his seminal book Working, Studs Terkel observed that many people feel their jobs are defined by a lack of meaning, as well as an intense disconnectedness, fatigue, and a droning anxiety about wasting their lives. But surveys of today’s employees, at least in the West, suggest that a majority are relatively satisfied with their job and that as many as 50%, or more, would want to continue working even if they did not need the money.
1. Will we need retraining to respond to AI?
When new technologies disrupted employment in the past, they typically led to an increase in aggregate employment, albeit not always immediately. This was true with the steam engine and spinning jenny during the Industrial Revolution, and with industrial robots and digitisation in the 20th Century. However, in the US, where labor unionisation has been mostly declining, these latter technologies also widened income and, especially, wealth inequalities. This was mainly due to two dynamics - the extent of which economists continue to dispute.
First, the technologies increased productivity and economic growth, but a growing share of this expanding pie went to capital owners, especially those with a significant ownership stake in fast-growing enterprises. Labour’s share, once inflation was accounted for, declined. In 2022, according to the economist Loukas Karabarbounis, the share of income going to labor in the US hit its lowest point since the Great Depression, at just under 60% of national income.
Second, the technologies complemented people with certain skills while displacing others - what economists refer to as ‘skills-based technological change’. Digitisation and industrial robots automated middle-wage occupations such as clerks, bookkeepers, and assembly line workers, while enabling high-paying roles for software engineers, roboticists and data analysts. These new roles also fostered demand for lower-wage roles, including to provide services to higher earners, for example in the retail, healthcare, food service or personal grooming sectors. These two trends made the labour market more polarised, as workers who lost their jobs or were unable to benefit from new technologies struggled to move into higher-wage work. If we expect AI’s impacts to be similar, this could provide a rationale for governments to fund large retraining programmes to help people retain their jobs and move into higher-wage roles.
Will AI’s effects be similar? We don’t know. Some efforts to address this question break jobs down into bundles of tasks and evaluate AI’s ability to perform them, now and in the future. These evaluations cover a wide range of jobs and tasks, but they don’t tell us whether organisations that hire people to do these tasks are investing in AI, or changing their hiring. Other studies do assess the impact of AI on real-world employment outcomes, for example on freelance employment, but only cover a small share of the labour market. No assessments yet give us breadth and depth.
In the near-term, the employees at greatest risk from AI are likely those that work in, or would like to work in, occupations where tasks are currently performed (almost) entirely on a computer. And where some degree of human error is already common and not catastrophic. This may include graduates aspiring to work in consultancies, legal firms or content agencies or the large number of people who work in remote customer service roles. If new kinds of AI-enabled robots become more capable and cheap, then other kinds of roles, for example in warehouses, could be at risk.
If AI starts to cause people in these roles to lose their jobs en masse, we can expect loud calls for new public retraining programmes. The idea that the government should help to retrain people in response to new technologies, trade shifts or other ‘shocks’ is ubiquitous in policy briefs, consulting reports, and academic research, including on AI. But, these reports typically don’t specify what an AI-induced retraining programme should look like, who should do it, and what lessons, if any, we should draw from past efforts.
In the remainder of this essay, I trace the history of US public retraining programmes and their impacts. In short, I find little evidence that they have been effective. In future essays, I hope to consider lessons from private retraining programmes and other countries.
2. A brief history of US public retraining programmes
In 1933, as the Great Depression reached its darkest moments, President Roosevelt signed the Wagner-Peyser Act, creating the United States Employment Services, a new national network of offices to help the ~25% of the labour force that was out of work. Their retraining offering was rudimentary but provided a foundation to build from. Since then, retraining has become an integral ‘Active Labour Market Policy’ in the US and beyond. If passive labour market policies, like unemployment insurance, aim to provide a safety net for the unemployed, active policies like retraining and job search assistance aim to provide a ladder back into stable work.
In 1962, John F Kennedy signed the Manpower Development and Training Act, the first federal retraining programme to operate at scale. Over the next decade, it retrained 1.9m people to navigate the ‘constantly changing economy’. For men, this typically meant retraining as machine shop workers, auto mechanics, and welders. For women, clerical and administrative roles. In 1973, Richard Nixon replaced the MDTA with the short-lived Comprehensive Employment and Training Act, which focussed on getting low-income individuals, the long-term unemployed, and students into subsidised, entry-level jobs in public sector agencies and nonprofits.
CETA began a process of decentralising US public retraining, putting decisions about how to run the programmes into the hands of cities and states, rather than the federal government. In 1982, the Reagan administration accelerated this further, when it passed the Job Training Partnership Act. In line with Reaganomics, the JPTA aimed to further empower local organisations to deliver retraining and boost private sector employment. To do so, it established Private Industry Councils, with representatives from local businesses, to help direct and supervise the programmes. It also tightly means-tested participants, with the vast majority coming from low-income or “hard to serve" backgrounds, which included people with disabilities, the homeless, offenders, welfare recipients, and out-of-school youth. The training focussed on cultivating basic skills, such as remedial reading and maths, ‘work habits’, such as punctuality and résumé writing, and short, entry-level courses for clerical, services or trades work.
As I expand on below, today the JPTA is typically viewed as a policy failure. In 1998, Bill Clinton replaced it with the Workforce Investment Act, which significantly widened the criteria for participation, making retraining available to anybody who wanted it, while giving low-income and disadvantaged people priority. If the JTPA was essentially a poverty reduction scheme, the WIA aspired to become a universal employment service, including for displaced middle-income workers, when budgets allowed. The WIA also sought to prepare individuals for a more fluid labour market. Unlike JPTA and CETA, which offered participants little choice, the WIA provided individuals with “individual training accounts” so that they could (at least in theory) choose the skills and sectors to invest their time in, once they had completed some general training.
In 2014, Barack Obama replaced the WIA with the more streamlined Workforce Investment and Opportunity Act, which today provides most US federally-funded retraining. The WIOA allows participants to directly participate in their preferred retraining services, without the need to first participate in more general training. It also allows regions to offer more locally-relevant retraining and has tried to increase accountability, by requiring more third-party evaluations.
Every year, approximately ~500,000 participants take part in the WIOA’s ‘Adult’ and ‘Dislocated Worker’ streams, of whom ~200,000 receive training vouchers, at a cost of ~$500m. As noted by David Deming and colleagues, this is a relatively low figure, when one considers that the US government spends 25bn a year on Pell Grants for undergraduate education. Most WIOA participants are low-income, but their profiles vary. For example, most of those on the ‘Adult’ stream are below or near the poverty line, with limited education or employment experience. In contrast, most of those on the “Dislocated Worker’ stream have lost stable employment, for example in manufacturing, and are more likely to be older with more substantial work experience. Although not mandatory, people who receive welfare and public assistance are encouraged to apply and make up approximately one third of WIOA adult participants, according to a 2022 evaluation.
The skills that WIOA retraining programmes impart and their method of instruction vary considerably across US states, owing to differences in the capacity of local retraining providers (who must bid for federal funding), employer needs, and political considerations, which can override more objective readings of labour demand. The result is a patchwork. In 2015, Burt Barnow and Jeffrey Smith distinguished between different types of retraining, from small group sessions focussed on basic skills to subsidised apprenticeships. In the early days of the Clinton era Workforce Investment Act, 47% of participants enrolled in formal, classroom retraining programmes, but this figure ranged widely across states, from 14-96%. According to data from 2023-24, less than 10% of WIOA training involved paid on-the-job training, and just 2% involved apprenticeships.
Source: Burt Barnow and Jeffrey Smith; Venus Krier
Summing together, over the last 80 years, we have seen a steady evolution in US public retraining, from more centralised, New Deal-style programmes to more decentralized efforts targeting local private sector employers. The goal has shifted from addressing widespread unemployment to reducing poverty and back towards a more universal employment service that integrates retraining with other policies, such as job search support.
We can expect further changes. The Trump Administration has proposed merging the WIOA’s programs into a single funding stream titled ‘Make America Skilled Again,’ which may result in a significant funding cut and replace much of today's federally funded training with apprenticeships. However, the proposal will likely be altered significantly as Congress deliberates on its details. So the future of US federal retraining, and how it may respond to AI, is still very much to be determined.
3. Does public retraining work? The evidence base
Consider the hypothetical example of ‘Tony’, who used to be employed at a mid-sized auto parts manufacturing plant in Ohio, until his employer steadily introduced a wave of industrial robots. As documented by Thomas Phillippon in The Great Reversal, many US localities are dominated by a handful of ‘good’ employers. The absence of alternative options reduces worker bargaining power and wages. It also makes layoffs more challenging as employees like Tony must compete against many others, most of whom also lack transferable skills to pursue other roles.
After a prolonged job search, Tony enters a Workforce Investment and Opportunity Act retraining program, run by his local American Job Centre. Owing to his low-income status, he is given priority. Upon arrival, the Centre screens Tony to see if he qualifies for the Dislocated Worker stream. Once confirmed, he is asked to participate in maths, problem-solving, and reading assessments, as well as an aptitude test. From there, a counsellor reviews labour market data and recognising Tony’s background in the auto trade, proposes a variety of skilled trades. She also proposes the opportunity to reskill into a new sector, like medical assistance. If Tony is under pressure to return to work quickly, he may move directly to job search assistance and on-the-job retraining. Alternatively, he may pursue longer classroom retraining at a community college or technical school. If all goes well, he will have regular meetings with his counsellor, participate in soft skills workshops and networking events, and will land a secure new job, with regular progress check-ins.
In reality, successful examples like Tony are rare. In 2016, the year of Donald Trump’s first election, David Autor, David Dorn & Gordon Hanson published ‘The China Shock’ - arguably the most impactful US economics paper of the past decade. The study demonstrated that, since the 1990s, import competition from China had devastated large parts of the American workforce, particularly regions focussed on manufacturing textiles, furniture, toys and other light goods. The shock reverberated across communities, igniting brain drain and depressing economic and social prospects for a generation. Meanwhile, other sectors, regions and employees benefited from cheaper imports.
The China Shock, and the wider technology-based automation that was occurring in these sectors, led to a glut of displaced workers and a stream of youth in search of alternative employment opportunities. This was the sort of challenge that the Clinton-era Workforce Investment Act and the Obama-era Workforce Investment and Opportunity Act were designed to address. However, Autor and colleagues showed that many displaced employees either failed to find employment or were forced to take up new roles in the service sector, for example as cashiers or security guards, that were often less-skilled, lower-paid and less rewarding.
These findings chime with the more formal evidence base on US public retraining programmes. To evaluate retraining programmes, researchers expend considerable effort to track key variables, including the proportion of participants who find work shortly after exiting, the proportion who remain employed for at least six months, and their average earnings. In general, researchers have failed to show any statistically significant benefit on these outcomes.
Teasing out why - and what this means for future retraining programmes, including for AI - is difficult. One key challenge is non-random selection. The population that takes part in retraining is not representative of the wider population of people who have been displaced. This means that we do not know the extent to which participants’ subsequent labour market outcomes are due to the impact of the retraining programme (or lack thereof), or other characteristics that are more common among participants, such as a willingness to take part in retraining in the first place.
To address this issue, researchers use quasi-experiments that aim to approximate randomised controlled trials by matching a group of people that did participate in public retraining programmes - say 10,000 middle-aged men from rural districts - with a similar group that didn’t. However, to do this well, researchers need to know what characteristics are most relevant to future labour market outcomes - prior education?, proximity to a nearby city? - so that they can control them. And many potentially important social or psychological characteristics are impossible to reliably capture in datasets. On top of this, researchers must try to account for the huge variance in the focus, format, and resources of different states’ programmes. As a result, some researchers conclude that it is impossible to make reliable causal claims about why public retraining is, or isn’t effective.
The evidence that does exist provides cause for skepticism. For example, a National Study to evaluate the Reagan-era Job Training Partnership Act, involved a genuine randomised controlled trial that ran from 1987 to 1992, with a representative sample of more than 20,000 participants. It found no statistically significant improvement in employment rates, employment duration, or earnings. In 2019, a 10-year evaluation of the Workforce Investment Act, and the Workforce Investment and Opportunity Act found that, while intensive one-on-one career counselling did improve employment and earnings outcomes, the programme’s retraining streams did not.
As of 2023, the most recent data available, 70% of participants in WIOA were employed in the 2nd and 4th quarters after finishing their retraining programmes. But these outcomes are not compared to a control group, so we don't know if, or to what extent, WIOA is truly improving them. Even when WIOA retraining is helping people find jobs, research by David Deming and colleagues suggests that ~40% of participants are being trained into ‘low-wage’ support roles, particularly in the healthcare sector. The most common roles, such as nursing assistants, come with an annual salary of less than $25,000. Demand for these roles is high, which explains the WIOA’s focus on them, but they often offer little scope for career growth.
There is even evidence that some retraining programmes may hurt participants. For example, a 2012 evaluation of the US Trade Adjustment Assistance programme, which provides retraining to workers displaced by outsourcing and trade, found that participants had lower employment rates in the two years after they were laid off, compared to similar workers who did not participate, potentially due to the opportunity cost of not being able to apply for more immediate work opportunities. Even four years after losing their job, TAA participants were underemployed and earned slightly less, compared to non- participants.
4. Why does retraining fail?
In the absence of clear causal evidence, researchers are left to speculate as to why US public retraining programmes have underwhelmed.
A first challenge relates to the participants and their ability and willingness to take part. Some potential participants may avoid retraining, or drop out, due to the costs involved, which range from transport to arranging childcare - single parents are over-represented among participants. These cost pressures are particularly strong for candidates who are still in work but at risk of losing their jobs. For those with little savings, even the offer of a payment to take part in retraining, may be insufficient.
In other instances, there may be a mismatch between the training and career paths on offer and what candidates are interested in, or capable of. For example, older workers, often close to retirement, have been overrepresented in some of the jobs displaced by digitisation and may be less enticed by retraining into a brand new sector. Retraining participants are also disproportionately likely to have been homeless, an offender, or to lack the basic skills that longer classroom training requires.
All participants may be bewildered by the choice on the offer. As David Deming and colleagues note, the WIOA funds ~7,000 Eligible Training Providers and ~75,000 programmes, in more than 700 occupational fields. Although it aspires to provide ‘informed consumer choice’, via its voucher system, the websites describing different programmes can quickly overwhelm candidates, while failing to provide the comparable programme information and performance data that people need.
A second challenge relates to training providers and their ability to offer a high-quality service that is well-curated to local employers’ needs. Experts note huge variance in the quality and format of local training providers, but with such a large number of providers, the evidence base does not allow us to reliably tease out the good from the bad. Training providers also struggle with the bureaucracy that public programmes entail and the challenge of ensuring that the skills they provide are useful in an ever more specialised economy, where many skills are not easily transferable. Providers also need to look beyond the current labour market and anticipate future skills demands - a task that has always been hard, if not impossible, and which AI is now exacerbating.
A final challenge is that there may simply not be enough skilled jobs for people to retrain into. The typical question for workers looking to retrain is not: “How do I find employment?”, but rather “How do I get a more secure, better paid job?” Past technologies did not increase the aggregate unemployment rate, but there is evidence that they did lead to short to medium-term reduction in the number of ‘skilled’ occupations for workers to retrain into. In the AI era, similar challenges could emerge if, for example, new university graduates were unable to find the kind of role, or career path, they expected.
Retraining & AI: Four ideas
What does this mean for concerns about AI? At a minimum, we should avoid assuming that public retraining programmes will be a useful response. The baseline hypothesis is probably that they won’t. However, there should be ways to make them more useful.
Here are four ideas:
1. Develop better labour market projections
There is vast uncertainty about how quickly AI capabilities will develop, diffuse through the economy, and affect workers. This uncertainty will not disappear any time soon. But AI labs and policymakers could make it easier for retraining providers to understand the jobs that may get displaced, prove more resilient, or emerge. At the moment the US Bureau of Labour Statistics provides high-level forecasts for demand for different occupations. AI labs could work with policymakers and researchers to develop much richer and more granular forecasts that draw on, among others, the latest AI capability evaluations; insights from how users are querying LLMs, online job postings, and government surveys of employers and graduates.
2. Experiment with new retraining approaches
Almost 80% of Workforce Investment and Opportunity Act retraining takes place fully in-person, while just 7% takes place fully online. This creates barriers for people in more remote regions and hinders innovation. It will be difficult to usefully change this, because delivering high-quality online education is hard. As the scholar Mary Burns noted in an evidence review for UNESCO, “few innovations have generated such excitement and idealism - and such disappointment and cynicism - as (digital) technology in education.”
But now is the time to experiment. Education providers are learning from their failures, such as the early Massive Open Online Courses that crudely transposed offline learning content. Some providers are shifting to hybrid formats, while others are developing targeted micro-credential courses. In the AI community, labs are training large language models, and the tutors based on them, to be more ‘pedagogically inspired’, while educators and students are using multimodal AI to personalise learning materials to the language, format, or substance they want. Against this backdrop, there should be opportunities to design AI-enabled retraining programmes that are more dynamic and better able to respond to labour market needs. Another goal of such retraining, at least for some participants, could be on how to use AI systems most effectively.
3. Collate better evidence about what works
At the moment, we have little evidence about what works, or doesn’t, with respect to public retraining programmes. This is particularly true for training provided to workers displaced by new technologies. Future evaluations should target this group, with a focus on those affected by AI, and understand how outcomes are affected by factors such as programme type, age, gender, geography, prior education, and existing skills. This will require better data collection by public sector institutions, with a focus on RCT-style evaluations, but also smaller-scale experiments that academics or companies could run, with standardised measures to harmonise the two.
One area to explore is the nascent positive evidence on training programmes that are co-designed with employers, with specific sectors in mind. Some RCTs in this area show positive effects on earnings and employment, but they are small, typically including a few thousand people, and we do not know if they will generalise across geographies and sectors.
4. Consider goals beyond employment
Finally, it may be time to reevaluate whether ‘work’ should remain the central way to measure a person’s economic contributions and the central goal of any retraining programme. As Tom Rachman wrote in a recent essay: educational policy tends to tinker with the ‘What’ of learning (curriculum) and fret about the ‘How’ (methods). But it’s the Why that demands its boldest recalibration since the Enlightenment.
In theory, education can serve many functions, from boosting an individual’s agency to promoting national unity and assimilation. But preparing students for a career has come to dominate both retraining and broader education. If scenarios where AI has more dramatic economic effects materialise, we need to think about what other knowledge, skills and values people will need to navigate this transition, and the other ways that they can contribute to society. For example, future training programmes could include best practices on how to use AI agents, or how to improve community life and ward against atomization. This more flexible understanding of ‘work’ and ‘training’ could give us a better chance of navigating the AI economic transition in a way that preserves worker livelihoods, opportunity, and dignity.
I would like to acknowledge and thank Burt Barnow for his guidance and contributions in developing this essay. Thank you to Venus Krier for the illustrations contained in this piece.
| 2025-06-26T00:00:00 |
https://www.aipolicyperspectives.com/p/ai-and-the-retraining-challenge
|
[
{
"date": "2025/06/26",
"position": 88,
"query": "universal basic income AI"
}
] |
|
AI at Work 2025: Momentum Builds, but Gaps Remain | BCG
|
AI at Work: Momentum Builds, but Gaps Remain
|
https://www.bcg.com
|
[
"Vinciane Beauchene",
"Sylvain Duranton",
"Nipun Kalra",
"David Martin"
] |
Machinery and Industrial Automation · Metals and Mining ... Build upskilling and reskilling capabilities to support workforce deployment.
|
AI is no longer a distant promise. Leaders and managers have woven it into the fabric of their daily work lives. However, frontline employees have not fully embraced the technology.
While more than three-quarters of leaders and managers say they use generative AI (GenAI) several times a week, regular use among frontline employees has stalled at 51%.
This gap comes at a critical time in the development of AI. Companies are realizing that merely introducing AI tools into existing ways of working isn’t enough to unlock their full potential. The real magic happens—and value generated —when businesses go further and reshape their workflows end-to-end.
One-half of companies, led by those in financial services and technology, are moving beyond productivity plays (what we call Deploy) to redesign workflows (Reshape).
These findings emerge from BCG’s annual AI at Work global survey of employees. (This year’s survey covers 11 countries and regions and more than 10,600 leaders, managers, and frontline white-collar employees. The results are outlined more comprehensively in the accompanying slideshow.)
1 / 27
Tech + Us: Monthly insights for harnessing the full potential of AI and tech.
Solving the Frontline Adoption Gap
The ability of companies to reshape workflows depends heavily on the engagement of frontline employees. The survey suggests ways for companies to help these employees break through the AI “silicon ceiling.”
Provide leadership support. When leaders demonstrate strong support for AI, frontline employees are more likely to use it regularly, enjoy their jobs, and feel good about their careers. For example, the share of employees who feel positive about GenAI rises from 15% to 55% with strong leadership support. Only about one-quarter of frontline employees say they receive that support.
When leaders demonstrate strong support for AI, frontline employees are more likely to use it regularly, enjoy their jobs, and feel good about their careers. For example, the share of employees who feel positive about GenAI rises from 15% to 55% with strong leadership support. Only about one-quarter of frontline employees say they receive that support. Provide the right tools. When employees don’t have the AI tools they need, more than half said they will find alternatives and use them anyway. This is a recipe for frustration, security risks, and fragmentation of efforts.
When employees don’t have the AI tools they need, more than half said they will find alternatives and use them anyway. This is a recipe for frustration, security risks, and fragmentation of efforts. Provide proper training. When companies train their employees in AI, they are more likely to be regular users and to express confidence in the technology. Regular usage is sharply higher for employees that receive at least five hours of training and have access to in-person training and coaching. Only one-third of employees say that they have been properly trained.
The Upside in Reshaping Workflows
Companies actively reshaping their workflows with AI benefit in many ways that generate value for the organization. Their employees save significantly more time than those in companies where the technology is less integrated into the workday. In addition, employees’ decision making sharpens and they work on more strategic tasks.
These results don’t just happen. Companies in Reshape mode do a better job of tracking value created by AI. They spend more time training their employees, and employees are more likely to say their leaders support them.
Yet this transformation isn’t without its challenges. Employees at organizations undergoing comprehensive AI-driven redesign are more worried about job security (46%) than those at less-advanced companies (34%). And leaders and managers (43%) are far more likely to worry about losing their job in the next ten years than frontline employees (36%). In other words, the work of allaying employee fears is ongoing. Appropriate training and upskilling can help reduce employees’ concerns.
Read more: AI Agents
AI Agents: Implementation Lags Potential
AI agents —smart digital assistants capable of learning, reasoning, and handling complex tasks independently—have been receiving a lot of buzz. But the survey reveals they are still in their infancy. Just 13% of employees see them deeply integrated into their daily workflows. Only one-third of employees understand how these sophisticated tools function.
Interestingly, when workers are well-informed and familiar with AI agents, apprehension turns into enthusiasm. Employees begin viewing AI agents less as threats and more as collaborative partners that enhance their work.
What’s Next for AI in the Workplace?
The survey reveals progress by companies in introducing and integrating AI. But it also exposes concerns, primarily about job security. As with last year, the survey reveals that the more employees use AI, the more their concerns grow. This represents a familiar challenge seen in other technological transitions—notably, from steam to electrical power.
The journey from AI adoption to impact is fundamentally about reshaping how people and machines collaborate. Companies committed to this transformation understand that AI’s true power lies in smarter ways of working. When done right, employees don’t just adapt—they thrive. Here’s how to start:
| 2025-06-23T00:00:00 |
2025/06/23
|
https://www.bcg.com/publications/2025/ai-at-work-momentum-builds-but-gaps-remain
|
[
{
"date": "2025/06/26",
"position": 93,
"query": "reskilling AI automation"
},
{
"date": "2025/06/26",
"position": 9,
"query": "AI workers"
},
{
"date": "2025/06/26",
"position": 4,
"query": "workplace AI adoption"
}
] |
How AI is being used in the hiring process, and how job seekers can ...
|
How AI is being used in the hiring process, and how job seekers can get their foot in the door
|
https://www.yahoo.com
|
[] |
How AI is being used in the hiring process, and how job seekers can get their foot in the door. WXYZ-Detroit Videos. Thu, June 26, 2025 at 3 ...
|
24,959 people played the daily Crossword recently. Can you solve it faster than others?
24,959 people played the daily Crossword recently. Can you solve it faster than others?
| 2025-06-26T00:00:00 |
https://www.yahoo.com/news/ai-being-used-hiring-process-105347111.html
|
[
{
"date": "2025/06/26",
"position": 86,
"query": "AI hiring"
}
] |
|
Unemployment among young college graduates outpaces overall ...
|
Unemployment among young college graduates outpaces overall US joblessness rate
|
https://www.9news.com
|
[] |
Artificial intelligence could be a culprit, particularly in IT. Matthew Martin, senior U.S. economist at Oxford Economics, has calculated that ...
|
For college graduates 22 to 27 years old, the unemployment rate was 5.8% in March — the highest, excluding the pandemic, since 2012.
WASHINGTON — While completing a master’s degree in data analysis, Palwasha Zahid moved from Dallas to a town near Silicon Valley. The location made it easy to visit the campuses of tech stalwarts such as Google, Apple, and Nvidia.
Zahid, 25, completed her studies in December, but so far she hasn't found a job in the industry that surrounds her.
“It stings a little bit,” she said. “I never imagined it would be this difficult just to get a foot in the door.”
Young people graduating from college this spring and summer are facing one of the toughest job markets in more than a decade. The unemployment rate for degree holders ages 22 to 27 has reached its highest level in a dozen years, excluding the coronavirus pandemic. Joblessness among that group is now higher than the overall unemployment rate, and the gap is larger than it has been in more than three decades.
The rise in unemployment has worried many economists as well as officials at the Federal Reserve because it could be an early sign of trouble for the economy. It suggests businesses are holding off on hiring new workers because of rampant uncertainty stemming from the Trump administration's tariff increases, which could slow growth.
“Young people are bearing the brunt of a lot of economic uncertainty,” Brad Hersbein, senior economist at the Upjohn Institute, a labor-focused think tank, said. “The people that you often are most hesitant in hiring when economic conditions are uncertain are entry-level positions.”
The growth of artificial intelligence may be playing an additional role by eating away at positions for beginners in white-collar professions such as information technology, finance, and law.
Higher unemployment for younger graduates has also renewed concerns about the value of a college degree. More workers than ever have a four-year degree, which makes it less of a distinguishing factor in job applications. Murat Tasci, an economist at JPMorgan, calculates that 45% of workers have a four-year degree, up from 26% in 1992.
While the difficulty of finding work has demoralized young people like Zahid, most economists argue that holding a college degree still offers clear lifetime benefits. Graduates earn higher pay and experience much less unemployment over their lifetimes.
The overall U.S. unemployment rate is a still-low 4.2%, and the government's monthly jobs reports show the economy is generating modest job gains. But the additional jobs are concentrated in health care, government, and restaurants and hotels. Job gains in professions with more college grads, such as information technology, legal services, and accounting have languished in the past 12 months.
The unemployment rate has stayed low mostly because layoffs are still relatively rare. The actual hiring rate — new hires as a percentage of all jobs — has fallen to 2014 levels, when the unemployment rate was much higher, at 6.2%. Economists call it a no-hire, no-fire economy.
For college graduates 22 to 27 years old, the unemployment rate was 5.8% in March — the highest, excluding the pandemic, since 2012, and far above the nationwide rate.
Lexie Lindo, 23, saw how reluctant companies were to hire while applying for more than 100 jobs last summer and fall after graduating from Clark Atlanta University with a business degree and 3.8 GPA. She had several summer internships in fields such as logistics and real estate while getting her degree, but no offer came.
“Nobody was taking interviews or responding back to any applications that I filled out,” Lindo, who is from Auburn, Georgia, said. "My resume is full, there’s no gaps or anything. Every summer I’m doing something. It’s just, ‘OK, so what else are you looking for?’”
She has returned to Clark for a master's program in supply chain studies and has an internship this summer at a Fortune 500 company in Austin, Texas. She's hopeful it will lead to a job next year.
Artificial intelligence could be a culprit, particularly in IT. Matthew Martin, senior U.S. economist at Oxford Economics, has calculated that employment for college graduates 28 and above in computer science and mathematical occupations has increased a slight 0.8% since 2022. For those ages 22 to 27, it has fallen 8%, according to Martin.
Company announcements have further fueled concerns. Tobi Lutke, CEO of online commerce software company Shopify, said in an April memo that before requesting new hires, “teams must demonstrate why they cannot get what they want done using AI.”
Last week, Amazon CEO Andy Jassy said AI would likely reduce the company's corporate workforce over the next few years.
“We will need fewer people doing some of the jobs that are being done today, and more people doing other types of jobs,” Jassy said in a message to employees. “We expect that this will reduce our total corporate workforce as we get efficiency gains from using AI extensively across the company.”
Zahid worries that AI is hurting her chances. She remembers seeing big billboard ads for AI at the San Francisco airport that asked, “Why hire a human when you could use AI?”
Still, many economists argue that blaming AI is premature. Most companies are in the early stages of adopting the technology.
Professional networking platform LinkedIn categorized occupations based on their exposure to AI and did not see big hiring differences between professions where AI was more prevalent and where it wasn't, said Kory Kantenga, the firm's head of economics for the Americas.
“We don’t see any broad-based evidence that AI is having a disproportionate impact in the labor market or even a disproportionate impact on younger workers versus older workers,” Kantenga said.
He added that the Federal Reserve's interest rate hikes have also slowed hiring in tech. Many IT firms expanded when the Fed pinned its short-term rate at nearly zero after the pandemic. In 2022, the Fed began cranking up rates to combat inflation, which made it harder to borrow and grow.
In fact, IT's hiring spree when rates were low — fueled by millions of Americans ramping up their online shopping and video conferencing — left many firms with too many workers, economists say.
Cory Stahle, an economist at the job-listings website Indeed, says postings for software development jobs, for example, have fallen 40% compared with four years ago. It's a sharp shift for students who began studying computer science when hiring was near its peak.
Zahid, who lives in Dublin, California, has experienced this whiplash firsthand. When she entered college in 2019, her father, who is a network engineer, encouraged her to study IT and said it would be easy for her to get a job in the field.
She initially studied psychology but decided she wanted something more hands-on and gravitated to data analysis. Her husband, 33, has a software development job, and friends of hers in IT received immediate job offers upon graduation a few years ago. Such rapid hiring seems to have disappeared now, she said.
She has her college diploma, but hasn't hung it up yet.
“I will put it up when I actually get a job, confirming that it was worth it all,” she said.
___
AP Writer Matt Sedensky in New York contributed to this report.
| 2025-06-26T00:00:00 |
2025/06/26
|
https://www.9news.com/article/news/nation-world/unemployment-young-college-graduates-overall-joblessness-rate/507-6281513a-ee36-490e-bcf7-a6993fe4e204
|
[
{
"date": "2025/06/26",
"position": 56,
"query": "AI unemployment rate"
}
] |
AI Education Podcast
|
AI in Education Podcast
|
https://podcasts.apple.com
|
[] |
They talk about Artificial Intelligence in Education - what it is, how it works, and the different ways it is being used.
|
After starting with an existential crisis - "Are we basically doing the AI equivalent of a maths calculator podcast from the 1970s?" - in this news and research update, Dan and Ray unpack the latest developments in AI and education. Starting with China’s decision to shut down AI tools during national exams, they then revisit NSW’s EduChat chatbot, now in widespread use, with compelling data on time savings for teachers and learning benefits for students. The hosts dive into fresh research from the LEGO Foundation and Microsoft, both highlighting how young students engage with generative AI—and the equity and creativity issues that come with it. They also tackle the viral MIT study suggesting AI could cause "cognitive debt" and discuss why such claims should be taken with academic caution. Finally, Dan and Ray trace the recurring media fear that each new technology - from books to bicycles - has been accused of making us stupid. As always, they bring wit, warmth, and real insight into how AI is shaping education. Links and references for the studies, news and research discussed: News China shuts down AI tools during nationwide college exams [Bloomberg, The Verge] AI is in every NSW public school classroom. Is that a good thing? Anthropic's copyright case with Claude Research Lego research into children's use of ChatGPT [Project website] New Microsoft report on AI in Education announced at ISTE Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task [Project website - Natalie Kosmina's LinkedIn announcement post - Time news story] And finally For your enjoyment, Donald Clark's "Sisyphean nature of moral panics against new technology" aka What's making us dumb this time? And if you want more enjoyment like Donald's article, then you'll love the Pessimists Archive on Twitter or their newsletter
| 2025-06-26T00:00:00 |
https://podcasts.apple.com/us/podcast/ai-education-podcast/id1481311877
|
[
{
"date": "2025/06/26",
"position": 27,
"query": "AI education"
}
] |
|
AI is already in the classroom. It's time colleges caught up.
|
AI is already in the classroom. It’s time colleges caught up.
|
https://www.freethink.com
|
[] |
Rather than banning AI, schools should adapt by designing assignments that promote responsible use and keep the focus on learning.
|
Subscribe to Freethink on Substack for free Get our favorite new stories right to your inbox every week Subscribe now
Over the past three years, large language models like ChatGPT have gone from curiosities to everyday tools used on college campuses around the world. While some professors embrace them, others ban them. Many institutions fall somewhere in between, setting vague policies or relying on detection tools that have been proven ineffective in many instances. AI may be the most significant innovation in education since the personal computer, and although this revolution has many different characteristics, it echoes past battles over calculators and computers — battles that were ultimately lost by those who tried to resist.
Technology doesn’t wait for policy, and as a current undergraduate student, I believe that the sooner schools catch up, the better we can use these tools to improve learning rather than undermine it. Still, an important question remains: Is it fair to compare AI with past innovations like calculators and the early internet, or is this a fundamentally different challenge?
If personal computers were a bicycle for the mind, today’s AI tools are more like self-driving race cars.
AI is not the first technology to disrupt higher education. In the 1970s, the pocket calculator triggered a wave of backlash among educational institutions. Teachers warned that it would weaken students’ arithmetic skills, and some schools tried to ban calculators altogether. But others saw the potential: If students no longer had to do long division by hand, they could focus on bigger-picture math problems. Eventually, calculators became standard classroom tools, allowing students to shift their focus from manual computation to understanding formulas and solving higher-level, conceptual problems. Studies show that calculators can improve conceptual understanding when used correctly.
This same cycle repeated in the 1990s with personal computers and the early internet. Critics feared that spell-check and copy-paste would erode writing skills, and that search engines like Google and communal encyclopedias like Wikipedia would replace real research. And yes, some students misused those tools. But once schools embraced the technology and taught students how to use it well, evaluate sources, and cite correctly, their academic work improved. Students were no longer limited to the outdated books in their campus libraries, but suddenly had access to a multitude of books, articles, and datasets in multiple languages, at any time.
The cycle of resistance and delayed acceptance is a recurring phenomenon in large institutions, especially those with long-standing traditions in education, such as Columbia University. These universities, responsible for the education of millions of Americans, cannot afford to change course without serious caution. Even when faculty are eager to adapt, such as by updating policies on AI use in student essays, their efforts are often delayed by the university’s complex bureaucracy and layered approval processes. These systems are designed to ensure thoughtful decision-making, but they can struggle to keep pace with rapid technological change. For example, a 2024 global survey conducted by the Digital Education Council found that 86% of students already use AI in their studies, underscoring the technology’s rapid and widespread adoption across disciplines.
However, it’s clear that the AI revolution is broader and more complex than past technological shifts. Instead of simply speeding up our work, AI can perform tasks that once required deep thinking and creativity, such as writing code or entire essays. Steve Jobs famously referred to the personal computer as a “bicycle for the mind” in 1981, believing it could enhance human intelligence, especially in education, the area where he envisioned the personal computer having the most impact.
But if personal computers were a bicycle for the mind, today’s AI tools are more like self-driving race cars: They don’t just help us think faster — they can take over the wheel entirely.
Rather than fostering an environment of uncertainty and mistrust, universities should redirect their energy toward adaptation.
The debate about integrating AI into the education system mirrors earlier debates, but it feels louder and more urgent. ChatGPT can help students draft essays, debug code, explain complex concepts, or practice new languages. Its capabilities dwarf those ushered in by calculators and the internet. For this reason, it can easily be misused, but banning it outright, as many universities have attempted, is a battle that was lost before it even started. Telling students not to use a tool that is nearly undetectable and freely available won’t stop its use; it will only push it underground and widen the gap between students who are proficient in using it and those who don’t yet know how to use it effectively.
Moreover, the AI detectors that many universities rely on as a first line of defense have proven deeply flawed; for example, some have flagged writing from international students because their sentence structure tends to be simpler. The current tension reveals a deeper problem. An experienced English professor probably doesn’t need software to spot AI-generated essays: The tone, structure, and sudden leap in fluency are often glaring to a trained reader. But without empirical proof, there is no ethical way to penalize the student. Intuition, no matter how informed, cannot serve as formal evidence. This leaves educators in an impossible position; they can either ignore the changes they notice or act on suspicion using imperfect AI detectors.
At the same time, my anecdotal experience suggests a strange double standard is emerging. In one of my classes, for example, the professor explicitly banned the use of AI but told us the assignment would be made harder because he assumed we’d use it anyway. On the other hand, some students who are unfamiliar with AI or choose not to use it are falling behind because the expectations for writing and coding have quietly shifted. Rather than fostering an environment of uncertainty and mistrust, universities should redirect their energy toward adaptation. That means adjusting assignments, rethinking evaluation, and integrating AI use transparently so the focus remains on learning, not on detection.
Professors can start by building trust and treating students as partners rather than suspects. Many serious students still want to develop strong writing, communication, and critical thinking skills, especially the ability to read and write at an academic level. Instructors can tap into that motivation by designing tasks that AI can assist with but not complete on its own. They can ask students to compare chatbot drafts with their own revisions, explain how they used AI in their writing process, reflect on the strengths and weaknesses of AI-generated responses, or even participate in short oral exams. These steps can make AI use more productive and, most importantly, keep the focus where it belongs: on human learning. While it’s true that AI may have a greater impact than tools of the past, it can still be incorporated into the learning process if it is approached with care, creativity, and a clear purpose.
Artificial intelligence is here to stay, and it will only grow more powerful with time. Detecting it will become harder, its capabilities will expand, and its presence will become even more embedded in student life. But this shouldn’t be seen as a threat or the end of education as we know it. We saw how the rise of the internet brought about similar fears, yet it ultimately made learning richer and more accessible. Resistance to change is part of human nature, and large institutions like universities often move slowly. But whether they choose to lift AI restrictions or not, one thing is clear: The current “in-between” approach is failing both students and faculty. It’s time for schools to stop pretending this technology can be “defeated” and instead begin building an education system that works with AI, not against it.
This article was reprinted with permission of Big Think, where it was originally published.
We’d love to hear from you! If you have a comment about this article or if you have a tip for a future Freethink story, please email us at [email protected].
| 2025-06-26T00:00:00 |
https://www.freethink.com/artificial-intelligence/ai-education
|
[
{
"date": "2025/06/26",
"position": 55,
"query": "AI education"
}
] |
|
Pros and Cons of AI in Education
|
Pros and Cons of AI in Education: Opportunities & Challenges
|
https://ai-pro.org
|
[
"Ai-Pro Team",
"Articles"
] |
The Pros of AI in Education · 1. Personalized Learning Experiences · 2. Enhanced Efficiency for Educators · 3. Increased Accessibility and Inclusion · 4. Data- ...
|
Teacher pointing to Yes and No chart
Pros and Cons of AI in Education
Two students representing Yes and No
Introduction to AI in Education
Artificial Intelligence (AI) has rapidly evolved from a futuristic concept to a practical tool reshaping various industries, with education being one of the most profoundly affected. From adaptive learning platforms and intelligent tutoring systems to automated grading and personalized curricula, AI’s integration into educational settings has transformed traditional teaching and learning paradigms. However, while AI offers remarkable opportunities to enhance efficiency, accessibility, and personalization, it also introduces significant challenges related to ethics, equity, privacy, and the human aspect of education.
In this comprehensive guide, we’ll explore the multifaceted impact of AI on education, delving into its key advantages, drawbacks, and the nuanced considerations that educators, students, and policymakers must balance. By understanding both the pros and cons of AI in education, stakeholders can make informed decisions that maximize benefits while mitigating potential harms.
Understanding the Basics of AI in education
Education process chart
Definition and Scope
AI in education refers to the use of computer algorithms, machine learning, and data-driven technologies to enhance, automate, or supplement educational processes. This includes a wide array of applications such as:
Adaptive learning platforms that tailor content to individual student needs.
Automated grading systems for essays and assessments.
Intelligent tutoring systems (ITS) that provide personalized feedback.
Chatbots and virtual assistants for student support.
Predictive analytics to identify students at risk or optimize learning pathways.
Evolution and Adoption
The adoption of AI in education has accelerated, spurred by advances in technology, increased digital connectivity, and the need for scalable learning solutions. Major tech companies and educational institutions are investing in AI-driven tools, with applications spanning K-12, higher education, and lifelong learning. While some schools have fully integrated AI into their classrooms, others are in exploratory phases, considering the implications for pedagogy and student outcomes.
The Pros of AI in Education
Man holding a check sign with stars
AI’s promise in education lies in its ability to revolutionize learning experiences, making them more personalized, efficient, and accessible. Below are the key advantages that AI brings to educational environments.
1. Personalized Learning Experiences
One of AI’s most celebrated benefits is its capacity to deliver personalized learning at scale. By analyzing data on individual students’ performance, learning styles, and progress, AI-powered systems can:
Adapt content in real-time: Students receive materials tailored to their current understanding, pacing, and interests.
Offer targeted feedback: AI identifies strengths and weaknesses, helping students focus on areas needing improvement.
Facilitate mastery learning: Learners can move forward only when they’ve demonstrated understanding, reducing gaps in knowledge.
Example: Platforms like DreamBox and Knewton use AI algorithms to adjust math problems or reading passages in response to a student’s answers, promoting continuous engagement and improvement.
2. Enhanced Efficiency for Educators
AI can automate many time-consuming administrative and instructional tasks, allowing educators to focus more on teaching and mentoring. Key efficiency gains include:
Automated grading: AI systems can assess multiple-choice, fill-in-the-blank, and even short-answer questions with speed and consistency.
Scheduling and resource allocation: Tools that optimize class schedules, room assignments, and learning resource distribution.
Streamlined communication: Chatbots answer routine questions, freeing up teachers’ time.
Example: Tools like Gradescope and Turnitin use AI to expedite grading and plagiarism detection, enabling faster feedback for students.
3. Increased Accessibility and Inclusion
AI can help break down barriers to education for students with diverse needs, including those with disabilities or in underserved communities. Benefits include:
Assistive technologies: AI-powered speech recognition, text-to-speech, and translation tools support learners with visual, auditory, or language challenges.
Remote learning support: Intelligent tutoring and virtual classrooms bridge gaps in teacher availability, especially in rural or low-resource regions.
Customized content: AI can generate materials at various reading levels or in multiple languages for greater inclusivity.
Example: Microsoft’s Immersive Reader uses AI to improve reading comprehension for students with dyslexia or other learning differences.
4. Data-Driven Decision Making
AI provides actionable insights by analyzing vast amounts of data from student interactions, assessments, and engagement metrics. These insights are made possible by technologies like large language models (LLMs), which can interpret patterns, understand natural language, and generate predictions at scale. This empowers educators to:
Identify at-risk students: Early warning systems flag learners who may need additional support.
Optimize curricula: Data reveals which teaching methods or materials are most effective.
Measure educational outcomes: Continuous analysis supports evidence-based policy and practice.
Example: Predictive analytics platforms help universities improve retention rates by identifying students likely to drop out and intervening proactively.
5. 24/7 Learning and Support
Unlike traditional classrooms constrained by schedules, AI-driven tools offer round-the-clock access to learning resources and support services:
On-demand tutoring: Virtual tutors provide explanations and practice problems anytime.
Instant feedback: Students receive answers to questions immediately, facilitating independent learning.
Scalable support: AI chatbots can handle thousands of student queries simultaneously.
Example: Khan Academy’s AI-powered chatbots answer questions and guide learners through complex concepts, regardless of time zone or classroom hours.
6. Fostering Creativity and Innovation
AI can inspire new ways of learning, teaching, and problem-solving by:
Generating creative content: AI tools help students brainstorm, write, and visualize ideas.
Simulating real-world scenarios: Virtual labs and simulations let students experiment safely.
Encouraging critical thinking: Adaptive challenges and open-ended projects require students to think deeply and creatively.
Example: AI-powered platforms like Google’s Teachable Machine enable students to create and train their own AI models, fostering hands-on learning.
The Cons of AI in Education
Woman doing a “No” signal
Despite its many advantages, AI in education is not without significant drawbacks and risks. Understanding these challenges is crucial for responsible adoption and policy development.
1. Loss of Human Interaction and Social Skills
AI-powered systems, while efficient, cannot replicate the empathy, mentorship, and nuanced understanding that human educators provide. Potential consequences include:
Reduced personal connection: Students may feel isolated or unsupported without meaningful teacher-student interactions.
Diminished social learning: Classroom discussions, group projects, and peer feedback foster collaboration and communication skills that AI cannot fully substitute.
Impaired emotional development: Young learners especially benefit from role models and social cues that only humans can offer.
Example: Overreliance on AI for instruction in virtual environments can limit opportunities for students to develop teamwork and leadership skills.
2. Bias and Fairness Issues
AI systems are only as unbiased as the data and algorithms they are built upon. Risks include:
Algorithmic bias: If training data reflects societal prejudices, AI may perpetuate or even amplify inequities (e.g., in grading, admissions, or resource allocation).
Lack of transparency: Black-box AI models make it difficult to identify and correct errors or biases.
Unequal benefits: Students from privileged backgrounds may benefit more from AI tools due to better access and support.
Example: AI grading tools have faced criticism for unfairly scoring students from certain demographic groups due to biased training data.
3. Privacy and Security Concerns
AI-driven educational platforms collect massive amounts of student data, raising significant privacy and cybersecurity issues:
Sensitive data exposure: Breaches or mismanagement can lead to unauthorized access to personal and academic records.
Surveillance risks: Continuous monitoring of student behavior may infringe on privacy rights and create a climate of mistrust.
Unclear consent: Students and parents may not fully understand how their data is used or shared.
Example: The use of AI-powered proctoring software during remote exams has sparked controversy over surveillance and data protection.
4. Dependence on Technology and Equity Gaps
Teachers and students require digital literacy training to effectively use AI tools in the classroom. Without foundational skills to work with AI, the benefits of these technologies can’t be fully realized—particularly in schools with limited access to resources or support. Bridging this skills gap is essential to ensure equitable adoption and prevent further educational disparities. Investing in professional development and AI education is just as important as investing in the tools themselves.
Example: During the COVID-19 pandemic, students without high-speed internet or AI-enabled devices fell behind peers with better access.
5. Threats to Academic Integrity
AI makes it easier for students to access information and generate content, often with minimal effort. Tools like AI text generators can quickly produce essays, summaries, or homework answers, which blurs the line between assistance and academic dishonesty. This raises concerns about originality and integrity, especially as advanced AI-generated content becomes harder to detect with traditional plagiarism checkers. As students increasingly rely on these tools, there’s a growing need to redefine academic standards and encourage critical thinking over convenience.
Automated essay writing is one of the most controversial uses of AI in education. Advanced AI essay writers can produce well-structured essays or solve complex problems with little to no human input. While these tools can aid learning when used ethically, they also make it easier for students to submit work that isn’t their own, raising serious concerns about plagiarism. As the quality of AI-generated content improves, it becomes increasingly difficult for educators to verify authenticity using traditional methods.
Example: The rise of AI-powered homework helpers has sparked debate over what constitutes academic dishonesty in the digital age.
6. High Implementation and Maintenance Costs
While AI promises long-term efficiency gains, the upfront and ongoing costs can be prohibitive:
Investment in infrastructure: Schools need robust networks, devices, and software to support AI.
Continuous updates: AI systems require regular maintenance, training, and updates to remain effective and secure.
Hidden costs: Licensing fees, technical support, and teacher training can strain budgets.
Example: Small schools or districts with limited funds may struggle to adopt or sustain AI initiatives, leading to unequal access.
Real-World Examples of AI in Education
Kid smiling at a robot in a computer
To better illustrate the practical impact of AI in education, let’s examine a few real-world case studies:
Personalized Learning Platforms
DreamBox Learning: Uses AI to adaptively adjust math lessons for K-8 students, analyzing their responses in real time to offer tailored challenges and support.
Duolingo: Employs machine learning to customize language lessons, track progress, and recommend review topics, making language acquisition more efficient.
Intelligent Tutoring and Virtual Assistants
Khan Academy’s AI Tutor: Offers step-by-step hints and explanations, providing instant feedback and scaffolding for learners struggling with concepts.
IBM Watson Tutor: Assists teachers by analyzing classroom data, suggesting differentiated instruction strategies, and even answering student questions.
Administrative Automation
Gradescope: Automates grading for assignments and exams, allowing instructors to review and adjust AI-generated scores, saving time and reducing grading bias.
Chatbots in Higher Education: Universities like Georgia State have deployed AI chatbots to answer admissions, financial aid, and course registration questions, improving student support.
Accessibility and Special Education
Microsoft Immersive Reader : Supports students with dyslexia by reading text aloud, changing fonts, and breaking down complex sentences.
AI-Powered Speech Recognition: Tools like Otter.ai transcribe lectures in real time, aiding students with hearing impairments.
Ethical Considerations and Policy Implications
Hologram that shows security symbol
The integration of AI into educational systems raises critical ethical questions and policy challenges that must be addressed to ensure responsible use.
Data Privacy and Security
Consent and transparency: Schools must clearly communicate how student data is collected, used, and protected.
Compliance: Adherence to data protection regulations like FERPA (in the U.S.) and GDPR (in Europe) is essential.
Fairness and Bias Mitigation
Regular audits: AI systems should be evaluated for bias and fairness, with mechanisms in place to address disparities.
Inclusive design: Involving diverse stakeholders in AI development helps prevent the amplification of societal biases.
Teacher and Student Empowerment
Professional development: Ongoing training for educators is crucial to effectively integrate AI tools and interpret AI-driven insights.
Student agency: AI should augment, not replace, student decision-making and creativity.
Accountability and Oversight
Clear guidelines: Policymakers must establish standards for AI use, including accountability for errors or adverse impacts.
Stakeholder engagement: Continuous dialogue with parents, students, teachers, and technologists ensures that AI aligns with educational values.
The Future of AI in Education: Opportunities and Challenges Ahead
Futuristic graphic of learning and education symbols
As AI technology continues to advance, its influence on education will only deepen. The future holds immense promise, but also new complexities.
Emerging Trends
AI-powered formative assessment: Real-time analysis of student work to inform immediate instructional adjustments.
Virtual and augmented reality: AI-driven simulations for immersive, experiential learning.
Emotion AI: Systems that detect student emotions and engagement levels to better personalize instruction.
Navigating the Path Forward
Balancing efficiency with humanity: AI should enhance, not diminish, the central role of human relationships in education.
Ensuring equitable access: Policymakers and educators must prioritize closing the digital divide to prevent worsening educational inequalities.
Promoting lifelong learning: As AI transforms the workforce, education systems must adapt to cultivate skills like critical thinking, adaptability, and digital literacy.
Conclusion: Weighing the Pros and Cons of AI in Education
Artificial intelligence is undeniably reshaping the educational landscape, offering powerful tools to personalize learning, streamline administration, and increase access for students of all backgrounds and abilities. The potential for AI to revolutionize education is immense, from adaptive tutoring and 24/7 support to data-driven insights that improve teaching and learning outcomes.
Yet, these benefits come with significant challenges. The risks of bias, privacy violations, loss of human connection, and unequal access must be carefully managed. Educators, policymakers, and technology developers share a collective responsibility to ensure that AI is deployed ethically, transparently, and inclusively.
Ultimately, the key to harnessing AI’s transformative potential in education lies in thoughtful implementation—one that prioritizes student well-being, safeguards data privacy, promotes equity, and maintains the irreplaceable value of human educators. By balancing innovation with caution, we can shape an educational future where AI is a powerful ally in fostering knowledge, creativity, and lifelong learning for all.
Frequently Asked Questions (FAQs) About AI in Education
Is AI replacing teachers in the classroom?
No, AI is not replacing teachers but rather augmenting their roles. While AI can automate certain tasks and provide personalized learning experiences, human educators remain essential for mentorship, emotional support, and fostering critical thinking and creativity.
How can schools ensure AI is used ethically?
Schools should adopt clear policies regarding data privacy, bias mitigation, and transparency. Involving teachers, parents, and students in decision-making, regularly auditing AI systems, and providing professional development are important steps toward ethical AI use.
What are the main barriers to AI adoption in education?
Key barriers include high implementation costs, lack of digital infrastructure, digital literacy gaps among teachers and students, and concerns about data privacy and bias.
Can AI help students with special needs?
Yes, AI-powered assistive technologies can greatly benefit students with disabilities by providing tailored support, accessible content, and tools that accommodate diverse learning needs.
Will AI widen the digital divide?
If not implemented thoughtfully, AI could exacerbate inequalities by favoring students with better access to technology. Ensuring equitable access to devices, connectivity, and training is essential to prevent this outcome.
Forward-thinking educators are tapping into the power of AI-driven chatbots to support student inquiry and using AI art tools to spark imagination in the classroom—real-world examples of how intelligent technology is reshaping not just how we teach, but how students learn and create.
Further Reading and Resources
By understanding the pros and cons of AI in education, stakeholders can take informed steps to harness its benefits while safeguarding against its risks, ensuring that the future of learning is both innovative and inclusive.
| 2025-06-26T00:00:00 |
2025/06/26
|
https://ai-pro.org/learn-ai/articles/pros-and-cons-of-ai-in-education/
|
[
{
"date": "2025/06/26",
"position": 71,
"query": "AI education"
}
] |
AI Tools for Education - Research Guides
|
AI Tools for Education
|
https://guides.libraries.uc.edu
|
[
"Katie Foran-Mulcahy"
] |
The following guide contains AI tools for educational use, including tools for teaching, presentations, accessibility, and general assistance for learners.
|
This guide was created by Mazid UI Hasan, eLearning Graduate Assistant in the CECH School of Education, University of Cincinnati. Additional content provided by Dr. Janet Zydney, CECH School of Education, and Katie Foran-Mulcahy, UC Libraries.
The following guide contains AI tools for educational use, including tools for teaching, presentations, accessibility, and general assistance for learners. See the left navigation menu for quick access to each AI tool category.
Artificial Intelligence (AI) has caused significant discussions in different fields, including education, since late 2022. Many educators have been grappling with the disruptive potential of generative AI, like ChatGPT, particularly regarding academic integrity. On the other hand, many others pointed out that technological advancements often disrupted existing practices historically, but when efficiently adopted, these technologies improved the current practices. Similarly, if we look beyond the disruptive nature of AI in education, AI can offer significant positive impacts on teaching and learning.
AI claims to revolutionize personalized learning by analyzing individual student needs, tailoring content and feedback, and creating customized learning pathways. AI tutors can offer conversational guidance and support, while tools like Diffit can adjust learning materials to individual reading levels. AI-powered text-to-speech, speech-to-text, and image description tools further enhance accessibility for diverse learners. AI tools can empower educators by providing lesson plans and quizzes, recommending resources, and assisting with grading and insights.
This guide highlights numerous benefits of using AI in education, describing several AI tools and their functionalities to improve educational practices. However, despite their great potential, there are concerns regarding the inaccuracies and biases in these tools’ responses. Sometimes, the tools may provide incorrect information and references and reproduce existing biases from the materials on which they were trained. Therefore, it is strongly recommended that with all AI, teachers check the output for accuracy and biases. Given this need to verify the accuracy of the output from Generative AI, teachers need to be careful about having students directly use AI tools without teacher intervention. Using AI tools for grading and feedback can introduce biases and unfairly grade students from certain demographics. There also can be issues regarding data privacy and security of the information provided to these tools.
AI tools highlighted in this guide are provided for informational purposes only. Highlighted tools have not necessarily been approved or endorsed by the University of Cincinnati or Digital Technology Solutions (DTS).
For information on AI tools and academic integrity concerns, consult the UC Student Code of Conduct, which lists "unauthorized use of artificial intelligence" as a form of academic misconduct under "Cheating" (p.9-10). Further information on generative AI and academic integrity can be found on the Preventing Student Plagiarism LibGuide from UC Libraries, linked below.
| 2025-06-26T00:00:00 |
https://guides.libraries.uc.edu/ai-education
|
[
{
"date": "2025/06/26",
"position": 74,
"query": "AI education"
}
] |
|
Data Security for Employers in the Era of AI, Remote Work ...
|
Data Security for Employers in the Era of AI, Remote Work and Ransomware
|
https://www.littler.com
|
[] |
In an era of rapidly advancing technology, employers face an increasingly complex landscape of data security challenges. Two points remain constant: ...
|
In an era of rapidly advancing technology, employers face an increasingly complex landscape of data security challenges. Two points remain constant: employees are still the top cause of data breaches, and HR data remains among the highest at-risk data at most companies. But the risks have grown.
During this 60-minute webinar, Littler attorneys Zoe Argento, William Simmons and Andrew Gray will explore the intersection of artificial intelligence (AI) and data protection, delving into the dynamic “cat-and-mouse” game where sophisticated phishing attacks are met with equally advanced AI-driven detection systems. They will also discuss the challenges posed by increasing regulatory scrutiny, high levels of remote work, ransomware attacks and the collection of new types of data, such as AI profiling data. Focusing on practical strategies, panelists will discuss how employers can manage data protection throughout the employment lifecycle – from conducting thorough background checks and training and monitoring to securing sensitive information during offboarding. Additionally, Stephanie Swenson from ComplianceHR will walk you through PolicySmart™ and the Reference Center, solutions designed to simplify the complexity of employment law.
Time:
10:00 - 11:00 a.m. PT
11:00 a.m. - 12:00 p.m. MT
12:00 - 1:00 p.m. CT
1:00 - 2:00 p.m. ET
| 2025-06-26T00:00:00 |
https://www.littler.com/events/data-security-employers-era-ai-remote-work-and-ransomware
|
[
{
"date": "2025/06/26",
"position": 34,
"query": "AI employers"
}
] |
|
Flawless | AI-Assisted Performance Editing
|
AI-Assisted Performance Editing
|
https://flawlessai.com
|
[] |
Discover Flawless, AI-assisted performance and dialogue editing for film, TV and commercials that puts actors first. Get started today.
|
AI Done Right We believe in using AI responsibly, ethically and transparently. Our technology exists to enhance human creativity—not replace it.
Cinematic Excellence Every frame exported by our technology deserves to meet the standards of the big screen.
Artists First Artists should chart the creative path, with technology accelerating the journey—not steering it.
| 2025-06-26T00:00:00 |
https://flawlessai.com/
|
[
{
"date": "2025/06/26",
"position": 40,
"query": "AI employers"
}
] |
|
G42 | Inventing a Better Everyday
|
Inventing a Better Everyday
|
https://www.g42.ai
|
[
"Tentwenty",
"Webdesign",
"Webshops",
"E-Marketing"
] |
G42 is a technology group that invents visionary artificial intelligence for a better everyday. Born in Abu Dhabi and operating across the world, ...
|
We’re G42 — born in Abu Dhabi, building globally, and pushing AI to do more for everyone.
We see artificial intelligence as a force for good. A partner to humanity. A tool to make lives healthier, journeys safer, and the future more connected.
From decoding disease to exploring deep space, we’re not waiting for tomorrow. We’re creating it — with partners, with purpose, and with people in mind.
At G42, progress is personal. And every day is a chance to invent better.
| 2025-06-26T00:00:00 |
https://www.g42.ai/
|
[
{
"date": "2025/06/26",
"position": 82,
"query": "AI employers"
}
] |
|
Can AI Tools Meet Journalistic Standards?
|
Can AI Tools Meet Journalistic Standards?
|
https://www.cjr.org
|
[] |
Certainly, AI is being used effectively by some journalists to crunch numbers at lightning speed and make sense of vast databases. That's a big benefit, one ...
|
Sign up for The Media Today, CJR’s daily newsletter.
Tech companies promise that AI tools can do more with less—so perhaps they can help news outlets survive declining subscription sales and evaporating advertising revenue. Certainly, AI is being used effectively by some journalists to crunch numbers at lightning speed and make sense of vast databases. That’s a big benefit, one that has contributed to prizewinning work in the public interest.
But more than two years after the public release of large language models (LLMs), the promise that the media industry might benefit from AI seems unlikely to bear out, or at least not fully.
Generative AI tools rely on media companies to feed them accurate and up-to-date information. At the same time, AI products are developing into something akin to a newsroom competitor, and a particularly problematic one at that: well-funded, high-volume, and at times unscrupulous.
We decided to survey cases of AI-produced text in the news industry with an eye on ethics. Can AI tools meet the standards of traditional reporting and publishing? Our research finds several recent instances in which AI tools failed to rise to the occasion.
One of the primary problems with AI-generated text is that none of the most common AI software models—including OpenAI’s ChatGPT, Google’s Gemini, Microsoft’s Copilot, and Meta’s Meta AI—are able to reliably and accurately cite and quote their sources. These tools commonly “hallucinate” authors and titles. Or they might quote real authors and books, with the content of the quotes invented. The software also fails to cite completely, at times copying text from published sources without attribution. This leaves news organizations open to accusations of plagiarism.
Last year, Forbes called out the AI tool Perplexity for ingesting its article on Google CEO Eric Schmidt and turning the story into an AI-generated article, podcast, and video without any attribution to the outlet. On YouTube, depressingly, the Perplexity video outranked Forbes’s original story. When confronted by Forbes’s John Paczkowski on X, Perplexity CEO Aravind Srinivas blamed the incident on “rough edges” in the tool.
In a Wired article titled “Perplexity Plagiarized Our Story About How Perplexity Is a Bullshit Machine,” also published last year, Tim Marchman and Dhruv Mehrotra described how they prompted Perplexity to summarize a recent story they’d published. Marchman and Mehrotra found that in its response, Perplexity exactly reproduced one of their sentences as if it had generated the words—a move that appeared to them to be plagiarism. The legal experts Marchman and Mehrotra spoke with were split on whether the lifted sentence would qualify as willful infringement of copyright claims, but there were other problems: Perplexity’s AI data crawlers had seemingly gone around the AI blockers Wired had put in place to prevent the use of its content.
Sign up for CJR’s daily email
Whether this type of generative AI production is legally considered plagiarism and copyright infringement—and therefore, whether media outlets should be paid for the ingestion of their work by generative AI tools—will likely be determined by several upcoming lawsuits.
The New York Times, the Center for Investigative Reporting (which oversees Mother Jones and Reveal), Intercept Media, and eight media outlets owned by Alden Global Capital have filed lawsuits accusing OpenAI and Microsoft of violating copyright laws by ingesting their content. In the Times’ suit, filed in the Southern District of New York in December 2023, the outlet accuses OpenAI of trying “to free-ride on The Times’s massive investment in its journalism by using it to build substitutive products without permission or payment.”
The Times’ filing includes several pages of examples in which OpenAI’s ChatGPT copied text from its archives and reproduced this text verbatim for users.
One possible—and worrying—outcome of all this is that generative AI tools will put news outlets out of business, ironically diminishing the supply of content available for AI tools to train on.
Some media companies, including The Atlantic, Vox Media, FT Group, the Associated Press, and News Corp, have made deals with AI companies to license portions of their content. It’s worth noting that in May 2025, the Times signed an AI licensing deal with Amazon, which allows the tech company to use the outlet’s content across its platforms.
Reporters and editors eye these deals warily. A week before The Atlantic announced its deal with OpenAI, Jessica Lessin, CEO of tech-journalism outlet The Information, warned against what she saw as a Faustian bargain with AI companies.
The tech companies “attempt to take all of the audience (and trust) that great journalism attracts, without ever having to do the complicated and expensive work of the journalism itself. And it never, ever works as planned,” Lessin wrote.
Generative AI results are only as good as the materials on which the systems are trained. Without a reliable way to distinguish between high- and low-quality input, the output is often compromised. In May 2024, Google unveiled its AI Overview, a tool meant to supplant search results. But it quickly proved flawed. The AI—seemingly regurgitating a twelve-year-old Reddit thread—produced a pizza recipe that included one-eighth of a cup of Elmer’s glue. In response to another query asking how many rocks someone should eat daily, AI Overview said “at least one small rock per day,” apparently sourcing its information from an Onion article.
Mistakes like these make these multibillion-dollar tools seem incapable of even basic common sense.
The AI tools also contain biases that are not so easily visible. Emilio Ferrara, a professor at the University of Southern California and research team leader at the USC Information Sciences Institute, found biases in data used during the training of generative AI, in its learning processes, within the tool’s infrastructure, or during deployment. Some of these biases are implicitly expressed in the selection of training-data texts that contain existing cultural biases, in the types of data collected, and through confirmation bias—the way an AI may be trained to yield particular results. More explicitly, a model may also produce stereotypes.
Generative AI models “may inadvertently learn and perpetuate biases present in their training data, even if the data has been filtered and cleaned to the extent possible,” Ferrara found. Ultimately, these LLMs reflect the biases of the people who program their algorithms and the internet’s complex ecosystem of users and creators—as well as, sometimes, the limited availability of content on a particular topic or authored by a particular group or in a particular language.
The bias can be most profoundly illustrated with image-oriented generative AI tools, which have consistently generated troubling results for nonwhite and non-male subjects. Attempts to correct these biases have thus far been clunky, at best, as when Google’s Gemini was asked to produce an illustration of a 1943 German soldier and generated drawings of Asian and Black Nazis. Or when prompts to illustrate the Founding Fathers resulted in images of people of multiple ethnic backgrounds.
Sometimes, the bias feels almost satirical. The automated-news company Hoodline runs a group of hyperlocal websites based primarily on AI-generated local news feeds and uses AI to generate location-specific reporter personas. Putting the dystopian nightmare of the business model aside, the names the AI generated for its personas reflected stereotypes about the communities they were intended to represent. Boston “reporters” had stereotypically Irish names like “Will O’Brien” and “Sam Cavanaugh,” while San Francisco’s AI-generated staffers were given names reflecting the city’s diversity, among them Leticia Ruiz, Tony Ng, and Erik Tanaka, Nieman Labs reported.
And then there are the user-side biases: primarily, a lack of understanding of AI’s limitations.
The apparent convenience of putting large language models in the hands of consumers who will rely solely on that information is “pretty worrisome,” said Mark Lavallee, the Knight Center’s director of technology, product, and strategy. “If you ask a question a certain way, it’s going to answer it a certain way.”
Nearly everyone agrees that keeping a human “in the loop”—and close to any generative AI use, to monitor for misfires—is a key factor of ethical AI use. But it’s unclear what that will look like in practice. If a journalist uses an AI tool to analyze fifty pages of documents, for example, should the journalist then review all the documents to ensure the synthesis is accurate and unbiased? If the business side of a company sets up a deal for AI-sponsored content, who monitors the result?
Perhaps nobody knows the challenge better than Sports Illustrated. In late 2023, the tech site Futurism noticed that some of SI’s stories were written by people who didn’t exist. One fake byline, Drew Ortiz, had a bio claiming “he grew up in a farmhouse, surrounded by woods, fields, and a creek.” The headshot attached to his profile was an AI-generated image available for purchase on a site called Generated Photos.
When Futurism inquired about the apparently fake writers, the company promptly deleted all content associated with those bylines. In a statement to Futurism, Sports Illustrated revealed that the content had been produced by a company called AdVon, which describes itself as “a digital commerce platform, developing trusted, SEO-optimized, user-centric AI and content solutions.”
SI said AdVon had assured it that “all of the articles in question were written and edited by humans. According to AdVon, their writers, editors, and researchers create and curate content and follow a policy that involves using both counter-plagiarism and counter-AI software on all content.” The fake headshots and bios, AdVon claimed, were “to protect author privacy,” a move SI was quick to clarify they didn’t condone.
The robotic writing in some of the posts raised eyebrows. One of Ortiz’s shopping guides, for “Full-Size Volleyballs,” awkwardly explains: “Even people who don’t watch sports can easily understand the intensity and skill required to play volleyball whenever they watch clips.”
In an all-hands meeting the day after the Futurism article was published, SI executives informed their staff that they had terminated their relationship with AdVon. (Meanwhile, SI’s parent company, Arena Group, publicly disputed the claim that it had published AI-generated work.) The damage was already done. Sports Illustrated, one of the oldest and once most respected sports outlets, lost much of its credibility with staff and readers alike.
“Along with basic principles of honesty, trust, journalistic ethics, etc.—I take seriously the weight of a Sports Illustrated byline. It meant something to me long before I ever dreamed of working here. This report was horrifying to read,” wrote staff writer Emma Baccellieri on X, commenting on Futurism’s story.
Two months later, after Sports Illustrated’s publisher announced it was in “substantial debt,” Baccellieri and nearly all her coworkers were laid off. Most, including Baccellieri, were soon rehired by SI’s new publisher.
Sean McGregor, founding director of the Digital Safety Research Institute and a member of the Partnership on AI, likens companies’ and newsrooms’ use of AI to the experience of riding in a self-driving car. As people become comfortable with the technology, they become inured to its inherent risks.
“There’s a tendency in all places where automation is introduced, where, you know, it’s a great tool, empowering people, and then it gets to a point of adequate performance…where you no longer have the ability, because of the way that our brains work, to pay attention and to safeguard the system,” he said.
Most consumers aren’t yet comfortable with the marriage of AI and news production. In 2023, Benjamin Toff from the University of Minnesota and Felix M. Simon from Oxford University’s Internet Institute surveyed 1,483 people about their attitudes toward AI. Their survey found that more than 80 percent believed news organizations should “alert readers or viewers that AI was used.” Among people who believed consumers should be alerted, 78 percent said news organizations should “provide an explanatory note describing how AI was used.”
AI has the potential to help journalists do their jobs more efficiently. Used wisely, it can be a marvelous reporting tool. But, undeniably, it also has the potential to misinform, falsely cite, and fabricate information. The role of journalists is to expose deception and misinformation, but AI, for all its promise, has made it exponentially more difficult for journalists—and ordinary citizens—to do just that. We would advise newsrooms and journalists to proceed with caution, but it may be too late for that.
Clarification: An earlier version of this article did not include the rehiring, by a new publisher, of most of the Sports Illustrated staff.
| 2025-06-26T00:00:00 |
https://www.cjr.org/analysis/can-ai-tools-meet-journalistic-standards.php
|
[
{
"date": "2025/06/26",
"position": 6,
"query": "AI journalism"
}
] |
|
No Turning Back: AI's Growing Role in News
|
No Turning Back: AI’s Growing Role in News
|
https://www.aspendigital.org
|
[] |
AI's role in news presents many risks, but it also represents an opportunity to fulfill the public service mission of journalism.
|
This illustration was generated by AI.
When generative AI burst into public consciousness, many in the news industry experienced a familiar sense of dread. Social media had decimated newsroom business models over the last decade, and here is yet another set of technologies out to kill them. But that sentiment is misguided. Indeed, AI’s role in news presents many risks to publishers, but—like the advent of the world wide web decades prior—it also represents an opportunity to fulfill the public service mission of journalism.
“No Turning Back: AI’s Growing Role in News” is the second in a series of reports on AI and News from Aspen Digital. It summarizes key insights from our March 2025 gathering in London of top news executives from the UK and Europe. What struck us most is how far things have come since we had a similar meeting in New York last spring. The following are our takeaways, authored by Dr. Felix Simon:
News rooms are using AI, but carefully – Newsrooms are embracing AI but for incremental improvements rather than revolutionary transformation. Most have focused on automating routine tasks like transcription, translation, and headline creation. Many organizations ’have established internal training programs, created specialized AI roles, and identified internal “AI influencers” to encourage adoption and mitigate resistance.
– Newsrooms are embracing AI but for incremental improvements rather than revolutionary transformation. Most have focused on automating routine tasks like transcription, translation, and headline creation. Many organizations ’have established internal training programs, created specialized AI roles, and identified internal “AI influencers” to encourage adoption and mitigate resistance. A shift to “distinctive journalism” – To mitigate the threats from AI presents for news discovery, publishers are focusing on the kind of distinctive journalism that AI cannot easily replicate, including investigative and enterprise reporting, and nuanced analysis.
Is imitation the highest form of flattery? – A central industry dispute involves the use of publishers’ content to train AI systems. Many technology companies have scraped news content without compensation, often justifying this through broad interpretations of fair use doctrine. In response, some publishers advocate for stricter enforcement of existing copyright laws and oppose copyright exemptions that favor AI developers. Proposed solutions include collective licensing arrangements or managed marketplaces to connect AI developers and rights holders.
Do audiences care? – User perspective is a major gap in the industry conversation. Despite frequent references to trust and transparency, limited attention has been paid to how audiences, especially non-expert or marginalized users, experience AI-driven news.
Small but mighty – Smaller media outlets, Global South news organisations, and freelancers are often overlooked in discussions around AI and news.
The report contains more detail and testimonials from key industry players.
| 2025-06-26T00:00:00 |
https://www.aspendigital.org/report/ai-role-in-news/
|
[
{
"date": "2025/06/26",
"position": 8,
"query": "AI journalism"
},
{
"date": "2025/06/26",
"position": 4,
"query": "artificial intelligence journalism"
}
] |
|
How newsrooms around the world use AI
|
How newsrooms around the world use AI: a JournalismAI 2023 global survey — JournalismAI
|
https://www.journalismai.info
|
[
"Charlie Beckett"
] |
A global survey of journalism and artificial intelligence. So much has happened in the world of AI since then and we're excited to share with you some of ...
|
Over the last few months, newsrooms and media organisations from around the world have been completing the second iteration of our JournalismAI survey. We conducted the first one in 2019 and published our findings in a report; New powers, new responsibilities. A global survey of journalism and artificial intelligence. So much has happened in the world of AI since then and we’re excited to share with you some of our preliminary findings in this new and updated research.
This year, we made it a point to reach a more diverse group of participants in terms of size, we invited small and large newsrooms; experience, participants include emerging and legacy organisations; and region; contributions came in from Latin America, Africa, the Middle East and North Africa, Asia Pacific, Europe, and North America. We’re immensely grateful to each and every one of the respondents.
More than 60 newsrooms and media organisations have shared their insights with us so far, with more coming in as we publish this update. The survey includes 35 questions ranging from the technical, to the ethical, the region-specific, and of course, we dedicated a section to generative AI technologies! The survey has been supplemented with great conversations we’ve had with many that have enriched this research.
This article will provide a glimpse of our findings thus far. A more thorough analysis of all the input we receive will follow in the comprehensive report we are publishing this September.
We can tell you that most newsrooms we surveyed have already experimented with generative AI technologies like ChatGPT, but not necessarily to create content. The use cases we’ve learned about are quite diverse: code writing, summaries, enhancing headlines and SEO. One respondent said they were using ChatGPT as a ‘banter buddy’, “Imagine having a trusted companion in ChatGPT, ready to engage in lively banter and brainstorming sessions,” they said.
Most respondents agree that generative AI technologies present a new set of opportunities other AI technologies have not provided, but they are more divided as to whether they also bring a unique set of challenges.
When we asked, “why do you use AI technologies in your newsroom? What do you hope to achieve by using these technologies?” More than half the respondents said they hoped to automate mundane tasks and simplify workflows to free up journalists to engage in “more creative, relevant, and innovative work.”
Limited resources and technical expertise are still the most significant challenges to AI adoption in the newsroom, compared to what respondents said in 2019, but this does not mean hiring more technical people. Many respondents told us that achieving interoperability and synchronisation with other departments was a challenge. It’s also about bridging the knowledge gap between technologists and journalists, in terms of tech skills and journalistic skills as well. This requires a nuanced understanding by the newsroom leadership of the types of training needed for each department. Similarly, the ethical aspect continues to be a central concern. Setting ethical guidelines and debiasing techniques seemed to be the most difficult area for many newsrooms.
For non-English speaking journalists, the challenges are more pronounced. Respondents highlighted language limitations of AI tools in other languages like transcription tools and algorithmic bias is experienced at seemingly higher margins than in English. This has pushed some to develop their own tools in-house, which takes considerable time and resources. One respondent lamented: “Applications used in [news] gathering failed, sometimes while trying to collect Arabic language data, this is why we developed our own internal tool.” In addition, many environments struggle with internet infrastructure and penetration, which makes AI adoption in the newsroom a luxury. Despite those challenges, the enthusiasm – as well as the scepticism – for AI in the newsroom remains high!
The full report will be launched at a yet to be confirmed date in September 2023. Sign up to the JournalismAI newsletter to be the first to know when this report will be launched.
This article was written by Mira Yaseen, Lead Researcher of JournalismAI, and Professor Charlie Beckett, who is leading the project.
| 2025-06-26T00:00:00 |
https://www.journalismai.info/blog/the-great-audience-experiment-a-research-synthesis-and-agenda-y68bj-f7wkk
|
[
{
"date": "2025/06/26",
"position": 12,
"query": "AI journalism"
},
{
"date": "2025/06/26",
"position": 23,
"query": "artificial intelligence journalism"
}
] |
|
Reuters Institute for the Study of Journalism | Reuters Institute ...
|
Reuters Institute for the Study of Journalism
|
https://reutersinstitute.politics.ox.ac.uk
|
[
"Nic Newman",
"Dr Craig T. Robertson",
"Dr Amy Ross Arguedas",
"Dr Richard Fletcher",
"Prof. Rasmus Kleis Nielsen",
"Dr Imke Henkel",
"François Nel",
"Neil Thurman",
"Sina Thäsler-Kordonouri",
"Dr Ayala Panievsky"
] |
Explore the Digital News Report 2025. This year's report offers insights on news influencers, platform changes, AI in journalism, reader revenue, news avoidance ...
|
Search by topic AI and journalism Audience Engagement Business of news Climate journalism Conflict Reporting COVID-19 Data Journalism Foreign correspondence Investigative Journalism Israel-Gaza war Journalism and elections Journalism beats Journalism in exile Journalists at work Local News Media regulation Mental Health Misinformation News Avoidance News podcasts Newsroom Diversity Newsroom Leadership Platforms and social media Polarisation Press Freedom Public Service Media Solutions Journalism Trust In News War in Ukraine Workplace conditions
Search by country Afghanistan Albania Algeria Argentina Armenia Australia Austria Azerbaijan Bangladesh Belarus Belgium Bosnia and Herzegovina Botswana Brazil British Virgin Islands Bulgaria Burkina Faso Cambodia Cameroon Canada Chile China Colombia Costa Rica Croatia Cuba Cyprus Czech Republic Democratic Republic of Congo Denmark Dominican Republic Ecuador Egypt El Salvador Estonia Ethiopia Fiji Finland France Georgia Germany Ghana Greece Guatemala Haiti Honduras Hong Kong Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Japan Jordan Kashmir Kazakhstan Kenya Korea Kyrgyzstan Latvia Lebanon Lesotho Lithuania Luxembourg Malaysia Malta Mexico Mongolia Montenegro Morocco Myanmar Namibia Nepal Netherlands New Zealand Nicaragua Niger Nigeria Northern Macedonia Norway Pakistan Palestine Panama Paraguay Peru Philippines Poland Portugal Qatar Romania Russia Samoa Serbia Singapore Slovakia Slovenia South Africa South Korea Spain Sudan Sweden Switzerland Syria Taiwan Tajikistan Tanzania Thailand Trinidad and Tobago Tunisia Turkey Uganda Ukraine United Kingdom United States Uruguay Venezuela Vietnam Yemen Zambia Zimbabwe
| 2025-06-26T00:00:00 |
https://reutersinstitute.politics.ox.ac.uk/
|
[
{
"date": "2025/06/26",
"position": 33,
"query": "AI journalism"
}
] |
|
EJTA publishes Recommendations for Integrating AI in ...
|
EJTA publishes Recommendations for Integrating AI in Journalism Teaching
|
https://ejta.eu
|
[
"Eufactcheck Launches With Bootcamp In Utrecht"
] |
It provides practical guidance on incorporating AI into journalism curricula while safeguarding the core values of journalistic integrity, transparency, and ...
|
Antwerp / Utrecht, June 26, 2025 — The European Journalism Training Association (EJTA) has released its first comprehensive set of recommendations to help journalism schools across Europe navigate the challenges and opportunities of artificial intelligence (AI) in journalism education.
Titled “Recommendations for Integrating AI in Journalism Teaching”, the document is the result of two years of collaboration by the EJTA AI Taskforce, involving educators from over twenty journalism schools. It provides practical guidance on incorporating AI into journalism curricula while safeguarding the core values of journalistic integrity, transparency, and responsibility.
“With AI rapidly transforming both journalism and education, we saw an urgent need for journalism-specific guidelines,” said Frederik Marain, co-coordinator of the EJTA AI Taskforce. “This document aims to support journalism educators in preparing students for an AI-driven media landscape.”
The publication includes 10 key recommendations, covering both the responsible use of AI in journalistic products and how to effectively embed AI-related skills and knowledge into teaching. Topics include transparency in AI usage, rejecting unreliable AI-detection tools, understanding AI’s ethical challenges, and ensuring students develop a critical understanding of the technology underpinning AI.
“This is just the beginning,” added Shannon Bakker, co-coordinator of the Taskforce. “This version is the “1.0” version. As AI continues to evolve, we encourage feedback and collaboration to refine and expand these guidelines.”
The document is now publicly available on the EJTA website.
| 2025-06-26T00:00:00 |
2025/06/26
|
https://ejta.eu/index.php/2025/06/26/ejta-publishes-recommendations-for-integrating-ai-in-journalism-teaching/
|
[
{
"date": "2025/06/26",
"position": 63,
"query": "AI journalism"
},
{
"date": "2025/06/26",
"position": 66,
"query": "artificial intelligence journalism"
}
] |
AI job growth in Design and Make: 2025 report | Autodesk News
|
Autodesk launches 2025 AI Jobs Report: Demand for AI skills in Design and Make jobs surge
|
https://adsknews.autodesk.com
|
[] |
Mentions of AI in US job listings have surged by 56.1% in 2025 (through April), building on explosive growth in 2023 (+114.8%) and 2024 (+120.6%). What was once ...
|
AI fluency is no longer optional across various Design and Make roles. Mentions of AI in US job listings have surged by 56.1% in 2025 (through April), building on explosive growth in 2023 (+114.8%) and 2024 (+120.6%). What was once a niche skillset is now a core qualification, reshaping hiring across nearly every function—from engineering to marketing to operations.
A new class of roles is emerging—and they’re not all technical. Positions like AI Engineer (+143.2%), Prompt Engineer (+135.8%), and AI Content Creator (+134.5%) are among the fastest growing this year. These roles reflect the rise of an AI-native workforce that blends technical fluency with creativity, communication, and applied insight.
Human skills aren’t being replaced—they’re being revalued. In fact, design has overtaken technical expertise as the most in-demand skill in AI-related job postings. Also in the top 10: communication, collaboration, and leadership. As AI systems become more capable, companies are placing greater value on the human qualities that guide, scale, and govern them—judgment, empathy, and imagination.
Autodesk today released its first AI Jobs Report, offering a detailed look at how artificial intelligence is reshaping the workforce across Design and Make industries—including architecture, engineering, construction, product design, manufacturing, media, and entertainment. The findings show that AI-driven job growth remains strong in 2025, with emerging roles, new skill demands, and regional shifts redefining what it means to be ready for the future of work.
Autodesk’s AI Jobs Report makes one thing clear: the future of work isn’t waiting. It’s here and moving quickly. The winners in this AI-driven economy will be the ones who can merge tech fluency with human creativity, ethics, and leadership.
Conducted in partnership with research firm GlobalData, the report analyzed nearly 3 million job listings across a two-year period and identified four major workforce trends:
AI fluency is on track to become a baseline expectation across the workforce
Mentions of AI in general job listings have skyrocketed: up 114.8% in 2023, up 120.6% in 2024, and up 56.1% year to date in 2025, signaling AI capabilities are no longer confined to technical or specialized roles.
Fluency in AI is quickly becoming a core requirement for career longevity across industries.
AI is creating a new class of jobs—with both technical and non-technical AI roles growing in parallel
From AI Coach to AI Strategist, entirely new roles are starting to gain traction across Design and Make, reflecting growing demand for those who can translate, communicate, scale, and govern AI—not just build it.
Roles in AI product, compliance, and enablement are also accelerating, further signaling the formation of a new, AI-native job class.
The data also shows that technical and non-technical AI roles are growing at similar rates. Listings for AI Engineer (+143.2%) and AI Solutions Architect (+109.3%) surged year over year—tracking closely with non-technical roles like AI Content Creator (+134.5%).
The top 10 fastest growing AI titles in Design and Make industries: AI Engineer: +143.2% AI Content Creator: +134.5% AI Solutions Architect: +109.3% Prompt Engineer: +95.5% AI Systems Designer: +92.6% AI Product Manager: +89.7% AI Coach: +57.7% AI Compliance Manager: +46.0% Machine Learning Engineer: +35.3% AI Strategist: +34.8%
Demand for human-centered skills in AI roles is increasing
In 2025, design skills have surpassed coding, cloud, and other technical competencies to become the most in-demand skill in AI-specific job listings—underscoring the growing importance of human-centered thinking in how AI is built and applied.
Communication, leadership, people, and collaboration skills also land in the top 10, signaling that interpersonal fluency and the ability to lead teams remain essential in AI-driven roles.
The top 10 most in-demand skills for AI roles in Design and Make industries: Design skills Technical skills Application Lifecycle Management skills Communication skills Coding skills People skills Leadership skills Analytical skills Collaboration skills Cloud service skills
Companies hiring for AI roles are looking for more than technical expertise—they’re seeking talent that can bring human ingenuity and strategic judgment to the work. As AI jobs grow, so does the demand for the uniquely human skills that make AI effective.
AI hiring by region
Autodesk’s report looked at the percent change in AI job listings year over year and found that Asia has surged ahead in AI hiring, with job listings growing 94.2% year over year—outpacing North America (+88.9%) and highlighting a widening global divide.
While Asia and North America are leading AI hiring growth, South America lags at 63.4%, raising questions about global AI readiness and talent investment strategies.
For the full 2025 AI Jobs Report and press assets, visit the AI Jobs Report media kit.
Methodology
Autodesk’s AI Jobs Report was conducted in partnership with third-party analytics firm GlobalData and examined nearly 3 million job postings over a two-year period across Design and Make industries—including architecture, engineering, construction, product design, manufacturing, media, and entertainment.
GlobalData used its proprietary Job Analytics platform to track daily job postings from companies globally. It also used its advanced platform to analyze job postings on company career pages and other trusted sources. All data is anonymized and does not include private or individual recruiter listings.
About the results
The data spans three rolling 12-month periods measured from May to April: the 2023 cycle includes postings from May 2022 through April 2023, the 2024 cycle includes postings from May 2023 through April 2024 (1.289 million job listings), and the 2025 cycle includes postings from May 2024 through April 2025 (1.488 million job listings). These totals include both AI-related and general job listings.
“AI-related” roles are defined as those where artificial intelligence is a major component of the position or its primary function—beyond surface-level mentions or general familiarity. This includes roles explicitly centered around AI use, implementation, oversight, and application.
| 2025-06-26T00:00:00 |
https://adsknews.autodesk.com/en/news/ai-jobs-report/
|
[
{
"date": "2025/06/26",
"position": 6,
"query": "AI labor market trends"
},
{
"date": "2025/06/26",
"position": 16,
"query": "future of work AI"
}
] |
|
How Generative AI is Disrupting the Relationship Between ...
|
How Generative AI is Disrupting the Relationship Between the Labor Market and Stocks
|
https://www.chmura.com
|
[
"Chris Chmura",
"James Stinchcomb"
] |
Unlike previous iterations of automation, generative AI enabled the automation of tasks designated for white-collar workers with high educational attainment and ...
|
How Generative AI is Disrupting the Relationship Between the Labor Market and Stocks
The historic link between stock market performance and job postings has broken down amid the rise of generative AI. While investor enthusiasm over AI technologies has sent stock prices soaring - particularly in tech - job postings have plunged, especially in high-wage white-collar sectors like software and finance. This divergence raises questions about whether we’re seeing a fundamental labor market shift, an AI investment bubble, or both.
| 2025-06-26T00:00:00 |
https://www.chmura.com/blog/stock-market-and-job-posting-divergence-the-impact-of-generative-ai-on-the-relationship-between-the-labor-market-and-stocks
|
[
{
"date": "2025/06/26",
"position": 10,
"query": "AI labor market trends"
},
{
"date": "2025/06/26",
"position": 7,
"query": "ChatGPT employment impact"
}
] |
|
Tech Giants Slash Thousands Of Jobs In 2025 Amid ...
|
Tech Giants Like Microsoft, Google, IBM Slash Thousands Of Jobs In 2025 Amid Restructuring, AI Integration
|
https://www.ndtv.com
|
[] |
Tech Companies Layoffs: Major tech companies are cutting thousands of jobs in 2025, driven by economic factors and the increasing integration of AI, which is ...
|
Tech Companies Layoffs: The tech industry is experiencing a major wave of layoffs in 2025, with leading companies like Microsoft, Google, Amazon, and IBM cutting thousands of jobs. This broad restructuring is driven by factors including sluggish revenue growth, global economic instability, and the increasing adoption of artificial intelligence, which is transforming traditional job roles.
Data from Layoffs.fyi indicates over 61,000 tech professionals have been laid off across more than 130 companies this year. Microsoft alone cut 6,000 positions, streamlining management and emphasising engineering over administrative roles. Google let go of hundreds in its Android, Pixel, and Chrome teams, following a voluntary exit programme.
IBM has allegedly laid off 8,000 employees, largely in HR, as AI takes over HR functions. Amazon recently eliminated approximately 100 jobs from its Devices and Services division, and Microsoft plans cuts within its Xbox division.
Bumble layoffs:
Bumble, the online dating platform, is set to lay off around 240 employees, representing approximately 30% of its global workforce. The decision, approved by the board, is part of a strategic realignment to optimize operations. In a securities filing, Bumble stated that these workforce reductions are expected to generate $40 million in annual cost savings. These savings will primarily be reinvested into product and technology development initiatives. The company is based in Austin, Texas.
Microsoft layoffs:
According to Reuters, Microsoft is planning to cut thousands of jobs, particularly in sales, as the tech giant streamlines its workforce amid increased investments in artificial intelligence, citing people familiar with the matter. The latest layoffs follow Microsoft's previous round of job cuts in May, which affected about 6,000 employees.
The tech giant has ramped up its investments in AI, aiming to solidify its leadership as companies across industries accelerate the integration of AI into their products and services to maintain a competitive edge. The layoffs are expected to be announced early next month, following the end of the tech giant's fiscal year. Microsoft had 228,000 workers as of June last year.
| 2025-06-26T00:00:00 |
https://www.ndtv.com/feature/tech-giants-slash-thousands-of-jobs-in-2025-amid-restructuring-ai-integration-8767043
|
[
{
"date": "2025/06/26",
"position": 84,
"query": "AI layoffs"
}
] |
|
How to Develop an Ethical AI Policy for your Newsroom
|
How to Develop an Ethical AI Policy for your Newsroom
|
https://texastipi.org
|
[
"Silvia Dalben Furtado"
] |
With the growing development of generative artificial intelligence systems, journalists all over the world are discussing ethical principles and values to adopt ...
|
With the growing development of generative artificial intelligence systems, journalists all over the world are discussing ethical principles and values to adopt these technologies in the newsroom. One important step in this process is developing guidelines to assist editors and reporters in deciding when and how these innovations can be safely incorporated into journalism practices.
Motivated by this discussion, TIPI recently participated in a panel titled “Developing an Ethical AI Policy for Your Newsroom” at the latest conference organized by the National Institute for Computer-Assisted Reporting (NICAR). The panel, moderated by Darla Cameron, Chief Product Officer at The Texas Tribune, featured four other participants, including Silvia DalBen Furtado, a student affiliate at TIPI and PhD candidate at the School of Journalism and Media at UT Austin.
Currently, Silvia is conducting a study with Tina Lassiter, a PhD student at the School of Information, in which they evaluate journalists’ perceptions about regulations and guidelines on the use of generative AI technologies in US newsrooms. During the panel, they presented the preliminary results of this study, which included a survey (N=310) and in-depth interviews (N=23), that highlighted these key findings:
1. Many journalists are already using or experimenting with generative AI technologies in their routines, and they agree there should be some regulation or guidance regarding its use in newsrooms.
2. Many of them don’t seem to understand the difference between AI and Generative AI. Thus, beyond discussing AI policies, it is essential to clearly explain the historical evolution of AI as a field and examine how AI technologies have shaped journalism practices over decades.
3. Our findings indicate that many AI guidelines have been developed through a top-down approach. However, the reporters and editors who participated in this study expressed a desire for more active involvement in the discussion, advocating for a bottom-up approach.
4. Moreover, journalists express interest in having standardized guidelines established by a consortium of news organizations, rather than develop individually by each newsroom. Many journalists fear that government regulations could lead to censorship of journalistic activities.
| 2025-06-26T00:00:00 |
https://texastipi.org/how-to-develop-an-ethical-ai-policy-for-your-newsroom/
|
[
{
"date": "2025/06/26",
"position": 40,
"query": "artificial intelligence journalism"
}
] |
|
AI and Workers: Artificially Managed, Actually Exploited
|
AI and Workers: Artificially Managed, Actually Exploited
|
https://seecheck.org
|
[
"Faktograf.Hr",
"Croatia",
"Var Molongui_Authorship_Byline_Params",
"Byline_Prefix",
"Byline_Suffix",
"Byline_Separator",
"Byline_Last_Separator",
"Byline_Link_Title",
"View All Posts By",
"Byline_Link_Class"
] |
“AI-driven management is already intensifying pressure on 427 million workers worldwide,” warned the International Trade Union Confederation (ITUC), which ...
|
Original article (in Croatian) was published on 05/02/2025; Author: Anja Vladisavljević
In the age of artificial intelligence, the enormous burden of technological progress is borne by workers, who are increasingly insecure and subjectable to control.
“AI-driven management is already intensifying pressure on 427 million workers worldwide,” warned the International Trade Union Confederation (ITUC), which called for urgent measures to protect workers’ lives and rights in the age of digitalization and artificial intelligence (AI) on the occasion of International Workers’ Memorial Day, 28 April.
On that April day, they reported to have remembered the dead workers and promised to continue fighting for the living. “Technology should work for us, not against us,” they wrote.
One of the most brutal examples of technology turning against workers is the case of Filipino Jasper Dalman, a Foodpanda platform courier who died in a terrible car accident in 2023 while doing his job. His death, according to the ITUC and the Philippine trade union of which Dalman was a member, showed “the deadly consequences of algorithmic exploitation that set impossible productivity targets”.
The tragic case from the Philippines is not isolated. The application of new technologies, the ITUC points out, without proper consultation with workers and their trade unions, is already causing serious violations of workers’ rights. Algorithmic management and the use of AI expose workers to precarious conditions, undermine workplace safety, undermine hard-won labour rights and discriminate against workers.
While May Day beans, distributed at gatherings, in squares and parks, are still being digested, it may be a good time to ask ourselves what it means to be a worker in the era of digitization.
Algorithm the boss
As ITUC points out in its new report (“Artificial intelligence and digitalization: A matter of life and death for workers”), with the development of technology, a multitude of jobs and modes of operation appeared that did not exist before: app-controlled couriers and drivers, content moderators, big data analysts and machine learning engineers.
While in traditional industries and industries there is a boss, manager, supervisor, a line of command and a union that oversee working conditions, in these newer occupations these functions are replaced (or completely abolished) by applications and digital tools.
Platform work is the most obvious example of how technology can be (mis)used against workers. Under the guise of flexibility and simplicity, digital platforms – applications for transport, delivery and other services – use algorithmic management to control workers, while offering them the minimum of the protection they have in traditional employment.
Algorithmic management involves continuous monitoring of workers’ behaviour through devices (e.g. mobile phone) and applications and continuous performance assessment based on collected data (user ratings, task execution speed, number of rejected orders).
Due to constant supervision, workers are under pressure to maintain or increase their efficiency, although very often they do not even know how the algorithms work. At the same time, they do not have much room to complain or seek feedback when faced with unfair treatment, because these are automated ratings and decisions, so they are not communicated with by a living person.
The range of industries where algorithmic management is used is expanding. One of the most famous examples is the Amazon online store where workers are monitored with special scanners to measure their productivity and record errors. In call centres, workers are also supervised by the machine, and some of such software can even automatically analyse and evaluate what workers are saying, what phrases they are using, and whether the mood during the call was “negative” or “positive.”
In the US, nurses are increasingly working through platforms (which connect them to hospitals and healthcare facilities) and are struggling with similar problems as Uber workers. According to a study by the Roosevelt Institute, there are automated metrics in the world of gig nursing that assess their reliability based on the number of shifts they complete, how early they cancel shifts, and whether they stay late at work. Women workers are offered different shifts, often for different amounts of “wages”, and they are often assigned to institutions where they have not worked before.
Algorithm the recruiter
Similar to the above cases, where the technology of supervision of workers is justified using the argument of time and resource effectiveness, it increasingly happens that workers are “scanned” even before they end up in a workplace. Artificial intelligence is also being integrated into recruitment processes and is displacing recruiters who have otherwise reviewed resumes, conducted interviews and made judgments based on experience and impression.
AI-driven tools address the logistics of selecting and scheduling interviews, eliminating time-consuming administrative work. AI can also analyse vast amounts of workforce data to anticipate a particular company’s future hiring needs and identify “ideal candidates” based on the company’s profile.
It can review the candidate’s CV, motivation letter, work experience, but also profiles on social networks, which calls into question their privacy and data security. If job interviews are conducted via a video link, which is no longer rare, facial recognition and voice analysis algorithms can evaluate responses, body language, word choice, and candidate tone, evaluating them against a predefined metric.
As analysed by the American Civil Liberties Union (ACLU), many of these tools pose a huge risk of exacerbating existing workplace discrimination based on race, gender, disability, and many other characteristics, despite marketing claims that they are objective and less discriminatory.
AI tools are trained with a large amount of data and make predictions about future outcomes based on correlations and patterns in that data. The tools used by a particular company can be “fed” with data on the employer’s own workforce and previous recruitment processes, so they can automatically eliminate certain social groups.
For example, if the system is trained on data from a company that employed more men than women, the tool could favour male candidates. Such favouritism can also be achieved in a very banal way, as can be seen in the case described by the BBC.
In one company, an AI resume checker was trained on the resumes of past workers, giving candidates extra credits if they listed baseball or basketball as hobbies because they were associated with “more successful staff,” often men. Candidates who mentioned softball – usually women – were demoted. Another example of bias singled out by the BBC is the case of a candidate who passed the selection process after changing his date of birth on his CV to make himself appear younger (before that change, and with the same application, he was excluded).
In some cases, the BBC explains, the biased selection criteria are clear – such as age discrimination or sexism – but in some they can be very blurry. As in the aforementioned cases of algorithmic management of workers, the lack of transparency is problematic, especially when candidates are rejected without knowing for what reason.
Does the worker help the AI or the AI worker?
At the same time, the potential positive impacts that artificial intelligence can have in the world of labour should be taken into account. As we read in various online sources (1, 2), and this is also not missed by workers’ rights organisations, AI can automate repetitive tasks, increase efficiency and reduce operating costs – freeing workers from monotonous duties and allowing them to focus on more creative work.
But since we are enumerating pros and cons as if we were at school, we cannot omit the most obvious con. One of the primary concerns about AI is the potential loss of jobs. As AI systems become increasingly capable of performing tasks traditionally performed by humans, there is an understandable fear that some occupations will become obsolete.
According to a poll onducted among American workers in January this year, there is widespread recognition of the impact of artificial intelligence on job losses, with 43 percent personally knowing someone who has lost their job due to artificial intelligence, and 89 percent expressing concern about their own job loss.
In September 2023, the first survey on AI perception in Croatia was conducted. For 60 percent of respondents, AI represents a sense of uncertainty or concern, while 30 percent find it useful.
However, in parallel, a perspective emerges that questions the notion of artificial intelligence exclusively as a job eliminator. In some cases, workers retain their jobs, but, contrary to the promise, the implementation of artificial intelligence brings them an increase in workload.
As we wrote earlier, such burdens are felt by workers in the field of culture. Literary translators, for example, are already receiving queries for the so-called post-edit, i.e. editing translations generated by artificial intelligence. This gives them a lot more work because they have to fix errors caused by machine translation.
In journalism, things are similar. If a journalist searches for answers via ChatGPT, they definitely have to go through several more rounds of verification, because this tool, unless well trained, does not distinguish between reliable and unreliable information, and often does not reveal where it got its source from. In principle, it is still difficult to leave AI to perform tasks without human supervision.
After all, the point of some jobs is the growth and development of artificial intelligence. We do not mean IT professionals, but “data workers” who, in stressful and precarious conditions and for low fees, collect, process, recognize, mark, moderate or enter data for the purpose of training and functioning of artificial intelligence systems.
Among them are moderators of social media content who are constantly exposed to toxic and disturbing content, in order to once train artificial intelligence to become more skilled in recognizing this harmful content.
Technology for the workers’ struggle
Finally, let’s return to the ITUC’s message, that technology should work for the workers, not against them. In addition to traditional actions, strikes and protests, which warn of the erosion of workers’ rights through technology and advocate for better legislation, workers and trade unions are considering using AI and digital tools to protect and improve workers’ rights.
As automation in the workplace poses a significant challenge for recruiting workers into the union – as many workers work remotely, through apps, and in short-term jobs – unions must also embrace digital tools to improve their outreach and advocacy.
The United Nations University (UNU) sees technological adaptation as part of the solution. Virtual platforms can connect union representatives with geographically dispersed members, and social media campaigns and targeted digital advertising can raise awareness of union benefits and workers’ rights in AI-driven workplaces.
“The answer to the challenges posed by automation lies in adaptation and innovation. Trade unions must embrace the same technologies that are disrupting the workplace. AI-powered chatbots can facilitate member recruitment and engagement, even reaching workers in traditionally difficult-to-organize sectors like domestic work,” suggests the United Nations University.
Indeed, some have already taken steps. WAO (Workers’ Algorithm Observatory), an initiative from Princeton University that assists workers and their allies in the research and monitoring of algorithmic systems in platform work, has developed tools to explore how algorithmic management affects workers. Through tools such as FairFare and the Shipt calculator, WAO allows workers to anonymously share information about their experiences, thus detecting irregularities in algorithmic wage and working conditions determination.
There are similar ideas on the domestic trade union scene. As Tomislav Kiš from Novi sindikat explained for the European AI & Society Fund, the goal of his organization is to organize domestic and foreign platform workers to pressure the Government into changing existing laws or create new legal solutions.
“To achieve this, we need to strengthen the capacity of workers to organize and express their demands, whether through advocacy or material support. One of our ideas is to develop our own app to control and verify the data managed by the platforms. This would be a first step towards gaining insight into how platforms work and, consequently, limiting the power they develop based on the data collected. Having accurate data would strengthen the bargaining power of trade unions in regulating mutual relations,” Kiš said.
It’s not unusual or unnecessary for much of the public discussion about AI to focus on how it threatens jobs and deepens inequality, but it may be time to change the narrative.
If algorithms can track and control workers, they can also be repurposed to protect them. As we often hear when we talk about artificial intelligence, technology itself is not the problem, the problem is how we use it.
| 2025-06-26T00:00:00 |
2025/06/26
|
https://seecheck.org/index.php/2025/06/26/ai-and-workers-artificially-managed-actually-exploited/
|
[
{
"date": "2025/06/26",
"position": 19,
"query": "artificial intelligence labor union"
}
] |
A Blueprint for an Artificial Intelligence Future
|
A Blueprint for an Artificial Intelligence Future
|
https://www.ccctu.org
|
[] |
Local 1600 and unions everywhere must not wait. This is a moment to lead. The future of academic labor, workplace democracy, and student success depends on our ...
|
Artificial Intelligence (AI) is no longer a distant prospect. It’s already reshaping our work and the curricula of our colleges. In the near future, we could potentially see this technology impact hiring practices, instructional design, student services, and much, much more. That’s why Local 1600 has released a new report: “ Facing the AI Future: A Call to Action for Union Members .”
This report is both a warning and a roadmap. If we act strategically, AI can enhance our work and reaffirm the human mission of education. But if we fail to act, AI will be used to undermine our jobs, erode academic freedom, and automate away the relationships at the heart of teaching and learning.
Key Takeaways from the Report:
Protecting Our Members: We must update our contracts and push for legislation that prevents employers from using AI to replace human educators, professionals, and staff. Collective bargaining must include language on algorithmic oversight, transparency, and human review.
Transforming Our Work (On Our Terms): We must explore forward-looking models, like AI-assisted apprenticeship structures, where AI handles repetitive tasks and frees human workers for higher-value, more creative work. We must demand control over how new technologies are implemented.
Keeping AI Aligned with Human Goals: From hiring software to student success dashboards, algorithms are already shaping decisions (often without accountability). We must fight for audits, transparency, and clear appeals processes to prevent biased or harmful outcomes.
Rethinking Learning: AI will change what students need to learn and how they learn it. Our faculty are already seeing the major impact of AI and are working to consider how to move forward. The report calls for curricula that center critical thinking, creativity, and AI literacy for students and workers.
Seeking Legislative Protections: During the “innovation interim” where change will be rapid and impactful, we must seek protections at the state and federal level. This should include worker protections from displacement, funding for retraining, and requirements for oversight.
Why This Matters to Our Union:
Local 1600 and unions everywhere must not wait. This is a moment to lead. The future of academic labor, workplace democracy, and student success depends on our actions today. AI policy is labor policy. It’s also educational policy.
This report is the beginning of a broader conversation for Local 1600. We’ll be holding meetings and sessions in the coming months to discuss next steps, develop bargaining strategies, and craft model legislative language. We encourage all members to read the report and join the conversation.
Facing the AI Future_ A Call to Action for Union Leadership .pdf Download PDF • 649KB
| 2025-06-26T00:00:00 |
2025/06/26
|
https://www.ccctu.org/post/a-blueprint-for-an-artificial-intelligence-future
|
[
{
"date": "2025/06/26",
"position": 48,
"query": "artificial intelligence labor union"
}
] |
TASC launch major research findings into the possible ...
|
Financial Services Union/ TASC launch major research findings into the possible effects of Artificial Intelligence in the Financial Services Sector.
|
https://www.fsunion.org
|
[] |
The Financial Services Union have today launched the findings of a substantial research project into the possible effects of Artificial Intelligence (AI) in the ...
|
26 June 2025
Job displacement, lack of reskilling opportunities, bias in decision making top list of concerns for workers.
The Financial Services Union have today launched the findings of a substantial research project into the possible effects of Artificial Intelligence (AI) in the Financial Services Sector. The research was undertaken in partnership with TASC, the think tank for social change in Ireland.
The report examined both the opportunities and challenges posed by AI and provides an in-depth analysis of its impact on workers, businesses, and the future of financial services in Ireland.
The findings reveal widespread concern:
88% of respondents believe AI will lead to job displacement and 60% report feeling less secure in their roles than they did five years ago. While many workers acknowledge AI’s potential benefits, including increased efficiency and improved decision-making, these advantages are overshadowed by fears of job loss, wage stagnation, and intensified managerial oversight.
Over 61% of respondents expressed unease about AI being used in hiring, firing, and promotion decisions. Furthermore, 58% of workers are concerned about increased managerial oversight and surveillance through AI systems, fearing a loss of privacy and greater performance monitoring.
Despite these concerns, some workers recognised AI’s positive impacts. Around 45% of respondents feel AI may lead to less time spent on administrative tasks and 30% feel it may improve data analytics.
Commenting on the research findings John O’Connell, General Secretary of the FSU said:
“The research is indicative of the concerns the FSU are hearing on a weekly basis from workers across the sector.
The use of artificial intelligence is expanding at an alarming rate across the financial services sector, and it is incumbent on all key stakeholders to ensure AI is used for the benefit of workers and consumers.
It is evident that workers feel unprepared and have justified concerns about the role that AI could possibly play in the future.
Ensuring a fair transition requires a shared commitment from all stakeholders—employers, workers, policymakers, and trade unions.
The FSU have successfully concluded an AI agreement with Bank of Ireland (BOI) which commits the bank to collectively bargain any changes that may occur due to the expansion of AI.
A collaborative approach such as that reached with BOI will not only help mitigate job displacement risks but also create opportunities for innovation, career growth, and economic stability.
This research confirms that AI is not just a technological development: it is a major social and economic shift. Successful AI integration must centre around more than profits and productivity by accounting for the wider disruptions it causes, including to workers’ rights, job security, and the environment.
We look forward to discussing the findings of this research with legislators and opinion makers in the sector.”
Commenting Molly Newell, researcher at TASC said
“As a leader in the European financial services sector, Ireland has a responsibility to be at the forefront of a fair and responsible AI transition - one that safeguards rights, promotes inclusion, and shares the benefits of innovation.
A just transition means placing workers at the heart of decision-making. That includes ensuring collective bargaining, preventing bias and intrusive surveillance by employers, and providing meaningful upskilling opportunities.
Without clear commitments to equity, inclusion, and transparency, the widespread adoption of AI in financial services risks deepening existing inequalities. We must ensure this technology serves the common good - strengthening, rather than undermining, social and economic cohesion.”
ENDS
- John O Connell, FSU General Secretary, is available for interview.
- Report: https://www.fsunion.org/latest/accounting-forworkersin-the-age-of-ai/
| 2021-06-10T00:00:00 |
2021/06/10
|
https://www.fsunion.org/latest/news/financial-services-union-tasc-launch-major-research-findings-1/
|
[
{
"date": "2025/06/26",
"position": 56,
"query": "artificial intelligence labor union"
}
] |
Ayres says Government AI plan includes role for unions
|
Ayres says Government AI plan includes role for unions
|
https://csirostaff.org.au
|
[
"Anthony Keenan"
] |
... Artificial Intelligence (AI) will protect local workers and industries alike. Meanwhile, Chief Executive Doug Hilton has spruiked a role for CSIRO as part ...
|
Science Minister Tim Ayres has pitched the potential productivity benefits of Artificial Intelligence, while insisting that unions have a role to play in representing the rights of workers during the introduction of the new technology.
That’s a challenge the movement is gearing up to accept, with senior union leaders stating that responsible regulation of Artificial Intelligence (AI) will protect local workers and industries alike.
Meanwhile, Chief Executive Doug Hilton has spruiked a role for CSIRO as part of the Federal Government’s larger challenge to boost economic productivity across the Australian economy.
Lean in to AI
In comments to an AI summit in Sydney earlier this month, Minister Ayres said Australia must “lean in, to secure a stake in global digital and AI development”.
“The Australian challenge is to lean in to adopt AI to lift productivity and living standards, deliver investment in infrastructure and capability and protect our security… other countries in the region are moving fast and so must we.”
The Minister said that the government would work with trade unions to “make sure that AI adoption makes jobs better”, adding that “confidence in AI adoption is key” and could be built by upskilling Australians.
Role for unions
“I will be looking in particular at how we can strengthen worker voice and agency as technology is diffused into every workplace in the Australian economy and I look forward to working with our trade union movement on all of this,” Minister Ayres said.
It’s an approach welcomed by the union movement. “We want to work with employers and government to realise the positive ambition,” ACTU secretary Sally McManus said.
“To achieve good adoption of AI, Australia needs responsible regulation which both protects Australian workers and Australian industries from malicious use and theft by overseas big tech,” Ms McManus said.
Fork in the road
Meanwhile, CSIRO Chief Executive Doug Hilton welcomed the policy focus on Australia’s productivity challenge, but says it presents the government with some stark choices in the funding of science.
In an interview with InnovationAUS, Dr Hilton said the challenges of falling government funding and business investment in research and development were not new, but they had become more urgent.
“It’s a fork in the road for Australia. We have an opportunity to consider the role of science in our national life in a way that is pretty stark,” Dr Hilton said.
CSIRO can help
“If I think about what CSIRO does for many different sectors of Australian industry, the two things that come to mind are productivity improvement and sustainability.”
“If we want Australia to be prosperous, if we want to maintain the standard of living for our kids and our grandkids, then we really need science and ideas to drive that productivity.”
“And CSIRO can certainly help. That’s not the only part of the (productivity) solution, but we can certainly help,” he said.
Related content
| 2025-06-26T00:00:00 |
2025/06/26
|
https://csirostaff.org.au/news/2025/06/26/ayres-says-government-ai-plan-includes-role-for-unions/
|
[
{
"date": "2025/06/26",
"position": 74,
"query": "artificial intelligence labor union"
}
] |
European Union AI Act: Meaning, Regulations, risks, and ...
|
European Union AI Act: Meaning, Regulations, risks, and compliance
|
https://www.scrut.io
|
[
"Susmita Joseph",
"Authored By"
] |
The EU Artificial Intelligence Act (AI Act) is the European Union's first comprehensive regulatory framework for AI, aiming to ensure that AI systems are safe, ...
|
As artificial intelligence (AI) continues to rapidly evolve, regulators are stepping up to ensure its responsible use. The EU Artificial Intelligence Act (AI Act) is the European Union's first comprehensive regulatory framework for AI, aiming to ensure that AI systems are safe, ethical, and aligned with fundamental rights.
In this blog, we explore the AI Act's key provisions, including its focus on general-purpose AI models, risk categories, and prohibited practices, along with its broader implications for organizations navigating the complex regulatory landscape.
What is the EU Artificial Intelligence (AI) Act?
The EU Artificial Intelligence Act, formally known as Regulation (EU) 2024/1689, is the European Union's first comprehensive legal framework for artificial intelligence. It establishes harmonized rules for the development, placement on the market, and use of AI systems across the EU, aiming to ensure that AI is safe, respects fundamental rights, and upholds the Union's values.
Introduced by the European Commission in April 2021 and formally adopted by the European Parliament and the Council in 2024, the Act entered into force on August 1, 2024. Non-compliance can result in substantial administrative fines, including up to €35 million or 7% of a company's global annual turnover for the most serious violations, such as using prohibited AI systems.
Providers, deployers, importers, and distributors of AI systems are responsible for compliance. They are expected to implement internal controls, maintain documentation, and ensure conformity before placing systems on the market.
From the Union's side, national authorities carry out market surveillance and enforcement actions, while the AI Office coordinates oversight efforts across Member States, especially for cross-border and high-risk AI use cases.
What role does the General-purpose AI model play?
General-purpose AI (GPAI) refers to an AI model that demonstrates significant generality and can competently perform a wide range of tasks, regardless of how it is marketed or integrated into various systems.
The role of GPAI models is to offer a versatile, scalable foundation that can be applied across industries and integrated into various downstream AI systems. While they may not be inherently high-risk, they can become part of high-risk systems, and providers are expected to cooperate to ensure compliance with the AI Act.
Rules for GPAI models under Regulation (EU) 2024/1689 include:
1. Technical documentation: Providers must create detailed documentation covering the model's training, testing, and evaluation results.
2. Information for downstream providers: Providers must supply essential information to those integrating the GPAI model to ensure an understanding of its capabilities and limitations.
3. Copyright compliance: Providers must respect the EU Copyright Directive and ensure compliance.
4. Training data transparency: A summary of the content used for training the model must be publicly available.
5. Free and open licenses: GPAI models under open licenses must comply with the above three obligations unless they are deemed systemic.
6. Systemic risks: If the model meets the threshold of over 1025 floating point operations (FLOPs) used in training, it is considered to present systemic risks, requiring additional measures:
Who does the EU AI Act apply to?
The EU AI Act applies to a wide range of actors involved in the development, deployment, and distribution of artificial intelligence systems within the EU market, regardless of whether they are based in the EU or outside. The regulation takes a lifecycle approach, assigning specific responsibilities to each actor based on their role, to ensure that AI systems placed on the EU market are trustworthy and safe.
1. Providers
A provider is any natural or legal person, public authority, agency, or other body that develops an AI system or a general-purpose AI model and places it on the market or puts it into service under its own name or trademark.
Providers are at the core of the EU AI Act's compliance structure. They are responsible for ensuring that AI systems meet all relevant legal requirements before being placed on the EU market. This includes implementing risk management procedures, drawing up technical documentation, undergoing conformity assessments (for high-risk AI), and ensuring transparency.
The developments in AI especially the increasing complexity and autonomy of systems have made it necessary to hold providers accountable for design choices and training practices from the outset.
2. Deployers
A deployer is any entity or individual that uses an AI system in a professional capacity within the EU, excluding personal non-professional use.
Deployers are responsible for using AI systems in line with their intended purpose and for ensuring that any obligations related to transparency, human oversight, or accuracy are respected in their specific use context. As AI use grows across sectors like healthcare, HR, and finance, deployers play a crucial role in how AI impacts end-users and society. The EU AI Act reflects this by requiring deployers especially of high-risk systems to implement appropriate safeguards and monitor AI performance in real-world settings.
3. Importers
An importer is any natural or legal person based in the EU who places on the market an AI system developed by a provider established outside the EU.
Importers act as the bridge between non-EU AI developers and the European market. They are required to ensure that the foreign-developed AI systems comply with EU law before distribution. This includes verifying that conformity assessments have been completed, the necessary technical documentation exists, and instructions for use are available. With the EU AI Act setting a high bar for safety and rights protections, importers share the responsibility of ensuring that AI systems from outside the EU meet these expectations.
What are some prohibited AI practices?
The EU AI Act sets clear boundaries by explicitly banning certain uses of artificial intelligence that pose unacceptable risks to fundamental rights, safety, and democratic values. These prohibited practices are considered so harmful that they are not permitted under any circumstances within the EU.
AI systems that use subliminal techniques to distort a person's behavior in a way that causes or is likely to cause physical or psychological harm
AI systems that exploit the vulnerabilities of a specific group due to age, disability, or socioeconomic situation, with the intent to materially distort their behavior
Real-time remote biometric identification systems in publicly accessible spaces for law enforcement purposes (with narrow exceptions such as searching for specific victims or preventing an imminent threat)
AI systems used for social scoring by public authorities that lead to detrimental treatment of individuals or groups in a way that is unjustified or disproportionate
AI systems that evaluate or classify people based on behavior or characteristics, resulting in unjustified or disproportionate consequences
AI systems used by law enforcement to make predictions solely based on profiling, location, or past criminal behavior
Emotion recognition systems used in workplaces or educational institutions, except in specific circumstances justified by law
The untargeted scraping of facial images from the internet or CCTV footage to create or expand facial recognition databases
What are the AI Act Risk levels?
The EU Artificial Intelligence Act (Regulation (EU) 2024/1689) adopts a risk-based approach to regulating AI, grouping AI systems into four categories based on the level of risk they pose to fundamental rights, health, safety, and society. The compliance obligations for each category vary stricter rules apply to higher-risk systems, while minimal-risk systems are largely exempt. Understanding these categories is essential for both AI providers and deployers to align with the regulatory requirements.
1. High-risk AI systems
These are AI systems that can significantly impact people's lives, particularly in safety-critical sectors or fundamental rights contexts. High-risk systems are subject to strict requirements such as risk management, high-quality data governance, technical documentation, human oversight, and post-market monitoring.
Use cases include:
AI used in medical devices and diagnostic tools
AI for recruitment and employee evaluation
Credit scoring or loan approval systems
AI in critical infrastructure, like transport or energy
AI used in education for student assessments
Organizations developing or using high-risk AI must adopt a robust risk management framework, maintain high-quality training data, document the system's capabilities and limitations, and ensure human oversight is built into the system.
Pre-market conformity assessments and continuous post-market monitoring are essential. Cross-functional collaboration between compliance, engineering, and product teams is critical for fulfilling these requirements.
2. Unacceptable-risk AI systems
These systems are considered a clear threat to citizens' rights and freedoms and are therefore prohibited under the Act. The ban is absolute, with very limited exceptions for law enforcement under strict safeguards.
Use cases include:
Social scoring by governments or corporations
AI that exploits vulnerable individuals (e.g., children or disabled persons)
Biometric categorization based on sensitive characteristics (e.g., race, religion, political beliefs)
Emotion recognition in workplaces or educational institutions
Indiscriminate scraping of biometric data from CCTV for facial recognition
The only way to comply is to avoid these practices altogether. Organizations must conduct thorough due diligence when designing or procuring AI systems to ensure that none of the functionalities fall into this category.
If there's a borderline case, seek expert legal advice early in the development lifecycle to mitigate legal and reputational risks.
3. Limited-risk AI systems
These are AI systems that pose some risk but not enough to trigger full regulation. The main obligation here is transparency users must be informed that they are interacting with an AI system or viewing AI-generated content.
Use cases include:
Chatbots and virtual assistants
AI-generated images, videos, or audio (e.g., deepfakes)
Recommender systems on e-commerce or media platforms
Transparency obligations include disclosing when content is AI-generated and informing users that they are communicating with a machine. A clear user interface design and accurate labeling can help organizations fulfill these requirements.
Although the rules are lighter here, ethical use and documentation are still advisable for trust and accountability.
4. Minimal-risk AI systems
These systems are considered low-risk and are exempt from legal obligations under the Act. They are still encouraged to follow voluntary codes of conduct and ethical AI principles.
Use cases include:
AI spam filters in email clients
AI used for weather prediction
AI in video games for character behavior or world generation
Even in the absence of legal obligations, organizations are encouraged to voluntarily uphold transparency, fairness, and privacy best practices. Doing so can future-proof systems and strengthen user trust, especially as public expectations and future regulations evolve.
What are some related laws affecting AI?
While the EU Artificial Intelligence Act (Regulation (EU) 2024/1689) is the cornerstone of AI regulation in the region, it does not operate in isolation. Several other EU laws complement and intersect with it to ensure a comprehensive regulatory approach. These frameworks address areas such as liability, privacy, product safety, and consumer protection each playing a critical role in governing how AI systems are developed, deployed, and used.
1. AI Liability Directive (AILD)
The proposed AI Liability Directive aims to harmonize rules for non-contractual civil liability related to AI systems. It introduces a rebuttable presumption of causality to ease the burden of proof for victims seeking compensation for damages caused by AI. However, as of March 2025, the European Commission has withdrawn the proposal from consideration, leaving its future uncertain.
2. General Data Protection Regulation (GDPR)
The GDPR (Regulation (EU) 2016/679) governs the processing of personal data within the EU. It mandates that organizations obtain explicit consent for data collection, ensure data accuracy, and uphold individuals' rights to access, rectify, and erase their data. For AI systems processing personal data, GDPR compliance is essential to protect user privacy and maintain trust.
3. Product Liability Directive (PLD)
The revised Product Liability Directive (Directive (EU) 2024/2853) modernizes liability rules to encompass digital products, including AI systems. It expands the definition of product to cover software and AI, shifts the burden of proof to manufacturers in certain cases, and allows claims for psychological harm and data loss. This directive ensures that consumers can seek compensation for damages caused by defective AI products.
4. General Product Safety Regulation (GPSR) 2023/988/EU
The GPSR, effective from December 13, 2024, replaces the previous General Product Safety Directive. It aims to ensure that all consumer products, including those incorporating AI, are safe for use. The regulation introduces stricter safety requirements, mandates clear product information, and enhances market surveillance to protect consumers from hazardous products.
What's the current status of the EU AI Act?
In June 2024, the EU adopted the world's first rules on artificial intelligence. The Artificial Intelligence Act (AI Act) officially entered into force on 1 August 2024, with its provisions coming into effect gradually to give stakeholders time to adapt. While the regulation will be fully applicable 24 months after entry into force, several obligations kick in earlier particularly those relating to unacceptable risk and general-purpose AI (GPAI) models.
Here's a quick overview of the key compliance milestones:
2 February 2025 : The ban on AI systems posing unacceptable risk begins to apply. This includes systems that manipulate human behavior, exploit vulnerabilities, or implement social scoring.
: The ban on AI systems posing unacceptable risk begins to apply. This includes systems that manipulate human behavior, exploit vulnerabilities, or implement social scoring. 2 May 2025 (nine months after entry into force): Codes of practice are expected to be adopted for providers of GPAI, offering voluntary compliance guidance before harmonized standards are finalized.
(nine months after entry into force): Codes of practice are expected to be adopted for providers of GPAI, offering voluntary compliance guidance before harmonized standards are finalized. 2 August 2025 : Rules on general-purpose AI models will apply to new GPAI models placed on the market. Existing models (i.e., those available before this date) have until 2 August 2027 to meet these requirements.
: Rules on general-purpose AI models will apply to new GPAI models placed on the market. Existing models (i.e., those available before this date) have until 2 August 2027 to meet these requirements. 2 August 2026 : Rules for high-risk AI systems come into effect. These cover systems used in sensitive areas such as hiring, law enforcement, healthcare, and critical infrastructure.
: Rules for high-risk AI systems come into effect. These cover systems used in sensitive areas such as hiring, law enforcement, healthcare, and critical infrastructure. 2 August 2027: Provisions apply to AI systems considered products or safety components of products already regulated under specific EU product safety laws (e.g., machinery or medical devices).
In summary, while the AI Act is already in force, organizations have staggered deadlines depending on the AI system's category and function. High-risk AI providers, in particular, have a 36-month window to ensure full compliance, ending in August 2027. Until then, businesses, regulators, and civil society groups are preparing for one of the most significant digital policy shifts in recent history.
What are some of the best AI frameworks and standards?
Apart from the EU AI Act, several global frameworks help organizations build, secure, and govern responsible AI systems, such as:
1. ISO 42001
ISO 42001 is a certifiable standard that guides organizations in managing AI risks through structured policies, controls, and continuous improvement.
2. NIST AI RMF
NIST AI RMF is a voluntary framework to help organizations govern and reduce AI risks, focusing on fairness, transparency, and security.
3. OWASP AI Security and Privacy Guide
The OWASP AI Security and Privacy Guide provides actionable best practices to secure AI systems and protect privacy, from threat modeling to incident response.
4. Google's Secure AI Framework
Google's Secure AI Framework emphasizes safe AI development and deployment, with principles like security by design and continuous monitoring.
Futureproof your AI compliance with Scrut
As AI regulations evolve and new frameworks emerge, keeping up and staying compliant can feel like a moving target. Scrut helps your organization stay ahead of the curve by centralizing AI risk management, automating evidence collection, and aligning your controls with global standards.
Whether you're navigating the EU AI Act or preparing for future audits, Scrut ensures you're not just reacting to change you're ready for it. Schedule a demo today to learn more.
FAQs
When was the EU AI Act passed?
The EU AI Act was passed on March 13, 2024, by the European Parliament. It was subsequently approved by the EU Council on May 21, 2024. The Act was published in the EU Official Journal on July 12, 2024, and entered into force on August 1, 2024.
Is AI safe?
AI safety depends on how it's built and governed. Regulations like the EU AI Act set rules for high-risk and generative AI to ensure transparency, accountability, and user protection.
What is the purpose of the European Union?
The European Union aims to promote economic cooperation, peace, and human rights across its member states. The European Commission is responsible for proposing and passing legislation like the EU AI Act.
How are the big AI companies regulated under the EU AI Act?
Big AI companies like Meta, Google, Microsoft, and ChatGPT are regulated based on the risk level of their AI systems. They must comply with the EU AI Act's provisions for high-risk AI, ensuring transparency, accountability, and safety standards are met.
What penalties can companies face under the EU AI Act?
Companies can face penalties of up to $35 million or 7% of their annual revenue, whichever is higher, for non-compliance with the EU AI Act.
What is the AI Regulation Agreement done by some EU Countries?
Germany, France, and Italy agreed on AI regulation, focusing on mandatory self-regulation for foundation models and promoting transparency and accountability. The agreement targets all AI providers, including smaller companies, with potential future penalties for non-compliance, while emphasizing the regulation of AI applications rather than the technology itself.
| 2025-06-26T00:00:00 |
https://www.scrut.io/post/eu-artificial-intelligence-ai-act
|
[
{
"date": "2025/06/26",
"position": 83,
"query": "artificial intelligence labor union"
}
] |
|
Artificial Intelligence
|
Artificial Intelligence
|
https://www.filene.org
|
[] |
As the digital landscape and emerging technology continues to evolve, credit unions must assess the potential benefits of using artificial intelligence…
|
Over the last 50 years we’ve experienced a time of rapid growth and change when it comes to technology and how it has impacted not only our everyday lives but also credit union business models. Recently OpenAI released ChatGPT which according to UBS research, "is the fastest-growing consumer application in history." Generative AI like ChatGPT is a true game changer for the financial services industry when it comes to driving efficiency through talent and process automation, enhanced member experience, while also posing potential security risks.
Depending on where your credit union is in the AI journey, Filene has you covered. We invite you to explore our current research insights and trends on the topic of artificial intelligence to help give you the information you need to implement the right AI strategy at your institution.
| 2025-06-26T00:00:00 |
https://www.filene.org/research/topics/artificial-intelligence
|
[
{
"date": "2025/06/26",
"position": 89,
"query": "artificial intelligence labor union"
}
] |
|
Expected impact of technology adoption on jobs worldwide ...
|
Expected impact of technology adoption on jobs worldwide 2023-2027
|
https://www.statista.com
|
[
"Ahmed Sherif",
"Jun"
] |
In the next five years, the overall work scenario expects the increasing implementation of new technologies.
|
Expert resources to inform and inspire.
See why Statista is the trusted choice for reliable data and insights. We provide one platform to simplify research and support your strategic decisions. Learn more
Statista R identifies and awards industry leaders, top providers, and exceptional brands through exclusive rankings and top lists in collaboration with renowned media brands worldwide. For more details, visit our website.
Transforming data into content marketing and design:
Strategy and business building for the data-driven economy
Statista+ offers additional, data-driven services, tailored to your specific needs. As your partner for data-driven success, we combine expertise in research, strategy, and marketing communications.
Directly accessible data for 170 industries from 150+ countries and over 1 million facts:
Detailed information for 39,000+ online stores and marketplaces
Insights on consumer attitudes and behavior worldwide
Market forecast and expert KPIs for 1000+ markets in 190+ countries & territories
All key figures about countries and regions
Detailed information about political and social topics
Consumer and brand insights and preferences in various industries
Key figures and rankings about companies and products
Industry and market insights and forecasts
Overview and forecasts on trending topics
Advertisement
Advertisement
Log in or register to access precise data. Get access now
Please create an employee account to be able to mark statistics as favorites. Then you can access your favorite statistics via the star in the header. Register now
Currently, you are using a shared account. To use individual functions (e.g., mark statistics as favourites, set statistic alerts) please log in with your personal account. If you are an admin, please authenticate by logging in again. Login
To download this statistic in XLS format you need a Statista Account
To download this statistic in PNG format you need a Statista Account
To download this statistic in PDF format you need a Statista Account
To download this statistic in PPT format you need a Statista Account
As a Premium user you get access to the detailed source references and background information about this statistic.
As a Premium user you get access to background information and details about the release of this statistic.
As soon as this statistic is updated, you will immediately be notified via e-mail.
… to incorporate the statistic into your presentation at any time.
You need at least a Starter Account to use this feature.
Want to see numerical insights? Login or upgrade to unlock hidden values.
Access all statistics starting from $2,388 USD yearly *
* For commercial use only Basic Account For single users $0 USD Always free Access limited to Free Statistics. Premium Statistics are not included. Free Statistics Based on your interests Starter Account For single users $199 USD per month, billed annually 1 Buy now Free Statistics
Premium Statistics The statistic on this page is a Premium Statistic and is included in this account. Professional Account For teams of up to 5 people $1,299 USD per month, billed annually 1 Buy now Free + Premium Statistics
Reports
Market Insights Compare accounts
Access all statistics starting from $2,388 USD yearly * * For commercial use only Basic Account For single users $0 USD Always free Access limited to Free Statistics. Premium Statistics are not included. Free Statistics Based on your interests Starter Account For single users $199 USD per month, billed annually 1 Buy now Free Statistics
Premium Statistics The statistic on this page is a Premium Statistic and is included in this account. Professional Account For teams of up to 5 people $1,299 USD per month, billed annually 1 Buy now Free + Premium Statistics
Reports
Market Insights Compare accounts Learn more about how Statista can support your business. Request webinar
World Economic Forum. (April 30, 2023). Expected impact of technology adoption on jobs worldwide from 2023 to 2027 [Graph]. In Statista . Retrieved July 15, 2025, from https://www.statista.com/statistics/1382997/impact-on-jobs-technology-adoption-forecast/
World Economic Forum. "Expected impact of technology adoption on jobs worldwide from 2023 to 2027." Chart. April 30, 2023. Statista. Accessed July 15, 2025. https://www.statista.com/statistics/1382997/impact-on-jobs-technology-adoption-forecast/
World Economic Forum. (2023). Expected impact of technology adoption on jobs worldwide from 2023 to 2027 . Statista . Statista Inc.. Accessed: July 15, 2025. https://www.statista.com/statistics/1382997/impact-on-jobs-technology-adoption-forecast/
World Economic Forum. "Expected Impact of Technology Adoption on Jobs Worldwide from 2023 to 2027." Statista , Statista Inc., 30 Apr 2023, https://www.statista.com/statistics/1382997/impact-on-jobs-technology-adoption-forecast/
World Economic Forum, Expected impact of technology adoption on jobs worldwide from 2023 to 2027 Statista, https://www.statista.com/statistics/1382997/impact-on-jobs-technology-adoption-forecast/ (last visited July 15, 2025)
Expected impact of technology adoption on jobs worldwide from 2023 to 2027 [Graph], World Economic Forum, April 30, 2023. [Online]. Available: https://www.statista.com/statistics/1382997/impact-on-jobs-technology-adoption-forecast/
| 2025-06-26T00:00:00 |
https://www.statista.com/statistics/1382997/impact-on-jobs-technology-adoption-forecast/
|
[
{
"date": "2025/06/26",
"position": 7,
"query": "job automation statistics"
}
] |
|
Top 16 IT Automation Trends, Predictions & Stats in 2025
|
Top 16 IT Automation Trends, Predictions & Stats in 2025
|
https://research.aimultiple.com
|
[] |
Gartner forecasts that 30% of enterprises will automate more than half of their network activities by 2026, highlighting a major shift toward automated network ...
|
Great business and IT leaders invest in areas that will be valuable in the future and avoid hyped-up tech that do not deliver results.
Knowing these IT automation trends can help business and IT leaders to unlock the full benefits of IT automation. Certain trends touch every aspect of IT automation and should be considered by all practitioners:
Common IT automation trends
IT automation enables organisations to automate repetitive tasks in IT operations, integrate systems and manage infrastructure by deploying various tools. Figure 1 shows the upward trajectory of interest in IT automation since 2011, pointing out the gradual recognition of its potential its potential to drive operational efficiency.
1- Artificial Intelligence (AI) & machine learning (ML)
90%of enterprise apps and software are expected to use AI by 2025. 61% of ML applications are in the automation market.
AI and ML technologies empower IT automation tools to autonomously learn and adapt, forming intelligent automation solutions. These tools analyze data, make decisions, and automate complex tasks to optimize business processes and enhance system performance. In fact, 50% of enterprises are projected to adopt AI orchestration platforms, a sharp rise from under 10% in 2020.
The ways AI/ML transforms IT automation efforts include:
Automated machine learning ( AutoML ) refers to automated processes that apply ML to real-world problems. AutoML can help data scientists in daily operations and increase efficiency. The autoML market is expected to grow by 43.7% until 2030.
( ) refers to automated processes that apply ML to real-world problems. AutoML can help data scientists in daily operations and increase efficiency. The autoML market is expected to grow by 43.7% until 2030. ML in test automation : ML algorithms and techniques can improve various aspects of test automation, such as test case generation, test case execution, and test data management.
ML algorithms and techniques can improve various aspects of test automation, such as test case generation, test case execution, and test data management. Intelligent document processing (IDP): allows businesses to automate document processes, including unstructured data such as PDFs and images, by leveraging natural language processing (NLP), optical character recognition (OCR), and robotic process automation (RPA).
2- Generative AI (GenAI)
The recent development in generative AI have also boosted interest and adoption in GenAI models. 97% of businesses are interested in developing GenAI models while 72% of businesses have already adopted data and ML pipelines to improve their GenAI strategies. The most preferred GenAI applications include:
Building integrations via API by 52%
Self-service automation for citizen users by 50%
Chat-based service support by 49%
Workflow creation by 45%
Error handling by 39%.
Figure 2: The most preferred GenAI capabilities across IT automation platforms. (Source 3)
3- Agentic AI
By 2028, 33% of enterprise software applications are expected to include agentic AI, allowing 15% of day-to-day work decisions to be made autonomously.
This growing adoption reflects how Agentic AI has been transforming IT automation by allowing systems to operate independently, make real-time decisions, and execute tasks without human intervention. Major players like Oracle and SAP have adopted Agentic AI in their platforms.
These intelligent agents process large volumes of data, detect anomalies, and take corrective actions, greatly enhancing efficiency and responsiveness in IT operations. A primary use of Agentic AI in IT automation is security monitoring and incident response.
For example, AI agents in financial institutions can detect fraudulent transactions, freeze affected accounts, and trigger investigations without manual oversight. Similarly, in IT operations, autonomous AI can monitor system performance, detect failures, and initiate recovery processes before issues escalate.
To maximize the benefits of Agentic AI, IT automation systems must be built on robust workflow engines that can integrate seamlessly across IT and business applications. This ensures AI agents operate with agility, precision, and adaptability, leading to more resilient and intelligent automation frameworks.
Explore more on agentic AI use cases and examples, such as agentic process automation to understand their impact on IT automation.
4- Hyperautomation
Every few years, vendors or analysts come up with new terms for existing concepts when the existing technologies fail to live up to the expectations. Hyperautomation is the new name for automation promoted by Gartner.
It specifically refers to automating end-to-end business processes, including structured and unstructured tasks, by combining AI/ML and multiple automation technologies, such as:
Business process automation (BPA)
RPA
Workflow automation
IT automation.
Almost all IT decision-makers consider automation a critical factor in their digital transformation strategy. Hyperautomation can accelerate digital transformation, ensuring higher efficiency, productivity, and agility levels.
5- No-code/Low-code automation
The low-code statistics show that 70% of new applications will use low-code or no-code technologies by 2025.
Low-code/ no code automation empowers non-technical users to create applications and automated processes without extensive programming knowledge. Low-code automation platforms provide visual interfaces and pre-built components that enable business users to drag and drop elements, define workflows, and configure automation logic.
No-code/ low-code automation helps mainly IT tasks and activities,such as:
Configuration by creating AI-driven workflows for business needs.
by creating AI-driven workflows for business needs. Monitoring and management by overseeing AI systems with a conversational interface.
These tools enable citizen developers to manage digital business initiatives, democratizing and streamlining the automation process with less automation spending.
6- Self-service automation
The widespread adoption of automation across IT, cloud, data, development, and business teams signifies that self-service automation is becoming a mainstream solution. Organizations are integrating automation deeply into their enterprise-wide operational strategies. In fact, 88% of a survey respondents claimed to offer self-service automation to their organisations in this year. (Source 3)
Figure 3: Self-service automation platforms usage by each functional role.(Source 3)
Previously, employees had to wait for IT requests to be completed, leading to delays, missed deadlines, and decreased productivity. However, with self-service automation, end-users can operate independently while IT operations teams retain centralized visibility and control.
7- Centralised management
The popularity of centralized scheduling and orchestration solutions is rising due to their ability to enhance speed, flexibility, scalability, and manageability in hybrid IT environments.
These tools orchestrate applications, infrastructure, and databases, including meta-orchestration of cloud, BPA, WLA, DevOps, and data/ML pipelines.
Below are the rates of automation solutions used for various data operations (e.g. data storage and ETL (Extract, Transform, Load)):
A combination of scripts and custom integrations managed in-house by 67%
An enterprise- grade scheduling / orchestration solution by 53%
Data tool-specific inbuilt job schedulers by 50%
An open-source scheduling/ orchestration solution by 44%.(Source 3)
It’s not just about using centrally managed tools; businesses are also forming centralized management teams. For example:
91% of organizations have a centralized IT automation team, up from 77% in the previous year, indicating substantial growth in adoption.
Centralized CloudOps teams increased to 74% from 53% in a year, enhancing cloud resource management and establishing enterprise-wide standards and innovation.(Source 3)
8- The rise of automation fabrics
Automation fabrics are emerging as a key trend in IT automation. These integrated frameworks unify applications, data, and workflows, eliminating the inefficiencies caused by disconnected automation tools. Instead of managing isolated systems that require constant maintenance, businesses are shifting toward seamless automation ecosystems that enable greater scalability and flexibility.
This shift aligns with the dissolution of automation islands, where enterprises consolidate disparate automation tools into unified platforms. Legacy applications, modern cloud solutions, and AI-driven automation can now coexist within a single, cohesive system. By adopting automation fabrics, businesses can ensure smoother operations, reduce downtime, and minimize technical debt.
Domain-specific IT automation trends
Figure 4: The image shows the most preferred capabilities in an IT automation platform by business leaders. (Source 3)
9- Cloud automation
Cloud automation tools are listed as top investment in this year by 50% of all companies. (Source 3)
IT automation can streamline the orchestration and management of complex cloud environments while scaling and monitoring resources across multiple cloud platforms. It can also enable hybrid cloud automation through data, IT operations and compliance management automation.
This is why other priority tools for this year’s investment include workload automation at 42% and service orchestration and automation platforms (SOAPs) at 38%. Since SOAPs encompass aspects of WLA, workload automation becomes the top priority investment in the IT automation domain, totalling 80%.(Source 3)
10- Container management
The rising adoption of cloud-native infrastructure will affect 75% of large enterprises to leverage container management by 2024. (Source 2) Container management refers to revising, adding, or changing large quantities of software containers.
IT automation streamlines container management by:
Providing infrastructure resource for container environments, including virtual machines and cloud foces.
Automating the creation, testing, and storage of container images, ensuring consistency and reproducibility.
Configuring and orchestrating containerized applications and their dependencies.
Enabling dynamic scaling of container r s based on predefined rules or resource utilization.
Configuring automated monitoring systems to detect issues and trigger alerts or remediation actions.
Automating lifecycle management processes like updating container images, version rollout, and canary/blue-green deployments.
Therefore, increasing container management will lead to adopting digital technologies like IT automation tools.
Resource availability
Workload priorities
Dependencies
Service Level Agreements (SLAs).
11- DevOps pipeline automation
DevOps pipelines refer to processes and strategies to build, test and deploy software applications. DevOps pipeline involves code compilation, testing, artefact creation, deployment, and monitoring.
According to estimates, 35% of this years’ automation efforts are allocated to DevOps automation. (Source 2) These efforts include adopting AIOps , MLOps and DataOps. For instance:
40% of IT teams will adopt AIOps and MLOps in these pipeline stages to reduce downtime by 20% this year. (Source 2)
DataOps has the potential to increase data output by 50%, shorten time to market by 30%, improve productivity by 10%, and lower IT expenses by 10%.
However, businesses need a systematic and automated approach to leverage AI and ML effectively. IT automation or RPA software can help scale these advanced technologies by providing the necessary infrastructure, tools, and workflows. For example, IT automation can:
Provide infrastructure resources required for DevOps pipelines Automate DevOps pipeline stages for a faster and error-free software delivery Enable the automated configuration management of infrastructure and application settings to increase consistency in the work environment. Automate testing activities to identify issues in application development Proactively set up monitoring configurations, define alerting rules, and trigger notifications.
If you are interested in DevOps terms and tools:
12- ITOps management
Organizations can reallocate 30% of ITOps management efforts into continuous engineering, such as automatic remediation and analytics by 2024. (Source 2) One way to reduce these efforts is to automate IT operations management with IT automation tools. Some of these tools include:
13- Workload automation and intelligent job scheduling
IT automation trends indicate that the adoption of workload automation has risen exponentially. For example, survey respondents reported that they:
Embraced workload automation by 82%
Consider automation as the first two to digital transformation by 47%.
Workload automation manages various tasks and workflows and executes batch jobs and business processes across different systems and applications to ensure the timely and accurate processing of workloads.
Despite the increasing interest, 82% of businesses also plan to add or replace a WLA platform since they need:
A more modern solution with more functionality by 67%
Better customer service by 53%
Reduced cost by 49%.(Source 3)
Intelligent job scheduling combines enterprise job scheduling capabilities with artificial intelligence and analytics to optimize task execution based on various factors, such as:
Discover WLA and Job scheduling tools in detail through our:
14- Service orchestration and automation platforms (SOAPs)
In the past, workload automation tools were just one of many isolated automation solutions used within organisations. Now, Service Orchestration and Automation Platforms (SOAPs) offer comprehensive integration across these disparate tools, enabling the orchestration of the entire IT stack from a single central point of control.
Figure 4: Service Orchestration and automation platforms past vs present.(Source 3)
SOAPs orchestrate a variety of specialised tools across diverse focus areas, including cloud management, data and machine learning pipelines, DevOps processes, and infrastructure automation. By the end of 2025, 80% of organizations that currently utilize workload automation are expected to switch to Service Orchestration and Automation Platforms (SOAPs) to orchestrate workloads across both IT and business domains. (Source 3)
15- Security automation
Cybersecurity becomes increasingly demanding for more organizations due to increasing cyberattacks. According to cybersecurity trends, at least 50% of companies will need to check the cybersecurity posture of their potential business partners by 2025.
IT automation can help enhance security automation through automated functionalities like:
Real-time threat detection
Incident response
Vulnerability management
Security policy enforcement.
16. Network Automation
McKinsey’s analysis of over 500 networking software projects reveals that rising software complexity is causing longer delivery times and increased effort despite improved quality. This challenge makes automation essential for managing and optimizing network operations effectively
Gartner forecasts that 30% of enterprises will automate more than half of their network activities by 2026, highlighting a major shift toward automated network management.
Network automation covers key activities such as:
Automated provisioning of network resources
Configuration management and compliance
Performance monitoring and fault management
Security policy enforcement and threat response.
AI has been integrated to improve network security use cases and other network operations like AI network monitoring. Explore what AI network security is and open source network security software.
Further reading
Explore more on IT automation types:
If you believe your business can benefit from IT automation, assess different vendors for each IT automation type by checking out our comprehensive and data-driven lists:
If you need more help, let us know:
| 2025-06-26T00:00:00 |
https://research.aimultiple.com/it-automation-trends/
|
[
{
"date": "2025/06/26",
"position": 25,
"query": "job automation statistics"
}
] |
|
Autonomous Vehicles and Job Market Disruptions
|
Autonomous Vehicles and Job Market Disruptions: Will AVs Kill or Create Jobs? (Labor Market Data)
|
https://patentpc.com
|
[
"Bao Tran",
"Patent Attorney"
] |
Get the latest labor market data on automation's impact. 1. 4.4 million U.S. jobs depend on driving, including truck, taxi, and delivery drivers. Driving jobs ...
|
The rise of autonomous vehicles (AVs) is shaking up industries and changing how people work. While some fear massive job losses, others see opportunities for new careers. This article breaks down the key labor market statistics and what they mean for workers, businesses, and policymakers.
1. 4.4 million U.S. jobs depend on driving, including truck, taxi, and delivery drivers
Driving jobs are the backbone of the U.S. economy. Millions rely on driving for their livelihood, whether it’s truck drivers hauling freight, taxi drivers serving cities, or delivery workers dropping off packages.
AVs threaten these traditional roles, but they also bring opportunities in new areas such as fleet management, AV maintenance, and logistics coordination.
To stay ahead, workers in the transportation industry should consider upskilling in technology, customer service, or logistics. Employers can support employees by providing training programs for AV-related jobs.
2. 94% of crashes are due to human error, which AVs could significantly reduce
Human mistakes cause the vast majority of accidents. AVs promise safer roads by eliminating distracted, impaired, and reckless driving. This shift could dramatically reduce the need for traditional auto repair jobs and first responders.
However, fewer crashes also mean lower demand for insurance claims adjusters, body shop technicians, and even emergency medical personnel. On the flip side, AVs will create demand for cybersecurity experts, software engineers, and AI specialists who maintain and improve vehicle safety systems.
3. AVs could cut 300,000 truck-driving jobs annually once fully adopted
Trucking is one of the largest employment sectors in the U.S. As AVs take over long-haul routes, many truck drivers could lose their jobs. However, the transition won’t happen overnight.
For those in the industry, now is the time to explore alternative roles like AV safety operators, logistics analysts, or even transitioning to local delivery jobs that still require human interaction. Companies should offer retraining programs to help workers move into emerging fields.
4. The autonomous trucking industry could save $100 billion per year in labor costs
Companies will save money by replacing human drivers with AVs. These savings will likely be reinvested into technology and infrastructure. However, job losses could hit hard if workers aren’t prepared for the shift.
Governments and businesses need to create policies that ensure workers benefit from these savings, such as wage subsidies for retraining or incentives for companies that hire displaced workers into tech-based roles.
5. 1.7 million heavy truck and tractor-trailer drivers in the U.S. face potential job displacement
Truck drivers are among the most vulnerable to automation. Many have built decades-long careers in the industry. The shift to AVs means these workers need to start thinking about the future.
One option is to specialize in areas that AVs can’t easily replace, such as hazardous material transport, which requires human oversight. Another option is to transition into fleet supervision or AV maintenance. Workers should begin learning digital skills and considering alternative career paths.
6. AV technology could create 100,000+ jobs in AI, robotics, and AV maintenance
The growth of autonomous vehicles (AVs) isn’t just transforming how we commute—it’s shaping entire new industries, especially in artificial intelligence (AI) and robotics.
As businesses prepare to integrate self-driving technology into their operations, we’re looking at an entirely new workforce that needs to be built from the ground up.
Roles in AI development, robotics engineering, data analytics, and machine learning are poised to boom. Companies that invest early in attracting and developing talent in these areas will position themselves as industry leaders and innovators, staying several steps ahead of their competition.
Skilled AV Maintenance Workers Will Be Highly Sought After
One area that often gets overlooked—but is absolutely crucial—is the AV maintenance sector. Autonomous vehicles are sophisticated, but like any advanced technology, they require specialized upkeep and regular monitoring to function safely and efficiently.
Businesses entering the AV space or adopting fleets of autonomous vehicles will need skilled maintenance personnel trained in both automotive and digital systems.
This opens substantial new employment pathways, ranging from vehicle diagnostics experts and AV technicians to remote fleet monitoring specialists. For businesses, proactively investing in training and certifying workers in AV maintenance today will mean smoother operations and reduced downtime in the future.
7. The AV industry is projected to be worth $1.2 trillion by 2030
The sheer size of the AV market means that businesses and workers who adapt early can benefit from massive growth. This market includes not just self-driving cars but also smart infrastructure, AV software, and mobility services.
Entrepreneurs should look into starting businesses that support AVs, such as sensor manufacturing, data analytics, or even AV-friendly urban planning. Investors should focus on startups that solve critical AV-related challenges.
8. 800,000 rideshare drivers (Uber, Lyft) could lose their jobs with AV adoption
As autonomous vehicle (AV) technology continues to evolve, many industries are bracing for significant changes. One of the most notable impacts will be felt in the rideshare industry, where around 800,000 drivers could lose their jobs as AV adoption gains traction.
Uber, Lyft, and other ridesharing platforms rely heavily on human drivers to provide their services. With the rise of AVs, however, the need for human drivers may drastically decline.
This disruption poses challenges for the workforce, but it also presents new opportunities for businesses and the labor market to adapt and innovate. Understanding the potential job loss in the rideshare sector and planning ahead can help businesses not only navigate this transition but also thrive in the changing landscape.
9. The autonomous vehicle market could create 500,000 new tech and engineering jobs
As the autonomous vehicle (AV) market continues to grow, one of the most exciting developments is the potential to create a significant number of new jobs in tech and engineering fields.
For businesses, understanding this shift is key to staying ahead of the curve, preparing for future needs, and attracting the talent required to drive innovation forward.
A Surge in Demand for Highly Skilled Workers
While it’s easy to focus on the potential job losses in traditional driving-related professions, the rise of autonomous vehicles brings about a surge in demand for highly skilled workers.
Engineers, data scientists, software developers, and cybersecurity experts are just a few examples of the roles that are becoming increasingly essential as autonomous technology matures.
The need for experts in these areas is only expected to grow as companies develop and implement AV technologies. With complex systems that require continuous innovation, testing, and safety improvements, businesses will find themselves in need of professionals who can navigate this highly technical landscape.
Additionally, industries that support AV technologies, such as AI, machine learning, and big data, will also experience job growth. For businesses, this opens the door to building more robust teams, enhancing capabilities, and tapping into the potential of the rapidly evolving tech space.
10. 25% of global driving jobs could be eliminated by full AV adoption
As autonomous vehicle technology accelerates, businesses must prepare strategically for substantial shifts in the global labor market. With studies projecting that around a quarter of global driving jobs could vanish due to AV adoption, now is the crucial time for companies to act.
Rather than waiting for disruption to unfold, savvy organizations can get ahead by proactively analyzing their workforce, identifying potential vulnerabilities, and initiating training or redeployment programs.
This approach not only helps protect your employees—it positions your company as responsible and forward-thinking in the eyes of customers, investors, and stakeholders.
Smart Workforce Transition Planning is a Must-Have Strategy
Companies that heavily rely on driving-based roles—such as logistics, delivery, and public transportation—need a clear, actionable plan for workforce transitions. Waiting until autonomous vehicles dominate the roadways will be too late, causing costly operational disruptions and reputational harm.
Instead, businesses should start mapping the skills of their current driving workforce today, identifying areas where retraining or reskilling could help employees transition into new roles within the company.
This strategic approach reduces future hiring costs, increases employee loyalty, and boosts company resilience in the face of technological disruption.
11. The AV software industry alone could generate $50 billion in revenue by 2030
As the autonomous vehicle (AV) sector continues to develop, one of the most promising areas for business growth lies in the AV software industry.
By 2030, this industry is projected to generate an estimated $50 billion in revenue, opening the door to immense opportunities for companies involved in technology, software development, and data analysis.
For businesses looking to capitalize on this growth, understanding the dynamics of the AV software industry and how it fits into the broader AV ecosystem will be critical.
The next few years could see a shift toward software-centric solutions that power self-driving vehicles, and businesses that strategically position themselves now stand to benefit from this wave of innovation.
12. 40% of logistics jobs may transition to supervisory roles rather than disappear
As autonomous vehicles (AVs) make their way into the logistics sector, one of the most significant impacts businesses can expect is a shift in the nature of many logistics jobs.
While automation may reduce the need for human drivers and delivery personnel, a large portion of the workforce is likely to transition into more supervisory and management-focused roles rather than face job displacement.
A Shift Toward Management and Oversight
For businesses, this transition presents both a challenge and an opportunity. As AVs become responsible for the heavy lifting of transporting goods, human workers will be needed more than ever to supervise the systems that ensure smooth operations.
Rather than simply driving trucks, employees will be tasked with overseeing the performance of automated fleets, managing technology interfaces, and ensuring that operations run efficiently.
Logistics companies will need to think strategically about this shift, investing in training programs to help their current workforce transition into these new roles.
These supervisory positions require workers to develop new skills, such as understanding AV systems, troubleshooting issues, and ensuring compliance with safety regulations.
This transition also opens up opportunities for employees to take on more decision-making responsibilities, such as route optimization and quality control.
13. 70% of Americans rely on driving jobs in some form for their livelihood
Businesses must come to terms with a powerful reality: driving-based jobs directly or indirectly support the livelihoods of approximately 70% of Americans. This staggering statistic signals a critical challenge—and opportunity—as autonomous vehicles (AVs) reshape the employment landscape.
For companies that rely on driving jobs, this is a wake-up call to proactively strategize and manage workforce transitions. Your business can either wait for disruption to unfold or take meaningful action now to safeguard both your employees’ livelihoods and your company’s future.
Strategic Workforce Mapping: A Vital Step for Companies Today
To navigate this immense employment shift successfully, strategic workforce mapping is essential. Businesses should promptly analyze how driving jobs connect to various aspects of their operations, from logistics and transportation to sales and customer service.
Understanding exactly where your company’s reliance on driving-based roles exists allows you to forecast potential disruptions and create targeted transition strategies.
Conducting a detailed skills assessment today will provide your business with a clear roadmap, ensuring smoother, less costly transitions as AV technology advances.
14. AVs could reduce transportation costs by 50%, impacting taxi and trucker wages
The promise of autonomous vehicles (AVs) isn’t just about revolutionizing how people travel or how goods are delivered—it’s also about drastically reducing transportation costs.
In fact, studies suggest that AVs could reduce transportation expenses by as much as 50%, leading to significant impacts on the wages of both taxi drivers and truckers.
While this cost reduction may bring numerous benefits to consumers and businesses, it could also create economic challenges for workers in these industries.
Understanding how AV technology can influence transportation costs, and how businesses can strategically navigate these changes, is critical for future-proofing your business and workforce.
Here’s a closer look at how AVs could lower transportation costs and affect workers’ pay, and how businesses can take proactive steps to adapt.
15. AVs could increase productivity by $1.3 trillion annually in the U.S. economy
The integration of autonomous vehicles (AVs) into the U.S. economy promises to be a game-changer, potentially increasing productivity by $1.3 trillion each year.
This substantial boost comes from a combination of enhanced efficiency, cost savings, and innovation. For businesses looking to stay competitive, understanding how AVs can impact productivity is critical for leveraging this transformative technology.
Driving Efficiency Across Multiple Sectors
One of the most immediate impacts of autonomous vehicles will be felt in industries where transportation and logistics play a central role. From freight transportation to personal delivery services, AVs will reduce the time and cost associated with human-driven transportation.
With autonomous systems operating 24/7, businesses can eliminate downtime, cut transportation costs, and increase throughput, leading to higher productivity across the board.
Moreover, AVs will streamline supply chains, creating more efficient routes, minimizing delays, and ensuring that goods arrive more reliably. This will not only reduce operational costs but also improve customer satisfaction, fostering stronger business relationships and repeat business.
For companies already operating in industries such as e-commerce, retail, and manufacturing, the adoption of AVs can create a massive competitive advantage, reducing overheads and maximizing output.
16. 60% of truck drivers are over the age of 45, making retirement-based job attrition likely
The trucking industry already faces a labor shortage as many drivers approach retirement. Instead of immediate job losses due to AVs, the industry may see a gradual shift where automation fills the gaps left by retiring workers.
This transition period presents an opportunity for younger workers to retrain for higher-paying tech-based roles within transportation. Companies should start offering retraining programs now to prepare their workforce for supervisory roles overseeing AVs rather than being displaced entirely.
For policymakers, this statistic suggests that workforce planning should focus on retraining rather than emergency relief measures. By gradually introducing AV technology alongside human workers, businesses can make the shift smoother and less disruptive.
17. AV-related industries could demand 250,000 new cybersecurity professionals
Self-driving vehicles rely on complex software systems that are vulnerable to hacking. As AVs become more common, cybersecurity threats will rise, creating new demand for professionals who can protect vehicle systems from cyberattacks.
This presents a huge opportunity for workers in the IT and cybersecurity fields. Those interested in future-proofing their careers should focus on ethical hacking, AI security, and network protection for autonomous vehicle systems.
Businesses investing in AV technology should also prioritize cybersecurity from the start, ensuring their fleets are protected from potential cyber threats. Governments may need to create new regulations for AV cybersecurity standards to keep both vehicles and passengers safe.
18. 85% of delivery jobs could be automated by 2040
Food, retail, and parcel delivery are among the most vulnerable jobs when it comes to automation. Self-driving delivery trucks and robots are already being tested, and their widespread adoption could drastically reduce the need for human couriers.
Workers in this sector should consider transitioning into roles related to AV fleet management, maintenance, or customer service. Instead of manually delivering packages, future delivery workers may oversee a fleet of AVs, ensuring deliveries are completed efficiently.
Retailers and logistics companies should begin preparing for this shift by investing in AV-compatible warehouse systems and training staff for new roles in an automated delivery ecosystem.
19. AV tech investment has exceeded $100 billion globally since 2015
The sheer scale of investment in AV technology highlights its inevitability. Major corporations, tech startups, and governments are pouring money into AV research, development, and infrastructure.
For entrepreneurs, this presents an opportunity to enter a fast-growing market. Whether through software development, AI training, or AV-related logistics solutions, there are countless ways to capitalize on this transformation.
Investors should also take note—companies that successfully integrate AV technology into their business models will likely see long-term financial gains. Startups focusing on AV infrastructure, such as smart traffic management systems or vehicle-to-vehicle communication, are particularly well-positioned for growth.
20. 5 million new high-skill jobs could emerge in AV manufacturing and programming
While AVs may replace some jobs, they will also create entirely new career opportunities. Engineers, software developers, and technicians will be in high demand to design, manufacture, and maintain these vehicles.
Workers looking to transition into this field should focus on acquiring skills in AI, machine learning, and AV hardware development. Universities and technical schools should also expand programs focused on AV-related disciplines to meet future labor demands.
Employers should consider hiring workers from adjacent industries, such as aerospace, robotics, and software development, to fill AV-related roles. By cross-training employees, companies can build a skilled workforce ready for the AV revolution.
21. AVs could reduce fuel consumption by 10-15%, altering jobs in fuel transport
Autonomous vehicles are designed to optimize fuel efficiency, which means the demand for fuel transport and distribution jobs may decline.
Gas station operators, fuel truck drivers, and oil industry workers should begin considering how to pivot into new roles. The growing electric vehicle (EV) market presents a strong alternative—jobs in battery production, EV charging infrastructure, and renewable energy are expected to increase.
For businesses in the fuel industry, adapting to this change means diversifying offerings. Investing in EV charging stations or alternative fuel technology could help them stay competitive in a rapidly shifting market.
22. 30% of public transit jobs could be impacted by AVs
Bus drivers, train operators, and transit maintenance workers may see significant job disruptions as AVs become more common. However, rather than eliminating these jobs entirely, AVs could shift these roles to system monitoring and control.
Public transit agencies should invest in workforce development programs that prepare employees for AV-related roles. Governments should also ensure that automation in public transit is introduced gradually, giving workers time to transition into new careers.
For transit workers, learning basic programming, maintenance, or AV fleet management skills could be the key to staying employed in an automated future.
23. $70 billion in potential annual savings from reduced traffic congestion
AVs could drastically reduce traffic congestion, leading to huge economic benefits. Less time stuck in traffic means lower fuel costs, fewer delays, and increased worker productivity.
Businesses should consider how to take advantage of these savings by optimizing logistics, reducing commuting times, or expanding remote work options. Governments should invest in smart infrastructure to maximize the benefits of AV technology.
Real estate markets could also shift as AVs make longer commutes more manageable, potentially increasing demand for suburban and rural housing. Entrepreneurs should look for opportunities in AV-adjacent industries, such as smart city planning and urban mobility solutions.
24. Over 50% of auto repair jobs could shift to AV software maintenance
Traditional auto mechanics will need to adapt as AVs replace conventional vehicles. Rather than fixing engines and transmissions, future repair jobs will focus on software updates, sensor maintenance, and AI troubleshooting.
Mechanics looking to future-proof their careers should start learning about AV technology now. Courses in automotive electronics, AI diagnostics, and cybersecurity can help workers stay relevant.
Auto repair shops should consider hiring software technicians or partnering with AV manufacturers to offer specialized maintenance services. By embracing AV technology early, businesses can stay ahead of the curve.
25. AVs could lower insurance industry revenue by $25 billion per year
Fewer accidents mean fewer insurance claims, which could disrupt the auto insurance industry. However, new types of insurance products will emerge, such as liability coverage for AV manufacturers and cybersecurity insurance for AV software.
Insurance professionals should consider specializing in AV-related policies, such as risk assessment for self-driving fleets or data privacy insurance. Companies should also prepare for regulatory changes that may shift liability from drivers to manufacturers.
26. 40% of food delivery jobs could be replaced by AV robots by 2035
Autonomous delivery robots and self-driving vehicles will change the food delivery industry. Restaurants, grocery stores, and delivery platforms should begin testing AV integration to stay ahead of competitors.
Workers in food delivery should look into transitioning into roles such as AV fleet monitoring, customer support, or logistics coordination. Businesses should offer training programs to help employees shift into tech-oriented roles rather than replacing them outright.
27. 3.5 million truck drivers could face job displacement in the U.S. alone
Long-haul trucking is one of the most vulnerable industries to AV automation. However, this transition will take time, allowing drivers to plan ahead.
Truck drivers should explore opportunities in local delivery, AV monitoring, or logistics management. Government programs should focus on reskilling workers before large-scale job losses occur.
28. 20-30% increase in demand for AV-related infrastructure jobs like sensor installation
AVs require significant infrastructure changes, including smart roads, traffic sensors, and communication networks. These upgrades will create thousands of new jobs.
Workers in construction, civil engineering, and IT should consider shifting toward AV infrastructure projects. Governments should prioritize funding for smart infrastructure to accelerate AV adoption.
29. AVs could create 200,000+ jobs in urban planning and smart city development
City planning will need to evolve to accommodate self-driving technology. This will create demand for urban planners, traffic engineers, and smart city developers.
Governments should invest in AV-friendly city planning now to ensure smooth integration. Urban planners should explore how AVs can improve city layouts, reduce congestion, and enhance public transit systems.
30. The transition to AVs could take 15-20 years, allowing gradual labor market adaptation
Despite concerns about job losses, AV adoption won’t happen overnight. This long timeline gives workers, businesses, and governments time to prepare.
Now is the time to invest in retraining, education, and policy planning. By acting early, industries can turn AV technology from a threat into an opportunity.
wrapping it up
The rise of autonomous vehicles is both an opportunity and a challenge. Millions of jobs that rely on driving could disappear, but at the same time, new industries and careers will emerge.
The key to navigating this shift is preparation. Workers must reskill, businesses must innovate, and governments must create policies that support a smooth transition.
| 2025-06-24T00:00:00 |
2025/06/24
|
https://patentpc.com/blog/autonomous-vehicles-and-job-market-disruptions-will-avs-kill-or-create-jobs-labor-market-data
|
[
{
"date": "2025/06/26",
"position": 39,
"query": "job automation statistics"
}
] |
25+ essential job interview statistics every recruiter must ...
|
25+ essential job interview statistics every recruiter must know
|
https://recruitcrm.io
|
[] |
62% of job applicants preferred automated information over prolonged email exchanges (Fit Small Business). The stat is a clear sign that candidates value ...
|
Looking for something?
Type your question in the search bar above to get started!
| 2024-06-21T00:00:00 |
2024/06/21
|
https://recruitcrm.io/blogs/job-interview-statistics/
|
[
{
"date": "2025/06/26",
"position": 87,
"query": "job automation statistics"
}
] |
Generational divide emerges on workplace AI
|
Generational divide emerges on workplace AI
|
https://workplaceinsight.net
|
[
"Neil Franklin"
] |
As artificial intelligence continues to reshape the world of work, younger employees are taking the lead in adopting and experimenting with new tools.
|
As artificial intelligence continues to reshape the world of work, younger employees are taking the lead in adopting and experimenting with new tools. According to a new survey by UKG and The Harris Poll, Gen Z workers are not only the most enthusiastic users of workplace AI but also the most likely to be self-taught. The research highlights a growing generational divide. While 84 percent of U.S. employees overall say they want AI to handle workplace processes, Gen Z – those aged 18 to 28 – are particularly eager. Ninety percent believe AI will save them time at work, with nearly a third expecting to reclaim up to 90 minutes a day. They’re also the most likely to have taken the initiative to learn AI skills independently, with 70 percent teaching themselves the tools they use.
Despite this enthusiasm, nearly half of Gen Z employees (49 percent) say their managers don’t understand the benefits of AI. That perception reflects a broader disconnect: just over a quarter of senior leaders in a 2023 UKG study believed Gen Z had the best grasp of AI at work. The new data suggests otherwise – and points to an opportunity for organisations to bridge that gap.
Across all generations, employees agree on one key principle: AI is a tool, not a colleague. Almost nine in ten (89 percent) say AI should support human work rather than replace it. Most want to see it used for repetitive, data-heavy, or error-prone tasks such as checking pay accuracy, creating schedules, or summarising policies – not for roles requiring judgment or empathy.
UKG’s chief product officer, Suresh Vittal, argues that this moment mirrors past technological shifts. “Every few decades, something changes everything – electricity, mobile phones, the internet,” he says. “AI is the next leap. The sooner organisations act, the more they’ll benefit.”
The research shows that while Gen Z may be the vanguard of AI adoption, their preferences align with wider employee sentiment. The majority want AI to enhance, not upend, the way they work. By learning from younger employees and promoting wider digital literacy, employers can use AI to free up time for more strategic and creative work – across every generation.
| 2025-06-26T00:00:00 |
2025/06/26
|
https://workplaceinsight.net/generational-divide-emerges-on-workplace-ai/
|
[
{
"date": "2025/06/26",
"position": 76,
"query": "workplace AI adoption"
}
] |
The biggest AI companies you should know - Yahoo Finance
|
The biggest AI companies you should know
|
https://finance.yahoo.com
|
[
"Fri",
"Jun",
"Min Read"
] |
Microsoft (MSFT), Google (GOOG, GOOGL), Meta (META), and Amazon (AMZN) continue to debut new AI-powered software capabilities while leaders from ...
|
AI continues to be the hottest trend in tech, and it doesn't appear to be going away anytime soon. Microsoft (MSFT), Google (GOOG, GOOGL), Meta (META), and Amazon (AMZN) continue to debut new AI-powered software capabilities while leaders from other AI firms split off to form their own startups.
But the furious pace of change also makes it difficult to keep track of the various players in the AI space. With that in mind, we're breaking down what you need to know about the biggest names in AI and what they do.
From OpenAI (OPAI.PVT) to Perplexity (PEAI.PVT), these are the AI companies you should be following.
OpenAI/Microsoft
Microsoft-backed OpenAI helped put generative AI technology on the map. The company's ChatGPT bot, released in late 2022, quickly became one of the most downloaded apps in the world. Since then, the company has launched its own search engine, 4o image generator, a video generator, and a file uploader that allows you to ask the bot to summarize the content of your documents, as well as access to specialized first- and third-party GPT bots.
Microsoft uses OpenAI's various large language models (LLM) in its Copilot and other services. Apple (AAPL) also offers access to ChatGPT as part of its Apple Intelligence and Visual Intelligence services.
Open AI CEO Sam Altman, left, appears onstage with Microsoft CEO Satya Nadella at OpenAI DevDay on Nov. 6, 2023, in San Francisco. (AP Photo/Barbara Ortutay) · ASSOCIATED PRESS
But there's drama behind the scenes. OpenAI is working to restructure its business into a public benefit corporation overseen by its nonprofit arm, which will allow it to raise more capital. To do that, it needs Microsoft's sign-off, but the two sides are at loggerheads over the details of the plan and what it means for each company.
In the meantime, both OpenAI and Microsoft are reportedly working on products that will compete with each other's existing offerings. Microsoft offers its own AI models, and OpenAI is developing a productivity service, according to The Information.
Still, the pairing has been lucrative for both tech firms. During its most recent quarterly earnings call, Microsoft said AI revenue was above expectations and contributed 16 percentage points of growth for the company’s Azure cloud business. OpenAI, meanwhile, saw its annualized revenue run rate balloon to $10 billion as of June, according to Reuters. That's up from $5.5 billion in Dec. 2024.
OpenAI offers a limited free version of its ChatGPT bot, as well as ChatGPT Plus, which costs $20 per month, and enterprise versions of the app.
Google Gemini
Google's Gemini offers search functionality using the company's Gemini 2.5 family of AI models. You can choose between using Gemini Flash for quick searches or Gemini Pro, which is meant for deep research and coding.
| 2025-06-27T00:00:00 |
https://finance.yahoo.com/news/the-biggest-ai-companies-you-should-know-165407928.html
|
[
{
"date": "2025/06/27",
"position": 5,
"query": "AI employers"
},
{
"date": "2025/06/27",
"position": 11,
"query": "AI employers"
},
{
"date": "2025/06/27",
"position": 7,
"query": "AI employers"
},
{
"date": "2025/06/27",
"position": 67,
"query": "AI employers"
},
{
"date": "2025/06/27",
"position": 12,
"query": "AI employers"
},
{
"date": "2025/06/27",
"position": 14,
"query": "AI employers"
},
{
"date": "2025/06/27",
"position": 3,
"query": "AI employers"
},
{
"date": "2025/06/27",
"position": 1,
"query": "AI employers"
}
] |
|
AI Boom Triggers Massive Layoffs: US Job Cuts Surge 80% As Tech ...
|
AI Boom Triggers Massive Layoffs: US Job Cuts Surge 80% As Tech Giants Slash Workforce
|
https://www.freepressjournal.in
|
[
"Tasneem Kanchwala"
] |
AI Boom Triggers Massive Layoffs: US Job Cuts Surge 80% As Tech Giants Slash Workforce · The US job market is facing turmoil with 696,309 layoffs ...
|
Canva
The US jobs market is going through a tough time. According to the latest data from Challenger, Gray & Christmas, employers in US have announced 696,309 job cuts, an increase of 80 percent from the 385,859 announced in the first five months of last year. The report suggests that it is 65,049 cuts away from matching the entire year’s total for 2024.
This rise in layoffs is attributed to the advent of AI which has emerged as a big disruptor in tech employment. Many firms including Amazon and Google have announced that layoffs are inevitable.
The report suggests that technology continues to be the leading job-cut sector as it faces mounting and rapidly changing disruptions. Technology companies announced 10,598 job cuts in May for a total of 74,716 cuts in 2025. This is up 35 percent from the 55,207 cuts announced during the same period last year.
“Technological Updates, including those related to AI implementation, led to 20,000 job cuts so far in 2025,” the report adds.
Amazon CEO Andy Jassy recently hinted at layoffs given the AI boom that the world has seen in the last few years. Jassy confirmed that the company will need fewer people as Amazon pushes for greater efficiency with the help of Generative AI.
Microsoft is reported to have laid off around 6,000 people in May, and has also done two rounds of layoffs in June as well. According to a report by The Information, the Google TV team laid off 25 percent of its staff in April.
| 2025-06-27T00:00:00 |
https://www.freepressjournal.in/tech/ai-boom-triggers-massive-layoffs-us-job-cuts-surge-80-as-tech-giants-slash-workforce
|
[
{
"date": "2025/06/27",
"position": 61,
"query": "artificial intelligence layoffs"
},
{
"date": "2025/06/27",
"position": 57,
"query": "AI layoffs"
},
{
"date": "2025/06/27",
"position": 52,
"query": "AI layoffs"
},
{
"date": "2025/06/27",
"position": 60,
"query": "artificial intelligence layoffs"
},
{
"date": "2025/06/27",
"position": 60,
"query": "AI layoffs"
},
{
"date": "2025/06/27",
"position": 56,
"query": "artificial intelligence layoffs"
},
{
"date": "2025/06/27",
"position": 56,
"query": "AI layoffs"
},
{
"date": "2025/06/27",
"position": 56,
"query": "artificial intelligence layoffs"
},
{
"date": "2025/06/27",
"position": 58,
"query": "AI layoffs"
},
{
"date": "2025/06/27",
"position": 60,
"query": "artificial intelligence layoffs"
},
{
"date": "2025/06/27",
"position": 58,
"query": "AI layoffs"
},
{
"date": "2025/06/27",
"position": 58,
"query": "AI layoffs"
},
{
"date": "2025/06/27",
"position": 65,
"query": "artificial intelligence layoffs"
},
{
"date": "2025/06/27",
"position": 54,
"query": "AI layoffs"
},
{
"date": "2025/06/27",
"position": 65,
"query": "artificial intelligence layoffs"
},
{
"date": "2025/06/27",
"position": 59,
"query": "AI layoffs"
},
{
"date": "2025/06/27",
"position": 59,
"query": "AI layoffs"
},
{
"date": "2025/06/27",
"position": 64,
"query": "artificial intelligence layoffs"
},
{
"date": "2025/06/27",
"position": 59,
"query": "AI layoffs"
},
{
"date": "2025/06/27",
"position": 55,
"query": "artificial intelligence layoffs"
},
{
"date": "2025/06/27",
"position": 90,
"query": "AI layoffs"
}
] |
|
K-12 Office Helps Build Tomorrow's AI/ML Workforce - Research
|
K-12 Office Helps Build Tomorrow’s AI/ML Workforce
|
https://research.lbl.gov
|
[] |
Artificial intelligence (AI) and machine learning (ML) are critical skills for today's and tomorrow's scientists. · At Berkeley Lab, the K-12 ...
|
Artificial intelligence (AI) and machine learning (ML) are critical skills for today’s and tomorrow’s scientists. So much so that the White House recently announced a presidential action in support of AI education for American youth. The Department of Energy is also focused on building an AI-ready workforce.
At Berkeley Lab, the K-12 team has already been providing data science and AI/ML training for the past five years. Since 2020, they have provided this training to more than 100 students (mostly 10th and 11th graders), building skills and encouraging interest. In fact, among the program’s alumni, a number of students are minoring in data science, computer science, and statistics, because of their experience at Berkeley Lab.
K-12 STEM Education Program Director Faith Dukes, stresses the importance of AI/ML skills. “Our program helps to develop skill sets that students need in order to get an internship at Berkeley Lab,” said Faith. “AI and ML are being integrated into so much of our research now, that it is a must-have skill set.”
The K-12 training program initially focused more on data science, but over the years AI and machine learning have become increasingly important, and Faith and Content and Instruction Manager Alisa Bettale have continued to iterate on the curriculum. Last year, Energy Technologies Area researchers Vi Rapp and Ana Comesana guided interns through the process of analyzing spectral data from chemical compounds and fuel samples. They applied machine learning techniques to this data to predict how potential bio-derived jet fuels might perform, contributing to the development of more alternative aviation fuels.
Computing Sciences Area senior scientist Dani Ushizima worked with students to use computer vision for image enhancement, and machine learning to detect and characterize plant leaves in EcoFAB plant growth devices. Finally, students used data from the Materials Project to train a machine learning model to predict the hardness of materials based only on their densities.
This summer, when the Lab welcomes the sixth cohort of the Berkeley Lab Director’s Apprenticeship Program (BLDAP), AI/ML training is taking center stage. BLDAP, also known as Interdisciplinary Pathways in Machine Learning and Data Science, is an Office of Science Workforce Development for Teachers and Scientists (WDTS) Pathways Summer School Program. About 20 students who may have little to no experience coding will complete an intro to Python/data science/machine learning course as part of the program. The students will then apply their knowledge on data sets from various Berkeley Lab research projects, and also work on machine learning applications. In addition to the BLDAP program, an additional 80 students at various summer internships throughout the Lab will also get exposure to AI/ML skills for science.
Said Faith, “Ultimately, we are exposing our students to the skills and tools needed for scientific research – the foundations for an internship at the Lab or at other national labs. These skills include data science, AI/ML, wet lab, fabrication and engineering skills.” The K-12 team is also working with the Quantum Systems Accelerator to run a quantum computing camp, also a DOE Pathways Summer School program, called QCaMP for educators and high school students this summer. At QCaMP, participants will get a primer on computing fundamentals, learn hands-on about quantum physics, and apply those phenomena to solve computing problems in new ways. The camp will help the teachers better expose their students to the opportunities related to quantum computing.
Sign up to be a Teaching Assistant this Summer
For this summer, the K-12 team is still seeking teaching assistants. Interested researchers can apply online or contact Faith or Alisa.
“The content for our training programs is based on research going on at the Lab. It’s what makes our program special and authentic,” said Faith. “I’m extremely appreciative of our scientists, especially postdocs. Our K-12 program provides the scaffolding and infrastructure, while the researchers provide the content and the real lab experiences.”
K-12 and Workforce Development and Education (WD&E) Offices to be Combined this Fall
To better support the Lab’s commitment to developing the next generation of scientists, engineers, and STEM professionals, the Lab is consolidating the K-12 programs and the WD&E Office within the Lab Directorate. Faith will serve as the office’s director. These changes will be in phases, with the new office fully operational in the fall. This new consolidated structure will improve efficiency and provide a more consistent experience for everyone involved; it will coordinate how the Lab supports interns across the Lab and also strengthen the relationships with teachers, faculty, and those in technical and operations roles.
For more information about the Lab’s efforts to help develop the next generation of scientists, visit the K-12 website and the WD&E Office website.
| 2025-06-27T00:00:00 |
2025/06/27
|
https://research.lbl.gov/2025/06/27/k-12-office-helps-build-tomorrows-ai-ml-workforce/
|
[
{
"date": "2025/06/27",
"position": 29,
"query": "machine learning workforce"
},
{
"date": "2025/06/27",
"position": 25,
"query": "machine learning workforce"
},
{
"date": "2025/06/27",
"position": 30,
"query": "machine learning workforce"
},
{
"date": "2025/06/27",
"position": 31,
"query": "machine learning workforce"
},
{
"date": "2025/06/27",
"position": 30,
"query": "machine learning workforce"
},
{
"date": "2025/06/27",
"position": 27,
"query": "machine learning workforce"
},
{
"date": "2025/06/27",
"position": 28,
"query": "machine learning workforce"
},
{
"date": "2025/06/27",
"position": 28,
"query": "machine learning workforce"
},
{
"date": "2025/06/27",
"position": 28,
"query": "machine learning workforce"
},
{
"date": "2025/06/27",
"position": 25,
"query": "machine learning workforce"
},
{
"date": "2025/06/27",
"position": 39,
"query": "machine learning workforce"
},
{
"date": "2025/06/27",
"position": 24,
"query": "machine learning workforce"
},
{
"date": "2025/06/27",
"position": 27,
"query": "machine learning workforce"
}
] |
Exploring the Challenges and Opportunities of Reskilling ... - Simbo AI
|
Exploring the Challenges and Opportunities of Reskilling Employees to Adapt to AI Integration in the Modern Workplace
|
https://www.simbo.ai
|
[] |
AI and Workflow Automation: Enhancing Healthcare Operations with Skilled Staff. AI plays a big role in automating work in healthcare ...
|
Artificial intelligence (AI) is now a normal part of many workplaces, including medical offices in the United States. AI can do simple, repetitive tasks, make decisions faster, and help work run more smoothly. Because of this, medical practice leaders and IT managers have to figure out how their workers can work well with AI. This means teaching employees new skills so they don’t get left behind.
Studies show that by 2025, about half of workers in many fields, including healthcare, will need to learn new skills to keep up with new technology. Many of the skills people use today will change. One-third of future skills will focus on technology, which many workers don’t know about now.
Healthcare leaders should know that AI will not take over all jobs but will change what people do. For example, AI can handle tasks like scheduling appointments, answering billing questions, managing records, and even initial patient checks. These jobs are important but take a lot of time. Letting AI do them means staff can spend time on harder tasks that need human thinking, caring, and medical skill.
This shift means employees must learn how to use AI tools and know the steps of how AI works. Skills like understanding AI, analyzing data, thinking critically, and working with AI systems are becoming more important. Experts say human understanding is still very important because people know context better than AI does. Workers also need to learn how to give good instructions to AI and make AI work efficiently.
Teaching staff new skills makes sure AI helps their work instead of causing problems or worries about jobs.
The Challenges Employers Face in Reskilling for AI
Many medical offices in the U.S. have a hard time teaching workers new AI skills.
One big problem is that employees often do not trust AI. Many worry AI might replace their jobs. This fear is real and based on economic and social issues.
There is also a gap between the skills workers have and the new skills they need. Many workers are trained only in clinical or office tasks and don’t have technical skills related to AI. They also need to improve soft skills like communication, solving problems, and being flexible.
Training is not easy to provide for all. Smaller medical offices often do not have enough money or links with schools to offer continuous AI training for workers.
Legal rules are another challenge. HR managers must follow strict laws when using AI in hiring, firing, and other work decisions. New laws, like one in Colorado, require fairness and clear explanations when AI is used. This makes HR’s job harder.
Training inequality can cause problems. If some workers or offices get good AI training while others do not, it can create a gap, cause workers to leave, and make healthcare less stable.
Opportunities Presented by Reskilling in AI Workplaces
Even with these challenges, there are good chances for medical offices that train their workers in new skills.
As AI takes over simple tasks, employees can do more meaningful work. For example, in fields like radiology, AI can help analyze images, so humans can focus on making decisions and analyzing information instead of just doing routine checks.
Training helps workers combine medical knowledge with AI skills. Learning basic AI, programming, and data can improve patient care because workers understand AI advice better and can help improve AI programs.
Studies show workers who get training feel happier at work. One study showed that 71% of people who learned new skills said their job satisfaction improved. This helps keep workers and reduce burnout problems.
AI-based personalized training is also useful. Some platforms can find what skills each worker needs and offer small learning lessons that fit their jobs. This allows busy healthcare workers to learn without leaving their work for long periods.
A 2024 survey found that 70% of workers felt ongoing learning made them closer to their workplaces. Medical practice leaders who support training may see better worker involvement, fewer mistakes, and happier patients.
✓ Voice AI Agent: Your Perfect Phone Operator SimboConnect AI Phone Agent routes calls flawlessly — staff become patient care stars. Claim Your Free Demo
AI and Workflow Automation: Enhancing Healthcare Operations with Skilled Staff
AI plays a big role in automating work in healthcare, especially in tasks done at the front desk, which usually take a lot of staff time.
AI can answer phone calls, book appointments, send reminders, and give routine info without help from humans. This reduces the workload of receptionists and office staff. They can then spend more time helping patients with kindness and good judgment.
Automation helps work run more smoothly by lowering mistakes in scheduling and admin tasks. It also helps keep patient data safe and follow rules.
But AI automation needs workers who can manage and watch over these systems. IT managers in medical offices must teach staff how to look after AI tools, understand AI reports, fix technical problems, and watch out for errors or biases in the AI.
Besides front-office tasks, AI helps with clinical tasks like first patient diagnosis, writing clinical notes, and billing codes. This means healthcare workers need to know about ethical use of AI, data privacy, and rules.
Automate Medical Records Requests using Voice AI Agent SimboConnect AI Phone Agent takes medical records requests from patients instantly. Start Your Journey Today →
Legal and Ethical Considerations in AI Implementation
Leaders in medical offices must focus on using AI in ethical ways. AI systems should be clear, fair, and protect patient privacy. This is very important because AI decisions can affect patient health, trust, and confidential information.
Training programs should teach workers about AI ethics and how to manage AI responsibly. HR teams must make sure AI use follows new laws like Colorado’s AI law, which requires human supervision in important AI decisions.
Employers should also plan for workers who might lose some jobs because of automation. Good communication and retraining can help these workers move to new roles in the same workplace.
Preparing a Future-Ready Healthcare Workforce
Healthcare leaders need to keep training workers continuously to stay up-to-date and meet rules.
Healthcare is changing like other industries. Workers need new tech skills like AI, cloud computing, data analysis, and cybersecurity.
Building a culture where workers keep learning is key. Medical offices can use AI learning platforms that give short lessons and real projects, like creating AI chatbots or planning data use. This teaches practical skills.
Continuous learning helps workers and improves how healthcare offices work. With better AI skills, workers can focus on important projects like patient care and communication, while AI handles simple office jobs.
Final Thoughts for Medical Practice Administrators, Owners, and IT Managers in the U.S.
Using AI in healthcare brings both problems and chances for training workers.
Medical offices cannot treat AI as a separate tool. Instead, they have to see AI as a partner that works with human workers.
Teaching workers new skills is key to making this partnership work. It is important to deal with worker fears, give everyone good training chances, and use AI fairly and openly. Learning AI basics, data skills, and people skills helps improve work, job happiness, and patient care.
Healthcare leaders in the U.S. should make training programs that fit their workers’ needs. As AI changes job roles, supporting workers during this change is important for having a strong and ready workforce.
| 2025-06-27T00:00:00 |
2025/06/27
|
https://www.simbo.ai/blog/exploring-the-challenges-and-opportunities-of-reskilling-employees-to-adapt-to-ai-integration-in-the-modern-workplace-624027/
|
[
{
"date": "2025/06/27",
"position": 86,
"query": "reskilling AI automation"
}
] |
STOP Taking Random AI Courses — Read These Books Instead
|
STOP Taking Random AI Courses — Read These Books Instead
|
https://medium.com
|
[
"Egor Howell"
] |
Deep learning is where all these generative AI algorithms came from, so ... Most AI jobs are so-called AI engineers, and it's closer to ...
|
STOP Taking Random AI Courses — Read These Books Instead Egor Howell 7 min read · Jun 28, 2025 -- 34 Share
A comprehensive guide to the books and courses that helped me learn AI
Photo by Kimberly Farmer on Unsplash
After working in AI and machine learning for four years, I want to share all the resources that helped me on my journey.
As there are quite a few, I am going to break them down into the following categories:
| 2025-06-28T00:00:00 |
2025/06/28
|
https://medium.com/data-science-collective/stop-taking-random-ai-courses-read-these-books-instead-352bca9fa303
|
[
{
"date": "2025/06/27",
"position": 68,
"query": "generative AI jobs"
},
{
"date": "2025/06/27",
"position": 78,
"query": "generative AI jobs"
}
] |
Reskilling Revolution: Preparing the Current Workforce for AI's ...
|
Reskilling Revolution: Preparing the Current Workforce for AI's Demands
|
https://www.linkedin.com
|
[] |
... AI demands. The Urgency of Reskilling in an AI World. AI-powered automation is already displacing routine and repetitive tasks across industries ...
|
As artificial intelligence reshapes the labor market at an unprecedented pace, the question is no longer if jobs will change, but how workers will adapt. The future belongs to those who embrace the reskilling revolution a massive, urgent effort to equip today’s workforce with the skills AI demands.
The Urgency of Reskilling in an AI World
AI-powered automation is already displacing routine and repetitive tasks across industries. From manufacturing floors to finance departments, roles once considered secure are evolving or disappearing altogether. For millions of workers, especially in middle-skill jobs, this shift is a clear call to action: reskill or risk obsolescence.
Unlike past technological disruptions, AI requires a broader range of skills not only technical literacy but also problem-solving, creativity, emotional intelligence, and adaptability. Preparing the workforce for these demands is an enormous challenge that governments, businesses, and educational institutions must tackle collaboratively.
Who Needs Reskilling?
While it’s easy to assume that only workers in manufacturing or low-skill jobs will be affected, AI’s reach is much wider. White-collar roles in accounting, legal services, marketing, and even healthcare are experiencing automation of core tasks. This means professionals across the spectrum must upgrade their skills to remain relevant.
Reskilling initiatives should therefore target a broad audience: frontline workers, mid-career professionals, and even executives who must understand AI’s strategic implications. The goal is to build a versatile workforce capable of complementing AI technologies rather than competing against them.
Effective Reskilling Models: What Works?
Successful reskilling programs combine accessibility, relevance, and flexibility. Online learning platforms, micro-credentialing, and modular courses allow workers to acquire new skills without leaving their jobs. Governments and corporations alike are investing heavily in these initiatives, recognizing that time is of the essence.
Moreover, mentorship and hands-on training accelerate learning by providing real-world context. Pairing AI tools with human expertise creates a powerful synergy, and companies that prioritize continuous learning often see higher employee retention and innovation rates.
The Role of Employers and Policymakers
Employers must view reskilling as a strategic imperative rather than a cost. Proactive workforce development can reduce turnover, improve productivity, and future-proof organizations. Forward-thinking companies are already partnering with educational institutions to co-design curricula that meet evolving industry needs.
Policymakers, meanwhile, must create supportive ecosystems through funding, incentives, and regulatory frameworks. Public-private partnerships can scale reskilling efforts and ensure equitable access across socioeconomic groups.
Overcoming Barriers to Reskilling
Despite growing awareness, several barriers slow reskilling progress. Financial constraints, limited access to training resources, and fear of change often discourage workers from engaging in upskilling efforts. Addressing these challenges requires comprehensive support systems including subsidies, flexible learning schedules, and career counseling.
Cultural attitudes toward lifelong learning must also evolve. Reskilling is not a one-time event but an ongoing journey that requires motivation, encouragement, and a growth mindset.
The Promise of a Reskilled Workforce
The reskilling revolution offers a path toward a more resilient, inclusive labor market. Workers empowered with new skills can navigate the AI era with confidence, contributing to innovation and economic growth. As AI transforms the nature of work, reskilling isn’t just a solution — it’s a necessity. Investing in people is the most effective way to ensure that technology enhances human potential rather than diminishes it. The time to act is now. The future of work depends on how well we prepare today’s workforce for the AI-driven world.
#Reskilling #FutureOfWork #AI #WorkforceDevelopment #LifelongLearning #Upskilling #DigitalTransformation
| 2025-06-27T00:00:00 |
https://www.linkedin.com/pulse/reskilling-revolution-preparing-current-workforce-yucwc
|
[
{
"date": "2025/06/27",
"position": 16,
"query": "reskilling AI automation"
}
] |
|
From Hiring to Privacy: How AI Is Reshaping California Workplaces
|
From Hiring to Privacy: How AI Is Reshaping California Workplaces
|
https://www.californiaemploymentlawreport.com
|
[
"Anthony Zaller",
"June",
".Wp-Block-Co-Authors-Plus-Coauthors.Is-Layout-Flow",
"Class",
"Wp-Block-Co-Authors-Plus",
"Display Inline",
".Wp-Block-Co-Authors-Plus-Avatar",
"Where Img",
"Height Auto Max-Width",
"Vertical-Align Bottom .Wp-Block-Co-Authors-Plus-Coauthors.Is-Layout-Flow .Wp-Block-Co-Authors-Plus-Avatar"
] |
1. AI Is Already in the Workplace—and Use Is Expanding · 2. California Is Leading with New AI Employment Regulations · 3. Employers Are Still ...
|
AI is no longer just a buzzword—it’s actively transforming the workplace. Whether employers are aware of it or not, AI tools are being embedded into daily operations across industries. With California pushing forward with proposed regulations that could take effect as early as July 1, 2025, employers must begin understanding the implications now. Here are five essential points to keep in mind:
1. AI Is Already in the Workplace—and Use Is Expanding
Many California employers are already using AI—even if only in limited ways. One of the most common use cases is resume screening. Large employers facing thousands of applications use AI to quickly sort resumes and identify the most qualified candidates. AI is also being used to:
Draft employee communications : HR teams are using tools like ChatGPT to write performance reviews, disciplinary notices, or coaching emails.
: HR teams are using tools like ChatGPT to write performance reviews, disciplinary notices, or coaching emails. Assist in onboarding : Chatbots can guide new hires through paperwork, benefits enrollment, and training schedules.
: Chatbots can guide new hires through paperwork, benefits enrollment, and training schedules. Enhance recruiting: Some available tools use video analysis and natural language processing to assess applicant responses.
Even managers are using AI to brainstorm better ways to give feedback or handle difficult conversations.
Example: An HR manager struggling to coach an underperforming employee may use ChatGPT to draft a constructive and empathetic email, saving time and ensuring the message is clear and legally sound.
2. California Is Leading with New AI Employment Regulations
California’s proposed Automated Decision Systems (ADS) regulations aim to ensure that AI tools used in employment decisions are fair, transparent, and compliant with anti-discrimination laws (see our prior article on the proposed regulations here). These rules would:
Require notice to applicants when AI tools are used
when AI tools are used Mandate anti-bias testing and corrections
Impose a four-year recordkeeping requirement
Apply to vendors and hold employers legally responsible for third-party tools
The regulations are designed to prevent unintentional discrimination—such as AI tools screening out candidates with gaps in employment (which may affect women or caregivers more).
Example: If your company uses AI to rank candidates and the system deprioritizes people who’ve taken career breaks, that could result in a discriminatory impact. Under the new rules, you’d need to detect and fix that.
3. Employers Are Still Liable—Even When AI Makes the Decision
You can’t delegate legal responsibility to an algorithm. If an AI screening tool inadvertently excludes protected classes (e.g., based on age, race, or disability), your business is still liable under existing discrimination laws.
A current case in California, Mobley v. Workday, involves a 40+ year-old Black man who alleges he was repeatedly rejected by AI tools used by employers. The case is moving forward under current federal and state anti-discrimination laws.
Example: Even if a third-party software provider made the AI, if it screens out applicants unfairly, and your business uses it, your company can be sued under FEHA or Title VII.
4. AI May Actually Help Reduce Bias—When Used Correctly
There’s hope for AI to help level the playing field. A study by researchers at Stanford and USC found that AI-led hiring processes were more successful at identifying qualified candidates—particularly younger, less experienced, and female applicants—than traditional resume reviews and human interviews.
AI can promote a more “blind” evaluation process, reducing the potential for human bias related to names, photos, age, or education pedigree.
Example: A company replaces its initial resume screening with a structured AI interview system. The result? A more diverse candidate pool, selected based on skills and responses, not superficial traits.
5. Wearables and AI Tools Raise Serious Privacy Concerns
With tools like AI-powered glasses (like Google’s new Gemini glasses) and Zoom note-takers, privacy risks are growing. These tools can record conversations, analyze speech, and even recognize faces. California is a two-party consent state—recording without consent is illegal and could lead to criminal and civil penalties.
Example: An employee shows up wearing smart glasses that record everything they see and hear. If they record private conversations without the other party’s consent, it could violate California Penal Code section 632 and create liability for the employer.
Employers should start preparing policies or training on the use of wearables and AI tools in the workplace—even if a formal “AI governance policy” feels premature.
Final Thoughts
AI can help your business stay compliant, attract better candidates, and operate more efficiently—but only if you understand the risks and responsibilities. Think of it like a powerful new employee: it needs supervision, training, and accountability. Don’t wait until your competitors—and the regulators—are ahead of you.
Start small. Use AI to help HR draft communications or streamline workflows. Just be sure you pair every tool with legal oversight and human judgment.
| 2025-06-28T00:00:00 |
2025/06/28
|
https://www.californiaemploymentlawreport.com/2025/06/from-hiring-to-privacy-how-ai-is-reshaping-california-workplaces/
|
[
{
"date": "2025/06/27",
"position": 94,
"query": "AI regulation employment"
},
{
"date": "2025/06/27",
"position": 96,
"query": "AI regulation employment"
},
{
"date": "2025/06/27",
"position": 14,
"query": "AI employers"
},
{
"date": "2025/06/27",
"position": 45,
"query": "ChatGPT employment impact"
},
{
"date": "2025/06/27",
"position": 49,
"query": "artificial intelligence employment"
}
] |
'The biggest risk is doing nothing': insights from early ...
|
‘The biggest risk is doing nothing’: insights from early adopters of artificial intelligence in schools and further education colleges
|
https://www.gov.uk
|
[] |
AI in education use is still a new and developing area and is largely experimental. AI can certainly save teachers time, and there is increasing evidence of its ...
|
Executive summary
The launch of ChatGPT in November 2022 dramatically increased public access to generative artificial intelligence ( AI ) and brought it into the mainstream. The availability of publicly-available AI tools like Microsoft Copilot and ChatGPT have also sparked widespread interest and discussion about the role that generative AI can play in education.
The UK government is ambitious for AI and views it as a fundamental part of its mission to break down barriers to opportunity for children and young people.[footnote 1] The Department for Education ( DfE ) has stated that:
If used safely, effectively and with the right infrastructure in place, AI can ensure that every child and young person, regardless of their background, is able to achieve at school or college and develop the knowledge and skills they need for life.[footnote 2]
The UK government’s AI Opportunities Action Plan sets out expectations from the Department for Science, Innovation and Technology for AI to improve education and ensure that regulation supports innovation. Regulators, including Ofsted, will be required to publish annually how they have enabled AI innovation in their sector.[footnote 3]
Generative AI can be used to streamline administrative tasks, plan lessons and support assessment.[footnote 4] This has made it particularly attractive for reducing teacher workload, so that teachers can focus on delivering high-quality teaching and on working directly with pupils. Although the UK government has identified education as an area that can benefit from AI , adopting it in schools and further education ( FE ) colleges faces considerable challenges. Half of teachers in England responding to a DfE survey now use generative AI tools.[footnote 5] However, of those who do not use them, 64% say they do not know enough about AI to use it in their role and 35% are concerned about the risks, particularly around data privacy, bias and safeguarding, and users’ ethical and responsible use of AI .[footnote 6]
AI in education use is still a new and developing area and is largely experimental.[footnote 7] AI can certainly save teachers time, and there is increasing evidence of its impact on the process of teaching and learning.[footnote 8] However, there is no conclusive, reliable evidence about its benefits and limitations, particularly its ability to lead to gains in knowledge.[footnote 9] A recent analysis of 143 literature reviews of AI in education concluded that:
The effectiveness of AIED to improve learning outcomes remains far from conclusive, especially in the long-term. As we currently stand, most studies are explorative, short-term and in limited domains [for example] language and academic writing.[footnote 10]
There is also no clear guidance yet about how to measure the impact of AI in education to show whether it is effective at improving educational outcomes or what the best measures of success would be.[footnote 11]
The DfE , therefore, commissioned Ofsted to carry out a study on AI in education to investigate how ‘early adopter’ schools and FE colleges are embedding AI to manage risks, support teaching and learning, and streamline administrative tasks and processes. By ‘early adopter’, we mean ‘someone who is one of the first people to start using a new product, especially a new piece of technology’.[footnote 12]
Our study was carried out in 2 stages. The first stage included having conversations with experts and reviewing the emerging evidence on AI use in education. This helped inform the research questions for the second stage. This stage involved online interviews with senior leaders and those leading AI adoption from 21 schools and FE colleges already invested in using AI in England.[footnote 13] The evidence we collected from the interviews provides insights into leaders’ reasons for adopting AI and shows how they have navigated and overcome some of the obstacles. This information may help other schools and FE colleges when considering their own approaches to using AI .
Our findings show that adoption of AI is complex and has many aspects to it. We can see that, in deciding to adopt AI , providers take different factors into account, depending on the ways they want to use it. These can range from using AI to streamline administrative tasks to allowing pupils use it in a direct and interactive way. Other factors such as differences in adoption readiness, existing experience of digital technology and the availability of resources also affect AI use. For example, schools already committed to using digital technology as part of teaching and learning will have staff expertise and experience of using EdTech and the hardware needed to support the integration of AI .[footnote 14]
It is important to distinguish between these different aspects of AI and how, when and why they are used. Doing so helps us understand how AI is used in different educational settings. It can also suggest how future policies and support mechanisms might be tailored to address the unique challenges and opportunities these different aspects of AI offer.
All the leaders we spoke to were curious and cautious in their adoption of AI . The AI landscape is still changing rapidly, and they need to balance innovation and risk. Typically, leaders saw beyond AI as a shiny new product, and none viewed it as a cure-all for education. Leaders had found ways to integrate AI into processes that they felt were likely to be beneficial for staff, learners and pupils in their college or school.
Most schools and colleges had an AI champion who was instrumental in getting senior leaders to embrace AI and bringing staff on board. In most cases, the champion was a teacher who had previous relevant experience or expertise in technology and AI . In other cases, it was someone who simply had a keen interest that was further fuelled by the release of publicly-available AI tools such as ChatGPT. AI champions typically created a ‘buzz’ around AI and played a vital role in demystifying it so that staff began to understand what it was and how they could use it. They used their expertise to address staff anxieties and build confidence so that staff did not feel overwhelmed. AI champions could determine what help teachers needed and show how AI could be used for this purpose, rather than using AI more generically. In larger schools and FE colleges, and multi-academy trusts ( MATs ), AI leadership brought together their data management teams, IT systems managers and curriculum leads.[footnote 15] This kind of structure recognised that, unlike other forms of technology, AI requires skills and knowledge across more than one department.
Senior leaders made sure there was a clear vision for AI which prioritised safe and ethical use by staff and pupils. They tended to take initial small steps to explore the potential of AI before adopting it across their school, college or MAT . Leaders frequently made sure that teachers had the space and time to experiment and learn how AI could support and enhance their own practice. This created a culture of openness and trust that encouraged innovation.
The use of AI tools in these providers was divided between those who told us the initial reason for introducing AI was to reduce workload, and those who wanted to use it to directly support pupil and student learning. However, we also found that the use of AI often shifted with time. Leaders were rarely prescriptive about the tools teachers could have, and many had a list of approved AI tools teachers could use. Interestingly, a few leaders had already developed, and were testing, their own AI chatbot, while others were in the process of doing so.[footnote 16] Several leaders also highlighted how AI allowed teachers to personalise and adapt resources, activities and teaching for different groups of pupils including, in a couple of instances, young carers and refugee children with English as an additional language.
Commonly, the leaders we spoke to were clear about the risks of AI around bias, personal data, misinformation and safety. They had different mechanisms and procedures to address these. Some had a separate AI policy, while others had added AI to relevant existing policies including those for safeguarding, data protection, staff conduct, and teaching and learning. The pace of change meant that many leaders were updating their AI policies as often as monthly. Importantly, these leaders encouraged regular and open discussion about AI between staff and with pupils to mitigate some of the risks associated with AI . This included developing their curriculum to teach pupils about the advantages and disadvantages of AI and how to use it safely.
Despite some of the perceived strengths of AI , leaders were also clear about several areas that they were looking to develop further. For instance, leaders regularly described their vision for AI to enhance learning or reduce teacher workload, but most were at the early stages of developing a longer-term strategy for AI that set out how it was integrated into their curriculum. Leaders had not yet thought systematically about integrating AI with pedagogy because of the rapid pace of change and because there are still not many AI tools tailored to individual school or college contexts. Some leaders had yet to think strategically about what success with AI looked like or how to evaluate its impact.
These findings provide insights into how early adopters have navigated the challenges of AI and what they see as the benefits of using it. They have helped to inform Ofsted’s own position on AI during inspection. Our statement ‘How Ofsted looks at AI during inspection and regulation’ makes it clear that AI is not a stand-alone part of Ofsted’s inspection and regulation practice. Inspectors will not directly evaluate the use of AI , nor any AI tool. However, when they come across the use of AI , inspectors will consider not only how it is used by providers, but also how it is used in a provider’s setting by others (including staff, parents, pupils and learners). We will also use the findings of this research to develop training for inspectors, to ensure that they are able to account for the use of AI when considering experiences and outcomes in this way.
This small-scale research has been an important first step to enable AI innovation in the sector. However, the study does not reflect the majority of schools, MATs and FE colleges that are yet to adopt AI . We only spoke to leaders and do not know the views and experiences of teachers, pupils and learners. Further research with a wider group of stakeholders could provide more in-depth understanding of the way AI is used, the impact it can make, and the implications for our inspection and regulation practices.
Introduction
Since the release of open-source AI , its adoption in schools and colleges has been met with both enthusiasm and concern by education experts, policymakers and practitioners. Generative AI has been perceived as having the potential to enhance learning and reduce administrative burdens.[footnote 17] However, it is also seen as a risk to academic integrity and cybersecurity.[footnote 18] Consequently, the DfE ’s call for evidence on the use of generative AI highlighted some of the ways in which schools and FE colleges currently use AI , the challenges they face and the impact its use has on them. The DfE has subsequently provided guidance on AI use in education. The guidance emphasises the importance of curriculum and responsible AI integration. It also lays out the relevant legal responsibilities.[footnote 19]
The UK government’s AI Opportunities Action Plan has identified education as an area where AI could have a positive impact. Recent initiatives have further highlighted the growing importance of AI in education. In August 2024, the DfE announced a £4 million investment to develop a set of AI tools for different ages and subjects to help manage the burden on teachers for marking and assessment.[footnote 20] The DfE has also funded development of Oak National Academy’s ‘Aila’ ( AI lesson assistant) and developed training materials on AI with the Chiltern Learning Trust and the Chartered College of Teaching. These are in addition to a new EdTech Evidence Board project funded by the DfE and led by the Chartered College of Teaching. This will evaluate available evidence submitted by AI developers about the effectiveness and impact of their products, as well as whether the products are ethical and comply with data protection laws.
Despite the hype surrounding it, AI adoption in schools is still at an early stage and adopters remain in the minority. For instance, 69% of UK teachers who responded to a 2024 Bett survey said their school has not implemented AI , and 32% of school and college leaders in England are not considering any changes to account for AI .[footnote 21] However, a survey by the National Literacy Trust found the proportion of 13- to 18-year-olds who say they have used generative AI has risen from 37% in 2023 to 77% in 2024. The survey also found that, although nearly half (47.7%) of pupils using AI usually added their own thoughts to what AI showed them, most (79%) did not do this when they used it for homework.[footnote 22] These surveys suggest that, although there is enthusiasm for AI among individual teachers and students, its adoption by school and college leaders is not keeping pace with teacher, pupil and learner use.
As the use of AI in education increases, we need to better understand how schools and colleges are using this technology and managing the risks it poses for pupils, learners and staff. We have to know what impact it is having on a range of outcomes. The DfE , therefore, commissioned Ofsted to carry out research on AI in education. This is intended to highlight the practice of early adopter schools and FE colleges in embedding safe, ethical and responsible AI use, which other educational settings can refer to, if and when they choose to develop their own AI practice.
Ofsted is gathering evidence about how AI is being used in schools and FE colleges. This research will add to Ofsted’s understanding of the mechanisms that support the adoption of AI . It will fill gaps in our knowledge around the use of AI and its impact on pupils and staff. Ultimately, it will inform our inspection and regulation practice, as well as the guidance and training we develop for inspectors in this rapidly evolving field.
The terms of reference provide further details on the aims and objectives of the study. The research covers the following areas:
How are schools and colleges using AI in administrative processes and to support teaching and learning?
in administrative processes and to support teaching and learning? What role do leaders play in embedding and supporting the use of AI ?
? How have schools and colleges approached introducing and using AI , and what have been the challenges, barriers, successes and benefits?
, and what have been the challenges, barriers, successes and benefits? How are schools and colleges monitoring the intended and unintended impacts of AI ?
? How are schools and colleges governing the use of AI and managing the risks to staff, pupils and learners?
Research methods
This was a small-scale qualitative study in 2 phases. In the first phase, we carried out a rapid review of the emerging literature on generative AI to identify its potential benefits in education and the main barriers and challenges schools and colleges may need to overcome. We also reviewed international legislation, policies and guidance related to AI in education, and spoke to international inspectorates and academics with knowledge of AI in education.
The literature review and conversations with experts helped inform the questions for the second stage of the study. This involved online interviews, in the spring term 2025, with leaders of ‘early adopter’ MATs , schools and FE colleges who had responsibility for the adoption of AI . These included leaders from maintained schools and academies and independent schools.
The leaders we interviewed were all enthusiastic about the benefits of AI and had decided to pilot generative AI in their school or college soon after ChatGPT was made publicly available. The interviews allowed us to capture their AI journey and, informed by the literature review, develop our understanding of the following:
leadership of AI : the role of leaders in enabling and embedding AI use
: the role of leaders in enabling and embedding use governance of AI : how leaders make sure staff, pupils and learners use AI ethically, safely and responsibly
: how leaders make sure staff, pupils and learners use ethically, safely and responsibly use of AI : how staff use AI inside and outside the classroom
Please see Appendix B for more details on the research methods and literature review.
Research literature
This section of the report outlines what we know from the literature about the potential benefits and disadvantages of AI in education as well the barriers and challenges to embedding and using AI tools. It also reports on how other countries are approaching AI and responding to some of these challenges.
What is artificial intelligence?
AI is not a new concept. The term was first used in the 1950s to describe machines capable of performing tasks that require human intelligence.[footnote 23] What is new is the introduction of generative AI and the public availability of generative AI tools such as Microsoft Copilot and ChatGPT.
AI is not a single thing. It is an umbrella term that describes a range of technologies and methods such as machine learning, natural language processing, data mining, neural networks and algorithms.[footnote 24] The UK government defines AI systems as ‘products and services that are “adaptable” and “autonomous”’.[footnote 25]
Generative AI refers to AI platforms designed to create new, unique responses to users’ requests. It uses a vast collection of works and other sources to create text, images and videos that can be indistinguishable from those created by humans.[footnote 26] However, generative AI does not understand anything. Unlike traditional search engines such as Safari and Google, it is a predictive tool. It generates an answer based on patterns in data and knowledge that it has learned, rather than by simply retrieving existing information. AI ’s ability to create new responses makes it susceptible to generating inaccurate or misleading outputs presented as fact. These ‘hallucinations’ can happen when AI misinterprets data, has difficulty responding to ambiguous prompts, lacks sufficient context or uses biased data.[footnote 27] For example, if AI has learned that 85% of employees in a company are male, it will predict that the perfect new employee for the company should also be male.
Generative AI includes chatbots and virtual assistants. It has been developed to answer test questions, write essays, translate and summarise texts, provide formative feedback, and even generate lesson plans tailored to individual pupil needs. It can also provide individual teaching that adapts to pupils’ pace of learning and helps understand how learning happens.[footnote 28]
Potential benefits and risks of AI in education
One of the most frequently cited benefits of AI in education is that it reduces teachers’ workload. By automating typical teacher tasks such as lesson planning, marking and resource creation, AI can give teachers more time to concentrate on aspects of teaching that have the most direct impact on pupil engagement and learning, such as producing high-quality resources and learning materials.[footnote 29] A recent trial studied the impact on teacher workload of using ChatGPT for lesson planning and resource creation. The study found that AI could save the time teachers spent on planning and administration by 31%, which was equivalent to 25 minutes per week.[footnote 30]
AI -driven platforms have also shown that they can support formative assessment and feedback.[footnote 31] These systems mark pupils’ and learners’ work and give detailed individual feedback that helps them to understand their progress and areas for improvement. Evidence also suggests that intelligent tutoring systems and chatbots can analyse real-time data on pupil performance and engagement to tailor resources and adjust teaching to individual needs.[footnote 32] AI chatbots respond to users’ questions by generating verbal instructions similar to those a teacher might give to help solve a problem. Pupils and learners can use the real-time feedback to improve their work.[footnote 33] When they use generative AI for personalised learning, it increases their motivation and improves their critical thinking skills.[footnote 34] For example, pupils using chatbots can prompt generative AI with questions and then evaluate the different viewpoints and insights provided. Instead of giving pupils the answer, the AI will use pupils’ prompts to clarify, expand, elaborate, verify and put their knowledge into context.[footnote 35]
However, there are concerns about how valid it is to use AI for setting, marking and assessing exams. Two of the main concerns often raised are that there is a narrow range of acceptable answers, and that AI markers are not able to give reasons for decisions.[footnote 36] Research also shows that AI tools can replicate human marking bias and may struggle to identify high- and low-scoring essays.[footnote 37] AI is also particularly bad at identifying exceptional and original work and may not be able to correctly assess nuance and creativity.
The literature suggests that AI could have a positive impact on teaching and learning. However, there is currently little independent academic evidence of its actual impact on outcomes.[footnote 38] This is particularly the case with generative AI tools as their newness means most of the available information comes from developers themselves.[footnote 39] Systematic reviews of academic literature and research with teachers indicate that AI can enhance personalised learning and provide immediate feedback.[footnote 40] However, these sources also suggest that relying too much on it may make it harder for pupils and learners to develop essential skills, such as essay writing, and higher-order processes such as problem-solving, creativity and critical thinking.[footnote 41] Overreliance on AI -generated responses may also weaken pupils’ capacity to engage deeply with learning material and hinder their ability to retain knowledge in the long term.[footnote 42] It may also create an illusion of learning where pupils and learners produce more but understand less.[footnote 43]
Teachers have also indicated that they are concerned about how AI use may affect them. Using AI for tasks such as marking, resource creation and lesson planning could deskill them.[footnote 44] Teachers may find that AI tools produce similar outputs regardless of their students’ specific needs or the local curriculum goals.[footnote 45] Academic research also suggests that AI may be biased towards particular pedagogical approaches.[footnote 46]
The impact of AI is also felt beyond education. For example, the literature does not give enough attention to the environmental and ecological impact of AI ’s high energy use.[footnote 47] There are also concerns about the lack of transparency around the algorithms and datasets that commercial AI tools use.[footnote 48]
The overarching conclusion is that despite literature indicating there is potential for AI to have a positive impact on teaching and learning, there is currently little reliable evidence available of its actual impact on outcomes.[footnote 49]
Barriers to AI adoption
The literature indicates that adopting AI into educational systems involves navigating a range of barriers and significant challenges. For instance, the use of AI by staff and pupils needs robust safeguarding and governance frameworks. This is because generative AI systems collect and analyse large data sets and there is significant potential for breaches of data privacy. Guidelines from the UK’s Information Commissioner’s Office stress the importance of ensuring that AI tools fully comply with data protection regulations such as the General Data Protection Regulation ( GDPR ).[footnote 50]
A further concern is the risk of AI perpetuating or even amplifying existing biases. AI systems rely on algorithms trained on historical data, which may reflect stereotypical or outdated attitudes.[footnote 51] Education providers need strong governance mechanisms to reassure parents, staff and pupils that AI tools have been evaluated for bias, data security and suitability for different demographics, before they are adopted in practice.[footnote 52]
Schools and colleges also need to be transparent about their use of AI . This includes informing parents, particularly if pupils are using AI . The DfE ’s current position is that schools and colleges should establish clear accountability and transparency around the AI systems they use.[footnote 53] Surveys indicate that parental views about AI play a crucial role in its adoption in education. For example, although parents recognise that AI can help teachers and are happy for them to use it, they are uneasy about pupils using AI , particularly outside school.[footnote 54] Engaging parents in discussions about AI use in schools and increasing their understanding of how it can be used would help overcome some of these concerns.[footnote 55]
AI ’s ability to adapt and personalise resources and learning material to meet the needs of individual pupils and learners can provide significant opportunities for schools and colleges to address educational inequalities. However, the ‘digital divide’ between those who have ready access to digital technologies at home and/or at their school or college or school remains a major barrier in realising this potential. Many schools, particularly those in deprived areas, do not yet have high-speed broadband and/or adequate access to digital devices needed to support AI .[footnote 56]
Bridging this divide would require considerable investment in digital resources and training to ensure that all pupils and learners benefit equally from AI . This is particularly important for those who may be doubly disadvantaged in not having access to AI at home or school/college. There is also the possibility of a digital divide between pupils and learners in schools and FE colleges where AI is embedded in teaching and learning and those in providers yet to adopt AI . Pupils and learners in schools and FE colleges yet to adopt AI may miss out on the benefits described earlier in the section ‘Potential benefits and risks of AI in education’.
Importance of professional development
There are several factors that influence the adoption of AI in education. These include the technological infrastructure in schools and colleges, and the types of support leaders put in place to address teachers’ concerns and increase their trust in AI outputs. Successive surveys of teachers by the DfE show that, although more teachers are using AI , they are concerned about the risks.[footnote 57] There are key distinctions between the risks associated with generative AI used in education and those related to EdTech use more widely, as discussed in the ‘Potential benefits and risks of AI in education’ section. These surveys indicate that teachers need a stronger emphasis on ethical considerations alongside an understanding of how AI tools work and how they can be used safely and responsibly. Professional development needs to address both the technical and pedagogical aspects of AI , so that teachers know how to critically evaluate AI -generated outputs and manage the ethical challenges associated with AI use.[footnote 58]
Decisions to use digital technology are often influenced by what teachers believe about its benefits and how confident they are in integrating technology into their practice.[footnote 59] In the case of AI , these beliefs are more complex because of teachers’ specific fears and misconceptions about the risks of AI .[footnote 60] Along with factors directly related to AI tools, teachers have indicated that things for schools and FE colleges to consider when introducing AI include:
not increasing teacher workload or anxiety
having support mechanisms in place
building teachers’ knowledge of how to use AI
addressing misconceptions about AI and its risks[footnote 61]
Teachers’ acceptance of AI is fundamental to its successful use. Evidence suggests that teachers need to trust AI and perceive its value before they are willing to incorporate it into their practice.[footnote 62] Teachers’ willingness to use AI is also related to how easy they think it is to use. Seeing practical examples of high-quality AI in use and the impact on pupils and learners before using it themselves can make teachers more enthusiastic. This may cause them to challenge their own digital practice and what constitutes effective use of AI in classrooms.[footnote 63] As teachers become more familiar with AI and see its impact, they become significantly more willing to embed it into their practice.[footnote 64]
Teachers’ beliefs about EdTech and its impact on learning also affect whether or not they use AI in the classroom, and how they incorporate it into their pedagogy. Teachers with first-hand evidence of how it enhances teaching and learning are more likely to experiment with AI and use it in the classroom.[footnote 65] On the other hand, teachers who are sceptical about its capabilities and concerned about potential negative consequences (such as decreased teacher–pupil interaction or a loss of critical skills) can be less willing to embrace it and may delay their adoption of AI . Schools and colleges with a supportive infrastructure that gives staff the time and space as well as the agency to explore the benefits of AI in their particular context are more likely to embrace AI tools effectively.[footnote 66]
One way to think about how teachers use AI is to apply the SAMR (Substitution, Augmentation, Modification and Redefinition) model.[footnote 67] This model has 4 levels of technology use – substitution, augmentation, modification and redefinition – which start from using technology-enhancing teaching methods and end with transforming the way pupils learn. When using educational technology early on, teachers often focus on the first 2 levels (substitution and augmentation), which involve replacing traditional materials with digital ones. Examples of this are lesson planning and adapting resources online, or recording lectures on video and making them available for asynchronous learning. At the last 2 levels, technology is used for tasks not previously possible, such as live interviews of AI -generated historical figures. Evidence from researchers and teachers suggests that AI is not yet being widely used to redefine teaching and learning. It tends to be used to automate existing practices rather than to develop new practices that only AI can support.
Two of the main reasons teachers give for not using AI are that they do not know enough about how to use generative AI tools, and that they are concerned about the risks.[footnote 68] Teachers must, therefore, receive comprehensive professional development so they have the guidance and support they need to use AI tools effectively and responsibly. This should address both the technical and pedagogical aspects of AI , so that teachers know how to critically evaluate AI -generated outputs and manage the ethical challenges associated with AI use.
International context for AI in education
International approaches to regulation and governance of AI in education vary considerably. Some countries have introduced new legislation to address the risks around AI use while others, such as the USA, rely on voluntary compliance with guidelines and self-regulation. Different approaches to regulation are driven by how governments believe AI development and innovation is best supported and encouraged.
In Europe, the AI Act is the first legal framework to establish rules for anyone using or developing AI tools for education. All AI in education is classed as high risk and regulated. Schools must show how they ensure that AI is used appropriately, monitor and record how they use it, and report serious incidents. EU legislation also emphasises transparency for staff, pupils and parents. If schools use AI to write reports or grade work, they must tell parents and pupils and explain the processes.
Singapore’s approach to AI regulation combines mandatory regulations with voluntary guidelines. There are no specific laws or regulations that directly regulate AI but regulators have set out compliance requirements for data, accountability, reporting incidents, security, transparency, research and testing that apply to education use. The focus of regulation is schools’ awareness of acceptable risk levels and how they address them. This approach to regulation offers both structure and flexibility.
The DfE has adopted a less prescriptive stance to AI regulation than the EU by building on existing frameworks and guidance for schools around data protection, safeguarding and intellectual property.[footnote 69] This aligns with the Department for Science, Innovation and Technology’s guidance for regulators and is designed to encourage innovation while making sure that schools and FE colleges still have robust governance structures.[footnote 70]
Estonia’s approach to regulating AI in education contrasts sharply with the EU. Use of AI in education relies on self-regulation. Ministry of Education guidance for schools on how to use AI is described as ‘suggestions’ rather than regulations. Safe, ethical and responsible use of AI is included in the digital competencies that are part of the Estonian national curriculum for all children from 4 to 18 years of age. The competencies cover all aspects of digital technology use including copyright, digital security, protection of personal data, privacy, and the environmental impact of digital technology. Schools are expected to teach and assess the competencies as part of their own curriculum.
Evidence from provider visits
The following section reports our findings from 21 online interviews with leaders who have embedded the use of AI across their MAT , school or FE college. Their views highlight the actions and decisions they took that have formed critical parts of their school or college AI journey.
Leadership of AI
Two aspects of leadership were suggested in all the interviews. First, senior leaders were committed to enabling AI adoption at a strategic level. Second, they had an ‘ AI champion’ who had a passion for AI as well as the expertise and seniority to communicate the benefits of AI to other staff and senior leaders. One digital lead from a MAT summed this up as follows:
What you really need is someone with leadership responsibility. Someone who really has knowledge about what’s going on in AI in education. And then someone who can speak “human” as well, rather than “techie”. And if you’ve got those 3 ingredients, which some schools have, they’re the schools that are driving forward with this. But if you miss out the knowledge of what’s going on with AI , you start to increase the risk, or you don’t know the benefits of it. If you haven’t got leadership responsibility, you can’t drive it.
These 2 aspects of leadership created the foundation for AI adoption and also a culture that balanced safe and ethical use of AI with innovation. In some providers, these 2 roles were performed by 1 person. In others, often larger colleges and MATs , this role fell to more than 1 person.
The influence of an AI champion
The introduction and uptake of AI in many settings was driven not by strategic leadership, but by a teacher or leader who championed the use of AI . We often found that these individuals played a vital role in influencing leadership and inspiring staff to embrace AI in their practice. Importantly, the AI champions we spoke to had the essential knowledge and understanding of generative AI needed to convince senior leaders, including governors and trust CEOs, and staff to adopt AI . One champion, who was the director of digital transformation in an FE college, described their impact on governors and trust CEOs as follows:
I think the biggest change was when [I was] invited to show SLT [senior leadership team] and the governors how to use it. That was the turning point, where we all could recognise that this was going to have a big impact on teacher workload, but also on how AI could impact on teaching and learning.
This description is typical of how others described the relationship between the AI champion and senior leaders. They worked in tandem to implement AI and develop an AI mindset among staff.
Case study 1 – The role of the AI champion
This FE college has always had a technology-enhanced learning environment. A few months after the launch of ChatGPT, the lead practitioner for e-learning established themselves as the AI champion and sat down with the college principal to show what AI could do. The meeting was only booked for 30 minutes, and I was in there for an hour and a half, just demonstrating the functionality and key support that AI can provide in the learning environment. One of the first things the principal said was, ‘This is an employability skill I need students to have.’ While some nearby FE colleges had decided to ban AI , the principal felt differently and was cautiously optimistic about exploring how it aligned with what the college already had in place as a Microsoft college.[footnote 71] The AI champion gave staff the confidence and skills to understand how to use AI effectively. This includes understanding different curriculum areas and teaching staff ‘prompt engineering’.[footnote 72] As the champion moved around the different curriculum areas and teams, they tailored their training to individual staff, depending on the needs of skills and assessment methods for the learners. For instance, the champion would adapt their examples of what generative AI can do for learners going into healthcare, by teaching staff how it can support the learners with writing or adapting care plans for their patients. Teaching the staff the importance of knowing how to correctly prompt ChatGPT, and what knowledge staff needed to share with their learners, was a critical part of their role. As the AI champion told us: “If you put junk in, you’ll get junk out.”
Laying the groundwork for AI
Commonly, leaders made sure that they had secured staff buy-in for AI before introducing it across all the schools in a MAT or in individual schools and colleges. This meant having a strategy for addressing staff anxiety and fears about and for dispelling some of the myths associated with AI around job losses. They also invested in raising staff awareness about the risks and challenges of AI and its potential benefits.
AI champions were frequently leading on this. As teachers, rather than IT specialists, they understood the structures and mechanisms that would support staff to use AI effectively, especially what its capabilities were in relation to teaching and learning. For instance, they were well positioned to match AI tools to what teachers actually wanted to use AI for. Often, the starting point was determining what teachers needed help with and showing them how AI could be used for this purpose, rather than using AI more generically.
Furthermore, these champions created a ‘buzz’ around AI through their own enthusiasm and passion. They played a vital role in helping to demystify AI and demonstrating what it could do. They were able to create an ‘ AI mindset’ where it became the norm for teachers to use it, rather than to see AI as a shortcut. As one college head of teaching and learning standards described, they made the use of AI contagious:
What we wanted is staff in the staff room to be able to go, ‘You know I’ve just created that on [our AI tool] and it’s brilliant’… and people will start discussing it with others and… they’ll go, ‘Right. I need to have a good look at this because I’m not using this [tool].’ That is what is starting to happen now and that’s working… we’ve got to allay fears around this.
Taking risks to innovate
Nearly all the leaders we spoke to had begun to research and learn about the potential benefits and risks of AI not long after ChatGPT became available to the public in November 2022. This meant they had a particular view on AI and where it sat in the current educational context. One headteacher from an independent school told us:
We’re only just at the start of this AI era and the biggest risk is doing nothing and assuming that you can just continue as is.
The speed of AI development after the launch of ChatGPT, and inconclusive evidence about its impact, meant these leaders typically took their time to research and understand AI and the different tools available. As one MAT academies director described it, their role was to make sure they saw beyond the hype of AI to decide what was right for their needs:
When products first came out, it’s like they’re sprayed in glitter and they look shiny, sparkly and wonderful, don’t they? So, everybody’s drawn to them… So, I guess it’s our job to make sure that we don’t fly over to the flashy or shiny, sparkly products.
Another MAT chief transformation officer expressed concern over developing their AI too fast, as with everything changing so quickly, there was a danger of ‘falling into the trap of doing something too reactive’.
Typically, leaders were managing the risks by adopting a cautious approach and making sure they had the groundwork in place for AI . Most had taken small steps and built a safe foundation, so staff and pupils were ready for AI . They prioritised the safety of staff and pupils and made sure AI was used responsibly and ethically. They used internal trials and staff working groups to help them understand which tools might meet a provider’s needs best. One MAT digital lead described it as ‘getting the fundamentals and the foundation pieces right and then that makes the next level journey much easier’. Another school headteacher highlighted how a process of ‘pre-mortem’ helped with developing their initial strategy for AI :
We did this thing called a pre-mortem. So, we [sat] around a table and acted as if we had already rolled out the project and it’s failed, and then we work backwards and talk about all the reasons why it failed. There were people in SLT [senior leadership team] that said, oh, well, the children were using it to cheat, or the children put inappropriate content into it, or the children were just copying out what it gave them and put it into their homework or into their books. That suddenly allowed us to strategise [and say] OK, let’s go back to the beginning, get back in the time machine, and fix it all. And that really worked [for us].
Something these early adopters had in common was leaders who showed an appetite for risk and who were willing to innovate, once the fundamentals were in place. A school headteacher said:
We have to be able to take a calculated risk. If we want to be innovators in this space, and we want to give our children the best experience, someone’s got to do it first. And whoever does it first is going to make some mistakes. So, we’ve accepted that, but [we place] pupils’ safety right at the centre. Everything else is up for grabs around that. That’s the way we’ve approached it.
This created a culture of openness and trust that gave staff ownership of AI use and encouraged innovation. Allowing staff to ‘experiment’ and ‘explore’ AI were core principles for these leaders. Additionally, leaders said that they encouraged staff to share and talk about their successes and challenges in using AI with other members of staff, which often helped to support further buy-in – as one school headteacher explained:
The culture that we’ve developed and grown is about it being purposeful and responsible and professional. And therefore, actually, we felt if we lock this down and say we’re only allowing you to do things that we think are beneficial, we’re not going to get this full scope.
An assistant head from an independent school also told us:
The idea at the moment is that we’re giving staff a real free rein to kind of explore what works.
Leadership structures
Leaders recognised early on that AI encompasses several different areas of knowledge. The size of the organisation tended to determine what this looked like in practice for each provider. However, the leaders we spoke to agreed that AI was not an IT- or curriculum-based solution. Adopting AI would have implications across curriculum, IT, safeguarding, data management and teaching and learning. This needed to be reflected in the leadership of AI and in who was involved in decision-making and development of a wider strategy.
The mechanisms and structures that supported the adoption of AI and encouraged staff buy-in varied by provider type. In large colleges and MATs , strategic leadership of AI drew on expertise from across the organisation. (See Appendix A for the varied roles of those leading AI in different providers.) MAT leaders described a clear structure which had leadership at different levels and provided day-to-day leadership of AI use by staff and strategic thinking about AI . MATs typically had a digital leader in each academy to support staff, often the AI champion.
In larger providers and MATs , AI leadership brought together their data management teams, IT systems managers and curriculum leads. This kind of structure recognised that, unlike other forms of technology, AI required skills and knowledge across more than 1 department. This kind of structure was harder to develop in standalone primary and secondary schools. In these smaller schools, senior leaders often established staff working groups to pool knowledge.
A strategy for AI
The leaders we spoke to emphasised that senior leaders needed to have a clear vision for AI and know how they wanted staff to use it as part of their own practice. As one school headteacher suggested:
It requires all the leadership team to be on the same page with what you’re trying to achieve. Do you want this to reduce teacher workload primarily? Do you want this to enhance teaching and learning primarily, or do you want it to be both prongs of that kind of AI journey? The emphasis here is on intentionality – knowing the “why” behind the adoption is just as critical as the “how”.
However, while leaders tended to have a clear vision for AI in the short term, very few had a longer-term strategy beyond the initial testing and piloting stage. When we asked about their strategy for AI , most talked about their reasons for adopting AI and developing the guidance, policies and mechanisms that ensured safe, ethical and responsible use of AI by staff and pupils. Very few leaders had established what they hoped to achieve with AI longer term, or what success with AI looked like beyond the initial piloting stage. For example, they had rarely considered what they wanted the impact on pupils’ learning, on teaching or on staff workload to be.
This short-term way of thinking was often related to the newness of AI and the pace of change. Despite being ‘early adopters,’ most of the leaders we spoke to were still learning about the technology itself and how it could align with existing practices, as this college deputy principal explains:
Because this is so new and we are learning day by day, it’s really difficult to see where that end is and what we want.
Others, such as this college principal expressed the same sentiment more bluntly:
I think anybody who’s telling you they’ve got a strategy is lying to you because the truth of the matter is AI is moving so quickly that any plan wouldn’t survive first contact with the enemy. So, I think a strategy is overbaking it. Our approach is to be pragmatic: what works for the problems we’ve got and what might be interesting to play with for problems that might arise.
This following comment by the same college principal paints a vivid picture of how schools and colleges are focused on keeping up with the pace of change and learning about AI before deciding if and how to use it across their school, FE college or MAT :
It’s the Wild West and all we are at the minute is the sheriff. What comes in and what goes out of the town is what we’re managing to deal with at the minute. Who’s a useful citizen, who’s not a useful citizen, is what we’re making the determination of. Once that Wild West has become more of a frontier town, you can start to make informed choices.
In contrast to this short-term way of thinking, we also spoke to 5 providers who were developing pupil chatbots. These included 2 MATs with a strongly centralised curriculum and pedagogy. They saw chatbots as a way to maintain quality and consistency across the trust for improving attainment. However, they were still in the early stages of deciding how and what to evaluate as evidence of success.
Case study 2 – AI leadership in a multi-academy trust
This MAT , which includes both primary and secondary schools, became a Google academy in 2015. The Covid-19 pandemic triggered trust leaders’ decision to become fully digital. They gave pupils and staff access to Google classroom and provided all pupils with a Chromebook or an iPad. The trust also appointed a member of the senior leadership team in each academy as a digital lead and appointed a Google trainer in each academy. There was also at least 1 digital champion in each academy. Digital leads supported the implementation of the trust’s digital strategy, and the digital champions were the ‘voice pieces to champion the software and the technology’. Google trainers worked alongside the digital leads to support technology adoption and teacher training. This digital leadership meant there was a structure in place to support the adoption of AI . After the introduction of ChatGPT, leaders realised they had to move quickly to have a position on AI and began to look at their existing systems and digital strategy. The academies’ director and chief information officer were the driving force behind AI adoption. They started talking about AI at termly meetings of academy principals and senior leaders. They aimed to dispel myths, explain what AI was, highlight its advantages and disadvantages, and demonstrate how it should and should not be used. At this stage in their AI journey, trust leaders blocked staff access to AI tools to give themselves time to use and understand the technology before rolling it out across the MAT . They also created an AI strategy working group to test several AI products before deciding which to adopt across the MAT . The tool they chose ‘was nicely packaged for teachers and had in-built training and resources’. It was shared with principals and senior leaders before being launched across the trust for all staff to access. Staff were encouraged to explore and play around with the tool and learn how to use it by themselves. It was promoted by a ‘tip of the week’ for the tool and weekly staff bulletins. It was also referenced on any occasion where staff came together. Trust leaders also created a digital toolkit with information about other tools staff could use which are ethical, and GDPR - and copyright-compliant. The trust also tracked the use of individual AI tools and surveyed students and teachers about their use of AI twice a year. This helped with assessing where the trust was on their AI journey and the impact it was having on education and workload. Leaders were conscious that students were probably already using AI tools outside of school, and that their knowledge was potentially further ahead than that of the teachers. To help mitigate this, leaders decided that all staff in the academies should be taught how to use AI and also learn about compliance and good governance for the tools. Teachers were also trained on how to understand and detect students’ use of AI .
Governance of AI
The DfE has published guidance about safe and responsible use of AI .[footnote 73] However, schools and FE colleges in England can set their own rules for AI use, as long as they follow legal requirements around data protection, child safety, and intellectual property. All the leaders we interviewed had prioritised safe, ethical and responsible use of AI . Most had comprehensive policies and procedures in place to address the risks to staff, pupils and learners.
Leaders had researched the benefits and risks of AI before proceeding with any development of AI . They were aware of the risks to pupils and staff around bias, data protection, intellectual property and safeguarding. Some leaders told us they had set up their own AI strategy groups to test new AI tools before distributing them more widely to staff. They told us these groups helped to determine whether a specific AI tool was the best available product to use, the risks of the tool and how to overcome these risks. A few leaders also mentioned that they felt these groups drove product use – particularly in approving what platforms teachers and learners can use – as well as maximising the gains of any products they were using.
However, there was no clear consensus about what to include in a policy, or whether to have a separate AI policy. The policies these providers were using tended to perform several functions. They specified guidance and responsibilities for AI use by staff and students, described safe ethical use of AI and provided information for parents. Some leaders had decided to incorporate AI use into existing policies. These tended to be the providers’ acceptable use policy, staff codes of conduct, teaching and learning strategies, and the safeguarding policy.
AI policies
Several providers were considering whether a separate AI policy might be needed in the future as their AI journey matured. One head of school curriculum said they would eventually need a separate policy to make sure that everything was covered:
So, AI is embedded, but I think that as we progress with our journey, I think we probably do need our own school AI policy. I think that’s probably what the majority of organisations moving forward will have to have because we need to be aware of, you know, hacking and in terms of GDPR . All of those things we need to encompass and consider.
However, most leaders said they found developing policies for AI quite a challenging area, largely because of the pace of change in the sector. This meant leaders were being constantly vigilant and forward-looking. Regularly reviewing their AI policies was, therefore, an important principle of governance. Several leaders said they were reviewing and updating AI -related policies at least termly, if not more often. For example, one primary school leader said they regularly reviewed their AI policy to check that it was still strong enough and that it addressed key issues adequately.
With policies in place, ultimately, it was the responsibility of leaders and staff to make sure they and their students used AI safely, ethically and responsibly and understood the risks. As one independent school deputy head explained:
Your responsibility is: know how it works, including biases and the ethical issues around how training works and how it produces responses. Be honest when you’re using it. And be responsible for whatever you create.
Keeping staff and pupils safe and using AI tools ethically and effectively required openness, robust procedures and policies and effective training. It also needed providers to create a culture that made it clear that, when it comes to safeguarding, AI was everyone’s business. As one leader said, ‘The technology itself is not inherently unsafe, just the way it is used.’
Transparency
Among the challenges leaders described was the pace of change. They had to balance the speed at which new AI tools were launched and staff and students wanting to use them with safety and security.
Many new tools are emerging, and the technology is developing at great pace. We want to ensure we are moving at the right speed to benefit our staff and students while also ensuring their safety, the security of our systems and data, and being aware of the ethics of using these emerging technologies.
However, in a few cases, the governance around AI proved to be an inhibitor that affected the speed of uptake. For instance, one headteacher told us they were initially hesitant to make AI a formal part of their teaching and learning policy due to the fast-changing nature of the technology. Instead, their priority was to keep a close eye on safeguarding, security and online safety. Other leaders told us that they encouraged a culture of openness to mitigate the risks. If staff and pupils were talking openly about the tools they were using and how they were using them, leaders could make informed decisions about the risks and how to mitigate them.
Importantly, these leaders did not want to stop staff from innovating and experimenting, but they needed to be sure that the AI tools being used were safe and appropriate. Two providers had AI tools approval committees, and a list of approved tools staff could use. These committees included IT (network managers) and teaching and learning leaders who considered both data compliance and pedagogical principles to confirm the tools had educational value. In one college, the teaching and learning, IT and GDPR teams had a monthly ethics meeting to discuss requests to use new AI tools and decide on whether to approve them for staff to use. Others approved only tools they knew were safe.
Two of the leaders we spoke to suggested that the government needed to provide more guidance and support around safe AI tools and also shift the focus to learning. One independent school leader said:
What we want is safe, useful technology that doesn’t undermine the learning process. And I think there’s a huge amount of focus on the safe and useful bit and not enough focus on the not undermining learning.
Research has shown that dependence on AI tools might hinder the development of pupils’ critical thinking and problem-solving skills if they are not used effectively.[footnote 74]
Case study 2 (continued) – Updating policies for AI use When staff were given access to AI tools within the trust, leaders began to work on their strategy and consider governance around how best to use them. In the same way they had created a digital strategy, they also developed an AI strategy. This enabled the trust to be clearer in their communication with their academies. Following this, their academies were also told to update their honesty policies around producing exam work. This generated policies to help the academies know what they should and should not do around students’ use of AI . Guidance was also created on how to use AI within the MAT . There were 3 versions created, communicating the different types of tools, and spelling out what to do and what not to do.
Using AI inside and outside the classroom
Most of the leaders we interviewed were not prescriptive about the AI tools teachers could use and how they should use them. Some had piloted different tools with staff before deciding which to buy licences for. Others had a system to approve the AI tools staff wanted to use.
Adoption of AI was split equally between those who gave teacher workload as the main reason for its adoption and leaders who prioritised pupils. We have used the idea of teacher-facing and learner-facing AI tools to describe how providers were using AI and the types of tools they used.[footnote 75] Teacher-facing AI tools support teaching and are used by staff for lesson planning, creating resources and suggesting activities. They can also support with administration and give personalised feedback. Learner-facing tools are used by pupils themselves and include intelligent tutoring systems and AI chatbots.
We found that leaders were mainly using teacher-facing tools to reduce staff workload. This was most likely to be the case where schools had more recently decided to adopt AI .
Although leaders talked about reducing teacher workload, they often qualified this by adding that it was not about reducing teacher workload overall but increasing the time teachers could spend on the things that had a more direct impact on learning. For instance, AI allowed staff to focus on the ‘human bits’ of education that technology cannot easily replicate. A secondary school principal explained:
We just want to redistribute where that time is. So those admin staff at the front, I’d rather them not spend 2 hours spell-checking a policy or changing dates. I’d rather them be proactively chasing poor attenders, making phone calls, [doing] home visits, doing the human bits.
All the leaders we interviewed said that they used teacher-facing tools to reduce workload for both teaching and administrative staff. Commonly, teaching staff used teacher-facing tools for planning lessons, adapting resources and creating quizzes, and revision help. For example, the assistant headteacher of one school said the top categories their teachers used in their AI tool were ‘help me write’, ‘slideshow’, ‘model a text’, ‘adapt a text’, ‘lesson plan’ and ‘resource generation’.
Many described AI being used by administrative staff to reduce time spent on tasks such as writing letters to parents, summarising long documents or updating policies. One leader described using AI as ‘another person to bounce off’. They used AI to review or proofread letters, reports and other documents rather than asking another member of staff to do this.
Leaders were also clear that, although AI can help reduce workload and save them time, it still needs human oversight to quality assure its outputs. Some also told us that they are mindful that AI was not always the best option and that it ‘doesn’t quite replace the expert’. Teachers needed to use their professional judgement and pedagogical knowledge to decide where AI could enhance teaching and learning and where it might not.
Providers who had longer experience of using AI were more likely to be using it with pupils. Most often, we found that teachers modelled its use rather than allowing pupils to use it themselves. Leaders told us that, where teachers were using AI in the classroom to generate outputs, they could use this as an opportunity to develop pupils’ digital literacy. It was also a way for pupils to see first-hand some of the risks of using AI when users didn’t understand how it works, and to critically evaluate its outputs. In this example, a primary school headteacher described pupils’ response to AI generated images of doctors.
It produced 5 images of a doctor that were all white and all male. We just asked the children, ‘Tell us what you see.’ And, actually, some of the children didn’t have a clue. They didn’t clock on to it because of their own bias in their head – a doctor is a white male – but a couple of children said, ‘Well, there’s no women in here and there’s no one that looks like me.’
This demonstration of AI use in the classroom provided the catalyst for critical discussion about bias and misinformation.
FE colleges were more likely to permit learners to use AI themselves because they were older. Primary schools had not yet reached the stage where they allowed pupils to use AI independently. The only exceptions to this were schools that had developed their own chatbot and determined it was safe for pupils under 13 to use.
Personalising and adapting teaching
Most of the leaders mentioned AI ’s ability to adapt and personalise resources as one of its strongest benefits. Several leaders talked about using AI tools to adapt lesson resources to make them more accessible for different groups of students, particularly those who have a special educational need and/or speak English as an additional language. As this school headteacher described:
It’s how are we enabling them to all access the curriculum and get that real quality teaching experience. As well as keeping the teachers still smiling and able to have a bit of a weekend.
During the interviews, we heard several clear examples of how learning was being personalised for specific groups of students. For instance, a lead practitioner from one college described how AI was allowing Syrian students who spoke English as a second language to access the curriculum. Teachers used AI to translate and adapt lesson resources such as PowerPoint slides and assessments. They also generated a glossary of terms in Arabic to give students a ‘leg up’. The lead practitioner for eLearning highlighted how:
It just levels the playing field and allows them to progress through the college rather than because that lecturer doesn’t have that skill, which maybe the ESOL [English for speakers of other languages] lecturers do, and ChatGPT gives them that.
Leaders from another college mentioned that staff were using AI to help young carers catch up on lessons they had missed because of their caring responsibilities. In this example, generative AI had created a 10-minute podcast from teaching slides and materials used in a full lesson. This included AI -generated voices talking about the lesson content. The idea was that pupils could fit the podcast around other responsibilities or listen while travelling, such as when they were going to college on the bus.
In a further example, leaders from a secondary school told us they were training teaching assistants to use AI tools to help the pupils they supported. For this purpose, every teaching assistant had a laptop they could use to adapt resources and learning to an individual pupil’s level of understanding and/or need.
When the teaching assistants put in the pupils’ learning needs and level of understanding of a topic, the AI tool they were using was able to adapt worksheets, learning objectives and success criteria to make it easier for pupils to access learning at their level.
However, as the literature review indicates, there is a lack of research that identifies the most effective ways AI can be used to adapt and personalise learning.[footnote 76] We have found from our curriculum research reviews[footnote 77] that adaptations can be ultimately unhelpful where they provide ‘workarounds’ to immediate barriers, but fail to address these barriers so pupils can access the curriculum in full and in the long term. For instance, if all resources for a pupil are adapted to their current reading age, this could widen gaps between them and their peers. Likewise, evaluations need to determine if bitesize lessons in alternative formats ensure that intended concepts are still learned in full and avoid producing misconceptions. If we do not scrutinise adaptations in this way, then AI use for personalised learning could simply worsen issues around lowering expectations for some students. This raises the need for providers to evaluate the impact of AI on pupil outcomes and monitor how it is being used to support learning.
Pupil learning about AI
All the leaders we spoke to said that teaching students how to use AI safely was one of their top priorities. This was often because they were concerned that they could not control pupils’ and learners’ use of AI at home. One leader told us that pupils were shocked to learn about ‘deepfakes’ in particular.[footnote 78] Pupils had not realised that what they saw on social media could involve elements that were AI generated, even though they may look real.
Therefore, curriculum development was an important part of the AI package offered by these providers. Teaching pupils and learners how AI works and how it uses their data, and raising awareness of bias and misinformation, were seen as important parts of pupils’ and learners’ digital literacy and safeguarding. Some providers addressed safe, ethical use of AI through their interactions with pupils. Others had developed specific teaching units as part of their computing or personal, social and health education (PSHE) curriculum. These explained how different types of AI work and how they use data to generate the different types of outputs pupils had seen and used. Teaching about AI often covered topics such as deepfakes, safe use, hallucinations and the need to critically evaluate what AI generates.
Developing chatbots
A few leaders described how that were developing and using their own bespoke chatbots for individual pupils to use to support learning. These generated AI responses by drawing on the background curricula, pedagogical approaches and intellectual property that each school, college or MAT had. The chatbots were also being tailored to particular attainment challenges.
One of these leaders described AI chatbots as ‘second teachers’ in the classroom. The chatbot was providing real-time assistance and feedback on assignments as well as responding to queries. Pupils were told that the chatbot was not replacing teachers, but ‘replacing where the teacher isn’t’. Pupils could use the chatbot if they were stuck or wanted to try out different ideas and get feedback. The chatbot was designed so that it would not give pupils a direct answer, but it could help them understand why something was wrong, or what question they had to ask to get to the right answer.
In another MAT , leaders were beginning to think about how technology and AI could support their adopted pedagogical principles. They were starting to match the technology to those strategies, as this MAT Chief Transformation Officer explained.
So, if you’re going to do modelling, this is how you could do modelling in a technology-enabled way. If you’re going to do a “think, pair, share”, this is what you could do. We’re now starting to map AI -type tools on to that so that it’s deepening the opportunities.
Case study 3 – AI chatbots in a primary school This 2-form-entry primary school with a higher-than-average proportion of disadvantaged children started its generative AI journey in the summer term of 2024. The headteacher had a prior interest in technology and a few professional connections. Through one of these connections, the school was invited to trial and test an AI platform and chatbot that was designed and built in collaboration with teachers, and considered safe to use with children. Before participating in the trial, and with safe use and safeguarding at the forefront of any decisions made around AI , the headteacher ensured all staff received training on AI through an inset day focused on the topic. Similarly, before the chatbot was introduced to children, the leadership team established a code of conduct and code of ethics around AI use. Pupils were also taught about the risks and benefits of using AI , along with what it was, and how it worked as part of their curriculum. This was done by teachers demonstrating on screen in front of the whole class how ChatGPT could help with writing or maths, and children taking turns to ask the AI questions. Once leaders were confident pupils understood how AI worked, Year 6 pupils were introduced to the chatbot and given the opportunity to ‘talk’ to it and find ways of using it that made sense to them. They did this through structured time on their laptops, where the teacher would first model use before pupils would try to apply this independently. Pupils were encouraged to first ask the chatbot questions they would normally want to ask a teacher, to see what answers it gave. If the response did not feel right, they were to let the teacher know. Staff noticed that, for the chatbot to be effective, pupils needed to use specific and well-thought-out questions and prompts. Limitations in pupils’ spoken and written language made a big difference to what they got out of using it. As the headteacher explained: [It] was a learning process for us as teachers to understand that actually this technology is a little bit different to what we’re used to… In Google you can just type out a word and it will check out a lot of stuff and you can pick [what you want] from that. But with an AI bot, you’ve got to be really specific and purposeful about what you’re asking it to do. This meant that teachers could link AI to the development of pupils’ oracy and literacy skills. A few months after the pupils had begun using the chatbot, leaders believed that they had started to see a positive impact on their metacognitive skills.[footnote 79] The school told us the next step is to trial the chatbot in other year groups, once pupils are taught about the risks and benefits and feel ready to do so.
Assessment and feedback
Several providers told us they used AI for marking, assessment and feedback. In one school, teachers used AI to give feedback on essays, using specific criteria decided by the teacher or set by exam boards. This school also used an AI tool that produces PowerPoint outputs to create ‘low stakes’ testing and quizzes from slides, websites, YouTube videos or PDFs. The AI marked as pupils answered the questions.
However, leaders tended to be more cautious about using AI for assessment compared with other ways of using it. First, they had concerns about accuracy. Second, some felt pupils wanted to know their work had been marked by a human. And third, there was a worry that using AI for this purpose may result in teachers becoming less well aware of the students and their work – as this MAT academies director describes:
We’ve played around with putting English assessment objectives in [to the AI tool] and then an essay in, and [asking] ‘Can you mark it?’, and ‘Tell me what you think’. And it’s not bad, but I think that’s a bit where teachers are most reticent because [they] want to know that they’ve looked at the work.
Generally, leaders were clear that using AI should never result in taking the assessment role away from teachers. Most emphasised that AI should only be used as a supportive tool, with the teacher still the expert at either end of the process. Several also mentioned that it was important that teachers were transparent about when they had used AI for assessment purposes. This was so that parents and pupils were fully informed and could voice any opinions on its use.
Case study 4 – Using AI for feedback Learners at this FE college have been told they can use AI to mark their assignments after submitting them, to see what feedback it gives. However, leaders have told learners they need to be mindful that AI may not always produce an accurate response. The college is also aware that their learners may sometimes use AI to help write their assignments. Leaders felt greater transparency was needed around how learners had used AI . They suggested some areas may need to change feedback sheets so that the focus is on getting pupils to explain how they had used AI rather than confirming whether or not they had used it. There is also a tutorial program that runs across the college. It trains learners on appropriate use of AI and includes different ways they can use word prompts. This is considered an acceptable use of AI , as it helps to support the learning process. Leaders also described how learners can use AI to proofread or give feedback on how a piece of writing flowed.
What next for these providers
Several leaders we spoke to identified 2 aspects of their AI use that they had either not yet thought about or were just beginning to discuss. These were the pedagogical uses of AI , and how they evaluated the impact of AI .
As our study has already indicated, the first stage of AI adoption for these leaders focused on exploring the technology, before they decided how it might support specific learning outcomes and goals. They made sure teachers understood what AI was capable of and where it could potentially enhance learning and address specific challenges. They also prioritised safe, ethical and responsible use at this early exploratory stage.
Systematic thinking about integrating AI into curriculum and pedagogy was still at an early stage and was often a second stage of their journey. We found most leaders had not, as one MAT leader described, ‘thought systematically enough about how to support pedagogy through technology in this new way yet’. Leaders in 2 MATs described how their trusts were beginning to think about where AI could integrate with their own pedagogy. However, one barrier they highlighted was that available AI tools did not have a contextual understanding of their school or college and the needs of students. As this MAT chief transformation officer told us:
The OpenAI-type chatbots – ChatGPT, Gemini – do not know your curriculum. They do not know where your pupils are. They do not know what the misconceptions are typically for those topics.
This leader also explained how for MATs with a centralised curriculum and pedagogical principles, the benefit of open AI tools was still limited because:
It doesn’t have the background context, and particularly the sort of curriculum, content and pedagogical approaches of our trust, which is very well defined.
Evaluating the impact of AI
We also asked leaders how they evaluated the impact of AI and understood what successful use of AI looked like. Most relied on feedback from staff and students or tracked and monitored staff usage of AI tools, rather than collecting data that could be used to measure the impact of AI specifically on pupils. Leaders told us they used low-stakes quizzes and tests to assess the impact of AI on pupils’ ability to retain and recall knowledge. However, it is not always possible to evaluate the extent to which any impact was due to AI , rather than to any other factors such as pupils’ prior knowledge, or the teaching approach.
Leaders also used direct feedback from pupils to assess the impact of using AI . One school leader had begun to include questions about AI use in their termly pupil survey. This asked questions such as: Do you see the purpose of AI ? How are subjects using AI ? And do they see any impact from using AI ? Leaders also used staff surveys to understand the impact of AI on workload.
There is a lack of evidence about the impact of AI on educational outcomes or a clear understanding of what type of outcome to consider as evidence of successful AI adoption. Not knowing what to measure and/or what evidence to collect makes it hard to identify any direct impact of AI on outcomes. One school leader said that they had steered away from hard measurements of AI and its impact. They felt that this kind of accountability measure could potentially restrict staff from using and experimenting with AI . For the leaders we spoke to, success was linked to a coherent approach to introducing, using and embedding AI across the school, college or MAT . The impact of AI at the early stages of their AI journey was seen through the eyes of those using it. A positive impact was when they felt it was a useful tool and did what they wanted it to.
A few leaders who were using pupil-facing AI tools had conducted more formal evaluations of their impact on pupils. However, these collected qualitative data to understand the impact of AI on pupils’ metacognition, critical thinking and independent learning rather than measuring what pupils know, understand and can apply. As this primary school headteacher explained:
You can’t really measure how much it’s moved learning forward, but what you can do is measure some qualitative aspects of what it’s doing for the children in terms of their teaching and learning.
The lack of evaluation focusing on pupil outcomes could also be because many of these leaders were piloting and experimenting with AI as a tool to reduce teacher workload. For these early adopters, there is still some way to go if AI is to achieve its full potential and go beyond the hype and hyperbole. As one MAT chief executive officer noted:
I don’t want people to go away with the idea that we’ve got AI nailed and everybody’s using it as a tool to change, because in fact what I’ve learned over 30 years of using tech in education is there’s bandwagons… I don’t think AI is like that, but I think there’s a lot of hype around it and a lot of misunderstanding or myth and rumour about it.
Conclusion
Educators and policymakers have talked about the potential of all forms of digital EdTech to revolutionise education for at least 25 years, and UK governments and schools have invested heavily in software and internet connectivity.[footnote 80] This study has highlighted the journeys that 21 providers have been on as early adopters of the most recent form of EdTech innovation, namely AI . It provides information on the systems they have established and the barriers they have overcome to use AI in what they believe are safe and secure ways, while also being innovative and flexible in meeting the needs of staff and pupils alike.
Our study also indicates that these journeys are far from complete. The leaders we spoke to are aware that developing an overarching strategy for AI and providing effective means for evaluating the impact of AI are still works in progress. The findings show how leaders have built and developed their use of AI . However, they also highlight gaps in knowledge that may act as barriers to an effective, safe or responsible use of AI .
More research and evaluation of AI in education is required, specifically on what works effectively to achieve gains in knowledge and influence pupil outcomes. Many of the concerns around AI , particularly views about its impact on education, and potential threat to teachers’ professionalism and pupils’ knowledge, are not new. They have been raised in relation to EdTech more widely. Even 15 years ago, some believed EdTech had the potential to transform learning, and others felt there was a need for greater scrutiny of its ability to improve pupil outcomes.[footnote 81] However, some of the specific aspects of AI , such as its ability to predict and hallucinate, and the safeguarding issues it raises, create an urgent need to assess whether intended benefits outweigh any potential risks.
The findings from this research have also been helpful to inform Ofsted’s own position on AI during inspection. The use of AI is not a stand-alone part of our inspection and regulation practice, and inspectors do not directly evaluate the use of AI , nor any specific AI tools. However, inspectors can consider how AI is used across the provider and its impact on the outcomes and experiences of pupils and learners. They should expect that pupils or staff members may be using AI in connection with the education or care they receive or provide (for example to help pupils complete homework). There is no specific expectation that schools and FE colleges will use AI . However, the government is keen that they adopt and embrace AI as set out in its AI Opportunities Plan.
The findings from this research will also inform the inspector training we aim to develop this summer. It will help us make sure that inspectors can record the impact of AI , how this is monitored, and the checks and balances leaders have put in place to ensure AI is used ethically and safely.
We are aware that the experiences shared by these early adopter schools and colleges do not reflect how the wider sector is using AI . More research is needed to better understand how schools and FE colleges who are earlier on in their journey of AI adoption are using it, and the implications for our inspection and regulation practice. We also want to reassure ourselves that, when schools and FE colleges do use AI , it is in the best interests of children and learners. We want to enable AI innovation in the sector, and this small-scale study has been an important first step in that direction.
Appendix A: overview of participants
Provider name Provider type Age range Start of AI journey Participants (job title) College 1 FE college 16 to 19+ Nov 2023 Deputy Principal, Head of Digital Learning College 2 FE college 16 to 19 Feb 2023 Head of Teaching, Learning and Digital College 3 FE college 16 to 19 Jan 2023 Vice Principal, Deputy Chief Executive, Lead Practitioner: eLearning College 4 FE college 14 to 19 Nov 2022 Principal, Director of Digital Transformation Independent school 1 Independent school 13 to 18 Sep 2023 Head of Digital Teaching and Learning Independent school 2 Independent school 4 to 18 Nov 2022 Assistant Head – Staff Development, Head of IT Independent school 3 Independent prep school 4 to 11 Nov 2022 Deputy Head – Innovation and Partnerships MAT 1 Multi-academy trust N/A Feb 2023 Digital Lead, CEO MAT 2 Multi-academy trust N/A Mar 2024 Chief Transformation Officer MAT 3 Multi-academy trust N/A 2015 Chief Information Officer, Academies Director MAT 4 Multi-academy trust N/A Jun 2023 Project Manager, EdTech and AI Lead, Director: Curriculum and Assessment, Digital Lead, Director of Teaching and Learning, ICT Infrastructure Architect Pilot 1 Academy converter 11 to 18 Sep 2023 Headteacher, Assistant Headteacher Pilot 2 FE and HE college group 16+ Sep 2023 Deputy Head of Digital Innovation, Change and Transformation Manager School 1 University technical college 14 to 19 Academic year 2022/23 Head of Social Sciences, Principal, Assistant Principal/Designated Safeguarding Lead School 2 Pupil referral unit 11 to 18 Summer 2023 Head of school: remote and outreach, Head of School Curriculum School 3 Academy sponsor-led – multi-academy trust 11 to 18 Summer 2023 Principal School 4 Voluntary-aided school 4 to 11 Summer 2023 Digital Leader, Headteacher, Upper Key Stage 2 Phase Leader School 5 Community school 3 to 11 Nov 2023 Assistant headteacher, Year 5 teacher, Headteacher School 6 Academy sponsor-led – multi-academy trust 2 to 11 Summer 2023 Headteacher and Designated Safeguarding Lead, Year 3 teacher School 7 Community school 3 to 11 Summer 2024 Headteacher School 8 Academy converter – multi-academy trust 2 to 11 2023 MAT CEO and Executive Headteacher, English Hub and Professional Development Lead
Appendix B: detailed research methods
This was a small scale in-depth qualitative research project commissioned by the DfE . The aim was to understand how and why early adopter schools and FE colleges had embedded AI . There was no intention to assess the impact of AI or evaluate the quality of AI tools they were using. The aim was to understand the journeys these schools and FE colleges have been on and the practice they have developed, and to share this with other schools and FE colleges who may have an interest in adopting AI .
Our high-level research question was:
How are schools and FE colleges that are early adopters of AI using it to support teaching and learning as well as to manage administrative systems and processes?
Data collection
We collected evidence from:
a rapid evidence review of peer-reviewed academic literature – we prioritised recent systematic reviews and meta-analyses that included research on generative AI
a review of DfE publications relating to AI , including policy statements, surveys, research and guidelines
publications relating to , including policy statements, surveys, research and guidelines discussions with international inspectorates about their approaches to inspecting AI ; where possible, we also reviewed their publications relating to AI
; where possible, we also reviewed their publications relating to 21 online interviews, including 2 pilot interviews, with leaders or those with specific responsibility for developing and implementing AI from a purposive sample of schools, FE colleges and trusts who have already adopted AI
The data we collected from the review of publications and discussions with international inspectorates informed the questions we asked during the interviews.
The interviews were carried out by 2 of His Majesty’s Inspectors and 1 Ofsted inspector between January and February 2025. They were semi-structured and conducted online. We asked providers for a maximum of 3 people to join the interview. We carried out 2 pilot interviews to check the validity of our interview questions. The data collected from the pilots is included in our final analysis, as there was little change between the questions asked on the pilots and in the remaining interviews. Each interview was 90 minutes long and broadly covered 3 main topics:
strategic leadership and oversight
governance and safe and ethical use of AI
how AI is used by teachers and pupils/learners
We carried out the research in line with Ofsted’s research ethics policy and it was approved by our research ethics committee.[footnote 82] All participants gave us their full consent to be involved in the research. We used AI to produce a structure and early first draft of the literature review based on the project research questions and the literature identified by researchers working on the project. The AI draft was rewritten and edited by humans. External experts reviewed the final report and provided feedback on the validity of our findings and the literature review.
Sample selection
The aim of the online interviews was to illustrate what some leaders had put in place to support AI adoption and use. This was so we could identify common strategies that appeared to be effective, and which could be used in similar contexts. We therefore selected a purposive sample of settings to invite to interview.
We have defined early adopters as MATs , schools or FE colleges where leaders have been supporting and embedding the use of generative AI by staff for at least 12 months. In these settings, AI is used by staff to enhance teaching and learning and streamline administrative processes and procedures. For most of these schools and colleges, their AI journey began a few months after the launch of ChatGPT when leaders saw early on the potential for generative AI to reduce teacher workload and/or support pupil learning.
We carried out a range of validation checks to make sure these settings were early adopters of AI . We sourced participants from DfE recommendations, our own regional intelligence, research team contacts, recommendations from leaders we interviewed, and the AI in education website. We further validated participants by looking at what they had published about AI on their website and asking contextual questions in the email we sent inviting leaders to take part in the project. The final selection was also determined by whether leaders were available and/or willing to be part of the research.
As our focus was on schools and FE colleges that had already adopted AI , we were not concerned with identifying a nationally representative sample. However, we did want a varied mix of provider types within the purposive sample selected. This was to help identify any similarities or differences among provider types in the way they were adopting generative AI and to highlight any innovative practice to share with the sector. We included independent schools in the sample because we felt that their access to more resources might mean they are further ahead in their AI journey than government-funded schools. The final sample included 5 primary schools, 3 secondary schools, 1 pupil referral unit, 5 MATs /college groups, 4 FE colleges and 3 independent schools.
Data analysis
We received participants’ consent to use Microsoft Teams to record the video and audio from the interview. Microsoft Teams was also used to transcribe the audio. We analysed the data using a thematic approach and coded data using MaxQDA. The project lead developed an initial coding framework using the themes identified in the literature as well as additional themes developed during phase 1 of the research. New codes were then added based on the interview data. The data was coded by 2 researchers, and a sample of the coded entries was checked by the project lead using the coding framework. Any proposed changes to the framework were discussed and agreed by researchers before being added to it.
Limitations
Our study has limitations in that we spoke with a purposive sample of mostly senior leaders about AI use. This gives a top-down view of the intended implementation of AI and how well they think their school or college has managed this. The decision to interview leaders and not include other staff members and pupils was determined by the nature of the research as well as time and available resource. This was a small-scale, fast-paced exploratory research project. Gathering a range of views from pupils, learners, teachers and other staff members would provide additional perspectives on what is and is not working. It would also help us understand how to implement AI more effectively and assess its impact.
| 2025-06-27T00:00:00 |
https://www.gov.uk/government/publications/ai-in-schools-and-further-education-findings-from-early-adopters/the-biggest-risk-is-doing-nothing-insights-from-early-adopters-of-artificial-intelligence-in-schools-and-further-education-colleges
|
[
{
"date": "2025/06/27",
"position": 11,
"query": "AI education"
}
] |
|
AI Solutions
|
AI Solutions
|
https://www.cdw.com
|
[] |
CDW accelerates time to value for AI projects with full-stack solutions that allow you to move fast, drive ROI and gain a competitive edge.
|
CDW can help with data governance, data quality and data security. We make AI sustainable, streamline the deployment of new use cases and enable your data to drive meaningful results.
Is Your Data Aligned with Your Project Goal?
CDW identifies and deploys the right SaaS applications to power your AI strategy, help you take advantage of the functionality within your existing AI platform or develop custom applications tailored to your organization.
Which App Will Facilitate It?
What Infrastructure Are You Going to Use?
CDW helps you deploy the right infrastructure for running AI workloads, whether in public or private clouds, on-premises or in hybrid environments.
| 2025-06-27T00:00:00 |
https://www.cdw.com/content/cdw/en/solutions/artificial-intelligence-ai.html
|
[
{
"date": "2025/06/27",
"position": 37,
"query": "AI employers"
},
{
"date": "2025/06/27",
"position": 83,
"query": "workplace AI adoption"
}
] |
|
10+ Top AI Development Companies [2025]
|
10+ Top AI Development Companies [2025]
|
https://brainhub.eu
|
[] |
Save hours with the research-based, non-sponsored ranking of top AI development companies. It gathers 11 top vendors that provide best AI development ...
|
Top AI development companies - shortlist
These top AI development companies are sorted by their ability to develop software with agility and achieve immediate impact on projects, as this is the primary factor to consider when selecting a business.
A top AI software development company stands out for its innovation in AI technology and a proven record of delivering impactful solutions, backed by a team of experts in AI and related fields. This should be combined with ability to iterate swiftly and thorough testing processes.
Top 10 AI development companies - details
Analyze the details about each AI development company from this ranking – services, skills, talents on board, and the juice from reviews.
Brainhub delivers custom software solutions for scale-ups, enterprises, and companies looking to gain a technological advantage in the market. With a focus on software delivery excellence, the company combines technical expertise with efficient processes to meet diverse client needs.
The team emphasizes fast iterations and thorough testing to ensure high-quality outcomes. Their approach is designed to maintain control over scope, budget, timelines, and risks, enabling predictable and effective project delivery.
Brainhub has extensive experience in web application development, creating software that aligns with modern user expectations while helping businesses achieve measurable ROI. Their ability to deliver end-to-end solutions supports clients in scaling operations and driving growth.
The company works with well-known organizations, including "Big 4" firms, National Geographic, and Beam. Their core delivery principles - continuous delivery, business-focused decisions, and structured project governance - help clients achieve results that align with business objectives.
With a Clutch rating of 4.9/5, Brainhub is recognized for its reliable delivery processes and technical capabilities. They partner with clients to develop software that supports long-term business success.
STANDS OUT FOR: tech expertise, effective communication and project management, solution-oriented approach and flexibility
REWARDS: FT 1000 Europe’s Fastest-Growing Companies, Rising Star Awards from Deloitte: 50 Technology Fast Central Europe, Top .NET Developers 2023, Top 100 Sustained Growth Companies, Top 1000 Global Companies by Clutch, Top Software Developers 2023 by Clutch, Top Firm Custom Software Development 50pros
SERVICES: custom software development services, AI development services, web application development, mobile development, desktop app development, cloud consulting, staff augmentation, digital transformation, legacy modernization, UX/UI design
TALENTS: software engineers, QA engineers, solution architects, business analysts, UX/UI designers, project managers
TECHNOLOGIES: JavaScript, TypeScript, .NET, Node.js, React.js, React Native, NestJS, Electron.js, Python
SKILLS: GraphQL, Kubernetes, AWS, Azure, GCP, DevOps, workshops, hybrid mobile app development, iOS app development, Android app development, PWAs, CI/CD, automated tests, BDD, TDD, information architecture, visual design, backend engineering, API development, serverless architecture, testing, UX design, user interface design, UX audit, UX workshops, architecture development, MVP, prototyping, product scaling, AI Development, Generative AI
INTERNATIONAL CLIENTS: National Geographic, PwC, Cubotoo, Go Kong, Rulrr, National Geographic, Paradox Interactive, Beam, Jackbox Games
CLUTCH REVIEWS: 4.9 stars on Clutch from 47 reviews
APPRECIATED FOR: tech expertise, top code quality, project management and delivery, transparency, business-oriented approach, timeline and budget control, flexibility, communication skills, innovative approach
CULTURE & VALUES: Brainhub values initiative and accountability, encouraging team members to actively participate in the entire business process. The company emphasizes effective communication as a cornerstone for addressing challenges and achieving results. They prioritize informed decision-making, collaboration, and continuous improvement, fostering a culture of knowledge sharing and growth.
METHODOLOGY: Agile and Prince2Agile methodologies
COMPANY SIZE: 100+
LOCATION: Poland
INDUSTRY EXPERTISE: FinTech, MedTech, e-commerce, digital banking, accounting, tax consulting
<span class="colorbox1" fs-test-element="box1"><p>Contact Brainhub and consult your project</p></span>
<h3 id="stx">STX Next</h3>
STX Next is a global IT consulting firm delivering AI-powered software solutions. With over 19 years of experience, the company offers a comprehensive range of services, including AI and data solutions, cloud consulting, product design, and technology consulting.
The team at STX Next emphasizes transforming vast datasets into actionable insights through AI, enabling businesses to analyze large datasets, detect patterns, and make informed decisions. Their cloud strategies aim to optimize operations by reducing IT costs and increasing efficiency, keeping clients ahead in the competitive landscape.
STX Next has collaborated with renowned organizations such as Canon, Decathlon, Unity, and Mastercard, delivering scalable and reliable software solutions. Their core delivery principles include continuous delivery, business-focused decision-making, and structured project governance, ensuring that projects align with clients' strategic objectives.
With a Clutch rating of 4.7/5 from 93 reviews, STX Next is recognized for its effective project management, timely delivery, and strong communication skills. Clients appreciate their commitment to quality and ability to handle complex challenges efficiently.
STANDS OUT FOR: AI expertise, cloud solutions, product design, technology consulting
SERVICES: AI and data solutions, cloud consulting, product design, technology consulting
TALENTS: AI specialists, cloud engineers, product designers, technology consultants
TECHNOLOGIES: Python, Node.js, .NET, React, Angular, Vue.js
SKILLS: Machine learning, data engineering, cloud strategy, product design, technology consulting
INTERNATIONAL CLIENTS: Canon, Decathlon, Unity, Mastercard
CLUTCH REVIEWS: 4.7 stars on Clutch from 93 reviews
APPRECIATED FOR: effective project management, timely delivery, strong communication skills, commitment to quality
CULTURE & VALUES: STX Next fosters a culture of continuous improvement and knowledge sharing. The company values effective communication and informed decision-making, encouraging team members to participate in the entire business process actively. This collaborative environment prioritizes client needs, leading to successful project outcomes.
METHODOLOGY: Agile methodologies
COMPANY SIZE: 500+ professionals
LOCATION: Poland, Mexico
INDUSTRY EXPERTISE: AdTech, EdTech, FinTech, eCommerce, Transport & Logistics
Upcoming webinar: How to drive AI adoption in your engineering team?
Adopting AI doesn’t just happen. It takes bold leadership, a shift in mindset, and a clear game plan.
Join us for our next session and find out how to bring AI into your team smoothly, without the drama.
P.S. The webinar will be in English.
<h3 id="10clouds">10Clouds</h3>
Founded in 2009, 10Clouds is a software development firm specializing in FinTech and Blockchain solutions. They bring deep expertise across the entire product development lifecycle, along with AI services and staff augmentation. Over the years, they’ve racked up some impressive accolades, including being named one of Europe’s Fastest Growing Companies by the Financial Times, making Deloitte’s list of the 50 Fastest Growing Companies in Central and Eastern Europe, and earning a spot among Clutch’s top 100 companies worldwide.
SERVICES: web development, mobile development, web design, product design, UX design, DevOps services, MLOps services, blockchain
TECH STACK: React.js, Angular, React Native, Node.js, Vue.js, Swift, Flutter, Kotlin, Python, Elixir
TALENTS: developers, designers, QA specialists, product delivery managers
SKILLS: blockchain, machine learning, DevOps, MLOps, design, mobile apps, web apps
PORTFOLIO: Asmodee, StepStone, Baidu, TrustStamp, Forbes, Skedulo, Swile, Coinquista
REVIEWS: 4.9 stars on Clutch from 57 reviews
WHAT CLIENTS APPRECIATE: transparency, cost-consciousness, engagement, dedication, effective workflow and project management, code quality, flexibility
CULTURE & VALUES: feedback, humanism, progress, celebrating achievements, care, appreciation
METHODOLOGY: Agile methodology
COMPANY SIZE: 200+
LOCATION: Poland, Warsaw (HQ), Poznan, Wroclaw
INDUSTRIES THEY'RE ESPECIALLY EXPERIENCES WITH: FinTech, banking, EduTech, HealthTech, IT, business services
<h3 id="10pearls">10Pearls</h3>
10Pearls is a software development firm that covers everything from product development and technology acceleration to product design. They specialize in working with enterprise and midmarket clients, guiding them through every stage - from strategy and software development to digital acceleration. Their work has earned recognition from Clutch, Gartner, and Forrester, and in 2022, the Financial Times named them one of the fastest-growing businesses in the country.
SERVICES: software development, web application development, enterprise mobility, digital transformation, UX and UI design, QA services Cloud & DevOps solutions
TECH STACK: JavaScript, Node.js, React Native, .NET, C#, Java, R, Objective-C, PHP, Angular, React, Meteor, Xamarin, MongoDB, MySQL, Python, Golang, Swift,
CLIENTS: AmWell, Docker, Hobsons, HughesNet, Johnson & Johnson, PayPal, CocaCola, Intuit, Stripe, AARP, Telmate, Homeland Security, WeatherBug, Homeland Security, Zubie
TEAM: software developers, QA engineers, DevOps engineers, data scientists, UX/UI designers, graphic designers, project managers, business analysts, delivery managers
REVIEWS: 4.9 stars on Clutch from 32 reviews
SKILLS: Artificial Intelligence, IoT, chatbots, AR/VR, blockchain, metaverse, voice & language processing, data & analytics, continuous security, QA, DevOps, CloudOps, AWS, Azure, GCP, containerization, market research, Docker, cybersecurity, data science, UX design, UI design, prototyping, wireframing, customer experience
WHAT CUSTOMERS VALUE: adaptability, being attentive to the demands of the client, committment, adhering to a schedule, transparency, providing all-around assistance
CULTURE & VALUES: being human-centered, employee development, learning, growth, altruistic intentions, charity
METHODOLOGY: Agile methodology
COMPANY SIZE: 1500+
LOCATION: USA (Washington, New York), UK (London), Costa Rica (San Jose), Colombia (Medellin), UAE (Dubai), Peru (Lima), Pakistan (Islamabad, Karachi, Lahore),
FOUNDED IN: 2004
PRICE RANGE: $25 - $49 / hr
INDUSTRIES THEY’RE EXPERIENCED WITH: fintech, energy & natural resources, medtech, education, telecommunications
<h3 id="miquido">Miquido</h3>
Founded in 2011, Miquido has made a name for itself in software development, especially in mobile app development. Their rapid growth earned them a spot on Deloitte Technology Fast 50 as the fastest-growing mobile development company in Central and Eastern Europe. They’re also a Google Certified Agency and have been featured in top publications like Time and Forbes. On top of that, they’ve been recognized as one of the leading mobile app development companies in the UK.
SERVICES: product design, web development, mobile development, Artificial Intelligence, product strategy, digital transformation, legacy modernization, Proof of Concept, innovation research, UX/UI design, UX workshops, UX audit, Cloud deployment
SKILLS: native mobile app development, cross-platform mobile app development, Artificial Intelligence, Machine Learning, Data Science, Computer Vision, AWS, Google Cloud Platform, cloud app development, cloud deployment, UX design, UI design, Business Intelligence, product strategy, workshop, NLP, market research, prototyping, PoC
TECH STACK: JavaScript, Angular, React, Node.js, Golang, Java, Flutter, Swift, Kotlin, TypeScript, Kubernetes
TALENTS: designers, developers, project managers
PORTFOLIO: Skyscanner, Abbey Road Studios, BNP Paribas, Santander Bank, Herbalife, Play, TUI, Empik, Onkyo Music, HelloFresh, Pando, Klassik Radio, HID, Nestle, Aviva, AXA, SBAB, Nextbank
REVIEWS: 4.8 stars on Clutch from 36 reviews
WHAT CLIENTS APPRECIATE: reliability, flexibility, consistency, quick turnaround time, ability to onboard rapidly, versatile range of skills, transparency, communication skills, commitment
CULTURE & VALUES: transparency, honesty, business value, putting people first, personal growth, competence development, satisfaction.
METHODOLOGY: Agile methodology
COMPANY SIZE: 200+
LOCATION: Poland, Cracow
INDUSTRIES THEY'RE ESPECIALLY EXPERIENCES WITH: FinTech (banking, insurance), e-commerce, MedTech, entertainment.
<h3 id="geniusee">Geniusee</h3>
Geniusee, a software development company founded in 2017 in Ukraine, specializes in catering to startups, small and mid-sized organizations, with a particular emphasis on EdTech and FinTech product development. They take pride in their proficiency across 64 different technologies and highlight a portfolio of more than 100 accomplished projects. Geniusee has gained recognition as a prominent provider of Android app development services by GoodFirms and has been featured among the top developers from Ukraine according to Clutch.
SERVICES: mobile app development, web application development, UX/UI design, website support, DevOps support
TECH STACK: JavaScript, React, Vue, Node.js, React Native, Swift, Kotlin, Python, .NET, Java, PHP,
TALENTS: software developers, frontend developers, backend developers, DevOps engineers, QA engineers, project managers, business analysts, UX designers, UI designers
SKILLS: mobile apps, native mobile app development, hybrid mobile app development, DevOps, AWS, business analysis, QA testing, QC testing, blockchain, serverless architecture, Data Science, Artificial Intelligence, Machine Learning, DevOps engineering, discovery phase, product maintenance, legacy reengineering, POC, MVP development
REVIEWS: 5.0 stars on Clutch from 36 reviews
CLIENTS: Zytara, Chegg Money, FactMata, Scout and Drum Technologies Inc., Dell, DataRobot, QuitGenius, Vrazo, RealmFive, CraveRetail, Swoon Editions, Kumulus Technologies
WHAT CUSTOMERS VALUE: understanding the expectations, collaborating smoothly, comprehending the project requirements, communication skills, transparency, involvement
METHODOLOGY: Agile methodology
COMPANY SIZE: 150+
LOCATION: Ukraine (Kyiv, HQ)
FOUNDED IN: 2017
PRICE RANGE: $25 - $49 / hr
INDUSTRIES THEY'RE EXPERIENCED WITH: financial services, EdTech, retail, automotive, real estate, transportation, tourism
CULTURE & VALUES: openness, transparency, collaboration, commitment, responsibility, offering support, delivering on schedule.
<h3 id="neoteric">Neoteric</h3>
Neoteric is a software development agency established in 2005, with a strong emphasis on Artificial Intelligence development. Their key principles for successful remote software development revolve around effective communication, collaboration, and transparency. Design Rush has recognized them as one of the top technology experts to hire in 2021, while Clutch has acknowledged them as one of the leading Artificial Intelligence companies and top web developers in the same year.
SERVICES: web development, product design, AI development
TECH STACK: JavaScript, Angular, React, Node.js, Nest.js, AWS, CD/CI, TypeScript
TEAM: software engineers, UX/UI designers, QA engineers, scrum masters, data scientists, product owners, PO proxies
SKILLS: Artificial Intelligence, Machine Learning, workshops, PWA, design strategy, UX/UI design, product design workshop, Rappid, Design Sprint, product strategy, wireframing, prototyping, user research, API development, digital transformation, PoC, predictive analytics, NLP, scoring models
PORTFOLIO: Siemens, Nestle, The World Bank, Liveramp, Appoint.ly, Jeppesen, RapidSOS, Crowdstrike, Approchid, Nanoramic, Client.io, Egain, AlchemAI
REVIEWS: 4.9 stars on Clutch from 38 reviews
WHAT CLIENTS APPRECIATE: professionalism, communication skills, proactive attitude, transparency, accountability, engagement, taking ownership, being highly responsive, being highly receptive to feedback, flexibility towards client’s needs, punctuality, responsibility, strong management skills, being keen on adapting to timeline changes
CULTURE & VALUES: One of the company’s core values is ownership and taking responsibility for one’s goals. They treat one another as family members, value the freedom of employees to choose the best solutions, and responsibility which naturally arises on that. The team treasures personal and professional growth and notices the importance of supporting one another.
METHODOLOGY: Agile methodology
COMPANY SIZE: 120
LOCATION: Poland, Gdańsk
INDUSTRIES THEY’RE ESPECIALLY EXPERIENCES WITH: business, IT, supply chain, logistics, transport, telecommunications, fitness, e-commerce, healthcare, real estate, financial services, education
<h3 id="spro">S-Pro </h3>
S-Pro specializes in offering dedicated teams with exceptional subject matter expertise, focusing primarily on fintech. Their services include consulting and software engineering, catering to startups, banks, and various financial institutions. The company frequently collaborates with accelerators such as BCCS Cluster, Sente.Link, and Founder Institute to facilitate the growth of their partners. In 2021, S-Pro received recognition from Clutch as one of the top Ukrainian software development companies and one of the Global Top 1000 Firms. Additionally, The Manifest featured S-Pro as one of the highly reviewed blockchain companies in Ukraine.
SERVICES: software development, web application development, mobile development, design
KEY CLIENTS: MeterQubes, Crypto Wallet, Refundmatic
TECHNOLOGIES: JavaScript, React, Angular, Node.js, Python, Java, Golang, PHP, Laravel, React Native, Flutter, Swift, Kotlin
TALENTS ON BOARD: software developers, tech leaders, QA engineers, UX/UI designers, DevOps engineers, project managers, business analysts
REVIEWS: 4.9 stars on Clutch from 32 reviews
SKILLS: blockchain, API development, Big Data, cloud, DevOps, branding, Artificial Intelligence, Machine Learning, UX design, UI design, PoC, infrastructure engineering, architecture, MVP, product migration strategy, quality assurance, marketplaces, trading bots, Firebase
WHAT CUSTOMERS VALUE: exemplary delivery skills, cordial yet professional communication, responsiveness, being a reliable partner, being proactive, excellent project management, engagement, and flexibility.
METHODOLOGY: Agile methodology
COMPANY SIZE: 250+
LOCATION: Ukraine (Kyiv)
FOUNDED IN: 2014
PRICE RANGE: $50 - $99 / hr
INDUSTRIES THEY’RE ESPECIALLY EXPERIENCED WITH: fintech, healthcare, logistics and transport, retail, real estate
CULTURE & VALUES: The group lays a strong emphasis on ongoing development and a thirst for knowledge. They take pride in their approach being product-focused. They place a great importance on creativity and high-quality work.
<h3 id="dataart">DataArt</h3>
DataArt is an established software engineering and artificial intelligence development company with a rich history spanning more than two decades. They specialize in fintech product development and consulting services.
DataArt excels in digital transformation and modernizing legacy systems. They possess extensive expertise in cybersecurity and using machine learning models. Due to their expansive team and global presence, DataArt maintains offices and teams across multiple continents and time zones. This broad distribution contributes to their wide range of skills and capabilities.
RANGE OF SERVICES: digital transformation and system modernization, legacy re-engineering, data management and analytics, insurance software development services, cyber security services
TOP FINTECH CLIENTS: Monex Europe, Nasdaq, Bematech
THEY WORKED WITH: enterprises, medium-sized companies
TECHNOLOGIES: .NET, Angular.js, React.js, Node.js, Ruby on Rails, Oracle, Spring MVC
TALENTS ON BOARD: software engineers, solution architects, Cloud engineers, Data engineers, DevOps engineers, QA engineers, business analysts, product owners, project managers, scrum masters, delivery managers, UX/UI designers, product designers
REVIEWS: 5.0 stars on Clutch from 12 reviews
SKILLS: Big Data, business intelligence, AR/VR, business analysis, usability, cloud security audit, secure code review, penetration testing, security assurance and consulting, cloud computing, cloud-native development, cloud migration, customer experience, user experience, Artificial Intelligence, Machine Learning
WHAT CLIENTS APPRECIATE: grasping business needs quickly, professionalism, ability to deliver, strong work ethic, strong communication skills, understanding how business works
METHODOLOGY: Agile methodology
COMPANY SIZE: 5500+
LOCATION: USA (New York, Dallas, Orlando, Pittsfield), UK (London), Poland (Cracow, Lublin, Wroclaw), Germany (Munich), Switzerland (Zug), Argentina (Buenos Aires)
FOUNDED IN: 1997
PRICE RANGE: $50 - $99 / hr
CULTURE & VALUES: They call themselves engineers with open hearts, driven by the people-first principle. They integrate human values into their business and work relations: curiosity, empathy, trust, honesty, and intuition. The team strives to integrate those values with engineering excellence. They treasure flexibility and variety, cherish empowerment and education over bureaucracy, and highly value trust.
<h3 id="eteam">eTeam</h3>
eTeam is a Ukrainian firm that specializes in the development of web and mobile applications. Founded in 2016, their range of services includes managed teams and staff augmentation. They primarily cater to startups and small businesses as their client base. eTeam achieved global recognition by being listed as one of the Top 1000 Companies by Clutch.
SERVICES: web app development, mobile app development, UX/UI design
SKILLS: developers, designers, QA engineers, project managers, DevOps engineers, React, React Native, Node.js, Golang, TypeScript, Ruby, Kotlin, Swift, MongoDB, Angular.js, Express, AWS, Kubernetes, Docker, Jenkins, Google Cloud, Azure, data science, data engineering, data analysis, Machine Learning, Cybersecurity, DevOps, project management, MVP
PORTFOLIO: VanillaDirect Pay, InComm, Bluesnap, Genie, Taksware, Elegant Open Banking, Armatic, Roost, Hirebook
REVIEWS: 4.9 stars on Clutch from 25 reviews
WHAT CLIENTS APPRECIATE: high standards of work and high quality, transparency, outstanding project management, flexibility, top-notch coding skills, diversity of the team, engagement, responsive and skilled approach, adjusting when issues arise, independence, understanding the business needs
CULTURE & VALUES: They care about growth and career development, as well as establishing a great work environment for their employees. They care about bringing more value to the table, and sharing their experience beyond just making apps.
METHODOLOGY: Agile methodology
COMPANY SIZE: 120+
LOCATION: Ukraine (Kyiv), Mexico (Guadalajara), USA (Aliso Viejo, CA)
INDUSTRIES THEY'RE ESPECIALLY EXPERIENCES WITH: fintech, telecommunications, banking, IT services, retail, edtech, fitness, health, recruitment
<h3 id="geekyants"GeekyAnts</h3>
GeekyAnts is a design and development company founded in 2006 that provides dedicated teams and extensive services for product development. They specialize in web and mobile development. One of their notable achievements is the creation of the UI library NativeBase specifically for React Native. They hold official recognition as service providers by Google and have authored the official documentation for Flutter. As part of their efforts to support employment, they have developed a crash course aimed at programmers.
SERVICES: UX/UI design, API development, web app development, mobile app development, consulting
SKILLS: React.js, Angular, Flutter, Svelte, Golang, Node.js, React Native, Laravel, Python, Vue.js, TypeScript, Firebase, AWS, GraphQL, Next.js, Express, microservices, cross-platform apps, UX research, branding, UX design, UI design, DevOps, project management, business analysis, quality assurance, MVP
PORTFOLIO: Siveco Romania, ChildMind Institute, Tellius, PayPoint, QuinType, EndLink, Mobile Premier League, Lamno, Cloud9, Khatabook
REVIEWS: 4.8 stars on Clutch from 45 reviews
WHAT CLIENTS APPRECIATE: understanding the business objectives, high-quality work, seamless project management, commitment, proactivity, transparency, ownership, collaborative attitude, addressing feedback professionally and in a timely manner.
CULTURE & VALUES: One of the top company values is constant learning and sharing of experiences. Transparency and communicating things on time are the basis of their teamwork. They cherish constant feedback sessions and one-on-one meetings to maintain and open-door policy and face problems ahead of time. They also value the quality of their work and strive to perfection.
METHODOLOGY: Agile methodology
COMPANY SIZE: 300+
LOCATION: India (Bangalore), US (California), UK (London)
INDUSTRIES THEY’RE ESPECIALLY EXPERIENCES WITH: healthcare, finance, education, banking, gaming, manufacturing, real estate, e-commerce.
<h3 id="diceus">Diceus</h3>
Diceus is a software development company that focuses heavily on creating software solutions for fintech, banking, and insurance industries. They prioritize the use of cutting-edge technologies such as artificial intelligence, blockchain, big data, and cloud solutions to optimize the functionality and performance of their financial software products.
RANGE OF SERVICES: lending management software, blockchain solutions, regtech, payments software solutions, blockchain fintech app development, loan management software, money transfer app development, fintech application development, mobile banking apps, IT consulting, system integration, insurance software development, online banking, core banking systems, mobile banking
TOP FINTECH CLIENTS: Risk Point, Bank al Etihad, Teambase, BriteCore
THEY WORKED WITH: small and medium-sized companies, corporations
TECHNOLOGIES: React.js, Node.js, Vue.js, Angular.js, Golang, Flutter, Java, .NET, Python, PHP, Ruby, Objective.C
TALENTS ON BOARD: frontend developers, backend developers, designers, architects, QA and test engineers, business analysts, project managers
REVIEWS: 4.8 stars on Clutch from 40 reviews
SKILLS: DevOps, Artificial Intelligence, Machine Learning, blockchain, big data, cloud solutions, data science, cross-platform apps, payment gateway development, payment integration services, contactless payments and POS, real-time payments, Digital Ledger Technology, smart contracts, banking loan software solutions, fintech money lending software, loan module in core banking, business process automation, loan decisioning software, money transfer functionalities, CRM, mobile banking apps, payment applications, IoT, ERP, Robotic Process Automation, system integration, software architecture
WHAT CLIENTS APPRECIATE: responsiveness, professionalism, and organizational skills, result-oriented approach, effective communication, expertise, timely reporting, commitment and dedication
METHODOLOGY: Agile methodology
COMPANY SIZE: 100+
LOCATION: Ukraine (Kyiv), Denmark (Hellerup), Lithuania (Alytus), USA (New York City)
FOUNDED IN: 2011
PRICE RANGE: $50 - $99 / hr
CULTURE & VALUES: The company’s mission is to deliver high quality. They want to bring as many values as possible with the right technology and people. They combine expertise with a quality-driven delivery model.
How was this ranking created?
The companies listed in this ranking meet specific criteria to ensure their reputation and reliability:
They have received a significant number of positive client reviews, with a minimum of 30 reviews on platforms such as Clutch, and many of them have accumulated over 50 reviews in total.
These companies maintain an overall score of 4.8 or higher on Clutch, indicating consistently excellent client satisfaction.
No entirely negative reviews are found about these companies on Clutch, further attesting to their positive track record.
The companies featured in this ranking have been operating in the market for at least 5 years and possess extensive experience in software development, demonstrated through their robust portfolios.
They employ skilled teams capable of delivering scalable custom software solutions.
These companies exhibit high levels of engagement, proactive behavior, a sense of ownership, and a problem-solving focus based on their past projects.
They promote an Agile working culture, enabling flexibility and adaptability in their processes.
Offering cross-functional teams composed of diverse specialists, these companies are dedicated to improving their clients' business outcomes.
It's important to note that there are no sponsored sections in this ranking. These companies have been genuinely top-rated and have undergone thorough research and evaluation by real individuals, rather than relying solely on algorithms.
The information used for this ranking was derived from a comprehensive analysis of the companies' websites, rankings on various portals, reviews, testimonials, and the content they publish on blogs and social media.
FAQ about AI solution development services
What is an AI software company?
An AI software company is a company that specializes in developing and providing software solutions that leverage artificial intelligence (AI) technologies. These companies focus on designing, building, and deploying software applications that utilize machine learning, deep learning, natural language processing, computer vision, and other AI techniques. They develop AI algorithms, models, and systems to enable automated decision-making, predictive analytics, pattern recognition, and other intelligent capabilities in software applications. AI software companies cater to various industries and sectors, offering solutions for tasks such as automation, data analysis, recommendation systems, speech recognition, image processing, and more.
How to choose the best AI development company?
When choosing the best AI development company for your needs, consider the following factors:
Expertise and experience
Look for a company that has demonstrated expertise and experience in AI development. Evaluate their track record, portfolio of AI projects, and the technologies they specialize in.
Domain knowledge
Consider whether the company has experience in your industry, ai technology or domain. AI solutions can vary greatly across sectors, so finding a company that understands the specific challenges and requirements of your industry can be beneficial.
Skill set
Assess the company's skill set in relevant AI technologies such as machine learning, deep learning, natural language processing, computer vision, or robotics. Determine if they have the necessary expertise to develop the specific AI solutions you require.
Collaborative approach
Look for a company that adopts a collaborative approach to working with clients. They should actively involve you in the development process, understand your business goals, and offer solutions tailored to your needs.
Reputation and references
Research the company's reputation by checking client reviews, testimonials, and case studies. Reach out to their past clients for references to gain insights into their working style, professionalism, and project outcomes.
Data security and compliance
Ensure that the company has strong data security measures and is compliant with relevant regulations and privacy standards. This is especially important when dealing with sensitive data.
Scalability and support
Consider the company's ability to scale their AI solutions as your business grows. Additionally, assess the level of ongoing support they provide after the implementation of the AI solution.
Budget and cost
Evaluate the company's pricing structure and determine if it aligns with your budget. However, be cautious of companies that offer significantly lower prices but compromise on quality.
Communication and transparency
Effective communication and transparency are crucial for successful collaboration. Ensure that the company has clear communication channels, regular progress updates, and provides you with visibility into the development process.
Innovation and future-readiness
Assess the company's commitment to innovation and staying updated with the latest AI trends and technologies. Look for a company that demonstrates a forward-thinking mindset and is prepared for future business challenges and advancements in AI.
By considering these factors and conducting thorough research, you can identify the best AI development company that aligns with your specific requirements and can deliver high-quality AI solutions.
How is AI used in software development?
AI is transforming software development in several key ways. In short, AI is used in software development for enhancing efficiency, accuracy, and innovation. AI tools can automatically generate code snippets or boilerplate code. What's more, AI algorithms helps to detect bugs and vulnerabilities. AI can also analyze user interaction data to tailor software behavior and interfaces to individual users, improving user satisfaction and engagement. AI techniques are also used to enhance software security by identifying and mitigating potential threats and anomalies in real-time, making software systems more resilient to attacks.
| 2025-06-27T00:00:00 |
https://brainhub.eu/library/top-ai-development-companies
|
[
{
"date": "2025/06/27",
"position": 70,
"query": "AI employers"
}
] |
|
Alphabet's AI Investments in 38 Companies in 2025
|
Alphabet's AI Investments in 38 Companies in 2025
|
https://research.aimultiple.com
|
[] |
Excluding Google's search efforts, Alphabet made investments into 38 AI companies such as Deep Mind, Nest, Waymo & startups in healthcare, finance, ...
|
After acquiring DeepMind, and spending more than $13 billion to build data centers Google became one of the leading players in the AI field Driven by its AI investments and search engine investments the tech giant reported a strong profit growth of 25+% in the second quarter of 2024, beating analysts’ expectations.
Alphabet
Alphabet is a conglomerate including Google which mainly consists of search, maps, YouTube, Chrome, Cloud, AdWords, AdSense, and the Android mobile phone platform.
Beyond Google, Alphabet consists mostly of moonshots and investments: Google X, Calico, Nest, Ventures, Fiber, and Capital.
To understand the current state of Alphabet’s AI strategy, one needs to look at:
Google, which we examined separately here since AI is baked into so many of Google’s products. Alphabet’s fully owned ventures outside Google, like Waymo or DeepMind Alphabet’s investments through Google Capital or Google Ventures
Focusing on 2&3, we structured these companies along the industries they serve. Most companies serve industries like Healthcare that are experiencing an AI revolution. Another large group of companies is active as AI enablers. Like Deepmind or API.ai they aim to build the building blocks of AI including systems, libraries, and APIs.
Google’s ventures are specifically focused on AI enablers, transport & logistics and healthcare.
Instead of diving into all of Alphabet’s bets in the field of AI, we will first focus on Deepmind, Waymo, and Nest, which are Alphabet’s leading investments leveraging AI.
DeepMind
DeepMind at the heart of Google operations
In April 2023, DeepMind merged with Google AI’s Google Brain division to become Google DeepMind, as part of the company’s ongoing attempts to accelerate AI research in response to OpenAI’s ChatGPT.
Google collaborates with DeepMind to solve some of its engineering challenges, like energy efficiency. By applying DeepMind’s ML to Google data centers, energy use for cooling was reduced by up to 40%. Their collaboration model is explained here.
DeepMind in chemistry
Google DeepMind’s AI researchers developed and used the neural network AI program AlphaFold to predict the intricate folding patterns of proteins, solving a five-decade scientific enigma. This computational technique for designing new proteins could fuel new boundaries of protein engineering by enabling scientists to create new proteins
AlphaFold is considered a “complete revolution” by the Nobel Committee, and it is being used to fold 200 million proteins globally.
DeepMind in digital health
DeepMind Health works with hospitals on mobile tools and AI research to help get patients from test to treatment as quickly and accurately as possible.
The company’s priorities are shaped by patients and clinicians, unlike top-down IT projects that can be costly and ineffective.
Nurses and doctors in that system and elsewhere simply don’t have the tools to instantly analyze each test result, determine the right treatment, and make sure that every single patient who needs complex or urgent care is escalated to the right specialist immediately.
MuZero, AlphaZero, and AlphaDev by DeepMind
DeepMind’s AI systems MuZero, AlphaZero, and AlphaDev approached the circuit as a neural network for accelerating chip design and improving performance.
DeepMind collaborated with YouTube to compress and transmit video, leveraging MuZero to improve the YouTube user experience by decreasing the bitrate by 4% while maintaining visual quality.
AlphaDev, a version of AlphaZero, made a novel breakthrough in computer science by optimizing the algorithm sorting process.
Sorting algorithms assist digital devices in processing and displaying information, including the ranking of online search results and social postings.
AlphaDev identified a method that improves performance for sorting sequences by 70% compared to the algorithms in the C++ library. This implies that results from user searches may be sorted significantly more quickly. When applied at scale, this saves enormous amounts of time and energy.
Artificial general intelligence with DeepMind
One of the crucial aspects of general intelligence is applying knowledge from one task to another.
DeepMind’s models solve advanced reasoning problems in mathematics: AlphaProof, a new reinforcement-learning-based system for formal math reasoning, and AlphaGeometry 2, an updated version of our geometry-solving system. These systems answered four of six problems from this year’s International Mathematical Olympiad (IMO), placing them on par with a silver medalist.
Waymo
Waymo is Google’s self-driving car project. It’s a large-scale AI model known as the Waymo Foundation Model, which underpins the vehicle’s capacity to sense its surroundings and make driving judgments.
Waymo continues to rev up autonomous driving with AI. In October 2024, Waymo co-CEO Tekedra Mawakana stated that the self-driving car business is providing 100,000 robo-taxi rides each week, doubling the 50,000 ride number in June.
CEO Dmitri Dolgov posted a video demonstrating how the software is continuously learning. The brief video shows how the Waymo Driver adapts its path as it travels through tunnels, storms, and narrow streets.
If you are interested in how ML-powered Google’s cars work, here are more geeky details from here.
Nest
Google Nest is a brand of smart AI-powered home appliances that includes smart speakers, smart displays. AI is baked into Nest. When you’re on your way home, Google will work with Nest to preheat or cool your home to your preferred temperature. Control your Nest with your voice from your tablet or phone app.
In 2024, Google announced 2 large smart home AI upgrades:
Natural language processing (NLP): Google claims that the revamped Nest now functions similarly to Amazon Alexa and Apple’s Siri, using natural language processing technology to respond to user inquiries.
Google claims that the revamped Nest now functions similarly to Amazon Alexa and Apple’s Siri, using natural language processing technology to respond to user inquiries. Gemini integration: Google is now integrating Gemini into the Google Home app for smart home Nest cameras, employing image recognition to provide descriptions of what the camera catches.
Nest’s built-in intelligent home appliances can help Google get into more houses, and allow users to get more involved in everyday life, some of which are carried out digitally each day.
Analysts are predicting that the Internet of Things will be a trillion-dollar market, which was one justification for Nest’s $ 3.2 billion price tag.
Bottom line
Google continues to innovate in AI, and we’ll keep track of their progress. To stay on the bleeding edge of AI, you can check out AI applications in marketing, sales, customer service, IT, data, or analytics.
You can also find our list of AI tools and services:
| 2025-06-27T00:00:00 |
https://research.aimultiple.com/alphabet-ai/
|
[
{
"date": "2025/06/27",
"position": 93,
"query": "AI employers"
}
] |
|
As job losses loom, Anthropic launches program to track AI's ...
|
As job losses loom, Anthropic launches program to track AI’s economic fallout
|
https://techcrunch.com
|
[
"Rebecca Bellan",
"Senior Reporter",
"Marina Temkin",
"Anna Heim",
"Sarah Perez",
"Zack Whittaker",
"Maxwell Zeff",
"Lorenzo Franceschi-Bicchierai",
"--C-Author-Card-Image-Size Align-Items Center Display Flex Gap Var",
"Media"
] |
As warnings mount about AI's potential to displace millions of jobs, Anthropic on Friday launched a its Economic Futures Program, ...
|
Silicon Valley has opined on the promise of generative AI to forge new career paths and economic opportunities — like the newly coveted solo unicorn startup. Banks and analysts have touted AI’s potential to boost GDP. But those gains are unlikely to be distributed equally in the face of what many expect to be widespread AI-related job loss.
Amid this backdrop, Anthropic on Friday launched its Economic Futures Program, a new initiative to support research on AI’s impacts on the labor market and global economy and to develop policy proposals to prepare for the shift.
“Everybody’s asking questions about what are the economic impacts [of AI], both positive and negative,” Sarah Heck, head of policy programs and partnerships at Anthropic, told TechCrunch. “It’s really important to root these conversations in evidence and not have predetermined outcomes or views on what’s going to [happen].”
At least one prominent name has shared his views on the potential economic impact of AI: Anthropic’s CEO Dario Amodei. In May, Amodei predicted that AI could wipe out half of all entry-level white-collar jobs and spike unemployment to as high as 20% in the next one to five years.
When asked if one of the key goals of Anthropic’s Economic Futures Program was to research ways to mitigate AI-related job loss, Heck was cautious, noting that the disruptive shifts AI will bring could be “both good and bad.”
“I think the key goal is to figure out what is actually happening,” she said. “If there is job loss, then we should convene a collective group of thinkers to talk about mitigation. If there will be huge GDP expansion, great. We should also convene policy makers to figure out what to do with that. I don’t think any of this will be a monolith.”
The program builds on Anthropic’s existing Economic Index, launched in February, which open sources aggregated, anonymized data to analyze the effects of AI on labor markets and the economy over time — data that many of its competitors lock behind corporate walls.
Techcrunch event Save up to $475 on your TechCrunch All Stage pass Build smarter. Scale faster. Connect deeper. Join visionaries from Precursor Ventures, NEA, Index Ventures, Underscore VC, and beyond for a day packed with strategies, workshops, and meaningful connections. Save $450 on your TechCrunch All Stage pass Build smarter. Scale faster. Connect deeper. Join visionaries from Precursor Ventures, NEA, Index Ventures, Underscore VC, and beyond for a day packed with strategies, workshops, and meaningful connections. Boston, MA | REGISTER NOW
The program will focus on three main areas: providing grants to researchers investigating AI’s effect on labor, productivity, and value creation; creating forums to develop and evaluate policy proposals to prepare for AI’s economic impacts; and building datasets to track AI’s economic usage and impact.
Anthropic is kicking off the program with some action items.
The company has opened applications for its rapid grants of up to $50,000 for “empirical research on AI’s economic impacts,” as well as evidence-based policy proposals for Anthropic-hosted symposia events in Washington, D.C., and Europe in the fall. Anthropic is also seeking partnerships with independent research institutions and will provide partners with Claude API credits and other resources to support research.
For the grants, Heck noted that Anthropic is looking for individuals, academics, or teams that can come up with high-quality data in a short period of time.
“We want to be able to complete it within six months,” she said. “It doesn’t necessarily have to be peer-reviewed.”
For the symposia, Anthropic wants policy ideas from a wide variety of backgrounds and intellectual perspectives, said Heck. She noted that policy proposals would go “beyond labor.”
“We want to understand more about the transitions,” she said. “How do workflows happen in new ways? How are new jobs being created that nobody ever contemplated before? … How are certain skills remaining valuable while others are not?”
Heck said Anthropic also hopes to study the effects of AI on fiscal policy. For example, what happens if there’s a major shift in the way enterprises see value creation?
“We really want to open the aperture here on things that can be studied,” Heck said. “Labor is certainly one of them, but it’s a much broader swath.”
Anthropic rival OpenAI released its own Economic Blueprint in January, which focuses more on helping the public adopt AI tools, building robust AI infrastructure and establishing “AI economic zones” that streamline regulations to promote investment. While OpenAI’s Stargate project to build data centers across the U.S. in partnership with Oracle and SoftBank would create thousands of construction jobs, OpenAI doesn’t directly address AI-related job loss in its economic blueprint.
OpenAI’s blueprint does, however, outline frameworks where government could play a role in supply chain training pipelines, investing in AI literacy, supporting regional training programs, and scaling public university access to compute to foster local AI-literate workforces.
Anthropic’s economic impact program is part of a slow but growing shift among some tech companies to position themselves as part of the solution to the disruption they’re helping to create — whether out of reputational concern, genuine altruism, or a mix of both. For instance, on Thursday, ride-hail company Lyft launched a forum to gather input from human drivers as it starts integrating robotaxis into its platform.
| 2025-06-27T00:00:00 |
2025/06/27
|
https://techcrunch.com/2025/06/27/as-job-losses-loom-anthropic-launches-program-to-track-ais-economic-fallout/
|
[
{
"date": "2025/06/27",
"position": 77,
"query": "AI job losses"
}
] |
2025 Summer School for Journalists and Media Practitioners
|
2025 Summer School for Journalists and Media Practitioners – Centre for Media Pluralism and Media Freedom
|
https://cmpf.eui.eu
|
[] |
Big tech companies have expanded their reach and diversified their offerings, including generative and general AI applications. This has enabled an entirely new ...
|
The Future of the Information Sphere and Journalism Intelligence Over the past decades, big technology companies have positioned themselves at the centre of our information systems, while challenging the very existence of traditional media and journalism and also increasingly aligning with political power. While these threats have also sparked creative resistance and some of the most remarkable journalism in recent years, the profession has simultaneously experienced a rapid decline, both in terms of a sustainable business model and its reach, particularly among young audiences who primarily access news through online platforms. Big tech companies have expanded their reach and diversified their offerings, including generative and general AI applications. This has enabled an entirely new ecosystem of communicators and opinion-influencers who are not journalists in the traditional sense but may play a similar or more persuasive role. In some cases, these voices disrupt the information sphere rather than enriching it. The 13th edition of the CMPF Summer School for Journalists and Media Practitioners (23-27 June 2025) will explore what these changes, along with the fact that private corporations with very limited liability control the infrastructure of the contemporary information sphere, mean for the future of journalism and a democratic information landscape. With renowned scholars and experts, we will examine opportunities for innovation and strategies to level the playing field between technology companies and journalism, ensuring the economic sustainability of the profession, particularly for investigative journalism. We will also discuss major regulatory interventions (at the EU and global levels) aimed at protecting and strengthening the integrity of the information space, enhancing the accountability and transparency of major online platforms, and safeguarding media freedom, with due consideration to geopolitical developments. A unique aspect of this year’s summer school will be a Practice Day, featuring a creative expression lab where journalists and artists can collaborate to imagine new, technology-assisted formats that may help revive the connection between journalism and its audience. The CMPF Summer School offers journalists and media practitioners an opportunity to learn, exchange ideas, and discuss key issues shaping journalism and informed citizenship. The programme will feature presentations by distinguished experts, followed by interactive sessions designed to enhance participants’ understanding, engagement, and networking.
Big Tech, AI, and journalism: practices within and beyond journalism
Mental well-being and safety of journalists
AI and media business: copyright, innovation, transformation, monetisation
EU Regulatory framework and global standards (Focus on the European Media Freedom Act, but also the Artificial Intelligence Act, Digital Services Act, Digital Markets Act, and Code of Practice on Disinformation)
Geopolitics of freedom of expression and freedom of the media
Key international developments in Internet governance and their potential impact on the future of journalism and the media sector
Creative resistance in journalism and by journalists, including strategies to protect journalists and media actors
Shared knowledge of trends affecting journalism, informed citizenship, and democracy;
Up-to-date overview of the technology and practice trends, legislative changes, and legal principles governing content online;
Strategies for the development of new business models in journalism;
Interactive session proceedings;
Facilitating networking among participants and between participants and speakers. A Certificate will be awarded to participants who successfully complete the training course.
The Summer School is open to early and mid-career journalists and other stakeholders in the news industry. Our aim is to gather participants from a variety of countries and backgrounds. The CMPF will select participants based on the information provided in the application form, assess the quality of applications, and take into account diversity criteria. The working language of the Summer School is English.
Fees Applicants who are not selected for a scholarship will automatically be considered for a self-funded place at the school. Scholarships are not available to participants who can be funded by their own institutions. Cost for self-funded participants: €200 (covering meals and refreshments at the venue). Scholarships We offer up to 31 scholarships within the following categories and conditions: CMPF Summer School Programme scholarships – 20 scholarships Available to applicants from countries participating in the Creative Europe programme, namely: The EU27;
Acceding countries, candidate countries and potential candidates participating in Creative Europe: Albania, Bosnia and Herzegovina, Georgia, Kosovo, Montenegro, North Macedonia, Serbia, Ukraine;
European Neighbourhood Policy countries participating in Creative Europe: Armenia, Tunisia;
EFTA countries which are part of the European Economic Area: Iceland, Norway, Lichtenstein. The CMPF scholarship covers travel expenses up to an established ceiling, accommodation for 5 nights, tuition fees, all course materials, access to the EUI library, Wi-Fi access at the EUI, social activities, lunches, and coffee breaks on lecture days. New! Scholarships for nationals of Turkey and Ukraine – 2 Available Funded by the Robert Schuman Centre, these scholarships are primarily intended for applicants from Turkey and Ukraine. Each scholarship provides a €1,000 contribution towards travel costs and accommodation for five nights. In addition, the Programme will cover tuition fees, all course materials, access to the EUI library, Wi-Fi on campus, social activities, lunches and coffee breaks on lecture days, as well as one cocktail event and one dinner. To be eligible for the scholarship, applicants must be nationals of Turkey or Ukraine.
In the event that there are no eligible applicants from Turkey or Ukraine, the scholarships may be awarded to applicants of other nationalities. Global scholarships – up to 5 scholarships Available to applicants from Africa, Asia-Pacific and Latin America, provided by the European Union in the framework of the Global Initiative on the Future of the Internet. The scholarship is intended for travel expenses (economy class fare), visas, accommodation for 6 nights, tuition fees, all course materials, access to the EUI library, Wi-Fi access at the EUI, social activities, lunches and coffee breaks on lecture days. For more information about global scholarships, applicants can contact Dr Patryk Pawlak at [email protected] EUI Widening Europe Programme scholarships – up to 4 scholarships Available to applicants from the countries part of the EUI Widening Europe Programme. The scholarship will contribute 1000 euros to cover travel expenses and accommodation for 5 nights. In addition, tuition fees, all course materials, access to the EUI library, Wi-Fi access at the EUI, social activities, lunches, and coffee breaks on lecture days, one cocktail, one dinner, will be offered by the Programme. To qualify for this scholarship, applicants must be nationals of one of the countries targeted by the Widening Europe programme: Inside the European Union : Bulgaria, Croatia, Cyprus, Czechia, Estonia, Greece, Hungary, Latvia, Lithuania, Malta, Poland, Portugal, Romania, Slovakia, and Slovenia.
: Bulgaria, Croatia, Cyprus, Czechia, Estonia, Greece, Hungary, Latvia, Lithuania, Malta, Poland, Portugal, Romania, Slovakia, and Slovenia. Outside the European Union: Albania, Bosnia & Herzegovina, Georgia, Kosovo(1), Montenegro, North Macedonia, Serbia, Moldova, and Ukraine. (1) This designation is without prejudice to positions on status, and is in line with UNSCR 1244(1999) and the ICJ Opinion on the Kosovo declaration of independence. Applicants must also affiliated with an academic institution based in a country targeted by the Widening Europe programme (students currently enrolled in a master/doctoral program, postdoctoral researchers, lecturers, or professors) The selection will take into account the candidate’s professional profile, language skills and additional competencies, such as having an international profile, work experience, certificates and other achievements. Please note that the CMPF can provide an invitation letter to the selected participants but cannot assist with the Visa application process or expenses for travel documents. The grant amount is directly linked to course attendance. A daily signature is required, and any absence will result in a reduction of the grant—specifically, €200 per day. The deadline for submitting applications is 4 May 2025.
| 2025-06-27T00:00:00 |
https://cmpf.eui.eu/course/2025-summer-school-for-journalists-and-media-practitioners/
|
[
{
"date": "2025/06/27",
"position": 75,
"query": "AI journalism"
}
] |
|
Tech Layoffs: US Companies With Job Cuts In 2024 And ...
|
Tech Layoffs: US Companies With Job Cuts In 2024 And 2025
|
https://news.crunchbase.com
|
[
"Crunchbase News",
".Wp-Block-Co-Authors-Plus-Coauthors.Is-Layout-Flow",
"Class",
"Wp-Block-Co-Authors-Plus",
"Display Inline",
".Wp-Block-Co-Authors-Plus-Avatar",
"Where Img",
"Height Auto Max-Width",
"Vertical-Align Bottom .Wp-Block-Co-Authors-Plus-Coauthors.Is-Layout-Flow .Wp-Block-Co-Authors-Plus-Avatar",
"Vertical-Align Middle .Wp-Block-Co-Authors-Plus-Avatar Is .Alignleft .Alignright"
] |
Tech layoffs: At least 95000 workers at U.S.-based tech companies were laid off in mass job cuts in 2024 and the cuts have continued into 2025.
|
Microsoft Layoffs Surge And Rivian Rejoins The Tracker After A Year-Plus Respite
Mass layoffs in the U.S. tech sector continued in recent weeks, with Big Tech once again leading the way.
Topping this week’s tracker by sheer number of affected workers is Redmond, Washington-based Microsoft. The company plans to trim its workforce — reportedly via the sales and Xbox teams, among others — by 9,000 workers, or about 4%, of its global staff, according to a report from CNN.
Electric vehicle manufacturer Rivian makes a return to the tracker after a year-plus layoff hiatus. Last week, the Plymouth, Michigan-based company told TechCrunch that it has let go of about 1% of its workforce, or around 140 workers, mostly in the manufacturing division. The cuts come as the company aims to improve operational efficiency for its R2 sport utility vehicle, which it will launch next year.
Venture-funding darling artificial intelligence also claimed a couple of spots on this week’s tracker.
New York’s Retrain.ai, a human resources startup that uses AI to help “employers connect the right people to the right positions” reported it has laid off 20 workers and shuttered operations as the company looks to sell its technology. Founded in 2020, the company raised a total of $34 million in four funding rounds, per Crunchbase data.
Although based in Vancouver, Klue, an AI-powered competitive enablement platform for salespeople, said it has laid off about 40% of its global workforce in an effort to reorganize itself, according to a report, to become “AI-first operationally.” It’s not clear how many of the affected employees are based in the U.S.
New additions
The following companies were added to the tracker this week:
Tech Layoffs: US Companies That Cut Jobs In 2022, 2023, 2024 And 2025
By the numbers
Layoffs during the week ended July 9, 2025: At least 9,245 U.S. tech sector employees were laid off or scheduled for layoffs, per a Crunchbase News tally.
In 2024: At least 95,667 workers at U.S.-based tech companies lost their jobs in 2024, according to a Crunchbase News tally.
In 2023: More than 191,000 workers in U.S.-based tech companies (or tech companies with a large U.S. workforce) were laid off in mass job cuts.
In 2022: More than 93,000 jobs were slashed from public and private tech companies in the U.S.
Companies with the biggest workforce reductions in 2024
3.4K Shares Email
Facebook
Twitter
LinkedIn Methodology This tracker includes layoffs conducted by U.S.-based companies or those with a strong U.S. presence and is updated at least bi-weekly. We’ve included both startups and publicly traded, tech-heavy companies. We’ve also included companies based elsewhere that have a sizable team in the United States, such as Klarna, even when it’s unclear how much of the U.S. workforce has been affected by layoffs. Layoff and workforce figures are best estimates based on reporting. We source the layoffs from media reports, our own reporting, social media posts and layoffs.fyi, a crowdsourced database of tech layoffs. We recently updated our layoffs tracker to reflect the most recent round of layoffs each company has conducted. This allows us to quickly and more accurately track layoff trends, which is why you might notice some changes in our most recent numbers. If an employee headcount cannot be confirmed to our standards, we note it as “unclear.”
Frequently Asked Questions
| 2025-07-09T00:00:00 |
2025/07/09
|
https://news.crunchbase.com/startups/tech-layoffs/
|
[
{
"date": "2025/06/27",
"position": 33,
"query": "AI layoffs"
}
] |
Microsoft Layoffs: Over 1000 Jobs to Be Cut Next Week, ...
|
Microsoft Layoffs: Over 1,000 Jobs to Be Cut Next Week, Including Xbox Staff
|
https://www.finalroundai.com
|
[] |
This would mark the company's third major round of workforce reductions in 2025, as it continues to shift resources toward artificial intelligence development ...
|
Microsoft is preparing to lay off thousands of employees in July, according to a report by Bloomberg. This would mark the company’s third major round of workforce reductions in 2025, as it continues to shift resources toward artificial intelligence development and streamline operations.
In May, the company laid off around 6,000 employees, primarily from product and engineering teams as part of a broader internal restructuring. The upcoming layoffs are expected to impact roles in sales and support functions, reflecting Microsoft’s evolving priorities and its effort to align teams with long term AI driven goals.
The layoffs come as Microsoft plans to spend $80 billion this fiscal year on A.I. infrastructure, primarily data centers, forcing the technology giant to cut costs elsewhere to maintain profit margins. The company's chief executive, Satya Nadella, recently told employees that artificial intelligence now generates 30 percent of Microsoft's internal code.
Fourth Major Round in 18 Months
The upcoming July layoffs mark Microsoft’s fourth major workforce reduction since early 2023.
In January 2023 Microsoft cut 10,000 jobs , or about 4.5% of its global workforce, citing post-pandemic recalibration.
Microsoft cut , or about 4.5% of its global workforce, citing post-pandemic recalibration. In January 2024 the company laid off around 1,900 gaming employees , following its acquisition of Activision Blizzard.
the company laid off around , following its acquisition of Activision Blizzard. In May 2025 Microsoft eliminated 6,000 roles, describing the move as an organizational shift to align with strategic goals. Official WARN filings showed 1,985 job cuts in Washington state alone, affecting teams across LinkedIn, GitHub, Azure, and Xbox.
Gaming divisions have been particularly hard hit, with Microsoft planning additional "major" Xbox layoffs as early as this week, according to The Verge.
Next in line are sales teams and middle managers, with Microsoft Customer and Partner Solutions among the hardest-hit divisions. The company is increasingly outsourcing sales for small and mid-sized business accounts to third-party firms.
Recent filings also revealed that software engineers comprised 22% of the 300 roles eliminated in Washington state in June 2025, reflecting a broader shift in workforce composition.
The Layoff Trend of Silicon Valley
Microsoft’s restructuring is part of a broader wave of mass layoffs sweeping through Silicon Valley. Since the start of 2025, tech companies have cut over 83,800 jobs, an average of 493 every single day.
"Microsoft needs to reduce headcount by at least 10,000 annually to offset the margin pressure from its AI investments," said Gil Luria, an analyst at D.A. Davidson, in an interview with Reuters.
The restructuring follows what insiders describe as a "builder ratio" strategy borrowed from Amazon, which prioritizes engineers over managers and seeks to flatten organizational hierarchies.
"It's like a horrible game of musical chairs," said V.L., a Microsoft employee laid off in May who spoke to KUOW on condition of anonymity. "There are fewer and fewer chairs for people in these industries."
Internal estimates suggest the July cuts could save Microsoft between $1.5 billion and $1.65 billion annually. Affected employees will receive 12 weeks of base pay plus two additional weeks for each year of service.
Andy Jassy, Amazon's chief executive, told employees this week that artificial intelligence agents would reduce the company's corporate workforce in coming years, according to Maginative.
As of now, Microsoft has not issued an official statement confirming the planned July layoffs.
| 2025-06-27T00:00:00 |
https://www.finalroundai.com/blog/microsoft-plans-july-layoffs-2025
|
[
{
"date": "2025/06/27",
"position": 73,
"query": "AI layoffs"
}
] |
|
The Impact of Artificial Intelligence on Job Markets - Kanwhizz's
|
The Impact of Artificial Intelligence on Job Markets
|
https://kanwhizz.in
|
[] |
In each of these sectors, tools like ChatGPT are playing a supporting role—enhancing productivity without entirely displacing human workers. Geographic ...
|
The Impact of Artificial Intelligence on Job Markets
6/28/2025 12:04:00 PM KanWhizz Team
The influence of artificial intelligence is being felt across nearly every sector, revolutionizing not only how businesses operate but also how people work. From automating mundane tasks to powering sophisticated data analysis, AI is transforming job markets around the globe. This technological wave, driven by innovations like ChatGPT, is creating both promising opportunities and significant challenges for employers and employees alike.
In this post, we’ll examine how artificial intelligence is reshaping the labor landscape—displacing some jobs, creating others, and prompting a shift in the skills needed for success in the future workforce.
AI as a Disruptor and a Creator
Artificial intelligence is a double-edged sword: while it has the power to make industries more efficient, it also threatens to replace a wide range of jobs. The evolution of AI tools—from automated checkouts to intelligent virtual assistants—has made routine tasks easier to manage but has also reduced the need for human involvement in certain areas.
Roles at Risk
According to projections from global research institutions, millions of jobs could be automated in the coming years. Tasks that involve repetition or predictable outcomes—such as those in manufacturing, data entry, and customer support—are most susceptible. With tools like ChatGPT, even knowledge-based roles like writing, tech support, and data processing are beginning to evolve, requiring fewer manual hours.
The workforce has been disrupted by technology before. Historical shifts, such as the industrial revolution and the rise of the internet, also caused widespread transformation in employment. What sets artificial intelligence apart is how quickly and broadly it can make an impact.
Emerging Opportunities
Despite fears of job loss, artificial intelligence is also fueling job growth in new and emerging areas. There’s increasing demand for AI specialists, machine learning engineers, and data analysts. Even beyond technical roles, new positions like AI ethicists, trainers, and content moderators have started to appear—particularly in support of generative AI systems like ChatGPT.
In many cases, AI doesn’t eliminate jobs entirely; it changes them. Professionals now spend less time on manual or repetitive work and more on tasks that require problem-solving, creativity, and human interaction. The job market is adapting rapidly, with new roles replacing old ones at an unprecedented pace.
The Skills Shift in Modern Job Markets
The rise of artificial intelligence has created a growing need for both hard and soft skills. As businesses adopt AI-driven tools, employees must learn how to use them effectively and ethically.
Technical and Human Skills in Balance
While technical know-how in programming, analytics, and AI tools is increasingly important, it’s not the only requirement. Human-centered skills like critical thinking, communication, empathy, and adaptability are essential in areas where AI can’t replace human judgment.
Employees who understand how to use AI tools like ChatGPT can gain a major advantage. For instance, marketers use it for content ideas, while coders rely on it for debugging. Knowing how to guide AI outputs, verify results, and apply them effectively is now a key part of workplace efficiency.
Rethinking Education and Training
Education systems must adjust to meet the needs of the AI-driven economy. This means shifting away from memorization and toward practical, interdisciplinary learning. Schools and training programs should teach students how to think critically, solve complex problems, and use AI tools responsibly.
Private and public sectors are beginning to invest heavily in upskilling. Online platforms now offer courses in artificial intelligence, data science, and prompt engineering. These programs aim to close the skill gap and prepare workers for roles that didn’t exist just a few years ago.
Sector-Specific and Global Impacts
The effects of artificial intelligence vary depending on the industry and region. Some sectors will see widespread transformation, while others will experience a more gradual shift.
Industry Changes
High Automation : Industries like logistics, retail, and manufacturing are adopting AI to streamline operations and reduce human labor.
Moderate Impact : Fields such as education, finance, and healthcare are integrating AI to support—not replace—professionals.
Minimal Disruption : Jobs requiring empathy, creativity, and strategic thinking—such as those in leadership or the arts—remain largely unaffected but may still benefit from AI assistance.
In each of these sectors, tools like ChatGPT are playing a supporting role—enhancing productivity without entirely displacing human workers.
Geographic Disparities
Advanced economies with strong technological infrastructure are adopting AI at a faster pace. This gives them an edge in developing high-paying AI-related jobs. Meanwhile, developing nations face challenges like limited access to digital tools and education. Still, by leveraging mobile technologies and cloud platforms, these regions can find opportunities to leapfrog traditional development paths and integrate AI-driven solutions into their economies.
Ethical Questions and Responsibilities
As artificial intelligence becomes more common in the workplace, ethical concerns are rising. Decisions made by AI—such as resume screening or automated hiring—raise questions about bias, fairness, and accountability. It's essential to ensure that AI systems do not reinforce existing inequalities in the job market.
Moreover, generative AI models like ChatGPT have sparked debate over content ownership, misinformation, and privacy. Companies must develop guidelines for responsible AI usage while governments establish frameworks to regulate and monitor these technologies.
The Road Ahead: How to Prepare
Rather than fear the rise of artificial intelligence, individuals, companies, and governments must work together to adapt. The goal should not be to resist change, but to prepare for it thoughtfully.
Action Steps:
For Professionals : Continuously upgrade your skills. Embrace tools like ChatGPT to improve productivity, but develop human-centric abilities AI can’t replicate.
For Employers : Implement AI responsibly. Provide training programs to help your teams transition into new roles.
For Policymakers : Support job transition programs and introduce policies that protect workers while encouraging innovation.
Conclusion
Artificial intelligence is reshaping global job markets faster than ever before. While some positions will disappear, many more will evolve—or be created entirely. The emergence of tools like ChatGPT illustrates just how quickly roles and workflows can shift.
Those who adapt, learn, and embrace the possibilities of working alongside AI will find themselves better prepared for a rapidly changing future. By fostering education, ensuring ethical deployment, and investing in people, we can harness AI’s potential to build a smarter, more inclusive workforce.
| 2025-06-27T00:00:00 |
https://kanwhizz.in/blog/the-impact-of-artificial-intelligence-on-job-markets
|
[
{
"date": "2025/06/27",
"position": 40,
"query": "ChatGPT employment impact"
}
] |
|
Artificial Intelligence in the Newsroom
|
Artificial Intelligence in the Newsroom: Emerging Challenges in Southeast Europe
|
https://seecheck.org
|
[
"See Check",
"Var Molongui_Authorship_Byline_Params",
"Byline_Prefix",
"Byline_Suffix",
"Byline_Separator",
"Byline_Last_Separator",
"Byline_Link_Title",
"View All Posts By",
"Byline_Link_Class",
"Byline_Dom_Tree"
] |
Artificial Intelligence in the Newsroom: Emerging Challenges in Southeast Europe · With Little Regulation, Journalists Take the Lead on AI · From Spam to Scam: ...
|
By: Maida Salkanović
In October last year, millions of viewers of TV Pink—a nationally licensed broadcaster in Serbia—had a chance to watch a four-minute video in which acclaimed film director Emir Kusturica appeared to speak about his ties to intelligence agencies, admitted to “mocking his own people,” and hinted at influencing a high school shooter who killed ten people in May 2023, all while praising TV Pink’s owner. The video, however, was generated by artificial intelligence (AI).
It was a retaliatory move by Željko Mitrović, the station’s owner, following an article in which Kusturica criticized Mitrović’s influence on Serbian society. It was not the first time TV Pink weaponized fakes against dissenters. The station, closely aligned with the ruling regime, had previously produced deepfakes of prominent opposition figures Marinika Tepić and Dragan Đilas. The videos were either not labeled as AI-generated or were labeled inadequately, prompting the Association of Journalists of Serbia (UNS) to publicly urge TV Pink to stop the use of manipulative content.
Across the border in Croatia, just two months later, presidential candidate Ivana Kekin played a fake audio recording at a press conference in which Prime Minister Andrej Plenković appeared to endorse her candidacy. Unlike TV Pink, Kekin used the stunt as a public service announcement, to highlight just how easily disinformation can be manufactured and circulated. Still, the incident raises an important question: how much harder will journalists’ jobs become in a world where truth can be synthetically distorted at scale?
Artificial intelligence has become the phrase of the moment. In journalism, it inspires a range of reactions, from panic over job security to opportunistic experimentation aimed at boosting clicks and profits. The field remains largely unregulated, and amid the chaos, journalistic communities across the region are scrambling to understand these technologies, and to shape the ethical and professional standards that must govern their use.
With Little Regulation, Journalists Take the Lead on AI
Across Southeast Europe, regulatory approaches to artificial intelligence remain uneven, but momentum is building. As an EU member state, Croatia is obliged to align with the EU’s regulatory framework and, in May 2025, the Ministry of Justice, Public Administration and Digital Transition formed a working group to begin drafting the country’s national AI law to implement the EU AI Act.
In Serbia, a national Strategy for the Development of Artificial Intelligence was adopted in early 2025, and the country’s Code of Journalists, updated in late 2024, now includes references to the ethical use of AI in media.
Bosnia and Herzegovina and Montenegro currently lack comprehensive, AI-specific legislation, but both are increasingly engaging with regional and international initiatives related to AI use in media and governance. In November 2024, Montenegro signed the Council of Europe Framework Convention on Artificial Intelligence, signaling its commitment to ensuring that AI development upholds human rights, democracy, and the rule of law.
Media professionals and civil society actors across the region are increasingly engaging with the challenges and possibilities of AI in journalism, working to establish ethical guidelines and shared standards. In May 2025, representatives of press councils from Southeast Europe and Turkey gathered in Ohrid, North Macedonia, where they signed the Regional Declaration of Press Councils from Southeast Europe and Turkey on the Ethical and Transparent Use of Artificial Intelligence in the Media.
One of the first research studies on the topic was published by BIRN Serbia, with support from the OSCE, also in May 2025. The findings reveal that while journalists in Serbia are increasingly experimenting with AI tools in their reporting, they do so without adequate training, clear guidelines, or a cohesive editorial strategy.
Tanja Maksić, the author of the study, told SEE Check that her research showed journalists are looking for some form of guidance when it comes to using AI, whether through regulation, editorial frameworks, or support from self-regulatory bodies.
“The big problem here in Serbia,” she said, “is that we have a fairly authoritarian government, closed off to dialogue and any kind of consultation. It’s genuinely difficult to reach any constructive agreement with them on anything.”
Maksić sees it as a positive sign that, even within a captured media system, journalists are exploring new tools, seeking out resources, and expressing concern about the ethical implications of AI. However, she notes that copyright, which is one of the main concerns about AI globally, was rarely mentioned by those surveyed.
Many journalists are also turning their attention to how AI is affecting their peers. Slađan Tomić, a journalist working across Bosnian-Herzegovinian and Serbian media, interviewed journalists in Bosnia to better understand how they are using AI in their daily work.
“I’m afraid that AI tools like ChatGPT could, in some newsrooms, replace journalists or part of the newsroom staff, and also contribute to journalists becoming lazy and relying on the machine instead of using their own knowledge, talent, and skills. That leads to intellectual stagnation, the death of creativity, and, more importantly, the erosion of journalistic excellence. Machines cannot replace human beings, and that needs to be made clear,” said Tomić.
From Spam to Scam: Slop and Synthetic Content Flood the Web
AI, says Maksić, also generates large amounts of so-called “slop”, a term journalist John Oliver recently described as “the newest iteration of spam.” This kind of content, Maksić explains, “has no informational value, no authorial signature, clogs up platforms, obstructs the flow of information, and at times, is genuinely difficult to distinguish from real reporting.”
In most cases, AI slop is profit-driven and sometimes used in outright scams. Deepfakes of journalists are sometimes exploited to promote these schemes, relying on the trust those individuals command. In Croatia, for instance, the image of RTL editor and TV presenter Mojmira Pastorčić, alongside that of President Zoran Milanović, was used in a fabricated promotion for a supposed “investment platform,” a scam designed to extract money from citizens.
Rašid Krupalija, Editor-in-Chief of the Bosnian fact-checking platform Raskrinkavanje, told SEE Check that scammers behind these types of schemes typically choose TV journalists whose faces are easily recognizable to the average social media user. According to Krupalija, this tactic helps lend credibility to the product being promoted.
“Unfortunately, the AI tools used to create these deepfake videos are getting more sophisticated. While it was relatively easy to spot a fake in the beginning, it’s becoming increasingly difficult now, as the videos look and sound quite authentic,” he said.
Famous Bosnian journalist Senad Hadžifejzović has been a frequent target of these scams. In an effort to inform the public that the advertisements were fraudulent, Hadžifejzović aired public service announcements on his channel Face TV, urging viewers not to purchase what he called “poison and scams.” “If you want to kill yourself, then buy it,” he said, referring to the warnings broadcast on the station, though the impact of those warnings remains unknown.
He told SEE Check that they reported the matter to the Prosecutor’s Office but never received a response. “It’s all up to the investigative bodies and prosecutors: we don’t know that they’ve done anything,” he said.
Some social media platforms now require AI-generated content to be labeled, but the approach remains deeply flawed. Meta, for example, mandates labeling only for “photorealistic video or realistic-sounding audio” created using AI, excluding images from this requirement. Krupalija warns that AI-generated content will inevitably become more difficult to detect, a development that works in favor of those using it for scams.
“It is the job of journalists to investigate and report on these types of fraud,” Krupalija told SEE Check, “but reporting alone won’t be enough without efforts to promote media and information literacy among readers. That is, building their resilience and skills to recognize scams and other harmful online content.”
Such misuse not only defrauds the public but can erode trust in the very journalists whose identities are being co-opted. Over time, this could contribute to a broader crisis of confidence in the media profession itself, especially in regions where trust in journalism is already precarious. A notable example is the Slovak case, where a deepfake audio clip mimicking journalist Monika Tódová was used to fabricate a conversation about election fraud. The aim was not only to discredit the political candidate, but also the journalist, showing how AI tools can be weaponized to undermine both individual credibility and public trust in journalism as an institution.
The phenomenon underscores a key vulnerability that extends beyond scams: the increasing difficulty in detecting AI-generated content poses a serious threat not just to consumer protection, but to the integrity of political reporting and journalism more broadly. As synthetic content becomes more convincing, the risk of its abuse in politically motivated smear campaigns, disinformation efforts, or fabricated interviews grows. In this landscape, identifying AI-generated content is not only a matter of countering fraud: it is critical to preserving editorial standards and democratic accountability.
AI as an Assistant: Supporting Journalists, Not Replacing Them
AI can undoubtedly be a valuable tool for journalists, enhancing both productivity and efficiency. This potential was recognized by the Journalists’ Association of Serbia (UNS), which partnered with the Center for Youth Activism Development (CROA) from Sarajevo, the Albanian Center for Quality Journalism (ACQJ) from Tirana, and the Media Center from Čaglavica to implement the project “How to Use Artificial Intelligence in Journalism.” The initiative resulted in a regional research study on the use of AI in media, as well as the creation of a regional network through which young people exchange experiences, tools, and training related to AI applications.
Aleksandra Ničić, one of the trainers in the project, said she was surprised by the level of knowledge demonstrated by young and aspiring journalists, which was higher than expected across the board. She also noted subtle regional differences in focus and concerns.
“My impression is that participants from Belgrade were primarily interested in the practical use of AI tools, those from Sarajevo were more focused on the privacy implications, participants from Čaglavica engaged most with the issues of AI hallucinations and deepfakes, while participants from Tirana were the most active in discussing the broader consequences of AI in journalism,” she said.
Ničić believes that there will be no serious negative consequences for the profession, as long as artificial intelligence is treated as an assistant that supports journalistic work, rather than a colleague doing all the work and creating problems through hallucinations.
“In other words, if we use AI tools to handle repetitive or mechanical tasks that consume our time, or to generate ideas that we then critically assess, I believe there won’t be negative consequences for our work,” she said.
Journalist Slađan Tomić agrees that AI can be a valuable tool when used as an assistant, but not as a content generator. He noted that there are already examples of media outlets using AI to produce content with no human oversight. In some cases, he added, journalists fail to even remove the AI’s built-in prompts, such as ChatGPT’s phrase: ‘If you want a shorter version, I can write one,’ which ends up appearing in the published article.
The use of AI appears to be more advanced in media outlets with lower editorial standards. In Serbia, Maksić observed that tabloids are among those furthest along in integrating AI tools into their content. These outlets frequently rely on text-to-speech and text summarization tools, often with poor results.
“It’s a mechanical voice, it gets the cases wrong, the diction is off, you can clearly tell,” she said. “But they’re using it consistently, and at some point, they’ll probably bring it to an acceptable level.”
According to Maksić, the combination of lower editorial standards and greater financial resources allows these outlets to experiment more freely with AI technologies than their peers in more rigorous journalistic environments.
“When you consider that these outlets already have a tendency to produce propaganda, disinformation, and fake news, and that they’ve been heavily engaged in smear campaigns against independent and critical voices in society,it becomes genuinely worrying,” said Maksić. “The issue now is that AI will enable them to further multiply low-quality content. They’ve already shown they’re willing to do it without AI, and now they’re gaining a powerful new tool to spread and accelerate these harmful practices.”
New Tech, Old Questions
AI continues to dominate conversations in Southeast Europe. New regulations are being drafted, media trainings are underway, and professional circles are actively debating how to approach this fast-evolving technology.
But this isn’t entirely new terrain, Maksić points.
“We started with printed newspapers, then came social media, and now AI. Over time, the profession has shown a certain resilience, and an ability to integrate new technologies into its workflows,” she said.
There are many new challenges ahead, but many journalists believe they can be overcome, so long as AI is approached with caution, responsibility, and a strong ethical foundation.
“A machine can be a tool and a support to the human, but nothing can replace human thought,” Tomić concludes. “Through irrational, unethical, and excessive use of AI in journalism, we risk permanently devaluing the profession.”
| 2025-06-27T00:00:00 |
2025/06/27
|
https://seecheck.org/index.php/2025/06/27/artificial-intelligence-in-the-newsroom-emerging-challenges-in-southeast-europe/
|
[
{
"date": "2025/06/27",
"position": 42,
"query": "artificial intelligence journalism"
}
] |
Webinar Report: Disinformation and AI – Towards Media ...
|
Webinar Report: Disinformation and AI – Towards Media Edukathon
|
https://www.ifj.org
|
[] |
Activities involved group testing of AI tools used in journalism, including text, audio, visual, and audiovisual content and a pannel discussion exploring the ...
|
The final session of the TADAM webinar series was held on 26 June and focused on "Disinformation and AI: Towards Media Edukathon". Activities involved group testing of AI tools used in journalism, including text, audio, visual, and audiovisual content and a pannel discussion to explore challenges facing journalists.
The event was designed to promote critical thinking and practical skills through expert-led insights and exchanges of good practices.
Activities involved group testing of AI tools used in journalism, including text, audio, visual, and audiovisual content and a panel discussion exploring the challenges facing journalists.
The panel discussion featured a diverse group of experts:
● Jon Schleuss, President of NewsGuild, USA and IFJ member
● Mihajlo Lahtov, Media and Information Literacy Specialist, North Macedonia
● Katerina Topalova, Journalist at MRTV, North Macedonia
● Maarit Jaakkola, Co-Director of Nordicom, Sweden
Panelists addressed AI’s dual impact on journalism - enhancing efficiency and innovation while also raising concerns around disinformation, algorithmic bias, and declining public trust. The conversation underscored the need for ethical standards, transparency, and continuous education to navigate these challenges responsibly.
As a next step, Jon Schleuss suggested to focus on AI journalism and ethics based on the IFJ code of ethics
The IFJ has published recommendations on the use of AI insisting that AI must serve journalism, not replace it, and calling for human oversight, fair compensation, and union-led negotiations with tech firms.
More on Tadam here.
WATCH the webinar
| 2025-06-27T00:00:00 |
https://www.ifj.org/media-centre/news/detail/category/tadam/article/webinar-report-disinformation-and-ai-towards-media-edukathon
|
[
{
"date": "2025/06/27",
"position": 55,
"query": "artificial intelligence journalism"
}
] |
|
At Hugging Face, a former journalist helps make AI more ...
|
At Hugging Face, a former journalist helps make AI more accessible
|
https://blog.mozilla.org
|
[
"Kristina Bravo",
".Wp-Block-Co-Authors-Plus-Coauthors.Is-Layout-Flow",
"Class",
"Wp-Block-Co-Authors-Plus",
"Display Inline",
".Wp-Block-Co-Authors-Plus-Avatar",
"Where Img",
"Height Auto Max-Width",
"Vertical-Align Bottom .Wp-Block-Co-Authors-Plus-Coauthors.Is-Layout-Flow .Wp-Block-Co-Authors-Plus-Avatar",
"Vertical-Align Middle .Wp-Block-Co-Authors-Plus-Avatar Is .Alignleft .Alignright"
] |
That's why I moved from journalism to AI. I could feel something shifting, not just in media, but everywhere, and I wanted to help make this foundational ...
|
Here at Mozilla, we are the first to admit the internet isn’t perfect, but we know the internet is pretty darn magical. The internet opens up doors and opportunities, allows for human connection, and lets everyone find where they belong — their corners of the internet. We all have an internet story worth sharing. In My Corner Of The Internet, we talk with people about the online spaces they can’t get enough of, the sites and forums that shaped them, and how they would design their own corner of the web.
We caught up with Florent Daudens, who led digital innovation in Canadian newsrooms before becoming press lead at Hugging Face, the open-source AI community. He talks about shaping his feeds to feel more like home, his move from journalism to AI, and why the best way to understand new tech is to start making things.
What is your favorite corner of the internet?
That rare, quiet part of the internet that actually makes you smarter without making you feel behind. For me, it’s a mix.
LinkedIn surprised me. I used to think of it as stiff and self-promotional, but it’s become where I exchange ideas with people wrestling with the same big questions: What’s AI doing to journalism? What’s worth building?
[X] is still very relevant for everything related to AI news. It’s where I get pulled into weird, fascinating rabbit holes. Someone posts a half-broken agent demo or a wild paper, and suddenly I have 12 tabs open. It’s chaotic in the best way.
And Hugging Face of course, to keep pace with AI releases!
I think what changed everything was narrowing my feeds. Once I stopped trying to follow everything and leaned into what really matters to me – AI, openness, news and creative industries – it all started to feel like home.
What is an internet deep dive that you can’t wait to jump back into?
My YouTube recommendations read like a personality test I didn’t mean to take:
obsessive AI build logs. I’m a sucker for “How I made this with that” videos to learn new skills related to AI.
Mandarin tutorials (six years in and still chasing tones…)
vintage French science shows that I now rewatch with my kid — equal parts nostalgia and wonder.
What is the one tab you always regret closing?
That post. You know the one — right under the other one. You meant to open it in a new tab, but you didn’t. And then the feed refreshed and it’s gone forever. A digital ghost.
What can you not stop talking about on the internet right now?
AI-generated videos that are totally unhinged and strangely beautiful. Like:
What was the first online community you engaged with?
CaraMail, back in France in the late ’90s. It was messy, anonymous, and kind of magical. That early feeling of connecting with people across borders, in French, about anything, was completely new. It opened up so many possibilities and shaped how I saw connection and community, and actually played a role in me moving to Montréal at 18.
If you could create your own corner of the internet, what would it look like?
Actually, I’m lucky; I am building it.
That’s why I moved from journalism to AI. I could feel something shifting, not just in media, but everywhere, and I wanted to help make this foundational technology open, accessible, and collaborative. As a former data journalist, I saw how open-source wasn’t just about sharing code. It was a force multiplier for learning, creativity, and community. With AI, that effect is even stronger.
So yeah, without a doubt: Hugging Face.
What articles and/or videos are you waiting to read/watch right now?
The LangGraph course on DeepLearning.ai on long-term agentic memory (it’s niche, I know)
And a new series on MCP, which my colleague Ben kicked off, because I genuinely think this protocol could unlock a whole new layer of what’s possible on the open web.
What’s the biggest opportunity you see right now at the intersection of AI, open-source and public-interest media?
Small experiments, bold new tools, but most of all, building.
With AI-assisted coding, I think the barrier to entry is lower than ever. You can go from idea to prototype really quickly, even without knowing how to code, but just by starting with your words and ideas. And that’s a game-changer.
Take AI agents: the only way to really understand their potential and their limits is to try building one yourself. That forces you into the mindset that matters most: empathy. Start with what people actually need, then design around that.
Open-source supercharges all of this. It lets you remix, test, and share. It makes scaling faster. And maybe most importantly, it’s the best way to stay independent from tech companies. You’re not just using tools; you’re shaping them.
Florent Daudens is the press lead at Hugging Face, the open-source AI community. A longtime advocate for the intersection of AI and journalism, he led the digital transformation of major Canadian media such as Le Devoir and Radio-Canada. He has overseen the development of AI-powered tools, helped shape ethical guidelines for AI, and trains newsrooms on its use. He also lectures on AI and journalism at Université de Montréal and ESJ Lille.
| 2025-06-27T00:00:00 |
https://blog.mozilla.org/en/internet-culture/interviews/hugging-face-florent-daudens/
|
[
{
"date": "2025/06/27",
"position": 67,
"query": "artificial intelligence journalism"
}
] |
|
TWU Tech Newsletter: Fighting Back Against an AI Giveaway
|
TWU Tech Newsletter: Fighting Back Against an AI Giveaway – Transport Workers Union
|
https://www.twu.org
|
[] |
In letters to both the House and the Senate, TWU joined labor unions across the country to argue that a 10-year ban on state-level AI regulations will “leave ...
|
This is the monthly edition of the Transport Workers Union’s Transportation Technology Newsletter. We aim to inform and educate our members, the labor movement, the public and policymakers about developments in transportation technology – and what the TWU is doing to ensure that new technology doesn’t undermine safety or harm the livelihoods of hard-working blue-collar workers. For suggestions and questions, please email [email protected] or [email protected].
ITEM OF THE MONTH
NO PREEMPTION: The TWU is taking aim at a Big Tech giveaway in the pending House and Senate Republican budget reconciliation bill that would impose a 10-year ban on states from protecting workers from the harms of artificial intelligence.
In letters to both the House and the Senate, TWU joined labor unions across the country to argue that a 10-year ban on state-level AI regulations will “leave everyone vulnerable to wide-ranging abuses stemming from irresponsible AI.” If enacted, this measure would end any state-level attempts to keep dangerous AI-enabled autonomous vehicles off their roads.
“This is yet another attempt by Big Tech to unleash unproven and dangerous autonomous vehicles on our roads without any safety oversight or accountability,” said TWU International President John Samuelsen. “During a time when the federal government isn’t doing its job to properly regulate AI deployments, it is reckless to shut down state attempts to protect residents from the improper or dangerous use of AI in transportation and across the economy and public agencies.”
Republicans and Democrats – both state legislators and attorneys general across the political spectrum – are urging Congress to strike this ban on state AI regulations. “State legislatures—working in a bipartisan fashion—have taken intentional and thoughtful action to build guardrails while making efforts not to stymie technological innovation. A federally imposed moratorium would not only paralyze this innovation but would also leave Americans exposed to emerging risks associated with the new technology,” state legislators wrote in a letter to Congress.
WHAT ELSE IS COOKING
CALIFORNIA CALAMITY: When major protests erupted in Los Angeles earlier this month, Waymos couldn’t get out of the way. Viral images of Waymos engulfed in flames spread across the world and were a reminder that driverless vehicles can become “sitting ducks” as NBC News reported. The unattended Waymos left in the middle of areas that were under a city-imposed curfew are the latest example of driverless technology not being ready for complicated driving environments. Robotaxis have previously driven through active crime scenes and blocked first responders.
“Driverless cars became sitting ducks in a dangerous environment – another example of why having human operators is essential,” said TWU International Administrative Vice President Curtis Tate.
Waymo service in San Francisco was also suspended during recent protests. But while transit options within the affected areas were up and running within hours of the protests subsiding, with TWU members providing bus and rail service throughout the city, Waymo users posted to social media screenshots of Waymos avoiding huge swaths of the city days after the protests ended.
“Ultimately, Big Tech sees driverless cars as replacing rideshare drivers first before moving on to public transit systems,” Tate said. “But what we’ve seen in Los Angeles and San Francisco should be a wake up call for elected officials and transit agencies – the cars are easy targets for violence in areas where they should be removed and the tech companies themselves don’t trust their tech enough to restart rides while transit workers are able to get cities up and running again within hours of civil unrest subsiding.”
Beyond the protests, driverless cars are also causing everyday problems. In Santa Monica, residents became fed up with Waymos hogging parking spots while charging and incessant beeping from cars as they constantly moved around parking lots. Residents took matters into their own hands, blocking a parking lot with cones and cars to keep Waymos away. In response, Waymo called the police, according to KTLA. The Los Angeles times has more.
The issues haven’t stopped Waymo from continuing to expand. The company announced later in June that rides are now available over a larger swath of San Francisco, Los Angeles, and Silicon Valley.
BIG TRUCK WANTS MORE: The trucking lobby is continuing to pressure federal regulators to eliminate restrictions on driverless trucks that are intended to promote safety, Freight Waves reports. In May, the Autonomous Vehicle Industry Association wrote to DOT urging FMCSA to update hours-of-service and inspection requirements that currently require action by a human – and are additionally continuing to fight a ruling on roadside service devices that requires a human to place safety triangles behind a disabled truck on the side of the road. The TWU successfully fought to keep the current requirements in place and the FMCSA ruled against the autonomous trucking industry on the matter in January.
IN THE NEWS: TWU International President John Samuelsen was quoted in a recent New York Times story on the expansion of autonomous trucking, noting that a fast proliferation is “potentially dangerous from a safety perspective” but the industry is still moving quickly “like a freaking Corvette, doing zero to 60.”
DRIVERLESS CARS IN MICHIGAN: Ann Arbor-based May Mobility announced that its autonomous Toyota Sienna minivans will be available for booking on Uber by the end of 2025, starting in Texas. Currently, May Mobility operates on a smaller scale in markets like its home in Ann Arbor, Michigan, where TWU members at Local 171 currently provide transit service. The company also has its sites on autonomous buses, Axios reports, seeking to deploy autonomous 30 person minibuses by 2026.
“We will stay vigilant to ensure that TWU Bus Operators and Mechanics in cities like Ann Arbor aren’t pushed out in favor of unproven tech,” Tate said. “We’ve already won contract language giving us veto power over autonomous buses in Ohio, and we intend to push for similar contract language around the country.”
TESLA TURMOIL: Tesla robotaxis are now on the road in Austin, and within a day of launching a series of viral videos showed the autonomous cars driving erratically – and spurring the federal government to investigate. In one instance, a Tesla robotaxi breaked hard in the middle of traffic and in a vehicle drove down the wrong side of the road in another video. The launch comes as local officials in Texas worry about the proliferation of robotaxis in a state where local municipalities are prohibited by the state from imposing rules on their usage.
“It’s been very frustrating on our end from a safety standpoint,” Austin Police Lieutenant William White told the Dallas Morning News. “If these machines are learning, they’re not learning at a quick enough pace for sure.”
AIR LOS ANGELES: When athletes from around the world converge on Los Angeles for the 2028 Summer Olympics and Paralympics, Archer Aviation will serve as the official airtaxi provider of LA28, in addition to showcasing its service in conjunction with the 2026 FIFA World Cup and 2027 Super Bowl, both in Los Angeles.
LA28 announced that through its partnership with Archer, they will “look to integrate Archer’s Midnight eVTOL aircraft across the LA28 Games in a variety of ways, such as transporting VIPs, fans, and stakeholders, while electrifying vertiport take-off-and-landing hubs for key venues and providing support for emergency services and security.” Archer plans to serve the Olympics and Paralympics from several so-called “vertiports” located at several adjacent locations.
So-called eVTOL, or electric vertical take-off and landing aircraft, remains an unproven technology that takes off and lands like a helicopter and flies like a plane. The Archer version is an all-electric 4-seater that has yet to receive all certifications from the Federal Aviation Administration. Some eVTOL developers contemplate running airtaxi service without a pilot onboard with airtaxi development plans targeting cities across the country including New York City, Miami and San Francisco.
WHAT WE’RE READING:
United Nations Warns Driverless Cars Could Be Terrorist Targets. The Times UK.
Rail Track Inspections by AI-Enabled Tech? Trains.
Google Gemini AI Chatbot in Volvo Cars. The Verge.
| 2025-06-27T00:00:00 |
https://www.twu.org/twu-tech-newsletter-fighting-back-against-an-ai-giveaway/
|
[
{
"date": "2025/06/27",
"position": 24,
"query": "artificial intelligence labor union"
}
] |
|
Will AI Replace or Transform Your Job? - CV Maker
|
Will AI Replace or Transform Your Job?
|
https://www.cvmaker.uk
|
[] |
According to the World Economic Forum's 2025 Future of Jobs Report, by 2030, nearly 40% of current skills will be transformed or outdated. To stay relevant in ...
|
As the workplace continues to evolve, many are wondering whether AI will transform their jobs. The United Kingdom (UK), now the third-largest artificial intelligence (AI) market, has become a vibrant hub for global talent and leading companies like Google DeepMind, ARM, and Wayve.
With AI already revolutionising industries like finance, healthcare, manufacturing, and the creative sectors, it’s time to explore how AI transforms jobs and what strategies can help individuals stay ahead in this rapidly changing landscape. While AI’s rise presents both challenges and opportunities, it’s clear that adapting to these changes will be essential for thriving in the future workplace.
In this article, we cover:
How is AI transforming the workplace?
How will AI reshape your job?
Tips for incorporating AI into your work.
Practical examples of AI in the workplace.
Boost your job application with CVMaker, the go-to platform for job seekers, offering professional CV templates that can be tailored to your career goals.
The best CV builder Effortlessly create a professional CV
Easy to use on any device
Integrated spelling and grammar check
Customisable job-specific CV examples Start now ArrowInlineEnd
How is AI transforming the workplace?
According to the 2025 Future of Jobs Report by the World Economic Forum, the job market is undergoing significant changes. AI is already leaving its mark across various industries, taking over tasks that humans once handled. In fact, here are a few areas where AI is already making an impact and transforming jobs or industries:
Administrative roles
AI chatbots and automation tools are increasingly taking on responsibilities traditionally managed by humans in administrative roles. Tasks like data entry, scheduling, and basic customer service are now being efficiently handled by these technologies, transforming the way organisations manage their workflows.
For example, virtual assistants like Google Assistant can manage calendars, schedule appointments, and send reminders without any human intervention. Automated email tools, such as AI-powered inbox assistants, can respond to routine emails, prioritise messages, and even sort them into relevant folders. Similarly, invoice processing has become more streamlined with tools like SAP Concur, which can scan, process, and approve invoices, reducing the time required for manual handling.
Retail jobs
AI is revolutionising the retail industry by taking over many tasks traditionally performed by human staff. Automated self-checkout systems, like those found in grocery chains and big-box retailers, allow customers to scan and pay for items independently, reducing the need for cashiers. AI-powered inventory management systems, such as those used by Amazon, track stock levels in real-time, predict demand, and even place restocking orders automatically, ensuring shelves are consistently stocked. Additionally, in-store robotic assistants, like Lowe's "LoweBot," help customers locate items while providing basic product information. These robots also assist with inventory checks, making retail operations more efficient.
Beyond the store, AI is reshaping the way customers engage with brands through personalised recommendations. Online retailers like Amazon and fashion platforms like Zalando use AI algorithms to analyse user preferences and browsing history, delivering tailored product suggestions that increase customer satisfaction and boost sales.
Manufacturing and assembly
AI-powered robots are transforming the industrial and manufacturing sectors by taking over repetitive and time-consuming tasks that were traditionally carried out by human workers. From assembly line operations to quality control and packaging, these robots are making production processes faster, more accurate, and cost-effective.
For example, automotive manufacturers like Tesla and Toyota utilise robotic arms to assemble cars with precision and consistency that humans would struggle to achieve over long periods. Similarly, in electronics manufacturing, robots handle the delicate task of soldering tiny components onto circuit boards, ensuring high levels of accuracy and reliability.
Transport and delivery
Autonomous vehicles and drones are revolutionising the logistics, delivery, and transportation industries by integrating AI systems that handle tasks like routing, driving, and even delivery operations without human input. Self-driving trucks are already being used for long-haul freight transport. Companies like Waymo and Tesla are testing autonomous semi-trucks that can travel long distances, reducing the reliance on human drivers and cutting transportation costs. These trucks use AI to detect obstacles, optimise routes, and adjust to road conditions in real-time, ensuring more efficient and safer deliveries.
Marketing
AI is transforming marketing by automating processes, making campaigns more precise, and saving time and resources. One impactful innovation is the use of AI tools for customer segmentation. These tools analyse data on customer demographics, purchase history, and online behaviour to group audiences into distinct segments. For example, an e-commerce platform might use AI to identify a group of customers who frequently purchase fitness products and another segment interested in home decor, allowing businesses to create tailored marketing strategies for each group.
Personalised email campaigns powered by AI take segmentation to the next level. Platforms like Mailchimp and HubSpot employ machine learning algorithms to deliver customised email content based on individual customer preferences and purchase history. For example, AI can predict which product recommendations will most likely engage a particular customer, increasing the chances of conversion. Similarly, AI enhances programmatic ad buying by automating the process of bidding on digital ad spaces in real-time. Platforms like Google Ads use AI to evaluate millions of data points, ensuring ads reach the right audience at the right moment, optimising both cost and effectiveness.
Data analysis
AI is rapidly transforming data-heavy roles by automating tasks like data collection, processing, and reporting, allowing professionals to focus on higher-value activities. For example, in the financial sector, AI tools such as Bloomberg Terminal and Kensho analyse market trends, process transaction data, and generate detailed reports in minutes, tasks that previously required hours of manual effort. Similarly, in healthcare, AI platforms like IBM Watson Health streamline the analysis of patient records and medical imaging, uncovering patterns that help diagnose diseases or predict treatment outcomes with remarkable speed and accuracy. Marketing teams also benefit from AI-driven tools like Google Analytics and Tableau, which collect web traffic data, visualise metrics, and identify customer behaviour trends–all with minimal human intervention.
Currently job hunting? Need a hand with improving your CV or cover letter? Explore these helpful resources to elevate your career:
Tips for writing a good CV.
A guide to creating a good cover letter.
How will AI reshape your job?
While AI may replace specific tasks in your job, it’s also enhancing others by supporting your unique capabilities. Instead of replacing roles, AI can assist with tasks like data analysis, allowing you to focus on decision-making, creativity, and strategic thinking. As we explore various industries in the UK, it becomes clear that AI is not just about automation but collaboration, where human expertise and AI work together to drive better results.
Consumer markets
In retail and e-commerce, AI helps personalise shopping experiences, predict consumer behaviour, and manage inventory. However, human professionals are still needed to interpret data, develop creative marketing strategies, and build customer relationships. While AI can recommend products, human-driven customer service remains essential for addressing complex queries and building trust.
Financial services
AI in finance can streamline tasks like fraud detection, risk assessment, and investment predictions by quickly processing vast amounts of data. Yet, financial advisors, analysts, and other professionals are still essential for interpreting complex situations, providing personalised advice, and managing client relationships. For example, while AI might automate portfolio management, human financial advisors are necessary for tailoring investment strategies for high-net-worth individuals.
Medical and healthcare services
In healthcare, AI has the potential to revolutionise diagnostics, treatment plans, and patient care by analysing medical data and images more efficiently than ever before. However, doctors, nurses, and healthcare providers are indispensable for interpreting the results, making nuanced decisions, and offering compassionate care. AI might assist in identifying cancerous cells in imaging scans, but a doctor’s experience is essential in creating a final diagnosis and discussing treatment options with the patient.
Industrial products
AI optimises supply chains, enhances manufacturing processes, and monitors equipment for predictive maintenance. However, human engineers and technicians are still needed for complex troubleshooting, design innovation, and system optimisation. While AI can predict potential failures by analysing factory machine data, humans are still required to repair and modify machines requiring hands-on expertise.
Technology, media, and telecommunications
AI is already used for content generation, customer support, and network management in the tech and media industries. While these processes will continue improving with AI, human professionals will be needed for strategic decision-making, creative work, and ethical standards. AI can generate written articles or news reports, but human journalists are still required to ensure accuracy, add context, and maintain editorial standards.
In the future, the workforce will collaborate with AI, using its capabilities to enhance performance while relying on human insight and expertise for decision-making, creativity, and emotional intelligence. Rather than replacing jobs, AI is reshaping them, allowing you to focus on higher-value tasks that leverage your unique skills. For more guidance on adapting to the job market, refer to our AI CV Writing Guide.
Are you looking for jobs in any of these fields? Explore these CV examples to help get you started:
Tips for incorporating AI into your work
If you're considering a career change or looking to integrate AI into your current job, there are several steps you can take to stay ahead of the curve and embrace the future of work:
1. Invest in learning
Upskill by taking online courses, certifications, or degree programs in AI and machine learning. Key areas to explore include data science, programming languages (like Python or R), and AI ethics. According to the WEF, technological skills, especially AI and big data, will become increasingly vital in the next five years.
2. Understand the basics
Even if you don’t plan to become an AI expert, understanding how AI works and its potential applications in your field is essential. Many industries seek employees to bridge the gap between technology and business. Identify areas within your role or organisation where you can integrate AI into existing processes and tools to help employees focus on more strategic tasks.
Discover how to embrace functional change with AI by identifying areas where you can integrate the technology into your current processes and tools.
3. Seek out AI-focused roles
Explore career opportunities requiring AI expertise and look for ways to incorporate AI into your current job. AI applications are expanding across industries, and businesses are eager to stay competitive. Consider platforms like AI Jobs for AI-specific roles and networking opportunities.
4. Network and collaborate
Attend AI and tech-related forums, conferences, and communities to stay informed about the latest trends. Networking with professionals in the AI field can provide valuable insights and open doors to new job opportunities. Explore AI-related events on platforms like Eventbrite to connect with others in the field.
Now that we've explored jobs at risk of being replaced and those being transformed, how can you embrace AI rather than fear it? According to the World Economic Forum’s 2025 Future of Jobs Report, by 2030, nearly 40% of current skills will be transformed or outdated. To stay relevant in your role, you need to adapt to these technological shifts and explore how AI can improve your work.
Practical examples of AI in the workplace
Automate routine tasks using AI tools, like project management software or CRM systems. These tools can handle scheduling, client communication, and data analysis, giving you more time for strategic work.
Leverage AI to process large datasets quickly and make data-driven decisions. Whether in marketing, finance, or operations, AI insights can improve decision-making and business outcomes.
Use AI to enhance creativity and innovation in roles like design, writing, or marketing. Tools can speed up tasks like image editing, proofreading, or generating ideas, leaving you free to focus on aspects requiring human intuition and creativity.
Develop soft skills like empathy, negotiation, and leadership. These uniquely human qualities will remain in high demand as AI continues to evolve and automate technical tasks.
The World Economic Forum’s Centre for the New Economy and Society collaborates with businesses, academia, and governments to help people globally prepare for the future economy, through initiatives like the Jobs Initiative and Reskilling Revolution platforms.
Key takeaways
AI’s impact on industries: AI is not just a trend; it’s the dawn of a new era that will reshape every industry. While some sectors will race ahead, others may take a bit longer to adapt, but one thing is certain: change is coming, and it’s happening fast. The world of work is transforming right before our eyes, and the ability to adapt and stay flexible will be your secret weapon to not just survive but thrive in this AI-driven future.
Job evolution: Yes, some jobs will be replaced by automation. But here’s the silver lining as many roles will evolve, and new, exciting opportunities will emerge. It’s time to embrace the change with open arms, to upskill, and to take ownership of your career’s evolution. The jobs of tomorrow are waiting for you, and with the right mindset, you can be at the forefront of this revolution.
Lifelong learning: To stay ahead in this fast-changing world, adopt a mindset of continuous learning. Stay curious, be proactive in learning new skills, and keep seeking opportunities for growth. The key to futureproofing your career lies in a commitment to never stop growing because the future belongs to the curious, the adaptable, and the willing.
Government and business roles: The UK government is already investing in tech skills, particularly AI and data science, recognising that the future workforce needs these essential tools to succeed. Meanwhile, businesses are stepping up, offering upskilling programmes designed to keep their teams competitive and equipped for the AI-driven world ahead.
Staying adaptable: In the AI-driven future, adaptability is everything. Embrace the culture of continuous learning, stay flexible, and welcome technological advancements. By doing so, you’ll not only maintain career relevance, you’ll set yourself up for success in a world that is constantly evolving.
Next steps?
Whether you're seeking a job in AI or want to highlight your AI skills on a CV, having a good CV and cover letter is essential. Our intuitive AI CV Maker and Cover Letter Builder, along with over 170 CV examples, allows you to easily tailor your documents to your needs. Alternatively, you can take advantage of our CV Writing Services, where one of our experts can help you craft the perfect application.
Improve your CV with AI Try Our Builder
FAQs
What are the top fastest-growing jobs in the UK?
The fastest-growing jobs for 2025 in the UK reflect advances in technology, healthcare, and sustainability. Roles such as Artificial Intelligence/Machine Learning (AI/ML) Engineers are in high demand due to AI's transformative impact across industries, with an 86% increase in job postings.
Other in-demand jobs include Cybersecurity Specialists, Software Developers, Project Managers, Healthcare Professionals, and Environmental Officers. Additionally, roles related to Data Governance and School Teachers are seeing significant growth due to increasing educational and recruitment needs.
Will IT jobs be replaced by AI?
AI is set to reshape, not replace, IT jobs. While routine tasks like basic coding and system monitoring may be automated, new roles will emerge, including positions for AI/ML engineers, data scientists, cybersecurity specialists, and cloud architects. Human oversight remains crucial, as AI requires creativity, ethical decision-making, and supervision. To stay competitive, IT professionals must upskill in areas like AI, data analysis, cybersecurity, and cloud computing. Ultimately, the future of IT is about transformation, offering new opportunities for those who adapt.
What is the best AI-proof job?
While it's impossible to predict precisely how AI will evolve in the next decade, experts agree that AI will continue to advance rapidly. The risk of under-preparing for these changes far outweighs any potential benefits of over-preparing. Even if AI’s progress slows, leveraging its current capabilities, investing in relevant technologies, and building a skilled workforce will still provide significant advantages. The key to staying "AI-proof" is focusing on roles that require human skills AI cannot replicate, such as creativity, emotional intelligence, complex problem-solving, and ethical decision-making, while embracing AI to enhance productivity and innovation.
| 2025-06-27T00:00:00 |
https://www.cvmaker.uk/blog/career/what-jobs-will-ai-replace
|
[
{
"date": "2025/06/27",
"position": 96,
"query": "future of work AI"
}
] |
|
Robotics & Automation: An Ultimate Guide
|
ROBOTICS & AUTOMATION: AN ULTIMATE GUIDE
|
https://www.uti.edu
|
[] |
Robotics and Automation Training & Job Outlook. Training. Technical ... Labor Statistics' May 2023 Occupational Employment and Wages. Entry-level ...
|
Robotics and automation technicians are responsible for maintenance, repairs, diagnostics, troubleshooting and innovation in automation technology. It is an important industry that improves productivity in various fields.
If you're interested in cutting-edge manufacturing processes, you should learn everything you can about them. Robotics and automation technology is used in industries such as electronics, healthcare, manufacturing, food and beverage, agriculture and military.
Universal Technical Institute (UTI) offers a Robotics & Automation Technician training programfor aspiring technicians to learn using industry-standard equipment and develop the skills they need in the field. Graduates of UTI's program can use their knowledge and training to pursue entry-level positions in the industry! 1
Keep reading to learn more. In this blog post, we'll look at the robotics and automation trade and what it's like to become a technician in the industry.
Key Points:
- Robotics and automation technology is crucial in enhancing productivity across various industries, including electronics, healthcare, manufacturing, food and beverage, agriculture and military applications. This technology focuses on performing tasks with minimal human input, improving efficiency and reducing errors.
- Universal Technical Institute (UTI) offers a Robotics & Automation Technician program designed to equip students with the necessary skills to pursue entry-level positions in the field after graduation. The program includes hands-on training on industry-grade equipment and in-depth robotics and automation courses taught by experienced professionals.
- Robotics and automation technicians are responsible for maintenance, repairs, diagnostics, troubleshooting and innovation within the manufacturing industry and other sectors. Technical training is essential for developing the skills required to create, maintain and operate robotic solutions safely and securely.
- UTI's program covers key aspects of robotics and automation, including electrical circuitry and programming industrial robotic systems. Students benefit from both classroom and online instruction, as well as hands-on application in labs. UTI also provides career services to help graduates prepare for job opportunities.
What Is Robotics and Automation?
Robotics is an interdisciplinary branch of computer science and engineering that focuses on the integration and operation of robots. Robots are machines that can automatically perform a complex series of actions. Automation is used in manufacturing and warehousing, including robotic manufacturing, to perform production processes with minimal human input.
Robotics vs. automation
Automation uses technology, programming and other processes to get machines to perform tasks with minimal need for human input. Robotics is one of the ways automation is used. While automation focuses on how to get machines to create certain outcomes, the goal of robotics is to design robots to perform specific tasks without the need for human mediation.
Benefits of Robotics Automation
Robots in automation are intended to precisely perform tasks that are considered dull, dirty and dangerous. That’s because the algorithms it employs ensure consistency and reduce the possibility of error. Robots also have no biological limits and can operate for long periods of time, making them more efficient at their intended functions. Because robotic machines can be built to be highly durable and heavy-duty, they can handle more difficult and time-consuming tasks. They eliminate the potential hazards of tasks previously assigned to humans, such as lifting heavy loads, transporting noxious chemicals and many others.
Uses for Robotics and Automation
Industrial automation and robotics have many potential applications. Several industries rely on robotics and automation to keep their operations up to modern performance standards, including:
Electronics: Robotic arms are used to test, manufacture and fabricate printed circuit boards (PCBs), as well as for inspection and assembly of components.
Robotic arms are used to test, manufacture and fabricate printed circuit boards (PCBs), as well as for inspection and assembly of components. Healthcare: Industrial robots are used in sanitation, surgery and even for packaging medical supplies.
Industrial robots are used in sanitation, surgery and even for packaging medical supplies. Manufacturing: Robotic arms, gantry robotics and welding robots are used to create various technologies and their components.
Robotic arms, gantry robotics and welding robots are used to create various technologies and their components. Food and beverage: Robotic arms are used to help prepare and package food cleanly and safely.
Robotic arms are used to help prepare and package food cleanly and safely. Agriculture: Automation is used to assist with precise and repetitive tasks. Smart sensors collect data about current conditions and adjust processes accordingly.
What Are Robotics & Automation Technicians?
Robotics and automation technicians may also be referred to as robotics technicians or automation technicians. They typically work in the manufacturing industry or the manufacturing sector of other industries like those listed above. Some of their primary duties and responsibilities include automation technology maintenance, repairs, diagnostics, troubleshooting and innovation.
Robotics and Automation Training & Job Outlook
Training
Technical training can be beneficial for those looking to develop essential technical skills for the robotics and automation industries. With technological advancements, robotic solutions are increasingly finding their way into everyday processes at home and work. Aspiring technicians can learn how to create, maintain and operate these solutions safely and securely by enrolling in robotics and automation courses.
Universal Technical Institute offers robotics and automation technician training at campuses nationwide.1We provide comprehensive technical training in key aspects of robotics and automation through this program, with the main focus being on understanding automation processes. Our Robotics & Automation Technician program's courses cover the fundamentals of electrical circuitry, programming industrial robotic systems and more.
Along with classroom and online instruction, UTI’s robotics and automation students gain valuable hands-on training in our labs.
UTI also has a Career Services team that can help grads learn about and prepare for job opportunities. Alumni can use these resources for many years after graduation, even decades!
Careers in robotics and automation
According to the Bureau of Labor Statistics (BLS), the median annual salary for robotics and automation technicians in the United States was $65,080 in May 2023.59 This means half earned more and half earned less. Keep in mind that salary depends on several factors, including experience, employer, demand and cost of living in the area.
Most of our grads start out working as technicians or in other entry-level roles. As with any industry, over time, they may be able to advance in their career with experience and hard work. Some entry-level and advanced roles could include:77
Entry level
Robotics and automation technician
Control systems technician
Maintenance technician
Advanced
Instrumentation and controls technician
Service technician III
Senior maintenance technician
Process control technician
Product tech specialist
Test engineering technician
If this is a work environment that interests you, it could be a good career path to pursue.
Working conditions
Robotics and automation technicians often work alone or in small groups. If the machines they service are in use 24/7, they may be required to be on call around the clock, and they may work night and weekend shifts.
Because they’re frequently employed in manufacturing, robotics technicians and automation technicians often work in noisy environments. Some may be required to travel long distances to service technology on-site. This sensitive technology also often necessitates privacy and protection, resulting in most of their work being done indoors.
UTI Robotics and Automation Training
Training for a career in robotics and automation could be a great choice if you’re interested in learning more about these manufacturing processes.
At UTI, you can learn how to maintain and repair robotics systems from experienced automation professionals and develop key skills that could help you pursue a robotics and automation career after graduation.1
Request more informationto learn how UTI's robotics program can help you pursue your career goals if you want to work in this industry! Apply today to see where robotics and automation training can lead you.
| 2025-06-27T00:00:00 |
https://www.uti.edu/blog/robotics-and-automation/what-is-robotics-and-automation
|
[
{
"date": "2025/06/27",
"position": 76,
"query": "job automation statistics"
}
] |
|
Disconnect Between AI Adoption And Policy Awareness In ...
|
Disconnect Between AI Adoption And Policy Awareness In Workplace: KnowBe4
|
https://securitymea.com
|
[
"On",
"In",
"Tagged"
] |
Varying AI Adoption Rates: While the average percentage of employees using AI in the workplace is 60.2% globally, adoption rates varied by region. France ...
|
KnowBe4 has shared new survey findings highlighting a severe AI governance gap. A new KnowBe4 survey of employees across Germany, South Africa, the Netherlands, France, the UK, and the US reveals that while a large majority of employees already engage with Artificial Intelligence (AI) tools at work, a strikingly low percentage are aware of their company’s official policies governing its use.
The findings reveal that, on average, 60.2% of employees are using AI tools in the workplace. In contrast, only 18.5% are aware of their company’s policy on AI usage. This significant gap suggests that the vast majority of AI activity within organizations is taking place without guidance or oversight. One in 10 employees (10%) have admitted to putting client data into an AI tool to complete a work task.
“An AI governance gap is like a ticking time bomb for organizations,” said Roger Grimes, data-driven defense evangelist at KnowBe4. “When the majority of your workforce is using AI but fewer than 20% understand the rules of engagement, you have a massive problem. AI tools are powerful, but without clear policies and training, employees may unknowingly feed sensitive information, like client data, into systems that were not designed to handle it securely. We often think of cyber risk as external, but in the age of AI, internal misuse, however unintentional, could lead to serious data breaches, compliance violations, and reputational damage.”
Other Takeaways Across Regions
Varying AI Adoption Rates: While the average percentage of employees using AI in the workplace is 60.2% globally, adoption rates varied by region. France shows the lowest adoption rate, with only 54.2% of employees saying they use AI tools at work, indicating a slower adoption rate. Conversely, South Africa records the highest at 70.1%, suggesting a more widespread use of AI.
While the average percentage of employees using AI in the workplace is 60.2% globally, adoption rates varied by region. France shows the lowest adoption rate, with only 54.2% of employees saying they use AI tools at work, indicating a slower adoption rate. Conversely, South Africa records the highest at 70.1%, suggesting a more widespread use of AI. Persistent Policy Awareness Gaps: An average of 14.4% of employees reported being unaware of their company’s AI policy. This lack of awareness is particularly notable in the Netherlands (16.1%) and the UK (15.8%), indicating a need for enhanced communication and training strategies.
An average of 14.4% of employees reported being unaware of their company’s AI policy. This lack of awareness is particularly notable in the Netherlands (16.1%) and the UK (15.8%), indicating a need for enhanced communication and training strategies. Sanctioned AI Use is Lagging: Only an average of 17% of employees use AI at work with their IT/security team’s knowledge. This figure, though highest in South Africa (23.6%), remains low overall, indicating a need for organizations to proactively provide and promote approved AI solutions.
The research emphasizes the critical need for organizations to bridge this awareness-usage gap. This requires not just establishing policies, but actively communicating them, providing comprehensive training on ethical and secure AI use, and offering approved, user-friendly AI tools to mitigate the significant risks posed by uncontrolled AI adoption.
| 2025-06-27T00:00:00 |
2025/06/27
|
https://securitymea.com/2025/06/27/disconnect-between-ai-adoption-and-policy-awareness-in-workplace-knowbe4/
|
[
{
"date": "2025/06/27",
"position": 25,
"query": "workplace AI adoption"
}
] |
AI Readiness: How AI is redefining the workplace
|
AI Readiness: How AI is redefining the workplace
|
https://www.robertwalters.ie
|
[] |
Discover how to assess your organisation's AI readiness and prepare your teams, data, and systems for successful AI adoption and integration.
|
Recently, the rapid growth and adoption of AI has impacted how organisations operate daily, but also how they think about the future of their business. Organisations have begun to consider their level of AI readiness and ways to prepare their business for the future with an AI-ready workforce. This includes evaluating current capabilities, identifying critical skill gaps, investing in continuous learning, and aligning AI strategies with long-term business objectives. But what is AI readiness?
What is AI readiness?
AI readiness refers to an organisation’s ability to implement AI into their operations and this ranges from foundational readiness such as incorporating elementary tools to AI transformation – the high-level use of AI tools that have a significant impact on how a certain function operates. AI readiness encompasses all the steps an organisation should take prior to implementing AI tools or systems.
While the barrier to entry for using generative AI tools such as ChatGPT or Microsoft Co-Pilot is fairly low, effectively using AI to augment and automate processes in the workplace is significantly more difficult. This goes beyond AI knowledge and into ethical and responsible use that complies with data governance policies.
Adopting AI tools requires a strategic approach and a strong understanding of the implications of AI. To gain insight into where organisations currently are on this journey, we conducted a poll to see how our audience views AI, especially in relation to job creation and job losses.
Attitudes to AI
While it’s key for businesses and employees to adapt to this technology, the sentiment around AI in the workplace is varied. In March 2025, our Advisory team launched several LinkedIn polls to gain some insight into our current audience and their view on AI in the workplace. Here are a few key stats:
• 54% of respondents expect AI to create less new jobs than it replaces
• 72% of respondents believe AI will make things better
• 58% of respondents believe AI has not provided any measurable benefit for their organisation’s hiring process yet
• 56% of respondents believe AI will replace low-skill jobs by 2030
While these stats present only our LinkedIn audience and those who engaged with the relevant polls, it’s interesting to note that while many respondents feel AI will provide general improvements, a large majority also haven’t yet seen any benefit of AI particularly in their hiring process. While many believe AI will drive improvement, most haven’t seen measurable outcomes just yet.
There’s no doubt that AI still plays a significant role in the growth and potential success of organisations, but what impact has it already made?
The impact of AI on the workplace
The tech space is already witnessing an exceptional AI impact, with Meta CEO, Mark Zuckerberg, stating that AI will replace mid-level engineers by 2025. In an article shared by Forbes, it stated that Zuckerberg believes “AI can take over coding tasks, allowing human engineers to focus on higher-level problem-solving and creativity.”
Outside of tech, AI has proven a positive addition to different processes in HR management, logistics, and manufacturing capability enhancements. Additionally, the drug discovery space has noticed accelerated research timeframes and reduced costs with the applications of AI. This quick adoption of AI was likely made possible by the high level of AI readiness that may already exist within these organisations and sectors.
The world has witnessed immense technological advancement over the last few decades and at a pace that many could not have imagined. While innovation and ingenuity should be at the forefront of any future-focused business, what are the effects of unregulated AI application?
The risks of AI
A roundtable between TechCentral and NTT DATA revealed that generative AI is "reshaping IT infrastructure, software development, cybersecurity, and business operations". However, the roundtable also placed significance on AI governance to find a balance between innovation and data protection.
In 2023, UNESCO highlighted key examples of ethical dilemmas with AI use. This ranged from AI systems delivering biased results, to AI in the court of law, and AI creating art. In terms of creating Art, UNESCO shared that AI is reshaping “what it means to be an author” and that the creation of original art plays a key role in inclusive societies.
For HR, it’s no different. To implement impactful but ethical use of AI, organisations need to understand what can be automated and what can’t. AI should be used in a regulated way, whether that’s in hiring, onboarding, or even gathering employee engagement insights. For example, automating administrative tasks in HR is one option, but what happens when companies begin automating their employee reviews? How do they ensure unbiased results that consider the employees’ tenure, their role, and their current circumstances? This balancing act is a crucial part of regulating AI in many areas, and particularly in a division of the organisation that engages your most valuable asset – your people. While HR teams should consider how they use AI, there's no doubt that job seekers are already tapping into these tools.
AI for job seekers
The possibilities of AI cannot be overstated, particularly for job seekers who often see it as a useful tool to tailor their resumes or cover letters. Nearly 65% of job applicants use AI at some point in the application process, according to a trend report from Career Group Companies.
During an application, employers are often checking if you’re the right fit, either from a skills or culture perspective. The information you provide should be reflective of your true capabilities and AI should help you enhance your application, not embellish.
“While AI can be helpful for quick applications, hiring managers value authenticity and a true reflection of a candidate’s experience.” Christ Eldridge, CEO of Robert Walters UK&I
For organisations, however, Forbes reported that employees selected based on AI recommendations tend to perform better as AI removes human bias and prevents hiring managers from making decision based on first impressions. Still, AI isn’t ready to make unsupervised decisions and should be used as a tool for experienced professionals who have their organisation’s objectives top of mind.
How to prepare for the future of AI at work
According to McKinsey & Company’s, The State of AI, survey from March 2025, the redesign of workflows will have the most significant impact on an organisation’s ability to see EBIT impact from gen AI use. In the same survey, they noted that only 27% of respondents whose organisations use AI review content generated by AI.
So, if redesigning organisational workflows with AI is the key to seeing a potential monetary impact but so few organisations are reviewing their AI content, what does this mean for the future of work?
It’s crucial to address the current and potential risks of AI, as well as security concerns. McKinsey & Company’s survey also highlighted that while respondents from larger organisations are more likely to say that their employer is managing AI risk, they are not more likely to address these risks.
From our own LinkedIn polls, we also know that 40% of respondents shared AI has not been explored at all while 52% noted using AI in some areas. Only 8% of respondents stated that AI has been fully integrated into their organisation – indicating that these organisations likely had a high level of AI readiness in order to act as quickly.
To prepare for the future of the workplace that most certainly includes the use of AI, it’s crucial to balance your gen AI use with cybersecurity practices and operational processes designed to mitigate risk on your journey to becoming AI ready.
Bridging the AI gap: How our AI Readiness Masterclass helps organisations prepare
With 40 years in recruitment, our teams have recognised the growing need for AI use in recruitment and hiring. The AI Readiness Masterclass was born out of a need to address some of the key areas of concern for HR and talent acquisition professionals, and how AI can support these roles. As organisations assess their AI readiness, understanding how to strategically apply AI in recruitment becomes increasingly critical. Packaged into five one-hour sessions, the AI Readiness Masterclass delivers key benefits including the commercial value AI can deliver for your business, such as lower hiring costs and increased productivity within HR and recruitment.
Contact our Future of Work specialists to find out more about our AI Readiness Masterclass.
| 2025-06-27T00:00:00 |
https://www.robertwalters.ie/insights/hiring-advice/blog/ai-readiness-in-the-workplace.html
|
[
{
"date": "2025/06/27",
"position": 61,
"query": "workplace AI adoption"
}
] |
|
Report: Most workforces not ready to leverage AI successfully
|
Report: Most workforces not ready to leverage AI successfully
|
https://www.siliconrepublic.com
|
[
"Colin Ryan",
"Colin Ryan Is A Senior Reporter",
"Sub-Editor With Silicon Republic",
"Having Joined The Company In January Coming A Background In Creative Media",
"Technology",
"Colin Has Previously Worked As A Researcher",
"Camera Operator. He Enjoys Watching Films",
"Listening To Music",
"Befriending Every Dog He Meets."
] |
Skills and trust. According to the report, there are three critical barriers that are inhibiting AI adoption: organisational change management, lack of employee ...
|
From C-suite disconnects to lack of trust, Kyndryl’s People Readiness Report highlights where organisations are falling short of successful AI adoption.
Last month, tech services provider Kyndryl released a global study that indicated a significant gap between AI investment and workforce preparedness in enterprise.
The People Readiness Report revealed that while 95pc of businesses have adopted AI in their operations, 71pc of business leaders believe their workforces are not ready to use the technology to its full potential.
The report, which surveyed more than 1,000 senior business and technology executives across 25 industries and eight geographies, found that only a small group of businesses – dubbed ‘AI Pacesetters’ – have aligned their workforce, technology and growth goals to benefit from AI adoption.
“The rest are often treating AI as a technical implementation rather than a transformation that demands cultural and operational change,” Nick Drouet, CTO of Kyndryl UK and Ireland explains to SiliconRepublic.com.
Drouet further explains that of the businesses leveraging AI, 66pc of them focus heavily on internal process optimisation while neglecting the ways in which AI can influence growth opportunities or workforce roles.
“Pacesetters, by contrast, embed AI into their enterprise and culture, and they empower their people through trust-building, change management and proactive upskilling. Not focusing on this holistic integration is where most businesses fall short.”
Skills and trust
According to the report, there are three critical barriers that are inhibiting AI adoption: organisational change management, lack of employee trust in AI and skills gaps.
“Many organisations underestimate the level of organisational change required,” says Drouet. “They also struggle to build trust in AI among employees – especially when fears of job displacement go unaddressed.”
Only four in 10 leaders surveyed say their organisation has fully implemented an overall AI adoption strategy to take them from their current state to a future state, while even fewer have implemented foundational strategies such as an AI governance framework or a change management strategy.
In fact, 53pc of responding leaders believe their workforce is ready to navigate changes related to AI over the next five years.
In terms of trust, half of leaders say there is a widespread fear of job displacement among their workforces, which is affecting employee engagement with AI. 45pc of CEOs state that their employees actively resist the tech.
While, 51pc of leaders say there is a lack of skilled talent to manage AI tech in their business.
“Solving the skills gap requires investment and intention,” says Drouet. “Businesses must understand not only what skills are missing but where demand is heading.”
C-suite contrasts
Interestingly, the report suggests that a disconnect exists between CEOs and CIOs/CTOs regarding how they view workplace readiness and how they can improve readiness.
According to the report, CEOs are more likely to report that their organisation is not currently using AI or is still in the early stages of implementation.
“CEOs tend to perceive more employee resistance to AI – 45pc say their teams are hostile or resistant – while 73pc of CTOs and CIOs say the opposite,” says Drouet. “This disconnect can result in misaligned strategies and missed opportunities.”
The disconnect is further present in regard to strategies for solving the skills gap.
80pc of CIOs and CTOs are focused on upskilling existing employees in AI, while 43pc of CEOs are prioritising hiring new employees to get those skills.
What can be done?
With the critical barriers to AI adoption identified, we asked Drouet how organisation can combat these challenges.
When it comes to trust, Drouet says transparency is key.
“Trust is foundational. People need to feel that AI is there to enhance, not replace, their work,” he says. “Organisations must be transparent about how AI will be used, explain its benefits and actively involve employees in its deployment.”
Drouet says that where most leaders fall in terms of AI adoption is underestimating the need for a full organisation transformation.
“Technology adoption is the easy part – it’s the cultural, governance and workforce alignment that make or break AI strategies,” he says.
“Kyndryl’s research shows Pacesetters are nearly three times more likely to have implemented a change management strategy and two times more likely to say their workforce is ready to navigate change. Too many organisations skip these foundational steps and focus only on AI tools.
“But tools don’t create value; people using them effectively do.”
Don’t miss out on the knowledge you need to succeed. Sign up for the Daily Brief, Silicon Republic’s digest of need-to-know sci-tech news.
| 2025-06-27T00:00:00 |
2025/06/27
|
https://www.siliconrepublic.com/careers/kyndryl-ai-report-workforce-skills
|
[
{
"date": "2025/06/27",
"position": 77,
"query": "workplace AI adoption"
}
] |
HR leaders are under pressure to adopt AI – but at what ...
|
HR leaders are under pressure to adopt AI – but at what cost?
|
https://www.humanresourcesonline.net
|
[] |
Privacy: Given that AI solutions in HR will be used on employee data, it's essential for them to embed privacy directly into the solution. Tech adoption: ...
|
As AI reshapes human capital management, James Saxton, VP Global Product Ambassador at Dayforce, shares insights on how organisations can adopt AI thoughtfully – ensuring ethical use, regulatory alignment, and meaningful impact for both business and workforce.
This article is brought to you by Dayforce.
AI has evolved from an intriguing HR add-on to a transformative force. While its potential is clear, so are the risks. As such, HR leaders face a paradox: they must drive innovation and efficiency through AI, while also ensuring ethical use, fairness, and compliance in a tightening regulatory climate.
In such a charged environment, where boards are demanding shareholder value, employees expect agility, and regulators want accountability, responsible AI adoption isn’t optional. CHROs must move beyond experimentation and hype to build practical, people-first AI frameworks that can deliver value and earn trust.
6 challenges HR faces in adopting AI
While enthusiasm for AI is rising, so are the implementation headaches. Here are six of the most common roadblocks HR teams face when adopting AI:
Compliance: Regional frameworks are constantly evolving, and AI solutions must be agile enough to adapt to these changes, helping organisations manage compliance today and tomorrow.
Bias: Employers, legislators, and employees alike are asking: how fairly and accurately can AI make judgments, especially when the goalposts for addressing bias are constantly shifting?
Ethics: Beyond compliance, organisations must ensure their use of AI does not cause harm to individuals or society, or compromise on fairness, transparency, and respect.
Transparency and quality: Understanding how AI arrives at its conclusions is concerning, especially when AI drives decisions affecting people. Additionally, AI models can deteriorate over time without robust monitoring.
Privacy: Given that AI solutions in HR will be used on employee data, it’s essential for them to embed privacy directly into the solution.
Tech adoption: Increasing AI adoption means taking concrete steps to building literacy, comfort, and creative thinking required for people to use the technology effectively.
To navigate these challenges successfully, HR needs a clear vision and a well-defined strategy for adopting AI thoughtfully and ethically.
As James Saxton, VP Global Product Ambassador at Dayforce, highlights, employees are increasingly seeking less friction in their work lives — whether it’s having greater flexibility in their careers, or seamless, consumer-grade digital experiences like mobile self-service. This, while organisations face mounting challenges, such as economic uncertainty and complex regulations.
How can we find balance between these business needs and employee expectations? Well, that’s where HR can truly shine. By harnessing AI strategically, HR leaders can simplify processes, personalise employee experiences, and build adaptive systems that prioritise both organisational resilience and workforce wellbeing.
Given his experience in engaging with key customers, partners, and industry influencers on shaping actionable strategies, we probe Dayforce’s Saxton a little further on the five non-negotiable principles in driving responsible, effective, and sustainable implementation of AI in human capital management (HCM). Let's dive into the insights.
Non-negotiable 1: Prepare your people
Saxton shares, that to drive AI adoption, organisations must take concrete steps to build literacy, comfort, and creative thinking required for people to use the technology effectively.
"This is where employee readiness and upskilling come in. Before investing in any AI, it’s essential to involve your team, as they are the primary users of the technology,” he adds, advising organisations to start by creating tailored learning programmes for everyone who will interact with AI.
"This training should cover AI ethics and correct usage, tailored to individuals' roles and the way they are expected to utilise the system. It would help to offer learning options that fit employees’ learning styles and monitor their progress to help ensure understanding."
However, he notes, such targeted training can be hard to implement, so using a learning management system (LMS) embedded in the HCM solution can help empower employees and manage timelines and completion criteria, allowing teams to track learners’ progress and provide feedback.
But it’s not just about theory. “Once training is set, building an AI “sandbox” can help users test what they’ve learned in a controlled environment and use the software as they would in the real world. This will help them build practical skills, get comfortable with the tools, and help them learn to think creatively as they use the tool so they’re ready once the real-world solution is deployed,” Saxton says.
These play zones can turn hesitant learners into confident AI champions.
Non-negotiable 2: Get real about compliance
Compliance in AI isn’t static — it’s a moving target that requires ongoing attention. From strict frameworks like the EU’s GDPR to new local regulations, organisations need AI solutions that not only meet today’s requirements but are designed to evolve with global regulations.
Saxton queries: “Is the AI solution agile enough to manage compliance today and tomorrow? This is critical, especially since legislation moves fast, but AI moves faster, and something that is legal today may become illegal in the future.”
True compliance means choosing AI tools that include processes for monitoring regulatory updates, adjusting policies as needed, and providing clear, auditable evidence of compliance across different regions. Relying on static certifications or promises isn’t enough.
Non-negotiable 3: Use AI only where and when you require it
When it comes to AI in HCM, a one-size-fits-all approach is a huge risk. Here are some ways you can stay ahead of the curve:
Challenge the toggle trap: Avoid platforms with only on/off AI controls. Choose the proper tools that allow you to tailor AI by role, function, or region.
Respect individual agency: Not everyone needs AI all the time. Enable opt-ins, opt-outs, or contextual functionality to build trust and boost adoption.
Not everyone needs AI all the time. Enable opt-ins, opt-outs, or contextual functionality to build trust and boost adoption. Governance without gridlock: Regulations change quickly. Use solutions with agile governance to adapt AI use without disrupting operations.
Some important questions Saxton urges leaders to ponder are:
How specific can you be about where and when AI is used? Can employees opt in or out of having access to it? Can you turn the tool on and off depending on which regulatory jurisdiction it's being used in?
In short, when it comes to AI in HCM, flexibility isn’t just a feature — it’s a must-have strategy to unlock human potential while maintaining robust control.
Non-negotiable 4: Shatter the black box… where possible
AI must be explainable. With a lack of transparency as one of the top challenges to AI deployment — particularly for third-party solutions—organisations should demand clarity on how models make decisions, both at a general level and in specific scenarios.
“It’s important to ask: how does AI arrive at its conclusions? How does the model influence decisions, both specific and general? How does the system get consent? And how can we ensure quality over time, especially once the AI model is influenced by real-world data?”
The best outcomes happen when AI and human insight work hand-in-hand. Here’s how that could happen:
Keep your people involved, especially for sensitive or strategic decisions. AI should inform and assist human insight – not replace them. Ask the critical questions: How does the model reach its conclusions? Are users clearly informed when AI is in play? Is consent sought and recorded where customers are involved? Prioritise quality over bias by partnering with providers who actively monitor and update AI models to ensure decisions stay accurate, fair, and defensible over time.
Non-negotiable 5: Protect everyone
Security, privacy, and transparency must be integral from the get-go. As Saxton says, “Your AI solution must uphold the highest standards of privacy as it will be dealing with the most sensitive part of your organisation, your people.
"It’s essential for AI solutions to follow ‘Privacy by Design’, a methodology that helps responsible AI solution providers create technology that can help to anticipate and prevent invasive events before they happen."
In addition to following the ‘Privacy by Design’ principle in your AI stack, AI solutions should also be engineered to prevent breaches before they happen – from data collection to processing and storage.
HR also has a crucial role in fostering open dialogue about AI’s ethical use, its impact on people, and its limitations. Leaders should ask and verify the tough questions:
Where exactly are AI models hosted?
Is employee or customer data shared with third parties?
Can individuals opt out of having their data used for training?
Does the AI rely on public or proprietary data sets?
Before integrating AI tools into the workplace, organisations should not settle for vague assurances, instead, scrutinise how privacy and security safeguards are implemented. Protecting everyone means leaving nothing to chance.
The future: Toward a balanced, people-first AI strategy
Skills-based hiring and predictive talent models are becoming the new norm, while human-AI co-piloting is shifting from novelty to necessity. But success won’t hinge on technology alone, it depends on how well organisations centre employee experience in their AI journey. That means empowering employees to make smarter decisions, automate the mundane, and focus on more strategic, creative, and value-driven work.
The new employee experience includes learning how to partner with AI, not compete with it.
"Much about the conversation around AI has centred around whether this technology can replace humans or if humans can delegate tasks to machines, but a lot of technology still needs the human touch. AI’s main role is still to understand and elevate work, not replace it," Saxton affirms.
To truly benefit from AI, organisations must help employees learn the steps of this "new tango" — the delicate balance between human and machine collaboration.
Conclusion
AI can unlock new levels of productivity, efficiency, and agility – when used the right way. Saxton drives home the importance of a true AI partner, that can allow HR professionals to work on the business and for employees in a strategically connected and fulfilling role.
"No more Job Descriptions, no more training material content, corporate policy documents, reporting metrics, and so on – all this being done automatically for you, so you can focus on what truly matters and do the work that you’re meant to do."
That’s where Dayforce comes in, with its offering of comprehensive, AI-powered people platform designed to help organisations unlock their full potential and work with confidence.
Go on, find out more information on how Dayforce can transform your workforce management, please visit here.
Do the work you’re meant to do with Dayforce. Learn more at dayforce.com/asia.
| 2025-06-27T00:00:00 |
https://www.humanresourcesonline.net/hr-leaders-are-under-pressure-to-adopt-ai-but-at-what-cost
|
[
{
"date": "2025/06/27",
"position": 90,
"query": "workplace AI adoption"
}
] |
|
AI 'could reshape essential function of journalism ' - Gulf Times
|
AI 'could reshape essential function of journalism '
|
https://www.gulf-times.com
|
[
"Joseph Varghese"
] |
Artificial Intelligence ( AI), in the coming years, could reshape journalism's essential function, noted a professor from one of the Qatar ...
|
Artificial Intelligence ( AI), in the coming years, could reshape journalism’s essential function, noted a professor from one of the Qatar Foundation partner universities while highlighting some of the substantial risks of AI integration in journalism.“As AI becomes more involved in content creation, it could begin to reshape journalism’s essential function in helping the public understand the world and make informed decisions. This is particularly critical in regions like the Global South, where AI systems may not recognise or value local perspectives,” Prof Eddy Borges-Rey, associate professor in residence, Northwestern University in Qatar told Gulf Times.Prof Borges-Rey said that currently journalists are cautiously experimenting with AI for specific tasks such as transcription, translation, summarisation, and initial drafts.“If the current trends continue, we may see a newsroom workflow where human editors are managing AI-generated drafts, optimising content for algorithms rather than audiences. The most radical shift will not be technical, it will be conceptual,” he explained.However, the professor cautioned that these experiments are occurring amid growing concerns and involve substantial risks.“Tools like ChatGPT and Gemini can produce plausible-sounding but inaccurate content, and generative outputs often lack context and editorial judgment. The BBC recently conducted a study asking major AI platforms to summarise 100 news stories; 51% of the results contained significant issues. These findings reflect a broader trend: while journalists explore automation, the risks remain substantial,” he said.The academic said that AI is rather a transformative force that challenges people’s assumptions about knowledge, authority, and responsibility. He stated : “If journalism is to remain a meaningful institution, we must be proactive in shaping how AI is adopted. That means investing in education, building internal safeguards, and centering voices from the Global South in global debates. We should be cautiously optimistic, but more importantly, we must move away from the rhetoric of ‘falling behind’.”Prof Borges-Rey noted the media faces several profound challenges in integrating AI. “First, there is the problem of bias — most large language models are trained on English-language data from the Global North, which can marginalise other cultures and viewpoints,” he said. “Second, the lack of transparency in how AI makes decisions raises questions about accountability.“Third, editorial authority is being blurred: when a machine suggests a headline or summary, who is ultimately responsible for its accuracy or ethical framing? And finally, there is mounting pressure to adopt AI quickly, often without adequate safeguards in place.”Prof Borges-Rey also highlighted some of the advantages and risk factors of integrating AI into journalism.“It can reduce the burden of repetitive tasks, improve accessibility through automated translations and voiceovers, and help identify patterns in large datasets for investigative reporting. It can also support local journalism by generating summaries or story alerts for underserved communities. But these benefits must be weighed against the ethical and professional risks. Used wisely, AI can support journalism’s mission. Used blindly, it can undermine the very trust it is meant to foster,” he added.
| 2025-06-28T00:00:00 |
2025/06/28
|
https://www.gulf-times.com/article/706699/qatar/ai-could-reshape-essential-function-of-journalism-
|
[
{
"date": "2025/06/28",
"position": 98,
"query": "AI journalism"
}
] |
Anthropic's AI Economic Program: A Catalyst for Crypto and DeFi ...
|
Anthropic’s AI Economic Program: A Catalyst for Crypto and DeFi Disruption?
|
https://openexo.com
|
[] |
Crypto Relevance: AI-driven disruption might accelerate DeFi adoption and blockchain innovation, offering decentralized tools for a shifting ...
|
Anthropic’s Economic Futures Program: Can AI Fuel a Decentralized Crypto Economy?
Anthropic, a heavyweight in AI research, has rolled out the Economic Futures Program, an initiative to dissect how artificial intelligence could reshape economies and labor markets. As advocates for decentralization and disruptive tech here at “Let’s Talk, Bitcoin,” we’re diving into this program not just for its AI focus, but for how its findings might ripple into the crypto space—potentially amplifying Bitcoin’s role as a financial hedge or boosting blockchain solutions like decentralized finance (DeFi) amid economic upheaval.
Core Mission: Anthropic’s program studies AI’s economic impact through research grants, policy forums, and data tracking, aiming to balance growth prospects with job displacement risks.
Anthropic’s program studies AI’s economic impact through research grants, policy forums, and data tracking, aiming to balance growth prospects with job displacement risks. Dire Warnings: CEO Dario Amodei predicts AI could slash 50% of entry-level white-collar jobs, pushing unemployment to 20% within five years.
CEO Dario Amodei predicts AI could slash 50% of entry-level white-collar jobs, pushing unemployment to 20% within five years. Crypto Relevance: AI-driven disruption might accelerate DeFi adoption and blockchain innovation, offering decentralized tools for a shifting economic landscape.
Decoding Anthropic’s Economic Futures Program
Let’s get straight to the nuts and bolts. Anthropic’s Economic Futures Program is a calculated effort to understand AI’s influence on economies, focusing on hard evidence over wild speculation. AI, for the uninitiated, refers to computer systems that mimic human intelligence—think algorithms that analyze data, make decisions, or even automate entire workflows. This initiative, detailed in their recent announcement of the Economic Futures Program, zeroes in on three pillars: dishing out rapid grants of $10,000 to $50,000 for researchers to study AI’s effects on labor and productivity (with results expected in six months), hosting symposia this fall in Washington D.C. and Europe to craft evidence-based policy proposals, and building datasets to track AI’s real-world economic footprint. They’re even providing access to their Claude API—credits worth $5,000—to help researchers crunch data using Anthropic’s own tech. This builds on their earlier Economic Index project from February, which used open-source data to start mapping AI’s long-term effects.
The program’s leadership isn’t shy about the stakes. Sarah Heck, Anthropic’s Head of Policy Programs, is adamant about grounding discussions in reality rather than knee-jerk reactions to AI’s promise or peril. Her goal? Figure out what’s truly happening before crafting solutions, whether that’s mitigating job losses or capitalizing on economic booms.
“It’s really important to root these conversations in evidence and not have predetermined outcomes or views on what’s going to [happen],” Heck stated.
This no-BS stance is refreshing in a field often drowned in hype—much like the crypto space where shillers peddle absurd price targets. If AI triggers massive job cuts, Heck wants a collective of sharp minds to brainstorm mitigation. If it sparks a GDP surge, policymakers need to be ready to channel that growth. It’s not a one-track narrative, and that complexity is key to understanding the road ahead, as highlighted in recent coverage of Anthropic’s efforts to track AI’s economic impact.
Labor Shakeup: AI as a Job Killer or Creator?
Here’s where the rubber meets the road. Anthropic’s CEO, Dario Amodei, dropped a bombshell earlier this year, warning that AI could wipe out half of all entry-level white-collar jobs—think data entry, basic accounting, or customer support roles—and drive unemployment to a staggering 20% within five years. To put that in perspective, that’s roughly double the peak unemployment rate during the 2008 financial crisis. We’re talking about a potential economic earthquake that could hit just as the next Bitcoin halving reshapes crypto markets. For deeper insights into these warnings, check out this analysis of Amodei’s job loss predictions.
“AI could eliminate half of all entry-level white-collar jobs and increase unemployment to as high as 20% in the next five years,” Amodei predicted.
But it’s not just about slashing jobs. Heck and her team are also peering into how AI reshapes workflows—how tasks are done in entirely new ways—and whether it spawns job categories we can’t yet fathom. Will some skills remain invaluable while others become obsolete overnight? Beyond labor, they’re exploring fiscal policy changes (how governments adjust taxing and spending in response to AI’s economic waves) and how businesses redefine value when machines handle more of the heavy lifting, a topic further explored in Anthropic’s labor market research findings.
Still, let’s pump the brakes on the doomscrolling. Not everyone agrees AI is an unstoppable job-killer. Take Klarna, a fintech giant that swapped out 700 customer service agents for AI in 2024, only to backpedal in 2025 when customers demanded human interaction. Turns out, people still value the messy, empathetic touch of a real person over a chatbot’s cold efficiency. Other experts, like Cisco’s Field CTO Andy Thurai, caution against blind cost-cutting with AI, pointing to mixed results when firms ditch seasoned pros for AI-augmented rookies. Automation without a damn good strategy, as LeapXpert CEO Dima Gutzeit puts it, can backfire—especially in regulated industries where human oversight isn’t just nice, it’s mandatory. Sounds a bit like the crypto space, doesn’t it? Tech can’t solve everything if the human element gets ignored.
AI Meets Blockchain: A Crypto Lifeline?
Now, let’s talk our turf. AI’s economic turbulence could send shockwaves through the crypto world, and not just because trading bots are already outpacing human investors on Bitcoin and Ethereum exchanges. These bots execute trades with ruthless precision—faster than a day trader hopped up on Red Bull during a bull run. But if Amodei’s 20% unemployment forecast plays out, could we see a flood of displaced workers turning to decentralized finance as a financial escape hatch? DeFi, for those new to the game, is a blockchain-based system where lending, borrowing, and trading happen without traditional banks, often powered by smart contracts on networks like Ethereum. For broader perspectives on this intersection, explore this research on AI and DeFi economic disruption.
Imagine millions sidelined by AI automation, seeking income through yield farming or staking in DeFi protocols as a hedge against economic uncertainty. Bitcoin, with its fixed supply and decentralized ethos, could become a go-to store of value for those burned by centralized systems failing to adapt. Hell, blockchain itself might offer solutions Anthropic could use—think transparent, decentralized datasets to track AI’s economic impact, leveraging projects like Chainlink for reliable data oracles. And if unemployment spikes, fringe ideas like blockchain-based universal basic income—where tokens are distributed on-chain as a safety net—could shift from Reddit threads to real-world experiments. Past attempts, like small-scale basic income tokens on Ethereum, show it’s not pure fantasy, even if scalability remains a hurdle. Community discussions on platforms like Reddit about AI’s economic effects echo similar concerns and ideas.
But let’s not get carried away with the utopian daydreams. Just as we roast baseless crypto price predictions, we’ve got to scrutinize AI-blockchain synergies with a sharp eye. AI can centralize power as easily as it decentralizes if big tech or governments weaponize it—much like how some altcoin projects promise freedom but end up as glorified Ponzi schemes. And while Bitcoin remains the gold standard of decentralization in our view, we can’t ignore Ethereum’s utility in marrying AI with smart contracts. Altcoins and other blockchains often fill niches Bitcoin doesn’t touch, and that diversity might be crucial if AI reshapes economic fundamentals.
Skepticism and Reality: AI Isn’t a Silver Bullet
Anthropic’s push for evidence over sensationalism mirrors our own disdain for crypto hype machines. Their symposia events could steer how governments tackle tech regulation, and that’s a double-edged sword for our space. If AI-driven economic shifts force a reckoning, might lawmakers revisit digital asset frameworks—especially if displaced workers flock to Bitcoin or DeFi for independence? Or will AI’s centralization risks—think mega-corporations hoarding data and power—spill over into tighter crypto oversight? If AI kills 20% of jobs, will bureaucrats ban it before they target Bitcoin again? Don’t bet on it. For additional context on Anthropic’s broader mission, their Wikipedia page offers a useful overview.
Playing devil’s advocate, let’s question whether AI’s economic threat is overblown. Beyond Klarna’s reversal, industries like telecom show AI’s limits—Oculeus CEO Arnd Baranowski notes that while AI handles scale, it lacks the human imagination to outsmart evolving fraud tactics. Cut human teams too deep, and you’re screwed. This hybrid reality could temper AI’s job-killing potential, much like how blockchain hasn’t fully displaced traditional finance despite two decades of disruption. AI and crypto share a truth: they’re tools of freedom and efficiency, but only if wielded with intent over blind faith. Similar discussions on AI’s future impact can be found in this Quora thread on AI and economic changes, alongside other relevant studies on AI’s economic influence.
Key Takeaways and Questions
What is the goal of Anthropic’s Economic Futures Program?
It aims to analyze AI’s impact on economies and labor through research grants, policy forums in D.C. and Europe, and data tracking, seeking to balance potential GDP growth with risks like massive job displacement.
It aims to analyze AI’s impact on economies and labor through research grants, policy forums in D.C. and Europe, and data tracking, seeking to balance potential GDP growth with risks like massive job displacement. How could AI disrupt the job market, per Anthropic’s leadership?
CEO Dario Amodei warns AI might eliminate 50% of entry-level white-collar jobs, driving unemployment to 20% in five years—a seismic shift that could rival past economic crises.
CEO Dario Amodei warns AI might eliminate 50% of entry-level white-collar jobs, driving unemployment to 20% in five years—a seismic shift that could rival past economic crises. What does AI’s economic impact mean for Bitcoin and crypto?
It could drive adoption of Bitcoin as a store of value and DeFi as a financial alternative for displaced workers, while blockchain might offer decentralized tools to track AI’s effects transparently.
It could drive adoption of Bitcoin as a store of value and DeFi as a financial alternative for displaced workers, while blockchain might offer decentralized tools to track AI’s effects transparently. Why focus on evidence over speculation in AI’s economic analysis?
Hard data ensures realistic policies, avoiding overreactions to AI’s hyped benefits or fears—much like we reject baseless crypto price predictions peddled by shillers.
Hard data ensures realistic policies, avoiding overreactions to AI’s hyped benefits or fears—much like we reject baseless crypto price predictions peddled by shillers. Are there counterpoints to AI’s job-killing narrative?
Yes, cases like Klarna’s reversal show humans are still preferred in some roles, and experts warn automation without strategy fails in regulated spaces, suggesting AI’s impact might be less apocalyptic than feared.
AI and blockchain are two sides of a disruptive coin—both challenge centralized systems, promising freedom and efficiency while risking misuse or overreach. Anthropic’s Economic Futures Program may not name-drop Bitcoin, but its focus on labor shifts, policy, and economic value hits home for anyone betting on decentralized tech to upend the status quo. We’re keeping tabs on whether this sparks ideas to fuse AI’s raw power with blockchain’s transparent ethos. Until then, hold your private keys tight and your skepticism tighter—disruption doesn’t wait for permission.
| 2025-06-28T00:00:00 |
2025/06/28
|
https://openexo.com/l/acaa509d
|
[
{
"date": "2025/06/28",
"position": 88,
"query": "AI economic disruption"
}
] |
The AI Backlash Keeps Growing Stronger - WIRED
|
The AI Backlash Keeps Growing Stronger
|
https://www.wired.com
|
[
"Reece Rogers",
"Will Knight",
"David Gilbert",
"Kate Knibbs",
"Matt Burgess",
"Zoë Schiffer",
"Caroline Haskins",
"Kylie Robison"
] |
Still, the potential threat of bosses attempting to replace human workers with AI ... worker-replacing technology. “AI companies have ...
|
Before Duolingo wiped its videos from TikTok and Instagram in mid-May, social media engagement was one of the language-learning app’s most recognizable qualities. Its green owl mascot had gone viral multiple times and was well known to younger users—a success story other marketers envied.
But, when news got out that Duolingo was making the switch to become an “AI-first” company, planning to replace contractors who work on tasks generative AI could automate, public perception of the brand soured.
Young people started posting on social media about how they were outraged at Duolingo as they performatively deleted the app—even if it meant losing the precious streak awards they earned through continued, daily usage. The comments on Duolingo’s TikTok posts in the days after the announcement were filled with rage, primarily focused on a single aspect: workers being replaced with automation.
The negative response online is indicative of a larger trend: Right now, though a growing number of Americans use ChatGPT, many people are sick of AI’s encroachment into their lives and are ready to fight back.
When reached for comment, Duolingo spokesperson Sam Dalsimer stressed that “AI isn’t replacing our staff” and said all AI-generated content on the platform would be created “under the direction and guidance of our learning experts.” The company's plan is still to reduce its use of non-staff contractors for tasks that can be automated using generative AI.
Duolingo’s embrace of workplace automation is part of a broad shift within the tech industry. Leaders at Klarna, a buy now, pay later service, and Salesforce, a software company, have also made sweeping statements about AI reducing the need for new hires in roles like customer service and engineering. These decisions were being made at the same time as developers sold “agents,” which are designed to automate software tasks, as a way to reduce the amount of workers needed to complete certain tasks.
Still, the potential threat of bosses attempting to replace human workers with AI agents is just one of many compounding reasons people are critical of generative AI. Add that to the error-ridden outputs, the environmental damage, the potential mental health impacts for users, and the concerns about copyright violations when AI tools are trained on existing works.
Many people were initially in awe of ChatGPT and other generative AI tools when they first arrived in late 2022. You could make a cartoon of a duck riding a motorcycle! But soon artists started speaking out, noting that their visual and textual works were being scraped to train these systems. The pushback from the creative community ramped up during the 2023 Hollywood writer's strike, and continued to accelerate through the current wave of copyright lawsuits brought by publishers, creatives, and Hollywood studios.
Right now, the general vibe aligns even more with the side of impacted workers. “I think there is a new sort of ambient animosity towards the AI systems,” says Brian Merchant, former WIRED contributor and author of Blood in the Machine, a book about the Luddites rebelling against worker-replacing technology. “AI companies have speedrun the Silicon Valley trajectory.”
| 2025-06-28T00:00:00 |
2025/06/28
|
https://www.wired.com/story/generative-ai-backlash/
|
[
{
"date": "2025/06/28",
"position": 87,
"query": "AI replacing workers"
}
] |
Government's Role: Policy Frameworks to Support Workers in an AI ...
|
Government’s Role: Policy Frameworks to Support Workers in an AI-Dominated Economy
|
https://www.linkedin.com
|
[] |
This includes revising unemployment benefits, healthcare access, and other social protections to better fit the realities of an AI-influenced ...
|
As artificial intelligence increasingly transforms the workforce, governments face the critical responsibility of ensuring that economic progress does not come at the expense of social stability. The rapid automation of tasks and jobs across sectors demands proactive policy frameworks designed to protect workers, foster innovation, and promote inclusive growth.
Navigating the Challenges of Workforce Automation
AI-driven automation threatens to disrupt traditional employment models by displacing workers in roles susceptible to mechanization. However, it also creates new opportunities in emerging fields that require a different set of skills. This dual nature requires governments to carefully balance regulatory oversight with incentives for innovation. Effective policies must address worker displacement while encouraging businesses to adopt AI responsibly.
Reskilling and Lifelong Learning as Cornerstones
One of the most significant roles for government is to enable workforce adaptability through investment in reskilling and lifelong learning initiatives. Public funding for training programs, partnerships with educational institutions, and collaboration with the private sector can equip workers with the skills necessary to thrive in AI-augmented jobs. Policies that prioritize accessible, affordable, and relevant education will be key to minimizing unemployment and underemployment caused by AI.
Strengthening Social Safety Nets
Alongside upskilling efforts, robust social safety nets must be in place to support workers during periods of transition. This includes revising unemployment benefits, healthcare access, and other social protections to better fit the realities of an AI-influenced labor market. Additionally, governments can promote job placement services and entrepreneurship programs to help displaced workers find new employment paths.
Ethical Standards and AI Governance
Building trust in AI technologies requires governments to implement ethical standards and regulatory frameworks that safeguard privacy, ensure fairness, and prevent bias. Transparent and accountable AI governance will not only protect workers but also encourage responsible AI development and deployment across industries.
International Collaboration and Inclusive Growth
Given the global nature of AI development, governments must also collaborate internationally to share best practices and address cross-border workforce challenges. Coordinated efforts can help harmonize standards, avoid a regulatory race to the bottom, and promote equitable distribution of AI’s economic benefits.
Governments that take an active, forward-looking approach to policy design will be instrumental in shaping an AI-driven economy where workers are empowered, businesses innovate responsibly, and society benefits broadly.
#FutureOfWork #AIandJobs #WorkforceAutomation #ReskillingRevolution #InclusiveGrowth #AIPolicy #LifelongLearning #SocialSafetyNets #EthicalAI #AIGovernance
| 2025-06-28T00:00:00 |
https://www.linkedin.com/pulse/governments-role-policy-frameworks-support-dwtac
|
[
{
"date": "2025/06/28",
"position": 7,
"query": "government AI workforce policy"
}
] |
|
Top 8 Artificial Intelligence Start-Ups to Watch in 2025
|
Top 8 AI Start-ups in 2025
|
https://www.fool.com
|
[
"Jeremy Bowman"
] |
In this discussion on AI start-ups, we'll review some of the hottest privately held companies working on artificial intelligence today.
|
Investor interest is surging in all things AI, so it shouldn't come as a surprise that artificial intelligence (AI) start-ups are also popping up on investors' radars. Ever since the launch of ChatGPT, the potential for AI has crystallized across the business world and among investors, and the implications for the new technology are vast. Among them is a new race among start-ups to challenge ChatGPT and, separately, to come up with the next big thing in generative AI.
Image source: Getty Images.
Not surprisingly, money from venture capital firms and other investors has poured into AI start-ups, and the industry is booming. In this discussion on AI start-ups, we'll review some of the hottest privately held companies working on artificial intelligence today, analyze the pros and cons of investing in AI start-ups, and answer some commonly asked questions about AI start-ups.
Definition Icon Artificial Intelligence Artificial intelligence is the use of machines to mimic human intelligence.
Best AI start-ups Best AI start-ups to watch this year 1. OpenAI 1. OpenAI As you might expect, ChatGPT owner OpenAI has received much of the attention in AI start-ups this year, and continues to set the pace in its cohort. OpenAI has developed other renowned products, including its image-generating AI, DALL-E, and text-to-video AI, Sora. Its success with ChatGPT and its high-profile partnership with Microsoft (MSFT -0.01%) makes it the premier AI start-up these days. OpenAI was founded in 2015 with several co-founders, including Elon Musk, though Musk eventually left the company to work on Tesla (TSLA 1.14%) and SpaceX.
Definition Icon AutoGPT AutoGPT is an artificial intelligence (AI) agent that can complete complex tasks without human intervention.
In March of 2025, Open AI raised $40 billion at a valuation of $300 billion, making it the largest private tech funding round on record. The round was led by SoftBank (SFTBF 0.31%), the prolific tech investor, which invested $30 billion; Microsoft and venture capital firms made up the remaining $10 billion. The Stargate Project, a joint venture between Softbank, OpenAI, and Oracle that was announced at the White House in January, is expected to receive $18 billion. Stargate aims to invest as much as $500 billion in AI infrastructure in the U.S. Key facts: Founded in 2015
Headquartered in San Francisco
Industries served: Technology, education, retail, manufacturing, healthcare, and others.
Services provided: Foundation models including GPT and DALL, chatbots, enterprise services, and an API platform.
2. Anthropic 2. Anthropic Anthropic is rapidly emerging as the chief start-up rival to OpenAI. Founded in 2021 by former OpenAI researchers, Anthropic counts Google and Amazon (AMZN 0.29%) as major investors. The Alphabet (GOOG 0.85%) (GOOGL 0.79%) subsidiary took a 10% stake in 2023, and Amazon has invested $8 billion in Anthropic. After its most recent funding round in March, it's valued at $61.5 billion, rising $3.5 billion at the time. Anthropic also counts Salesforce (CRM 0.53%) and Zoom (ZM 1.92%) as investors. Anthropic is best known for its generative AI chatbot, Claude, which it launched in March 2023. Some users think Claude is friendlier than ChatGPT, though they say that ChatGPT is better for analyzing and summarizing documents. It's also said to be more versatile than Claude.
According to some reviews, Claude gets better results with things like creative tasks, following instructions, and answering trivia questions. Anthropic describes Claude as being "much less likely to produce harmful outputs, easier to converse with, and more steerable" than other AI chatbots. In other words, Claude seems designed to avoid some of the problems that have plagued ChatGPT and Google's AI chatbots. Key facts: Founded in 2021
Headquartered in San Francisco
Industries served: Technology, healthcare, customer support, finance, and others
Services provided: Claude AI models, focus on AI safety, enterprise services, cloud partnerships.
3. Perplexity AI 3. Perplexity AI Valued at $14 billion as of May 2025, Perplexity AI is another promising AI start-up. Perplexity is backed by Softbank's Vision Fund, the prolific start-up investors known for backing companies like Uber (UBER -1.58%), DoorDash (DASH 1.0%), Arm Holdings (ARM -0.96%), and WeWork. Perplexity has also raised money from Nvidia (NVDA -0.46%), Amazon founder Jeff Bezos, and Shopify (SHOP 4.16%) CEO Tobi Lutke. Perplexity has differentiated itself from other AI chatbots with a focus on search tools that feature sources and citations. Some see Perplexity as the best AI alternative to a traditional Google search. In fact, both Apple (AAPL -1.12%) and Samsung (SSNL.F 9.01%) are considering integrating its search engine into their hardware. Perplexity said it crossed $100 million in annualized revenue March with 6.3x growth in Perplexity, its paid subscription tier. Key facts Founded in 2022
Headquartered in San Francisco
Industries served: Education, healthcare, media and entertainment, travel, and others
Services provided: Real-time search, citations, conversational interface, file uploads, and others.
4. xAI 4. xAI Elon Musk has had his hand in a wide range of emerging technologies, including electric vehicles, renewable energy, spacecraft and rockets, and satellite internet, so it shouldn't come as a surprise that he also has an AI start-up. (Musk was even a co-founder of OpenAI, although he left that company in 2018.) xAI, his AI start-up, is one of the most valuable today, and in June 2025 was aiming for a funding round with the help of Morgan Stanley (MS 1.19%) that would value the company at more than $100 billion in a deal that includes $5 billion debt and $20 billion in equity. xAI is the creator of Grok, the chatbot featured on the social media platform X, which Musk also owns. That gives xAI something of an advantage since most AI start-ups don't have an allied platform like X that can help draw users to the product. Some users think Grok is less censored than ChatGPT. Key facts: Founded in 2023
Headquartered in San Francisco
Industries served: Technology, finance, healthcare, autonomous vehicles, manufacturing, and others.
Services provided: Grok chatbot, models for developers, and enterprise services.
5. Mistral AI 5. Mistral AI Mistral AI is one of the youngest AI start-ups to make a splash in the industry. The company was able to easily raise money since it was founded by execs from Meta Platforms (META 0.46%) and Google. After a funding round in June 2024, the start-up is now valued at $6.2 billion, raising $640 million from the likes of Andreessen Horowitz, Nvidia, and Samsung. Mistral is unique among AI start-ups. It's based in France and has received a strong endorsement from the French government. It takes an open-source approach to AI, meaning its code is available to anyone who wants to use it. It's chatbot is called Le Chat and is known for being strong in a wide range of languages. Key facts: Founded in 2023
Headquartered in Paris
Industries served: Financial services, healthcare, customer support, education, and others
Services provided: Large language models, API access, open-source models, cloud-based access.
6. Scale AI 6. Scale AI Scale AI is different from other companies on this list because it doesn't make a chatbot or a generative AI interface. Instead, the company helps prepare data for AI training, a process called data labeling. Scale AI's technology is impressive enough that Meta Platforms just spent $14.3 billion on a 49% stake in the company, hoping it will accelerate its ambitions in AI. As part of the deal, Scale's 28-year-old CEO Alexandr Wang will join Meta, and will reportedly lead a research lab at the tech giant. Given that Meta didn't take a majority stake, Wang's agreement to leave is a bit odd, but the relationship could favor Scale in the long run. Key facts: Founded in 2016
Headquartered in San Francisco
Industries served: Autonomous vehicles, healthcare, e-commerce, generative AI, robotics, and others
Services provided: Data annotation/labeling, model training, human-in-the-loop labeling, and tools for building custom LLMs.
7. Databricks 7. Databricks Databricks is also unlike most of the AI start-ups on this list. It's older than the ones focused generative AI as it was founded in 2013, and its focus is primarily on data analytics. Its AI platform offers machine learning and generative AI applications to help its customers deploy AI models. As of December 2024, the company was valued at $62 billion after raising $10 billion. Databricks has been one of the more anticipated IPOs for a while, but the company has not given any indication of when it will go public. Key facts: Founded in 2013
Headquartered in San Francisco
Industries served: Financial services, healthcare, retail, media, and others.
Services provided: Data lakehouse, machine learning platform, analytics platform.
8. Cohere 8. Cohere Founded in 2019 by ex-Google AI researchers, Cohere is an enterprise AI platform focused on large language models and natural language processing. Cohere allows developers and businesses to build their chatbots and virtual assistants, and the company also provides services like data analysis and search. The company aims to provide higher performance and accuracy with a specific focus on the enterprise market. Cohere reached an annualized revenue of $100 million in May 2025, and its valuation was $5.5 billion as of June 2025. It counts Nvidia and Cisco (CSCO -0.19%) among its backers. Key facts: Founded in 2019
Headquartered in Toronto
Industries served: Financial services, healthcare, manufacturing, retail, and others
Services provided: LLMs, API access, text generation, summarization and data extraction.
Related investing topics
Should you invest? Should you invest in AI start-ups? Start-ups, by definition, are privately held, which means it's difficult for retail investors to invest in them. However, there are ways to get exposure to AI start-ups. The easiest way is by investing in a publicly traded company that has a stake in an AI start-up. For instance, you could buy shares of Microsoft, which would give you indirect ownership of OpenAI. Similarly, you could buy stock in Alphabet to get exposure to Anthropic. Investors should remember that start-ups tend to be riskier than publicly traded companies, and many start-ups won't succeed. However, if you find an AI start-up that looks promising, it's worth investigating if any publicly traded companies have a stake in it. Investors looking for opportunities in artificial intelligence can also consider investing in AI stocks or AI ETFs.
FAQ
AI start-up FAQ What are AI start-ups? angle-down angle-up Artificial intelligence (AI) start-ups are early-stage companies that are developing AI technologies or using them in their products and generally raising money from venture capital firms. Those could include everything from natural language processing like chatbots to robotics to machine learning. How do AI start-ups make money? angle-down angle-up Some AI start-ups make money by selling their products to customers, but most AI start-ups are unprofitable. They raise money from venture capitalists and others to fund research, develop new products, and bring them to market. What are the five big ideas in AI? angle-down angle-up The five big ideas in AI are: Perception: Computers need to sense the world through seeing and hearing like humans do. Representation and reasoning: Computers use data to construct representations to help them develop reasoning algorithms. Learning: Machine learning algorithms that use statistical inference from large amounts are a foundational concept in AI. Natural interaction: AI agents need to be able to converse in human languages and read facial expressions and emotions. Societal impact: AI is a powerful technology, and it's important for industry leaders to consider the potential for harm, as well as the other ethical implications of their products. What is the success rate of AI start-ups? angle-down angle-up Estimates vary, but according to AI4SP, around 90% of AI start-ups fail. AI is highly competitive, and while billions of dollars are flowing into AI start-ups, those are typically for a select few companies with pedigreed founders and known products. Why do most AI start-ups fail? angle-down angle-up AI start-ups face competition for investment dollars and attention from users, plus there's only room for so many chatbots on the market. It's also difficult for these companies to make a profit right now, so raising cash is crucial. What are the risks of AI start-ups? angle-down angle-up Any start-up is risky, but AI start-ups face a number of risks, including an inability to raise cash, differentiate its product, and find a customer base.
| 2025-06-28T00:00:00 |
https://www.fool.com/investing/stock-market/market-sectors/information-technology/ai-stocks/ai-startups/
|
[
{
"date": "2025/06/28",
"position": 88,
"query": "AI employers"
}
] |
|
Salesforce says AI does 50% of company's work as ...
|
S.F.’s largest employer, which cut 1,000 jobs this year, says AI does 50% of the work
|
https://www.sfchronicle.com
|
[
"Rachel Swan"
] |
Salesforce, San Francisco's largest employer, says AI bots do 50% of the company's work. Experts see this as the start of a wave of workforce change.
|
The CEO of Salesforce, which resides in Salesforce Tower, said 50% of the company’s work is done by AI bots. Stephen Lam/The Chronicle
As one of San Francisco’s more outspoken tech leaders, Marc Benioff is no stranger to media firestorms, provoked by his unflinching stances on homelessness or surprise cheerleading for President Donald Trump.
The Salesforce CEO ignited a new controversy on Thursday, when he said during an episode of “The Circuit with Emily Chang” that artificial intelligence does “30 to 50% of the work” at his cloud computing company.
Long a happy warrior for AI, Benioff tried to put a positive spin on its encroachment into his company’s workforce culture. With bots taking over labor once performed by humans, he said, the human employees can “move on to do higher value work.”
Advertisement Article continues below this ad
But given that Salesforce has cut 1,000 positions this year, Benioff’s remark stung. Salesforce is extremely influential, both as the city’s top employer and a proponent of returning to the office. Benioff is also a highly visible public figure. His championing of robot labor comes at a moment of eviscerating layoffs across the tech industry. Although most companies haven’t blamed automation for these cuts, they coincide with a major industry push toward AI.
Salesforce CEO Marc Benioff is speaking publicly in support of using AI tools in the workforce. Analysts say he may have no choice but to do so. Brontë Wittpenn/S.F. Chronicle
After Thursday’s segment aired, immediately drawing more than 100,000 views, people pushed back on social media. A few self-identified Salesforce employees insisted the CEO had exaggerated, and that the human workers at Salesforce are too valuable to be replaced by software.
To industry observers, Benioff is just being realistic.
“There’s no doubt that AI agents are replacing, and will replace, a substantial chunk of the workforce,” said Professor Saikat Chaudhuri, faculty director of the Management, Entrepreneurship & Technology Program at UC Berkeley’s Haas School of Business.
Advertisement Article continues below this ad
Chaudhuri describes this moment as having a similar tectonic effect as the Internet Revolution, which caused pain for print media and brick-and-mortar stores, before opening a new world of possibilities. It became “something that people had to acknowledge,” Chaudhuri said, making some jobs obsolete but creating new ones.
He offered an example from the travel sector. In the old days, people made appointments with human travel agents to plan their vacations, find flights and handle other logistics. By today’s standards, the agents were expensive and inefficient, and became anachronisms once online booking took hold. At that point, consumers could plan trips on their own, by doing internet searches and entering their information into web pages that had to be built by human engineers.
Looking ahead, the travel agent could be revived, but not in human form. The new iteration would be a concierge-style AI bot that listens to the consumer’s requests and culls flight schedules instantaneously. With booking web pages no longer needed, the engineers are, theoretically, freed up for more creative pursuits.
Data gathered by economists at Stanford University corroborates that view, suggesting that Benioff, while bullish on AI deployment, isn’t necessarily an outlier. Rather, he’s pulling back the curtain on what’s actually a widespread practice. Usage spiked over the past two quarters, with 40% of firms across the country now saying they use generative AI at work — up from 30% last December, according to a survey called “The Labor Market Effects of Generative Artificial Intelligence.”
“It’s increasing very rapidly, even surprisingly,” said Jon Hartley, a policy fellow at Stanford’s Hoover Institution and lead author of the survey. Silicon Valley executives, in turn, have become more unapologetic about gambling in the technology. During a recent call with shareholders, Nvidia CEO Jensen Huang envisioned a future society with “billions of robots.”
Advertisement Article continues below this ad
At some level, corporations have an incentive to put out these messages, said Jeff Hancock, a professor of communication at Stanford and founding director of the Stanford Social Media Lab. Over the past few years, many businesses have invested heavily in AI programs and most are seeking some kind of return. They at least need to convey to shareholders that the bet was worthwhile.
Zeal from the C-suite doesn’t necessarily mean the employees are on board. Some might feel intimidated and reject the technology altogether. Others will simply program the software to do their jobs, viewing it as a substitute rather than a helper. Many will find this new phase of work to be discouraging and dehumanizing.
Two schools of thought have emerged around artificial intelligence, Hancock said. The first is a “pilot” mindset, which casts AI as a tool to augment performance and help people achieve their goals. Hancock describes the second mindset as that of a “passenger,” or someone who feels a loss of power and control when interacting with AI.
By many measures, Benioff seems to fit in the first camp. He embraced a concept called “agentic AI,” which refers to technology so sophisticated, it can accomplish tasks without human supervision. At its best, this class of AI should broaden possibilities for workers and create an opening for projects that previously would have been too burdensome. This is the AI that reads and summarizes your emails, manages your calendar, handles the customer service call with that person who wants to return shoes.
Benioff is so enamored of this model that he refers to Salesforce’s AI bots as an army of digital “agents.” According to Chang, he spent more than $20 million to license physicist Albert Einstein’s likeness for Salesforce’s AI branding. Salesforce seeks to have 1 billion active agents by the end of the year.
Advertisement Article continues below this ad
Whether Salesforce workers accept this new “AgentForce” depends largely on how they interpret Benioff’s attitude toward AI. And his remarks this past week could serve as an inflection point.
Because the technology is so new and could so profoundly change labor, executives are uniquely positioned to shape the mentality at their companies, Hancock said. If Benioff portrays AI as productive and liberating, then his optimism will flow down from managers to lower-level employees. Hancock calls this a “leadership cascade.”
On the flip side, if Salesforce employees construe Benioff’s comments as a warning that he plans to lay off half the staff, then people will feel degraded and overwhelmed, as though they’re being whip-sawed by new machinery.
That creates problems for employee retention, Hancock said. As the bots take over, the humans will leave. The question is where they go next.
Advertisement Article continues below this ad
Chaudhuri remains hopeful.
| 2025-06-28T00:00:00 |
2025/06/28
|
https://www.sfchronicle.com/sf/article/ai-work-employee-salesforce-20396370.php
|
[
{
"date": "2025/06/28",
"position": 99,
"query": "AI employers"
},
{
"date": "2025/06/28",
"position": 58,
"query": "AI layoffs"
}
] |
I Asked ChatGPT If AI Could Really Replace Our Day Jobs
|
I Asked ChatGPT If AI Could Really Replace Our Day Jobs — Here’s What It Said
|
https://www.yahoo.com
|
[] |
ChatGPT's final summation is that, “Yes, AI can replace or automate many traditional job functions. Fully replacing a day job with AI is possible, but usually ...
|
Many people are concerned that as AI technology advances, it could potentially take over roles that are traditionally filled by humans, putting people out of work for good. Others are actually looking forward to the mundane and monotonous tasks of their labor being replaced by AI. No matter how you view the scenario, is any of it true or even possible?
Read More: I Asked ChatGPT How Much Money I’ll Need To Retire in 5 Years
Explore Next: How Much Money Is Needed To Be Considered Middle Class in Your State?
GOBankingRates decided to ask AI itself, posing questions to ChatGPT about whether or not artificial intelligence is poised to replace your day job. Here is what it said:
Jobs That Are Already Being Augmented or Replaced by AI
ChatGPT responded, “You can replace some or even most aspects of a day job with artificial intelligence — but whether you can fully replace your specific job depends on several factors.”
Advertisement Advertisement
Advertisement Advertisement
The first factor is the type of job you are working. ChatGPT noted that types of assignments that are “Repetitive/Rule-Based” such as data entry, transcription and scheduling can be done by an AI. Information processing, like market research, report writing and analysis, are also able to be taken care of by AI.
Additionally, creative tasks including social media posting and customer support, are already being handled in numerous industries by artificial intelligence.
I’m a Self-Made Millionaire: Here’s How I Use ChatGPT To Make a Lot of Money
Goals for Having AI Replace Your Job
Next, ChatGPT asked what is the desired outcome of having AI fill the role or do the work of a human? “You want to replace income,” it stated, “you can build AI-based side hustles or businesses that may replace your salary.”
Advertisement Advertisement
Advertisement Advertisement
As some examples, ChatGPT listed selling AI-generated content (ebooks, art, templates), running a dropshipping or print-on-demand store with AI marketing, and offering AI-enhanced services (e.g., resume writing, website copy) as ways AI could aid in replacing your salary without you doing much heavy lifting.
If you want to replace your workload, ChatGPT outlined that “you can offload a huge chunk of repetitive or time-consuming tasks using AI, reducing your working hours. This is more about augmentation than replacement.”
Limitations and Considerations
In ChatGPT’s estimations, human judgment and creativity are still hard for AI to replicate at a deep level. On top of that, it pointed to legal and ethical concerns, including but not limited to violating intellectual property agreements and creating AI-generated misinformation. Even if artificial intelligence did take your job, ChatGPT predicted companies would probably require some sort of human oversight or hybrid roles to ensure the AI was doing the work correctly and on time.
Conclusion
ChatGPT’s final summation is that, “Yes, AI can replace or automate many traditional job functions. Fully replacing a day job with AI is possible, but usually requires building income streams or freelance-style work using AI tools. The more you understand how to use AI, the more you can reduce dependency on traditional nine to five roles.”
More From GOBankingRates
This article originally appeared on GOBankingRates.com: I Asked ChatGPT If AI Could Really Replace Our Day Jobs — Here’s What It Said
| 2025-06-28T00:00:00 |
https://www.yahoo.com/lifestyle/articles/asked-chatgpt-ai-could-really-110953213.html
|
[
{
"date": "2025/06/28",
"position": 19,
"query": "ChatGPT employment impact"
}
] |
|
AI's Rapid Workplace Shift: How to Secure Your Job in the ...
|
AI's Rapid Workplace Shift: How to Secure Your Job in the Age of Automation
|
https://www.investopedia.com
|
[
"Tobi Opeyemi Amure",
"Learn About Our",
"Editorial Policies",
"Peter Gratton",
"M.A.P.P.",
"Ph.D.",
"Is A New Orleans-Based Editor",
"Professor With Over Years Of Experience In Investing",
"Risk Management",
"Public Policy. Peter Began Covering Markets At Multex"
] |
AI automation is expected to threaten 300 million jobs globally by 2030. Learn which roles are most at risk and discover five expert-backed strategies to ...
|
The rapid rise of artificial intelligence (AI) is reshaping the workplace faster than most people realize. What started with automating back-office tasks and customer service roles has now expanded into programming, legal research, financial analysis, and even creative fields such as writing and design. Experts predict that by 2030, up to 30% of U.S. jobs could be automated, with as many as 300 million jobs globally at risk because of AI and related technologies.
As AI tools become smarter and more accessible, the line between human and machine work is blurring—and the pressure to adapt is mounting. If you’ve noticed your workflow getting “smarter” or your company talking more about efficiency than expertise, you’re not imagining things. The age of AI-driven disruption has arrived, and it’s rewriting the rules of the workplace worldwide.
Key Takeaways AI is rapidly automating roles in customer service, data entry, programming, content creation, and analysis-heavy jobs across finance, law, and medicine.
The most at-risk jobs are those with repetitive, rules-based, or entry-level tasks.
Human-centric skills like judgment, empathy, and creativity remain in demand.
Which Jobs Are Most At Risk from AI?
The first wave of AI automation swept through customer service, data entry, and routine administrative work, said Dima Gutzeit, CEO of LeapXpert, a New York-based tech vendor that provides modern business communication tools with AI capabilities.
Now, he said, even roles in software development, content creation, finance, law, and medicine are being reshaped by code-writing engines, AI copywriters, and data-crunching models. Entry-level and repetitive positions are especially vulnerable, as AI excels at handling foundational tasks that once helped early-career professionals gain a foothold.
A June 2025 study by the Federal Reserve Bank of Dallas argued that most claims for what AI will do are "speculative" at this point. Indeed, many—including the World Economic Forum—have argued that the jobs AI produces will far outnumber those it renders redundant—170 million versus 90 million, respectively.
Nevertheless, the jobs most at risk from language-modeling AI include clerks, administrative assistants, and certain teaching positions. The telltale signs your job could be next? Your daily workflow starts to feel more software-driven, tools gain “AI-powered” features, and management talks about “co-pilots” and “automated insights.” If your responsibilities are becoming more about overseeing software than applying your unique skills, it’s time to take action.
While AI is rapidly transforming the workplace, experts agree that the best way to stay relevant is to focus on the qualities that make us uniquely human.
Here are some strategies to avoid being replaced by AI:
1. Demonstrate Your Humanity
AI can process data, but it can’t replicate judgment, empathy, or ethical decision-making. “What sets you apart isn’t your ability to process data—it’s your ability to interpret it, communicate it, and act on it,” Gutzeit told Investopedia. Employers are increasingly valuing creativity and abilities that remain stubbornly human, like relationship-building and nuanced communication.
2. Become an AI Power User
Don’t just fear the new tools, master them. Learn how to use AI platforms relevant to your field, from prompt engineering in content creation to AI-driven analytics in finance. The fastest learners today will be tomorrow’s leaders. Experiment with AI, critique its output, and figure out how to make it work for you.
3. Automate the Repetitive, Focus on the Unique
Identify the mechanical parts of your job and automate them, freeing up time for higher-value work.
“Strip the mechanical from your day so you can invest in the interpersonal-relationships, storytelling, negotiation,” Gutzeit said. The more you focus on tasks AI can’t do, the more secure your position becomes.
4. Upskill Continuously
Stay ahead by regularly updating your technical and soft skills. Pair AI literacy with human-centric strengths: Combine analytics with storytelling, or prompt engineering with leadership. The best opportunities will go to those who can bridge the gap between algorithmic speed and human nuance.
5. Watch Industry Trends and Pivot Early
Monitor which roles and industries are being automated, and be proactive about moving into areas where human expertise is still essential. Look for companies that use AI to amplify, and not replace, human value.
“Professionals who understand that partnership create more value than either humans or machines can deliver alone," Gutzeit said.
The Bottom Line
AI isn’t just coming for your job; it’s already transforming the workforce. But the future belongs to those who adapt early, master new tools, and double down on the skills that make us human. It’s important to stay curious, proactive, and relentlessly focused on value. You can turn the AI revolution into an opportunity instead of a threat.
| 2025-06-28T00:00:00 |
https://www.investopedia.com/protect-your-job-from-ai-11755710
|
[
{
"date": "2025/06/28",
"position": 22,
"query": "future of work AI"
}
] |
|
How Will Artificial Intelligence Affect Jobs 2025-2030
|
How Will Artificial Intelligence Affect Jobs 2025-2030
|
https://www.nexford.edu
|
[] |
The World Economic Forum has estimated that artificial intelligence will replace some 85 million jobs by 2025. Freethink says that 65% of retail ...
|
How artificial intelligence will change the world
Will AI help the world or hurt it?
Like any controversial subject, there will always be people who are for it, and those that are against it. Artificial Intelligence is no different. In fact, as new ai tools are introduced, and the news around them grows, so the division between the two camps will grow with it.
Many market research analysts say that AI has the potential to bring about numerous positive changes in society, including enhanced productivity, improved healthcare, and increased access to education. But we need to adapt right now.
Others will say, mostly those working in human work types of jobs that are manually repetitive, that ai and robotics is a disruptive force and when it comes to the future of jobs it merely serves to steal jobs.
But robots and ai technologies can and will create a great many new vocations and help solve complex problems and make our daily lives easier and more convenient.
The jury is not yet out on this, but the leaning is more toward ai being a positive force rather than a negative one.
How will AI affect jobs and the economy?
McKinsey global institute says that at the global average level of adoption and absorption and advances in ai implied by their simulation, AI has the profound impact to deliver additional global economic activity of around $13 trillion in the foreseeable future and by 2030, or about 16% higher cumulative GDP compared with today.
This amounts to 1.2% additional GDP growth per year. If delivered, this impact would compare well with that of other general-purpose technologies through history. This will mainly come from substitution of labor by automation and increased innovation in products and services.
The same report went on to say that By 2030, the average simulation shows that some 70% of companies will have embraced the ai revolution and adopted at least one type of AI technology but that less than half will have fully absorbed the five categories.
Forbes say ai has the potential to be among the most disruptive technologies across global economies that we will ever develop.
How will artificial intelligence affect society and future?
Forbes says that the future of AI brings endless possibilities and applications that will help simplify our lives to a great extent. It will help shape the future and destiny of humanity positively, whilst Bernard Marr & Co says that the transformative impact of artificial intelligence on our society will have far-reaching economic, legal, political and regulatory implications on all types of jobs and industries that we need to be discussing and preparing for.
Others in the know say that AI has the potential to bring about numerous positive changes in society both now and in the future, including enhanced productivity, improved healthcare, and increased access to education. AI-powered technologies can also help solve complex problems and make our daily lives easier and more convenient.
How Will AI Affect Jobs - How many jobs will AI replace by 2030
Artificial intelligence (AI) could replace the equivalent of 300 million full-time jobs, a report by investment bank Goldman Sachs says. It could replace a quarter of work tasks in the US and Europe but may also mean new jobs and a productivity boom.
And it could eventually increase the total annual value of goods and services produced globally by 7%. The report also predicts two-thirds of jobs in the U.S. and Europe “are exposed to some degree of AI automation,” and around a quarter of all jobs could be performed by AI entirely.
Researchers from the University of Pennsylvania and OpenAI found some educated white-collar workers earning up to $80,000 a year are the most likely to be affected by workforce automation.
Forbes also says that According to an MIT and Boston University report, AI will replace as many as two million manufacturing workers by 2025.
A study by the McKinsey Global Institute reports that by 2030, at least 14% of employees globally could need to change their careers due to digitization, robotics, and AI advancements
What jobs are most likely to be automated?
1. Customer service representative
Most human customer service interactions are no longer done by phone with human employees manning the lines. Most of the time, the queries and problems of customers are repetitive.
Answering these queries does not require high emotional or social intelligence. Therefore, AI can be used to provide automated responses to frequently asked questions.
2. Receptionists
The majority of companies across the world are now using robots at their reception. Even the calls are being managed by AI now. For example, AimeReception can see, listen, understand, and talk with guests and customers.
3. Accountants/Bookkeepers
Many companies are now using automation and ai for their bookkeeping practices. AI-powered bookkeeping services provide an efficient accounting system and flexibility and security, considering that they are available as cloud-based services.
Using ai algorithms, AI will ensure the data is collected, stored, and analyzed correctly. Using an AI accounting service is significantly less costly than paying an employee’s salary to do the same job.
Are you ready to take your career to the next level?
Nexford's Career Path Planner takes into account your experience and interests to provide you with a customized roadmap to success.
Receive personalized advice on the skills and qualifications you need to get ahead in areas like finance, marketing, management and entrepreneurship.
Take the quiz to get started now!
4. Salespeople
Gone are the days when corporations required salespeople for advertising and retail activities. Advertising has shifted towards web and social media landscapes. The built-in target marketing capabilities in social media allow advertisers to create custom content for different types of audiences.
5. Research and analysis
The fields of data analysis and research are areas that already implement the use of artificial intelligence as a method of streamlining the process and identifying new data without human assistance.
The processing power of modern computers allows for the efficient sorting, extrapolation and analysis of data. As artificial intelligence continues to improve, there may not be a need for humans to play a role in data analysis and research.
6. Warehouse work
Online sales is a steadily growing industry and comes with an increasing need for processes and automated systems that efficiently get orders onto trucks for delivery.One area of focus for streamlining the process has been the use of automation.
Basic automation and artificial implementation in a warehouse allow for easy access to computerized systems to locate packages and direct staff, and future AI may even perform mechanized retrieval and loading to increase shipping capacities.
7. Insurance underwriting
When making assessments on the viability of insurance applicants, the most important work is often in analyzing the data available and applying it within a set of formulas or structures.
Automation can easily complete these tasks and is continually adapting to perform more complicated duties, which may reduce how many underwriters a company requires.
8. Retail
Self-checkout stations at stores are an example of automation in the retail sphere and have gained prominence in grocery stores and big-box outlets. When a company makes use of self-checkout areas, it results from a cost-benefit analysis.
Although allowing customers to scan their own items can increase the instances of theft, the company saves more money by reducing the need for employees working registers.
How to quickly change career
Experts say that ai and machine learning will help workers by creating more occupations than it replaces. That said, in order to ride the wave and build a new career, you have to have procured the skills necessary to get the job done.
If you're exposed to ai and looking to pivot into an AI-focused role, demonstrating your knowledge and experience with AI development can give you an edge.
Why not take a read of our top 10 highest paying AI jobs article here.
To acquire the skills to stand out from other would be candidates you should: ramp up your technical skills, complete online courses, understand the industry, gain work experience, and develop your soft skills.
AI will require extensive research and collaboration as it is still an emerging area. Soft skills will help set you apart from other developers who only have technical skills.
Which jobs will not be replaced by ai?
It is widely touted that ai will create more jobs than it replaces. Further to that, many in certain industries will breath a sigh of relief that ai will not threaten their vocation and livelihood.
These are some of the jobs that will not involve repetitive tasks and be prone to disruption. This means that ai will not replace those that perform them in the open labor market.
1. Teachers
Teachers often represent a reference point for many of us. Often, our academic decisions are partly based on how inspiring a particular teacher has been with us in the years prior. For all these reasons, it is almost impossible that we will have a fully digital teaching experience in the Future.
2. Lawyers and judges
These positions have a strong component of negotiation, strategy and case analysis. A lot is based on the personal experience and knowledge of each specialist.
It requires a certain set of skills to be able to navigate complex legal systems and argue in defense of a client in court. There is a human factor involved when it comes down to consider all the various aspects of a trial and take a final decision that could turn into years in prison, in the case of a Judge.
3. Directors, Managers and CEOs
Managing teams inside an organization is a matter of Leadership and this is not a stack of behaviors that can be written down in a code and processed in a linear way.
A CEO is also the person responsible for sharing the company’s mission and value down to the team. It is very unlikely that investors will ever feel comfortable investing in a company managed by robots or algorithms.
4. HR Managers
Although ai does assist in the hiring process to make sifting through CVs so much easier and quicker, Human Resource Managers still cover a variety of very important tasks inside an organization.
Hiring new professionals is just part of their prerogatives. They also are a key position inside the organization for maintaining the staff motivated, detecting early-on signs of discontent, and manage them if possible.
Are you ready to take your career to the next level?
Nexford's Career Path Planner takes into account your experience and interests to provide you with a customized roadmap to success.
Receive personalized advice on the skills and qualifications you need to get ahead in areas like finance, marketing, management and entrepreneurship.
Take the quiz to get started now!
5. Psychologists and Psychiatrists
Although a lot of face recognition technology is currently being used to develop initial AI counseling care and support, given the growing demand, mental health is a very delicate topic. Human touch is essential when it comes down to supporting people to succeed in their lives in all of the aspects that it can entail.
6. Surgeons
For sure, technology has seriously increased the accuracy with whom we are today able to diagnose and detect diseases in any medical report. Micro robotics also enhance the precision of the surgeons when it comes down to operation, enabling less invasive procedures.
But being a surgeon requires the ability to connect with the patient on so many other different levels while taking a vast number of the factor under consideration at the same time. Experience, knowledge, and skills acquired throughout the years are all factors that need to be condensed in a matter of minutes during an operation.
7. Computer System Analysts
No matter how automated we become, there will always be the need of a human presence that can run maintenance work, update, improve, correct, and set-up complex software and hardware systems that often require coordination among more than one specialist in order to properly work.
Reviewing the system capabilities, controlling the workflow and schedule improvements and increase automation is only part of a Computer System Analyst, a profession that is a great demand in the last years.
8. Artists and writers
Writing especially is such an imaginative fine art, and being able to place a specific selection of words in the right order is definitely a challenging endeavor.
So even if AI technically would have the capacity of absorbing the content of most books in the world, in probably any language and come up with a somewhat personal style of communication, the magic and thrill of creating art with words is something that is pretty much going to rest in our domain of competition in the years to come.
How many jobs will be lost to ai by 2025?
The World Economic Forum has estimated that artificial intelligence will replace some 85 million jobs by 2025. Freethink says that 65% of retail jobs could be automated by that year, saying that this is largely due to technological advancements, rising costs and wages, tight labor markets, and reduced consumer spending.
How many jobs will be lost to ai by 2030?
PwC estimates that by the mid-2030s, up to 30% of jobs could be automatable, with slightly more men being affected in the long run as autonomous vehicles and other machines replace many manual tasks where their share of employment is higher.
During the first and second waves, they estimate that women could be at greater risk of automation due to their higher representation in clerical and other administrative functions.
How to embrace AI and learn skills to take advantage of this new technology
You may be wondering how you can start familiarizing yourself with AI in your work to help advance your career. LinkedIn says that the good news is that you probably already have experience with AI whether you know it or not.
Asking voice assistants like Alexa and Siri questions uses AI, for example. Plenty of the apps on your phone also use AI, too. Generative AI, which is taking up all the headlines lately, is really the next step for this technology.
The company went on to say that to stay ahead in the era of artificial intelligence, it is essential to develop new skills and adapt to the changing job market. Here are some strategies for staying ahead in the era of artificial intelligence:
1. Embrace lifelong learning
In the era of AI, it is important to be constantly learning and adapting to new technologies and ways of working. This means taking courses, attending workshops and conferences, and keeping up-to-date with the latest trends in your industry.
2. Develop soft skills
While AI is great at performing routine tasks, it is still far from replicating human emotional intelligence and creativity. Developing soft skills such as communication, problem-solving, and collaboration will be crucial in the era of AI.
3. Be agile
In the era of AI, the ability to adapt quickly to changing circumstances will be key. This means being willing to learn new skills, take on new responsibilities, and pivot to new career paths.
4. Specialize
As AI becomes more ubiquitous, there will be increasing demand for workers with specialized skills and knowledge. By developing expertise in a particular area, you can increase your value to employers and differentiate yourself in the job market.
Learn from a next-gen university which embraces change
If there is one word that you need to take out of the way to transition from the current job market to the new world order of the job market affected by ai, is the word, 'agility'. The other is 'skills' and skills development at that.
Besides learning on the job, which can take a long time and effort for all concerned, many of those looking to switch careers or start a new one, are looking to online next-gen universities that can pivot on a penny and offer the programs at a specific period in time to take advantage of the drive to greater numbers of ai related jobs.
Here at Nexford University, we offer a BBA degree with a specialization in AI.
Doing the degree will mean that learners will learn and develop skills based on the latest employer needs and market trends – this is what the 100% online learning university calls their Workplace Alignment Model which is designed to equip those learners with the skills needed and what employers are looking for.
We also offer a MBA degree with specialization in advanced AI, for those looking for postgraduate education.
Conclusion
The neigh sayers have seemingly concluded that ai will take millions of jobs and put people out into the street, whilst those that are excited for it and ready to embrace the change are saying that ai has the ability to create more new types of jobs than it replaces.
That said, it would appear that resistance is futile, and that people must accept that artificial intelligence is becoming a part of our everyday lives. Every job role should embrace it, considering the efficient and cost-effective solutions it brings.
It lets people focus on more creative goals by automating the decision-making processes and tedious tasks.Artificial intelligence offers great promise to drive businesses forward, automate manufacturing processes, and deliver valuable insights.
AI is increasingly being used across various industries, including logistics, manufacturing, and cybersecurity. Small businesses have also made rapid progress in creating speech recognition software for mobile devices.
To stay ahead in the era of artificial intelligence, it is essential to embrace lifelong learning, develop soft skills, be agile, and specialize in a particular area. By developing these skills and adapting to the changing job market, workers can thrive in the era of AI and take advantage of the opportunities it presents.
Enrolling to do a BBA in Artificial Intelligence or an MBA in artificial intelligence can help people to get ahead and stay ahead in an ever evolving job market.
Nexford offers an online BBA program and online MBA program that equip learners with the necessary skills to succeed in the ever competitive ai job market and avoid job loss.
For a more in-depth analysis download our free report.
| 2025-06-29T00:00:00 |
https://www.nexford.edu/insights/how-will-ai-affect-jobs
|
[
{
"date": "2025/06/29",
"position": 1,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/29",
"position": 18,
"query": "job automation statistics"
},
{
"date": "2025/06/29",
"position": 10,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/29",
"position": 9,
"query": "AI labor market trends"
},
{
"date": "2025/06/29",
"position": 24,
"query": "ChatGPT employment impact"
},
{
"date": "2025/06/29",
"position": 10,
"query": "robotics job displacement"
},
{
"date": "2025/06/29",
"position": 2,
"query": "AI employment"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI impact jobs"
},
{
"date": "2025/06/29",
"position": 1,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/29",
"position": 17,
"query": "job automation statistics"
},
{
"date": "2025/06/29",
"position": 11,
"query": "AI labor market trends"
},
{
"date": "2025/06/29",
"position": 16,
"query": "ChatGPT employment impact"
},
{
"date": "2025/06/29",
"position": 11,
"query": "robotics job displacement"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI employment"
},
{
"date": "2025/06/29",
"position": 6,
"query": "artificial intelligence workers"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI impact jobs"
},
{
"date": "2025/06/29",
"position": 1,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/29",
"position": 4,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 18,
"query": "job automation statistics"
},
{
"date": "2025/06/29",
"position": 11,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/29",
"position": 7,
"query": "future of work AI"
},
{
"date": "2025/06/29",
"position": 13,
"query": "AI economic disruption"
},
{
"date": "2025/06/29",
"position": 10,
"query": "robotics job displacement"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI employment"
},
{
"date": "2025/06/29",
"position": 6,
"query": "artificial intelligence workers"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI impact jobs"
},
{
"date": "2025/06/29",
"position": 5,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 11,
"query": "AI economic disruption"
},
{
"date": "2025/06/29",
"position": 2,
"query": "AI employment"
},
{
"date": "2025/06/29",
"position": 9,
"query": "AI labor market trends"
},
{
"date": "2025/06/29",
"position": 8,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 1,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/29",
"position": 5,
"query": "artificial intelligence workers"
},
{
"date": "2025/06/29",
"position": 46,
"query": "automation job displacement"
},
{
"date": "2025/06/29",
"position": 8,
"query": "future of work AI"
},
{
"date": "2025/06/29",
"position": 19,
"query": "job automation statistics"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI employment"
},
{
"date": "2025/06/29",
"position": 19,
"query": "artificial intelligence employers"
},
{
"date": "2025/06/29",
"position": 1,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/29",
"position": 11,
"query": "future of work AI"
},
{
"date": "2025/06/29",
"position": 20,
"query": "job automation statistics"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI employment"
},
{
"date": "2025/06/29",
"position": 10,
"query": "AI labor market trends"
},
{
"date": "2025/06/29",
"position": 5,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 21,
"query": "artificial intelligence employers"
},
{
"date": "2025/06/29",
"position": 20,
"query": "job automation statistics"
},
{
"date": "2025/06/29",
"position": 11,
"query": "AI economic disruption"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI impact jobs"
},
{
"date": "2025/06/29",
"position": 12,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/29",
"position": 14,
"query": "ChatGPT employment impact"
},
{
"date": "2025/06/29",
"position": 92,
"query": "artificial intelligence wages"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI employment"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI impact jobs"
},
{
"date": "2025/06/29",
"position": 11,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/29",
"position": 5,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 15,
"query": "ChatGPT employment impact"
},
{
"date": "2025/06/29",
"position": 33,
"query": "artificial intelligence employers"
},
{
"date": "2025/06/29",
"position": 4,
"query": "artificial intelligence workers"
},
{
"date": "2025/06/29",
"position": 18,
"query": "job automation statistics"
},
{
"date": "2025/06/29",
"position": 9,
"query": "AI economic disruption"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI impact jobs"
},
{
"date": "2025/06/29",
"position": 11,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/29",
"position": 5,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 15,
"query": "ChatGPT employment impact"
},
{
"date": "2025/06/29",
"position": 22,
"query": "artificial intelligence employers"
},
{
"date": "2025/06/29",
"position": 1,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/29",
"position": 5,
"query": "artificial intelligence workers"
},
{
"date": "2025/06/29",
"position": 57,
"query": "automation job displacement"
},
{
"date": "2025/06/29",
"position": 6,
"query": "future of work AI"
},
{
"date": "2025/06/29",
"position": 20,
"query": "job automation statistics"
},
{
"date": "2025/06/29",
"position": 16,
"query": "robotics job displacement"
},
{
"date": "2025/06/29",
"position": 9,
"query": "AI economic disruption"
},
{
"date": "2025/06/29",
"position": 9,
"query": "AI labor market trends"
},
{
"date": "2025/06/29",
"position": 3,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 16,
"query": "ChatGPT employment impact"
},
{
"date": "2025/06/29",
"position": 19,
"query": "artificial intelligence employers"
},
{
"date": "2025/06/29",
"position": 1,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/29",
"position": 48,
"query": "automation job displacement"
},
{
"date": "2025/06/29",
"position": 8,
"query": "future of work AI"
},
{
"date": "2025/06/29",
"position": 11,
"query": "robotics job displacement"
},
{
"date": "2025/06/29",
"position": 10,
"query": "AI economic disruption"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI employment"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI impact jobs"
},
{
"date": "2025/06/29",
"position": 9,
"query": "AI labor market trends"
},
{
"date": "2025/06/29",
"position": 5,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 1,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/29",
"position": 4,
"query": "artificial intelligence workers"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI employment"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI impact jobs"
},
{
"date": "2025/06/29",
"position": 9,
"query": "AI labor market trends"
},
{
"date": "2025/06/29",
"position": 3,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 16,
"query": "ChatGPT employment impact"
},
{
"date": "2025/06/29",
"position": 35,
"query": "artificial intelligence employers"
},
{
"date": "2025/06/29",
"position": 42,
"query": "automation job displacement"
},
{
"date": "2025/06/29",
"position": 19,
"query": "job automation statistics"
},
{
"date": "2025/06/29",
"position": 9,
"query": "AI economic disruption"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI employment"
},
{
"date": "2025/06/29",
"position": 12,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/29",
"position": 6,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 4,
"query": "artificial intelligence workers"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI employment"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI impact jobs"
},
{
"date": "2025/06/29",
"position": 10,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/29",
"position": 9,
"query": "AI labor market trends"
},
{
"date": "2025/06/29",
"position": 3,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 1,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/29",
"position": 60,
"query": "automation job displacement"
},
{
"date": "2025/06/29",
"position": 24,
"query": "job automation statistics"
},
{
"date": "2025/06/29",
"position": 12,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/29",
"position": 9,
"query": "AI labor market trends"
},
{
"date": "2025/06/29",
"position": 3,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 18,
"query": "artificial intelligence employers"
},
{
"date": "2025/06/29",
"position": 1,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/29",
"position": 5,
"query": "artificial intelligence workers"
},
{
"date": "2025/06/29",
"position": 48,
"query": "automation job displacement"
},
{
"date": "2025/06/29",
"position": 7,
"query": "future of work AI"
},
{
"date": "2025/06/29",
"position": 11,
"query": "robotics job displacement"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI impact jobs"
},
{
"date": "2025/06/29",
"position": 3,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 61,
"query": "artificial intelligence wages"
},
{
"date": "2025/06/29",
"position": 49,
"query": "automation job displacement"
},
{
"date": "2025/06/29",
"position": 8,
"query": "future of work AI"
},
{
"date": "2025/06/29",
"position": 19,
"query": "job automation statistics"
},
{
"date": "2025/06/29",
"position": 12,
"query": "robotics job displacement"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI impact jobs"
},
{
"date": "2025/06/29",
"position": 12,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/29",
"position": 9,
"query": "AI labor market trends"
},
{
"date": "2025/06/29",
"position": 3,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 16,
"query": "ChatGPT employment impact"
},
{
"date": "2025/06/29",
"position": 5,
"query": "artificial intelligence workers"
},
{
"date": "2025/06/29",
"position": 51,
"query": "automation job displacement"
},
{
"date": "2025/06/29",
"position": 11,
"query": "robotics job displacement"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI employment"
},
{
"date": "2025/06/29",
"position": 12,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/29",
"position": 9,
"query": "AI labor market trends"
},
{
"date": "2025/06/29",
"position": 3,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 1,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/29",
"position": 56,
"query": "automation job displacement"
},
{
"date": "2025/06/29",
"position": 6,
"query": "future of work AI"
},
{
"date": "2025/06/29",
"position": 16,
"query": "robotics job displacement"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI employment"
},
{
"date": "2025/06/29",
"position": 3,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 17,
"query": "ChatGPT employment impact"
},
{
"date": "2025/06/29",
"position": 21,
"query": "artificial intelligence employers"
},
{
"date": "2025/06/29",
"position": 5,
"query": "artificial intelligence workers"
},
{
"date": "2025/06/29",
"position": 49,
"query": "automation job displacement"
},
{
"date": "2025/06/29",
"position": 10,
"query": "future of work AI"
},
{
"date": "2025/06/29",
"position": 12,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/29",
"position": 10,
"query": "AI labor market trends"
},
{
"date": "2025/06/29",
"position": 16,
"query": "ChatGPT employment impact"
},
{
"date": "2025/06/29",
"position": 29,
"query": "artificial intelligence employers"
},
{
"date": "2025/06/29",
"position": 46,
"query": "automation job displacement"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI impact jobs"
},
{
"date": "2025/06/29",
"position": 10,
"query": "AI labor market trends"
},
{
"date": "2025/06/29",
"position": 1,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/29",
"position": 19,
"query": "job automation statistics"
},
{
"date": "2025/06/29",
"position": 16,
"query": "robotics job displacement"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI impact jobs"
},
{
"date": "2025/06/29",
"position": 5,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 1,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/29",
"position": 52,
"query": "automation job displacement"
},
{
"date": "2025/06/29",
"position": 19,
"query": "job automation statistics"
},
{
"date": "2025/06/29",
"position": 9,
"query": "AI economic disruption"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI employment"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI impact jobs"
},
{
"date": "2025/06/29",
"position": 9,
"query": "AI labor market trends"
},
{
"date": "2025/06/29",
"position": 3,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 23,
"query": "artificial intelligence employers"
},
{
"date": "2025/06/29",
"position": 1,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/29",
"position": 19,
"query": "job automation statistics"
},
{
"date": "2025/06/29",
"position": 9,
"query": "AI economic disruption"
},
{
"date": "2025/06/29",
"position": 12,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/29",
"position": 5,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 15,
"query": "ChatGPT employment impact"
},
{
"date": "2025/06/29",
"position": 22,
"query": "artificial intelligence employers"
},
{
"date": "2025/06/29",
"position": 4,
"query": "artificial intelligence workers"
},
{
"date": "2025/06/29",
"position": 48,
"query": "automation job displacement"
},
{
"date": "2025/06/29",
"position": 8,
"query": "future of work AI"
},
{
"date": "2025/06/29",
"position": 12,
"query": "robotics job displacement"
},
{
"date": "2025/06/29",
"position": 9,
"query": "AI economic disruption"
},
{
"date": "2025/06/29",
"position": 6,
"query": "AI employment"
},
{
"date": "2025/06/29",
"position": 12,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/29",
"position": 3,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 57,
"query": "automation job displacement"
},
{
"date": "2025/06/29",
"position": 11,
"query": "robotics job displacement"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI employment"
},
{
"date": "2025/06/29",
"position": 8,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/29",
"position": 5,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 10,
"query": "ChatGPT employment impact"
},
{
"date": "2025/06/29",
"position": 100,
"query": "automation job displacement"
},
{
"date": "2025/06/29",
"position": 74,
"query": "job automation statistics"
},
{
"date": "2025/06/29",
"position": 12,
"query": "AI economic disruption"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI employment"
},
{
"date": "2025/06/29",
"position": 19,
"query": "artificial intelligence employers"
},
{
"date": "2025/06/29",
"position": 1,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/29",
"position": 10,
"query": "future of work AI"
},
{
"date": "2025/06/29",
"position": 82,
"query": "job automation statistics"
},
{
"date": "2025/06/29",
"position": 12,
"query": "AI economic disruption"
},
{
"date": "2025/06/29",
"position": 6,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 28,
"query": "artificial intelligence employers"
},
{
"date": "2025/06/29",
"position": 84,
"query": "job automation statistics"
},
{
"date": "2025/06/29",
"position": 12,
"query": "robotics job displacement"
},
{
"date": "2025/06/29",
"position": 2,
"query": "AI employment"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI impact jobs"
},
{
"date": "2025/06/29",
"position": 13,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/29",
"position": 11,
"query": "AI labor market trends"
},
{
"date": "2025/06/29",
"position": 5,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 10,
"query": "ChatGPT employment impact"
},
{
"date": "2025/06/29",
"position": 2,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/29",
"position": 8,
"query": "artificial intelligence workers"
},
{
"date": "2025/06/29",
"position": 83,
"query": "job automation statistics"
},
{
"date": "2025/06/29",
"position": 8,
"query": "robotics job displacement"
},
{
"date": "2025/06/29",
"position": 12,
"query": "AI economic disruption"
},
{
"date": "2025/06/29",
"position": 29,
"query": "AI employers"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI employment"
},
{
"date": "2025/06/29",
"position": 1,
"query": "AI impact jobs"
},
{
"date": "2025/06/29",
"position": 12,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/29",
"position": 5,
"query": "AI labor market trends"
},
{
"date": "2025/06/29",
"position": 4,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 2,
"query": "ChatGPT employment impact"
},
{
"date": "2025/06/29",
"position": 2,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/29",
"position": 7,
"query": "artificial intelligence workers"
},
{
"date": "2025/06/29",
"position": 1,
"query": "automation job displacement"
},
{
"date": "2025/06/29",
"position": 13,
"query": "future of work AI"
},
{
"date": "2025/06/29",
"position": 3,
"query": "job automation statistics"
},
{
"date": "2025/06/29",
"position": 5,
"query": "machine learning workforce"
},
{
"date": "2025/06/29",
"position": 1,
"query": "robotics job displacement"
},
{
"date": "2025/06/29",
"position": 30,
"query": "workplace AI adoption"
}
] |
|
AI could cause newsprint to outlive the hyperlink
|
AI could cause newsprint to outlive the hyperlink
|
https://mattdpearce.substack.com
|
[
"Matt Pearce"
] |
... journalism) and publishers (who have to pay for it). Reporters tend to be more sanguine about open-sourcing and unpaywalling their best ...
|
When it comes to journalistic intellectual property — what you and I normally call the news — there’s an inherent tension inside traditional commercial newsrooms between reporters (who do the journalism) and publishers (who have to pay for it).
Reporters tend to be more sanguine about open-sourcing and unpaywalling their best stuff for the largest audiences possible. That big scoop doesn’t get much impact if nobody knows about it! As long as the facts get out there, you’ve done your job for the democracy, right? It’s the boss who has to process the biweekly payroll who’s touchier about PopCrave ripping off a quality reporter’s work without chipping in for salary.
But those traditional newsrooms have been crumbling, shoestring indiedom surging, collapsing the old class division between crusading journalist and bill-paying publisher. There’s a grouchy new synthesis: The ripped-off reporter-businessperson, for whom impact and neglect can look like the same thing.
The excellent records hound Seamus Hughes of CourtWatch, a fellow Project C member who I just bumped into at the Investigative Reporters and Editors conference in New Orleans, describes the vampire swamp of the digital news ecosystem as scoop-minded indie journalists encounter it:
With 11,000 subscribers, no outside funding, no paid ads, no special SEO magic – we are used to people taking our reporting, repacking it and reaching a larger audience with proper attribution. Hell, we have an entire page on our site dedicated to highlighting that. Having been a terrorism scholar for the last two decades and a reporter for half that time, we knew it was an interesting case so we partnered with our friends at 404 Media to report it out. We assumed that other news organizations would also take notice of our reporting, cite it, and write their own copy. That’s how journalism is supposed to work. But we don’t think we fully appreciated how much the Internet ecosystem and parts of the established news organizations are parasites to original reporting. [Subscribe to Courtwatch here.]
If you’ve managed to get the goods, it’s often somebody else transmuting your journalistic lead into traffic gold. Maybe it’s some day-late New York Times reporter with slower feet but a huger platform, or some rando creator who’s really charismatic (and more casually defamatory) on TikTok. Very frustrating, this dynamic. And very hard to solve in a digital ecosystem increasingly contemptuous of citing the sources of digital information.
But there’s also something much weirder and bigger happening right now with the third-party extraction of value from higher-quality digital journalism.
In Cannes last week, Cloudflare CEO Matthew Prince reeled off numbers about the exploding robotic readership of journalists’ journalism. Axios:
Startling stat: Ten years ago, Google crawled two pages for every visitor it sent a publisher, per Prince. He said that six months ago: For Google that ratio was 6:1 For OpenAI, it was 250:1 For Anthropic, it was 6,000:1 Now: For Google, it's 18:1 For OpenAI, it's 1,500:1 For Anthropic, it's 60,000:1
While journalists are starved for attention from flesh-and-blood humans — Pew says just 17% of Americans pay for news — publishers’ eroding traffic from humans on platforms is being replaced by AI training visits.
"The future of the web is going to be more and more like AI, and that means that people are going to be reading the summaries of your content, not the original content,” Prince told Axios.
Put another way: For the first couple of hundred years of journalism’s history, humans were the primary readers of a journalist’s work. But in 2025, a reporter’s most loyal audience is the machine.
It’s the bill-paying publishers of those legacy-type newsrooms who have been most keyed up about this AI scrapage and what to do about it. The word leverage comes up a lot — in the sense of not having any if you’re putting journalism on an open web. The Atlantic:
At least 72 licensing deals have been made between publishers and AI companies in the past two years. But figuring out how to approach these deals is no easy task. Caccappolo told me he has “felt a tremendous imbalance at the negotiating table”—a sentiment shared by others I spoke with. One problem is that there is no standard price for training an LLM on a book or an article. The AI companies know what kinds of content they want, and having already demonstrated an ability and a willingness to take it without paying, they have extraordinary leverage when it comes to negotiating. I’ve learned that books have sometimes been licensed for only a couple hundred dollars each, and that a publisher that asks too much may be turned down, only for tech companies to take their material anyway… A publisher’s negotiating power is also limited by the degree to which it can stop an AI company from using its work without consent. There’s no surefire way to keep AI companies from scraping news websites; even the Robots Exclusion Protocol, the standard opt-out method available to news publishers, is easily circumvented.
“There’ll be creators who will create for AI,” Google CEO Sundar Pichai said of this conundrum, at the Dealbook Summit. “People will figure it out.”
Well, Cloudflare is one of the major tollbooths of the internet, better known for thwarting DDoS attacks, and CEO Matthew Prince’s AI saber-rattling suggests publishers could gain bargaining power by throwing down spike strips on the information superhighway. In March, Cloudflare announced the AI Labryinth, “a new mitigation approach that uses AI-generated content to slow down, confuse, and waste the resources of AI Crawlers and other bots that don’t respect ‘no crawl’ directives.” At what point is it cheaper to pay a publisher to stop triggering higher AI energy costs?
There’s another painful solution to this AI conundrum: slamming shut the borders of the open web. Paywalls on stories had already taken many commercial publishers halfway there. What about turning away from the traffic spigot entirely?
Some larger digital newsrooms are already laying off staff or otherwise hunkering down to prepare for Google Zero, the day referral traffic finally dies. Indie local news publishers I know, already frustrated by the junkiness of digital distribution, are increasingly turning to in-person events, print editions and zines and printed handout cards with QR codes.
A news business still counting on referral traffic is a news business built for the 2010s. The hyperlink is a legacy news medium that might currently be in steeper decline than newsprint. The new question is whether you’ll want robot readers, and if they’re paying customers.
| 2025-06-29T00:00:00 |
https://mattdpearce.substack.com/p/ai-could-cause-newsprint-to-outlive
|
[
{
"date": "2025/06/29",
"position": 89,
"query": "AI journalism"
},
{
"date": "2025/06/29",
"position": 85,
"query": "AI journalism"
}
] |
|
Goodbye to thousands of jobs at Amazon - artificial intelligence is ...
|
Goodbye to thousands of jobs at Amazon – artificial intelligence is already replacing workers in key roles
|
https://unionrayo.com
|
[] |
Duolingo: it will replace their employees in charge of repetitive tasks by AI, and just in the case of being unable to automate the teamwork ...
|
Amazon announces AI will transform the work structure of the company in the U.S. Being one of the most influential companies in the world, Amazon has started a new strategy incorporating artificial intelligence to its workforce. This translates into many corporate jobs probably disappearing in the next few years, mostly the ones in which AI can do the tasks in a more efficient way.
This strategy is part of a global trend that is changing the way we work and starts the debate about the future of our jobs in artificial intelligence times. So, let’s see how Amazon is trying to incorporate this tool.
Amazon and AI
Andy Jassy, Amazon CEO, has announced this week they will be cutting the corporate workforce in the following years because they want to make use of artificial intelligence (AI). Why? Well, it’s commonly known that AI is showing huge improvements when it comes to efficiency and the more developed it is, the more efficient it will be.
Jassy explained that as AI starts getting more into the company processes, human presence won’t be necessary in some jobs. However, as AI gets included, it is said other jobs will appear to cover technological needs.
An investment of millions
Amazon is one of the companies with the highest number of employees in the world, more than 1.5 million people work at Amazon. However, the investment on AI is making the company spend around $100 billion in order to improve the AI services and build more data centers to make these systems bigger.
Last year, the investment in AI from Amazon was $83 billion, which shows the company is putting their faith in technology very fast.
New ways of working
The CEO of Amazon also said that AI agents, those programs capable of doing tasks on their own, will change the way we live and work. He’s talking about something that doesn’t exist in its majority, but he is convinced they will all be here very soon. What’s more, he drew attention to the fact that these tools will increase the innovation speed, which will be beneficial for Amazon clients.
If we count all Amazon’s services and AI applications, they have more than thousand of these working or in development in the company. So, they know what they are talking about.
Worrying among workers
This situation is making employees in the corporate world feel confused and worried about their work situation, since Amazon will influence other companies (and already doing it) to incorporate AI to do the tasks which are done by humans at the moment.
According to a study by Bloomberg Intelligence, AI could be taking up to 200,000 jobs in the banking sector and, as a consequence, spreading the uncertainty to other sectors about what will happen to their employees and their jobs.
Are other companies copying Amazon’s strategy?
Of course, companies from other sectors are already starting to introduce AI as a strategy to improve efficiency. Let’s see what companies are:
CrowdStrike: cybersecurity company that fired 5% of their workers in May.
Shopify: where the CEO said managers have to show tasks at this company can’t be done by AI before more employees get fired.
Duolingo: it will replace their employees in charge of repetitive tasks by AI, and just in the case of being unable to automate the teamwork more, more jobs will be announced.
BT Group CEO (UK) said they are thinking about firing 400,000 jobs in the next decade, but he warned this figure doesn’t show the impact AI could have.
So, as you can see AI seems more like a threat for all these people who have been trained for these jobs and have been working so long. We don’t know what the future will be and if we could really coexist with AI in the work environment. Let’s hope there’s a chance of humans and new technology working together.
| 2025-06-29T00:00:00 |
2025/06/29
|
https://unionrayo.com/en/amazon-jobs-replace-ai-artificial-intelligence/
|
[
{
"date": "2025/06/29",
"position": 43,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 38,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 43,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 41,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 38,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 40,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 42,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 39,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 38,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 27,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 39,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 39,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 39,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 42,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 38,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 41,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 42,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 42,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 42,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 37,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 38,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 38,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 36,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 40,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 49,
"query": "artificial intelligence labor union"
}
] |
Anthropic Program Probes 'Good and Bad' of AI Disruption
|
Anthropic Program Probes ‘Good and Bad’ of AI Disruption
|
https://www.pymnts.com
|
[] |
Anthropic has debuted a program to study AI's impact on the labor market and come up with policy proposals for this economic shift.
|
Anthropic has debuted a program to study artificial intelligence’s (AI) impact on the labor market.
By completing this form, you agree to receive marketing communications from PYMNTS and to the sharing of your information with our sponsor, if applicable, in accordance with our Privacy Policy and Terms and Conditions .
Complete the form to unlock this article and enjoy unlimited free access to all PYMNTS content — no additional logins required.
The AI company’s Economic Futures Program, announced Friday (June 27) will also help come up with policy proposals to ready the world for this economic shift, TechCrunch reported.
“Everybody’s asking questions about what are the economic impacts [of AI], both positive and negative,” Sarah Heck, head of policy programs and partnerships at Anthropic, told TechCrunch. “It’s really important to root these conversations in evidence and not have predetermined outcomes or views on what’s going to [happen].”
The report noted that among the prominent figures to offer their views on the potential economic impact of AI is Dario Amodei, Anthropic’s chief executive.
Last month, he predicted AI could eliminate half of all entry-level white-collar jobs and send unemployment to as high as 20% in the coming years.
Asked by TechCrunch if one of the goals of the program was to research ways to alleviate AI-related job loss, Heck was “cautious,” the report said, arguing that the disruptive shifts AI will bring could be “both good and bad.”
“I think the key goal is to figure out what is actually happening,” she said. “If there is job loss, then we should convene a collective group of thinkers to talk about mitigation. If there will be huge GDP expansion, great. We should also convene policy makers to figure out what to do with that. I don’t think any of this will be a monolith.”
PYMNTS reported last month on new research that examined how how AI agents performed in a simulated work environment.
The findings? While AI agents can enhance the productivity of workers, “they’re not ready to replace real-world human jobs,” said co-author Boxuan Li in an interview with PYMNTS.
As that report noted, these results stand in contrast to the vast amounts being invested in AI agents by companies betting on the idea of smart automation.
“So much money is going to the agent area,” noted co-author Yufan Song in an interview with PYMNTS. Agents “can help speed up our productivity, but to replace humans, I think, still needs some time.”
Meanwhile, PYMNTS Intelligence research has shown that 54% of workers are concerned that generative AI poses a “significant risk of widespread job displacement.” This worry was more common among workers who showed some familiarity with generative AI platforms at 57%, while just 41% of those unfamiliar with AI platforms expressed similar concerns.
| 2025-06-29T00:00:00 |
2025/06/29
|
https://www.pymnts.com/artificial-intelligence-2/2025/anthropic-program-probes-good-and-bad-of-ai-disruption/
|
[
{
"date": "2025/06/29",
"position": 81,
"query": "AI economic disruption"
},
{
"date": "2025/06/29",
"position": 96,
"query": "AI economic disruption"
},
{
"date": "2025/06/29",
"position": 77,
"query": "AI economic disruption"
},
{
"date": "2025/06/29",
"position": 76,
"query": "AI economic disruption"
},
{
"date": "2025/06/29",
"position": 77,
"query": "AI economic disruption"
},
{
"date": "2025/06/29",
"position": 91,
"query": "AI economic disruption"
},
{
"date": "2025/06/29",
"position": 65,
"query": "AI economic disruption"
},
{
"date": "2025/06/29",
"position": 66,
"query": "AI economic disruption"
}
] |
10 Artificial Intelligence (AI) Companies to Buy Now and Hold Forever
|
10 Artificial Intelligence (AI) Companies to Buy Now and Hold Forever
|
https://www.fool.com
|
[
"Scott Levine"
] |
1. Nvidia · 2. Alphabet · 3. Microsoft · 4. Meta Platforms · 5. Broadcom · 6. Amazon · 7. Palantir Technologies · 8. Taiwan Semiconductor.
|
From the growth of self-driving cars to the explosion in generative artificial intelligence (AI) capabilities, it's clear that AI is going to become increasingly integrated in our lives.
Recognizing this fact, investors should keep tabs on leading AI companies since these stocks have the potential to provide sizable returns in the years to come.
1. Nvidia
Nvidia (NVDA -0.46%) is a semiconductor stalwart that pioneered the development of the graphics processing unit (GPU). Invaluable for AI applications, GPUs are also critical components found in data centers, where AI computing occurs.
The company consistently generates strong free cash flow -- just one of many reasons why Nvidia stock is a must-consider for any investor looking to gain AI exposure.
2. Alphabet
The parent company of numerous businesses, Alphabet (GOOG 0.85%) (GOOGL 0.79%) incorporates its large language model (LLM) chatbot, Gemini, into offerings like Google Search and Android phones. Other companies also integrate Gemini into their products, like visual messaging provider Snap and strategy and consulting leader Accenture.
Besides Gemini, Alphabet provides extensive AI exposure through its cloud computing service, Google Cloud.
3. Microsoft
Expanding beyond the software offerings that initially made it famous, Microsoft (MSFT -0.01%) offers AI exposure through its generative AI chatbot, Copilot, found in several Microsoft products like Microsoft 365. Investors also gain AI exposure through the company's cloud computing platform, Microsoft Azure.
Microsoft also provides indirect AI exposure as the company is a major investor in OpenAI, the owner of ChatGPT.
4. Meta Platforms
Meta Platforms (META 0.46%) may be most recognizable as the parent company of Facebook, but the company emerged as a leader in AI tools after developing Meta AI, an AI-powered assistant that's integrated in other Meta apps and built on the Llama LLM.
In June 2025, Meta broadened its AI reach with a $14.3 billion investment in Scale AI, a company pursuing artificial general intelligence.
5. Broadcom
Like Nvidia, Broadcom (AVGO 0.48%) is another leading semiconductor stock that has close ties to the AI industry. Data center growth is contributing to strong demand for Broadcom's AI accelerators. For Q2 2025, Broadcom reported over $4.4 billion in AI semiconductor revenue, a 46% year-over-year increase. AI networking represented 40% of AI revenue, a 70% year-over-year gain.
6. Amazon
Once upon a time, Amazon (AMZN 0.29%) was merely a bookseller. Today, however, it has a robust cloud computing business. Launched almost 20 years ago, Amazon Web Services has emerged as a premier cloud computing option, providing the foundation for companies to develop their own AI resources as well as AI services and tools like Amazon Bedrock and Amazon SageMaker.
At the end of 2024, AWS achieved a $115 annualized revenue run rate. For context, Amazon reported total revenue of $638 billion for 2024. Considering its scale and its dedication to innovation, Amazon is sure to remain a premier AI force for years to come.
7. Palantir Technologies
From assisting customers with data integration, to security and compliance, to healthcare advances, to supporting the militaries of the U.S. and allies, software company Palantir Technologies (PLTR 4.97%) developed a sophisticated platform for analyzing large datasets.
In strong financial health, Palantir is consistently profitable and ended the first quarter 2025 with $5.4 billion in cash and cash equivalents with no debt. Plus, it routinely generates strong free cash flow.
8. Taiwan Semiconductor
With its Dedicated IC Foundry business model, Taiwan Semiconductor Manufacturing (TSM -0.70%) produces semiconductors for customers instead of original semiconductors for itself. Nvidia, for example, is a Taiwan Semiconductor customer, turning to it for help in production of the Blackwell GPU, which is used in AI applications.
Illustrating its strong exposure to AI, Taiwan Semiconductor stated that 2024 revenue from AI accelerators represented "close to mid-teens percent" of its total revenue.
9. Tesla
Most recognize Tesla (TSLA 1.14%) for its electric vehicles (EVs) but its leadership in AI warrants recognition. For one, the company's EVs have sophisticated autonomous driving capability -- capability that's only expected to increase -- and it's making steady progress in advancing its robotaxi business.
Tesla reported about $5 billion in 2024 AI-related capital expenditures, and it expects about the same in 2025. Considering Elon Musk's enthusiasm for AI, it would be unsurprising if Musk moves toward a Tesla acquisition of his AI start-up, xAI.
10. CoreWeave
Providing infrastructure for AI computing, CoreWeave (CRWV 5.37%) developed a cloud platform to support AI's high computing demands. The allure of its technology is highlighted by its recent $11.9 billion deal with OpenAI to develop AI infrastructure.
CoreWeave is in rapid growth mode. In Q1 2025, it reported revenue of $982 million, a year-over-year increase of 420% resulting from high demand for the company's cloud platform.
| 2025-06-29T00:00:00 |
2025/06/29
|
https://www.fool.com/investing/2025/06/29/10-artificial-intelligence-ai-companies-to-buy-now/
|
[
{
"date": "2025/06/29",
"position": 16,
"query": "AI employers"
}
] |
This Dirt Cheap Healthcare Stock Could Be a Hidden Artificial ...
|
This Dirt Cheap Healthcare Stock Could Be a Hidden Artificial Intelligence (AI) Opportunity (Hint: It's Not Eli Lilly)
|
https://finance.yahoo.com
|
[
"Adam Spatacco",
"The Motley Fool",
"Sun",
"Jun",
"Min Read"
] |
Artificial intelligence (AI) has the potential to transform several different areas of the healthcare industry.
|
But before you go writing UnitedHealth off as a broken business, let's examine how AI has the potential to help the health insurance industry and how UnitedHealth specifically could implement this technology to improve the business over time.
In short order, the stock price plunged and has shown no indications of recovery, so far. For 2025, share prices are down 40%, making UnitedHealth the poorest-performing stock in the Dow Jones Industrial Average this year.
Back in April, UnitedHealth greatly disappointed investors after the company published revised financial guidance that indicated a lower-than-expected earnings outlook for the remainder of the year. Management blamed the lower profitability on two primary factors. First, utilization rates in the company's Medicare Advantage program exceeded internal forecasts, taking a toll on the company's cost structure. Second, reimbursements in the company's pharmacy benefits management (PBM) platform, Optum Health, were negatively impacted by reductions in Medicare funding as well as changes to some of the patient demographic profiles in this segment of the business.
While such use cases are exciting, I see another pocket of the healthcare industry that could be positively disrupted by AI: insurance. Let's explore why UnitedHealth Group (NYSE: UNH) could be an under-the-radar growth opportunity because of the intersection between healthcare and AI.
Both companies are also looking into the potential that artificial intelligence (AI) can bring to their operations -- and for good reason. Accounting and consulting firm PwC estimates that the total addressable market (TAM) for AI in healthcare could reach $868 billion by 2030. One of the obvious applications that AI has for healthcare is facilitating pharmaceutical companies in clinical trials and drug discovery.
When it comes to popular healthcare stocks, investors have focused a lot of attention lately on Eli Lilly and Novo Nordisk and the potential of their blockbuster weight management treatments, including Mounjaro, Zepbound, Ozempic, and Wegovy. While these drugs are likely to lead to billions in revenue, Lilly and Novo aren't relying solely on these drugs to grow their businesses.
UnitedHealth Group experienced some operational challenges this year, but AI could wipe away these shortcomings in the long run.
Insurance is another healthcare-related industry likely to benefit from AI, which could aid scenario modeling, predictive analytics, and natural language processing.
One major potential use case for AI in healthcare is drug discovery for pharmaceutical companies.
Story Continues
...AI has the potential to transform the business
The underlying issue surrounding UnitedHealth's challenges right now has to do with forecasting. There isn't anything fundamentally broken with the business. Rather, unforeseen changes in the macroeconomic environment led to a different reality than what management had previously modeled -- ultimately leading to higher costs and compressed profit margins.
By using machine learning, UnitedHealth could train AI models on claims data and subsequently integrate these feeds into electronic health records (EHR) to help predict more accurate utilization trends. More efficient data feeds could help UnitedHealth hone its pricing strategy and better plan for cost spikes.
In addition, AI has the ability to build predictive models that can more accurately assess patient risk profiles. In theory, this has the potential to analyze more granular detail around various segments of patient data as it relates to engagement rates and risk profiles. This could help improve reimbursement forecasts for the Optum business.
Lastly, natural language processing (NLP) can also be used to create scenario models by simulating how a business could be impacted based on changes in the regulatory landscape. An example of a company that specializes in this area of AI training is FiscalNote. This could help UnitedHealth plan more strategically as it pertains to budgeting decisions during periods of political uncertainty.
Is UnitedHealth Group stock a buy right now?
While shares of UnitedHealth trade at a slight premium to other large health insurers based on forward earnings multiples, the bigger takeaway from the trends below is that the stock price is hovering near a five-year low.
While UnitedHealth's operational challenges won't be fixed overnight, it is key to remember that management believes the company can course correct throughout the second half of this year and be better positioned by 2026.
Whether UnitedHealth transitions into an AI-powered service remains to be seen. Investors with a long-run time horizon might want to consider holding on to their shares, though, as the ideas explored above showcase how AI has the potential to become a game-changing advancement for the health insurance industry over time.
Looked at a different way, UnitedHealth could transform its business over the next several years by making cognizant investments in this technology. Nevertheless, the stock appears dirt cheap right now, and I think patient investors will be rewarded as the company turns things around over the next couple of quarters.
Should you invest $1,000 in UnitedHealth Group right now?
Before you buy stock in UnitedHealth Group, consider this:
The Motley Fool Stock Advisor analyst team just identified what they believe are the 10 best stocks for investors to buy now… and UnitedHealth Group wasn’t one of them. The 10 stocks that made the cut could produce monster returns in the coming years.
Consider when Netflix made this list on December 17, 2004... if you invested $1,000 at the time of our recommendation, you’d have $713,547!* Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you’d have $966,931!*
Now, it’s worth noting Stock Advisor’s total average return is 1,062% — a market-crushing outperformance compared to 177% for the S&P 500. Don’t miss out on the latest top 10 list, available when you join Stock Advisor.
See the 10 stocks »
*Stock Advisor returns as of June 23, 2025
Fiscal Note is a transcription service used by The Motley Fool. Adam Spatacco has positions in Eli Lilly and Novo Nordisk. The Motley Fool recommends Novo Nordisk and UnitedHealth Group. The Motley Fool has a disclosure policy.
This Dirt Cheap Healthcare Stock Could Be a Hidden Artificial Intelligence (AI) Opportunity (Hint: It's Not Eli Lilly) was originally published by The Motley Fool
| 2025-06-29T00:00:00 |
https://finance.yahoo.com/news/dirt-cheap-healthcare-stock-could-075500302.html
|
[
{
"date": "2025/06/29",
"position": 99,
"query": "artificial intelligence healthcare"
},
{
"date": "2025/06/29",
"position": 62,
"query": "artificial intelligence healthcare"
}
] |
|
CEOs Are Quietly Telling Us the Truth: AI Is Replacing You - Gizmodo
|
CEOs Are Quietly Telling Us the Truth: AI Is Replacing You
|
https://gizmodo.com
|
[
"Luc Olinga",
"James Pero",
"Matt Novak"
] |
He's preparing employees for a reality where AI replaces entire job categories across the board, and where hiring slows or stops altogether ...
|
The fear is real. In meetings, Slack chats, and after-work drinks, one question is quietly eating away at millions of employees: Will AI take my job?
In public, CEOs like to sound reassuring. They say generative AI will “enhance productivity” or “streamline operations.” But when you actually read what they’re telling their own employees, or what slips out in investor memos, the message is chilling: virtual workers are here, and they’re not just assistants. They’re replacements.
Let’s take a closer look at what some of the world’s most powerful tech CEOs are saying. Not in hype videos, but in official internal messages, blog posts, and investor updates.
1. Amazon’s Andy Jassy: “We will need fewer people”
Amazon CEO Andy Jassy recently published a company-wide message that sounds reasonable, until you actually read it.
“As we roll out more generative AI and agents, it should change the way our work is done. We will need fewer people doing some of the jobs that are being done today… We expect this will reduce our total corporate workforce as we get efficiency gains from using AI extensively across the company.”
The key phrase? “Next few years.” That’s corporate speak for 2026 to 2028. Not ten years away. This is soon.
Jassy is not talking about automating only simple or repetitive tasks. He’s preparing employees for a reality where AI replaces entire job categories across the board, and where hiring slows or stops altogether for roles that machines can now do.
2. Duolingo’s Luis von Ahn: “Headcount will only be given if” AI can’t do the job
In a memo posted to LinkedIn, Duolingo CEO Luis von Ahn was even more blunt. “Most functions will have specific initiatives to fundamentally change how they work… Headcount will only be given if a team cannot automate more of their work.”
Translation: No more hiring unless your job is impossible for AI to do. The company is betting that most teams will soon need fewer humans.
3. Shopify’s Tobi Lütke: Why can’t AI do it?
Shopify CEO Tobi Lütke shared a similar directive on X: “Before asking for more headcount and resources, teams must demonstrate why they cannot get what they want done using AI… What would this area look like if autonomous AI agents were already part of the team?” Lütke is openly asking managers to reimagine teams as if AI agents are already integrated, and to justify why any humans are still necessary.
The message from these CEOs is clear: human employees are now the last resort. The new default is automation.
Salesforce CEO Marc Benioff recently stated that AI is already doing 50% of the work within his company, shortly before announcing another 1,000 job cuts. The CEO of Klarna, a major fintech company, was even more blunt, revealing that AI has already allowed the company to reduce its workforce by 40%.
The Reality: Virtual Workers Already Exist
These aren’t future scenarios. This is already happening.
The reason for this sudden shift is the rapid evolution of AI technology. As OpenAI CEO Sam Altman explained in a recent podcast, the latest “reasoning models” have made a critical leap. In simple terms, these AI systems can now do more than just find information; they can “think” through complex, multi-step problems. Altman suggested these models can reason on par with someone holding a PhD, meaning they are now capable of performing the high level analytical tasks once reserved for highly educated humans.
This capability is being actively harnessed. Three sources working at major AI labs told Gizmodo that they are training powerful models to perform real world tasks in nearly every “knowledge work” profession, including banking, financial analysis, insurance, law, and even journalism. These sources, who requested anonymity as their contracts prohibit them from speaking publicly, described how their work is used in side by side comparisons with AI models to refine the technology until it can produce professional grade output with minimal errors. Virtual employees are already doing our jobs; the current phase is simply about making them more perfect.
The “next few years” Jassy spoke of may be closer to two years at most.
Layoffs Are Accelerating
Consider the tech industry’s recent layoff trends. In 2024, 551 tech companies laid off nearly 152,922 employees, according to data from Layoff.fyi. The pace has accelerated dramatically this year. In just the first six months of 2025, 151 tech companies have already laid off over 63,823 people. On average a tech company cut 277 workers in 2024. If that rate is maintained for the rest of the year, the average number of layoffs per tech company in 2025 would soar to 851, roughly three times the 2024 average.
While there is no direct evidence linking all these layoffs to AI, the trend is happening during a period of record economic strength. The Nasdaq just closed at an all time high, and eight of the world’s ten largest companies are in the tech sector. Profitable, growing companies are shedding workers at an alarming rate, and the quiet implementation of AI is the most logical explanation.
Our Take
Tech CEOs won’t tell you outright that you’re being replaced. But the memos speak for themselves.
AI is already here, and your company is likely building a roadmap to automate you out of your role. One internal pilot project at a time. One chatbot at a time. One hiring freeze at a time. If you want to understand what’s next for the American workforce, don’t listen to the marketing. Read the footnotes in the CEO’s blog. Because they’re already telling you the truth.
| 2025-06-29T00:00:00 |
2025/06/29
|
https://gizmodo.com/ceos-are-quietly-telling-us-the-truth-ai-is-replacing-you-2000621907
|
[
{
"date": "2025/06/29",
"position": 72,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 96,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 93,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 98,
"query": "AI replacing workers"
},
{
"date": "2025/06/29",
"position": 96,
"query": "AI replacing workers"
}
] |
Union Leaders, Good Mayors, and AI Bots - The Chief Organizer Blog
|
Union Leaders, Good Mayors, and AI Bots
|
https://chieforganizer.org
|
[] |
Other workshops looked at bargaining strength in labor shortages and how to use radio to communicate more broadly. A surprisingly big hit was a ...
|
Marble Falls Local 100 has conducted an annual leadership training workshop for stewards for more than 40 years, but this year’s session in Little Rock was the first in-person meeting since the pandemic. It was good to see old and new leaders getting to meet each other, often for the first time.
Going to Little Rock made sense so that we could help celebrate coming to a tentative first agreement with the City of Little Rock on a contract for more than 450 workers. A sign of the union’s progress included a visit by the Mayor Frank Scott, Jr, the first directly elected Black mayor in the city, now midway in his second term. The mayor knew the audience and was careful in describing how closely he was following the bargaining, but seemed pleased to hear that the parties had a tentative agreement. Encouragingly, he won the crowd by noting that he had managed to see an across the board raise for the workers in every year that he had been in office, even if sometimes it was only a small bump in the pay envelope. His failure to win an increase in the local sales tax is where he would put the blame, but it was all positive with the stewards.
In the afternoon, there was a great workshop conducted by several stewards, one from the State of Arkansas and another from the City of Little Rock, on how to handle grievances. Everyone in the room had an experience they wanted to share from the trenches and tips about how to navigate the rules, regulations, and whims of supervisors. Other workshops looked at bargaining strength in labor shortages and how to use radio to communicate more broadly.
A surprisingly big hit was a late entry on the agenda on digital organizing to enable more worker-to-worker organizing and servicing. Working with a former staffer and organizer who had been intrigued by the project, we had wondered if there was a way that we could use artificial intelligence to expand the range and tools for Local 100 members to represent their co-workers and organize new units. This session was going to be a coming out party for a trial run of the Local 100 Bot using a contract with ABM, a New Orleans cleaning contractor, for teaching the bot with a series of questions that were preprogrammed that would likely be on a member or steward’s mind. When hands were first raised hardly anyone had every tried ChatGPT, so as the Zoom displayed and the projector whirred, our Philly-based programmer, walked everyone through the steps to get the bot on their screens. While the stewards were trying to sign up, they could see on the screen some sample answers to common questions, where the Local 100 Bot would cite the article and section of the contract with the answer and offer suggestions on next steps to handle the issue and involve other members.
Honestly, no one could believe how well this worked, and what a difference it could make. Stewards wanted to know if they could also get their contracts uploaded, as well as the rule books and manuals used in their workplace. The answer was absolutely, exciting people even more. Most of us might be techno-peasants in this world, but everyone knew that if we could master these tools, we might have an edge in the workplace. On the spot, everyone joined a WhatsApp group to continue to work to improve the bot and get better at using it.
There’s nothing more old school in a union than handling grievances, but Local 100’s stewards were excited to graph some new school advances to build member power in their workplaces. Fingers are crossed that we can keep the excitement up and take the next steps once everyone is back home.
| 2025-06-29T00:00:00 |
2025/06/29
|
https://chieforganizer.org/2025/06/29/union-leaders-good-mayors-and-ai-bots/
|
[
{
"date": "2025/06/29",
"position": 84,
"query": "AI labor union"
}
] |
It's true that my fellow students are embracing AI
|
It’s true that my fellow students are embracing AI – but this is what the critics aren’t seeing | Elsie McDowell
|
https://www.theguardian.com
|
[
"Elsie Mcdowell"
] |
Reading about the role of artificial intelligence in higher education, the landscape looks bleak. Students are cheating en masse in our assessments or open ...
|
Reading about the role of artificial intelligence in higher education, the landscape looks bleak. Students are cheating en masse in our assessments or open-book, online exams using AI tools, all the while making ourselves stupider. The next generation of graduates, apparently, are going to complete their degrees without ever having so much as approached a critical thought.
Given that my course is examined entirely through closed-book exams, and I worry about the vast amounts of water and energy needed to power AI datacentres, I generally avoid using ChatGPT. But in my experience, students see it as a broadly acceptable tool in the learning process. Although debates about AI tend to focus on “cheating”, it is increasingly being used to assist with research, or to help structure essays.
There are valid concerns about the abuse and overuse of large language models (LLMs) in education. But if you want to understand why so many students are turning to AI, you need to understand what brought us to this point – and the educational context against which this is playing out.
In March 2020, I was about to turn 15. When the news broke that schools would be closing as part of the Covid lockdown, I remember cheers erupting in the corridors. As I celebrated what we all thought was just two weeks off school, I could not have envisioned the disruption that would mar the next three years of my education.
That year, GCSEs and A-levels were cancelled and replaced with teacher-assessed grades, which notoriously privileged those at already well-performing private schools. After further school closures, and a prolonged period of dithering, the then-education secretary, Gavin Williamson, cancelled them again in 2021. My A-level cohort in 2023 was the first to return to “normal” examinations – in England, at least – which resulted in a punitive crackdown on grade inflation that left many with far lower grades than expected.
At the same time, universities across the country were also grappling with how to assess students who were no longer physically on campus. The solution: open-book, online assessments for papers that were not already examined by coursework. When the students of the lockdown years graduated, the university system did not immediately return to its pre-Covid arrangements. Five years on, 70% of universities still use some form of online assessment.
This is not because, as some will have you believe, university has become too easy. These changes are a response to the fact that the large majority of current home students did not have the typical experience of national exams. Given the extensive periods of time we spent away from school during our GCSE and A-level years, there were inevitably parts of the curriculum that we were never able to cover. But beyond missed content, the government’s repeated backtracking and U-turning on the format of our exams from 2020 onwards bred uncertainty that continued to shape how we were assessed – even as we progressed on to higher education.
In my first year of university, half of my exams were online. This year, they all returned to handwritten, closed-book assessments. In both cases, I did not get confirmation about the format of my exams until well into the academic year. And, in one instance, third-year students sitting the exact same paper as me were examined online and in a longer timeframe, to recognise that they had not sat a handwritten exam at any point during their degree.
And so when ChatGPT was released in 2022, it landed in a university system in transition, characterised by yet more uncertainty. University exams had already become inconsistent and widely variable, between universities and within faculties themselves – only serving to increase the allure of AI for students who felt on the back foot, and make it harder to detect and monitor its use.
Even if it were not for our botched exams, being a student is more expensive than ever: 68% of students have part-time jobs, the highest rate in a decade. The student loan system, too, leaves those from the poorest backgrounds with the largest amounts of debt. I am already part of the first year to have to pay back our loans over 40, rather than 30, years. And that is before tuition fees rise again.
Students have less time than ever to actually be students. AI is a time-saving tool; if students don’t have the time or resources to fully engage with their studies, it is because something has gone badly wrong with the university system itself.
The use of AI is mushrooming because it’s convenient and fast, yes, but also because of the uncertainty that prevails around post-Covid exams, as well as the increasing financial precarity of students. Universities need to pick an exam format and stick to it. If this involves coursework or open-book exams, there needs to be clarity about what “proportionate” usage of AI looks like. For better or for worse, AI is here to stay. Not because students are lazy, but because what it means to be a student is changing just as rapidly as technology.
| 2025-06-29T00:00:00 |
2025/06/29
|
https://www.theguardian.com/commentisfree/2025/jun/29/students-ai-critics-chatgpt-covid-education-system
|
[
{
"date": "2025/06/29",
"position": 9,
"query": "AI education"
}
] |
7 AI tools employers want you to know
|
7 AI tools employers want you to know
|
https://mashable.com
|
[] |
7 AI tools employers want you to know · AI Chatbots · Grammarly · Otter.ai · Fireflies.ai · Google Workspace AI and Microsoft 365 Copilot · Adobe tools with AI · Canva ...
|
We examine how AI is changing the future of work — and how, in many ways, that future is already here.
AI is becoming increasingly common, and since its big promise is to make your work life easier , a lot of people are curious. On top of that, employers are increasingly expecting workers to incorporate AI into their daily workflow to save time and stay current. There are hundreds of AI tools that claim to make you more productive, so where do you start?
As a tech writer who's been using AI to get more efficient, I wanted to put together a list of common AI tools you may soon be expected to use at work.
Before we begin the list, there are a few things you should know going into it. The first is that you should never let AI do the work for you, but rather let it assist you in doing the work. It may not be noticeable when you first do it, but research has shown that letting AI do everything for you reduces your engagement with the task, which will ultimately cause you to underperform. So, use AI as a tool and not as a replacement for your brain.
You May Also Like
Secondly, while researching this article, I came upon many bits of advice for using AI at work , and one of the best ones is to never copy and paste proprietary business information into your AI tools. AI companies may use users’ interactions with their AI to further improve the AI, and giving them your company’s information is not a good idea. Other AI tools for professionals, like Google’s Workspace, expressly state that they don’t use data for training purposes. So, be sure to check the terms of service before using them for company matters.
With that, let’s get started. These are the AI tools that you're most likely to encounter in the workplace. Pro tip: Mastery of these tools would be a useful skill to add to your resume.
AI Chatbots
The first and obvious choice is the humble AI chatbot. You can find these everywhere, but the biggest ones are ChatGPT, Google’s Gemini, Microsoft’s Copilot (which is powered by ChatGPT), Anthropic’s Claude, and xAI’s Grok. These chatbots are good starting points because they’re widely available, can answer a host of questions about various tasks at your job, and are free to try, giving you the ability to see if they’ll help before you spend any money.
For the most part, the best use for chatbots is to ask questions and get answers. Need some help with a piece of code? Don’t know how to work an email? These are the scenarios that chatbots are built to help with. As per our earlier advice, we wouldn’t copy and paste company code directly into the chatbot, but nondescript snippets may be okay, and you can ask them to code functions in specific languages if need be. There are limitations to using chatbots, but they’re still helpful if you need them for basic stuff.
AI chatbots can also help with tasks like:
Summarizing PDFs
Generating images for presentations
Help brainstorm ideas
Copyedit emails and documents
Automate repetitive tasks
Many companies are also creating custom AI chatbots to help with customer service or internal company communication. If you know how to use these chatbots to your advantage, you'll have an advantage over your coworkers who don't.
Grammarly
Grammarly is a neat tool that existed before the big AI boom. At its most basic, Grammarly is a writing tool that helps you make better grammar decisions and helps with punctuation. I’ve been using this tool for years to help with my awful punctuation, and it’s helped a lot. Grammarly also has a desktop tool that you can use if you want its advice in other apps.
Mashable Light Speed Want more out-of-this world tech, space and science stories? Sign up for Mashable's weekly Light Speed newsletter. Loading... Sign Me Up By clicking Sign Me Up, you confirm you are 16+ and agree to our Terms of Use and Privacy Policy Thanks for signing up!
Those who opt for the Pro subscription get a lot more stuff, including an AI writing assistant that uses its existing tools to help you create emails and briefs quickly and efficiently. I recommend reading over anything it helps you generate to make sure it’s correct, but otherwise, it’s a handy tool. It also helps that it’s easy to install and works in every major browser alongside its desktop app.
Otter.ai
Otter.ai is one of our favorite AI tools for professionals, and it's used by some of Mashable's reporters. This work-oriented app uses AI to do a host of things that are otherwise quite boring. For example, it can quickly create transcriptions of meetings , take notes on your behalf, and summarize meetings and presentations. I used Otter.ai to transcribe this year’s Google I/O keynote, making it so much easier for me to find quotes and highlights without having to scrub through the full two-hour keynote.
The tool isn’t a one-trick pony either. You can integrate it right into Microsoft Teams or Slack to give coworkers an AI chat to play with for work purposes, along with a channel where people can talk and the AI takes notes to fill you in later on what’s going on. About the only thing to note is that Otter’s terms of service expressly state not to give it confidential or sensitive information (a common AI security risk), so make sure to keep that in mind if you use it.
Fireflies.ai
Fireflies.ai is a direct competitor to Otter and does a lot of the same things differently. On top of transcribing and summarizing meetings, Fireflies also offers language translation of over 100 languages, making it much easier to deal with multi-cultural teams that don’t all speak the same language natively. Once it transcribes and summarizes everything, you can search through transcripts at your leisure.
In addition, Fireflies integrates into all sorts of other apps, including Zoom, Google Meet, Slack, and many others. It also integrates into dialers, calendars, and other tasks to assist with that stuff as well. It’s a pretty powerful AI sweet for businesses, and knowing how to use it might help you land a job one of these days.
Google Workspace AI and Microsoft 365 Copilot
Arguably, the best use of AI so far is Google Workspace and Microsoft 365 Copilot . Not only do you get the usual features, like a chatbot to answer questions and the ability to do simple things like take notes, but both brands are slowly but steadily intermingling their AI solutions with just about every tool in their portfolio. That means AI in Microsoft Word to help edit your work and in Google Sheets to help you manage data.
The potential upside here is pretty huge. It takes a lot of effort to master these apps on their own, especially coding custom stuff in Excel or Sheets. Having an AI there can make it much faster and more efficient. The Gemini and Copilot are also integrated into each company’s chat and video call software, where they provide additional utility. At the very least, you should be aware of what each company’s AI can do in the workspace environment.
Adobe tools with AI
Adobe is one of the most recognized names in productivity, and the company’s various apps now have plenty of built-in AI tools. The list is pretty long and includes familiar faces such as Photoshop, Lightroom, Acrobat, Adobe Express, and several others. It’s true that Adobe mostly caters to the creative types, but nearly every type of work has the occasional creative element. Better yet, Adobe has also made it very clear that it doesn’t use consumer data to train its AI.
For the most part, Adobe keeps its AI use fairly tame. In Photoshop and Lightroom, there are AI tools to spruce up photos or images and make some tasks quicker, like background removal or subject selection. In Acrobat, Adobe has an AI assistant that can summarize PDFs, answer questions about them, and help you find pertinent information. You can also generate images with Adobe Firefly and use them in Express to build social media graphics and things like that.
In years past, mastering Photoshop could take years. But as AI makes image editing and Photoshop more accessible, we expect more professionals to start listing this sophisticated software on their resumes.
Canva Pro
Canva Pro is another creativity suite powered in part by AI. In fact, I've designed my own resume using Canva for the past couple of years (I like that its templates are pretty minimal). In any case, on top of its various design offerings, it bakes AI into many of its tasks, which means you can use it to help you complete various design tasks.
So, using my use case as an example, you’d access Canva AI and say that you want to design a resume. It’ll walk you through the steps of doing so, helping you select a template and all of that, and then you get started. Outside of this, Canva Pro can also help you generate images, improve PowerPoint presentations, and create social media graphics.
As AI tools become more mainstream (and as AI-savvy college grads enter the workforce), employers may come to expect an understanding of these tools. They may even seek out prospective employees who have AI skills listed on their resumes.
So, even if you have no intention of using AI, you should at least learn how to use it for future reference. You may end up needing it sooner rather than later.
| 2025-06-29T00:00:00 |
2025/06/29
|
https://mashable.com/article/ai-tools-employees-should-know
|
[
{
"date": "2025/06/29",
"position": 12,
"query": "AI employers"
}
] |
10 Artificial Intelligence (AI) Companies to Buy Now and ...
|
10 Artificial Intelligence (AI) Companies to Buy Now and Hold Forever
|
https://www.nasdaq.com
|
[
"June",
"Am Edt",
"Scott Levine"
] |
10 Artificial Intelligence (AI) Companies to Buy Now and Hold Forever · 1. Nvidia · 2. Alphabet · 3. Microsoft · 4. Meta Platforms · 5. Broadcom · 6. Amazon · 7 ...
|
From the growth of self-driving cars to the explosion in generative artificial intelligence (AI) capabilities, it's clear that AI is going to become increasingly integrated in our lives.
Recognizing this fact, investors should keep tabs on leading AI companies since these stocks have the potential to provide sizable returns in the years to come.
Where to invest $1,000 right now? Our analyst team just revealed what they believe are the 10 best stocks to buy right now. Learn More »
1. Nvidia
Nvidia (NASDAQ: NVDA) is a semiconductor stalwart that pioneered the development of the graphics processing unit (GPU). Invaluable for AI applications, GPUs are also critical components found in data centers, where AI computing occurs.
The company consistently generates strong free cash flow -- just one of many reasons why Nvidia stock is a must-consider for any investor looking to gain AI exposure.
2. Alphabet
The parent company of numerous businesses, Alphabet (NASDAQ: GOOG) (NASDAQ: GOOGL) incorporates its large language model (LLM) chatbot, Gemini, into offerings like Google Search and Android phones. Other companies also integrate Gemini into their products, like visual messaging provider Snap and strategy and consulting leader Accenture.
Besides Gemini, Alphabet provides extensive AI exposure through its cloud computing service, Google Cloud.
3. Microsoft
Expanding beyond the software offerings that initially made it famous, Microsoft (NASDAQ: MSFT) offers AI exposure through its generative AI chatbot, Copilot, found in several Microsoft products like Microsoft 365. Investors also gain AI exposure through the company's cloud computing platform, Microsoft Azure.
Microsoft also provides indirect AI exposure as the company is a major investor in OpenAI, the owner of ChatGPT.
4. Meta Platforms
Meta Platforms (NASDAQ: META) may be most recognizable as the parent company of Facebook, but the company emerged as a leader in AI tools after developing Meta AI, an AI-powered assistant that's integrated in other Meta apps and built on the Llama LLM.
In June 2025, Meta broadened its AI reach with a $14.3 billion investment in Scale AI, a company pursuing artificial general intelligence.
5. Broadcom
Like Nvidia, Broadcom (NASDAQ: AVGO) is another leading semiconductor stock that has close ties to the AI industry. Data center growth is contributing to strong demand for Broadcom's AI accelerators. For Q2 2025, Broadcom reported over $4.4 billion in AI semiconductor revenue, a 46% year-over-year increase. AI networking represented 40% of AI revenue, a 70% year-over-year gain.
6. Amazon
Once upon a time, Amazon (NASDAQ: AMZN) was merely a bookseller. Today, however, it has a robust cloud computing business. Launched almost 20 years ago, Amazon Web Services has emerged as a premier cloud computing option, providing the foundation for companies to develop their own AI resources as well as AI services and tools like Amazon Bedrock and Amazon SageMaker.
At the end of 2024, AWS achieved a $115 annualized revenue run rate. For context, Amazon reported total revenue of $638 billion for 2024. Considering its scale and its dedication to innovation, Amazon is sure to remain a premier AI force for years to come.
7. Palantir Technologies
From assisting customers with data integration, to security and compliance, to healthcare advances, to supporting the militaries of the U.S. and allies, software company Palantir Technologies (NASDAQ: PLTR) developed a sophisticated platform for analyzing large datasets.
In strong financial health, Palantir is consistently profitable and ended the first quarter 2025 with $5.4 billion in cash and cash equivalents with no debt. Plus, it routinely generates strong free cash flow.
8. Taiwan Semiconductor
With its Dedicated IC Foundry business model, Taiwan Semiconductor Manufacturing (NYSE: TSM) produces semiconductors for customers instead of original semiconductors for itself. Nvidia, for example, is a Taiwan Semiconductor customer, turning to it for help in production of the Blackwell GPU, which is used in AI applications.
Illustrating its strong exposure to AI, Taiwan Semiconductor stated that 2024 revenue from AI accelerators represented "close to mid-teens percent" of its total revenue.
9. Tesla
Most recognize Tesla (NASDAQ: TSLA) for its electric vehicles (EVs) but its leadership in AI warrants recognition. For one, the company's EVs have sophisticated autonomous driving capability -- capability that's only expected to increase -- and it's making steady progress in advancing its robotaxi business.
Tesla reported about $5 billion in 2024 AI-related capital expenditures, and it expects about the same in 2025. Considering Elon Musk's enthusiasm for AI, it would be unsurprising if Musk moves toward a Tesla acquisition of his AI start-up, xAI.
10. CoreWeave
Providing infrastructure for AI computing, CoreWeave (NASDAQ: CRWV) developed a cloud platform to support AI's high computing demands. The allure of its technology is highlighted by its recent $11.9 billion deal with OpenAI to develop AI infrastructure.
CoreWeave is in rapid growth mode. In Q1 2025, it reported revenue of $982 million, a year-over-year increase of 420% resulting from high demand for the company's cloud platform.
Should you invest $1,000 in Nvidia right now?
Before you buy stock in Nvidia, consider this:
The Motley Fool Stock Advisor analyst team just identified what they believe are the 10 best stocks for investors to buy now… and Nvidia wasn’t one of them. The 10 stocks that made the cut could produce monster returns in the coming years.
Consider when Netflix made this list on December 17, 2004... if you invested $1,000 at the time of our recommendation, you’d have $713,547!* Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you’d have $966,931!*
Now, it’s worth noting Stock Advisor’s total average return is 1,062% — a market-crushing outperformance compared to 177% for the S&P 500. Don’t miss out on the latest top 10 list, available when you join Stock Advisor.
See the 10 stocks »
*Stock Advisor returns as of June 23, 2025
Suzanne Frey, an executive at Alphabet, is a member of The Motley Fool’s board of directors. Randi Zuckerberg, a former director of market development and spokeswoman for Facebook and sister to Meta Platforms CEO Mark Zuckerberg, is a member of The Motley Fool's board of directors. John Mackey, former CEO of Whole Foods Market, an Amazon subsidiary, is a member of The Motley Fool’s board of directors. Scott Levine has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Accenture Plc, Alphabet, Amazon, Meta Platforms, Microsoft, Nvidia, Palantir Technologies, Taiwan Semiconductor Manufacturing, and Tesla. The Motley Fool recommends Broadcom and recommends the following options: long January 2026 $395 calls on Microsoft and short January 2026 $405 calls on Microsoft. The Motley Fool has a disclosure policy.
The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.
| 2025-06-29T00:00:00 |
https://www.nasdaq.com/articles/10-artificial-intelligence-ai-companies-buy-now-and-hold-forever
|
[
{
"date": "2025/06/29",
"position": 42,
"query": "AI employers"
}
] |
|
Technology
|
Technology
|
https://www.opb.org
|
[] |
Intel expands layoffs, cutting more than 10% of Oregon workforce ... In a first-of-its-kind decision, an AI company wins a copyright infringement lawsuit brought ...
|
📨 Daily news in your inbox
Sign up today for OPB’s “First Look” – your daily guide to the most important news and culture stories from around the Northwest.
| 2025-06-29T00:00:00 |
https://www.opb.org/tag/technology/
|
[
{
"date": "2025/06/29",
"position": 77,
"query": "AI layoffs"
}
] |
|
High-paying corporate jobs are shrinking. Is AI to blame, or ...
|
High-paying corporate jobs are shrinking. Is AI to blame, or do these roles now require specialised expertise?
|
https://indianexpress.com
|
[
"Karan Mahadik",
"Anuj Bhatia",
"Anuj Bhatia Is A Personal Technology Writer At Indianexpress.Com Who Has Been Covering Smartphones",
"Personal Computers",
"Gaming",
"Apps",
"Lifestyle Tech Actively Since He Specialises In Writing Longer-Form Feature Articles",
"Explainers On Trending Tech Topics. His Unique Interests Encompass Delving Into Vintage Tech",
"Retro Gaming",
"Composing In-Depth Narratives On The Intersection Of History"
] |
And while Amazon has not yet announced another round of layoffs, Jassy's memo is a clear indicator that job cuts are coming soon — and they are likely to hit ...
|
A new trend seems to be emerging in the corporate world: the elimination of middle managers. (Image: Anuj Bhatia/The Indian Express)
In Gurugram, everything looks glossy — swanky offices, high-rise apartments, premium restaurants and pubs, and a lifestyle only a few can dream of in a country with a population of 1.4 billion. This is largely thanks to the boom in IT and tech, as Gurugram is home to several Fortune 500 companies with offices located here.
But as big tech companies and large corporates come under increasing pressure to cut costs, many are laying off employees who earn far more than the average Indian. Although most of these layoffs are happening in the US, neither Gurugram nor Bengaluru — India’s Silicon Valley — is immune.
A look at subreddits reveals that both young and middle-aged IT professionals are facing growing uncertainty about their jobs, with many recent engineering graduates struggling to find employment. While mass layoffs have jolted corporate America, there are signs that no one is safe right now, as most of these companies also operate large offices in countries like India and maintain a sizeable presence here.
Story continues below this ad
Layoffs are happening across other industries as well, from media to FMCG. (Image: Anuj Bhatia/The Indian Express) Layoffs are happening across other industries as well, from media to FMCG. (Image: Anuj Bhatia/The Indian Express)
Though many large tech companies have declined to provide specific reasons for announced job reductions, tech leaders, and those who hold substantial power, are increasingly citing artificial intelligence as a key factor in hiring and headcount reductions.
On June 18, Amazon CEO Andy Jassy announced in a memo to its 1.5 million employees that, as the company embraces artificial intelligence tools across the organisation, it will ultimately “reduce our total corporate workforce as we get efficiency gains” over time. Jassy added that generative AI will ‘change the way our work is done,’ and said the company will eventually ‘need fewer people doing some of the jobs that are being done today, and more people doing other types of jobs.’
And while Amazon has not yet announced another round of layoffs, Jassy’s memo is a clear indicator that job cuts are coming soon — and they are likely to hit corporate employees (those with high salaries, annual bonuses, and stock awards) the hardest.
Microsoft, too, is planning to cut corporate jobs, according to a Bloomberg report on June 19. The cuts are expected to affect employees in sales roles. While the exact timing of the layoffs hasn’t been finalised, several thousand jobs are expected to be eliminated. If carried out, this would mark Microsoft’s fourth round of job cuts this year. Last month, during the company’s most recent round of layoffs, 3 per cent of Microsoft employees were affected globally — roughly 6,000 people — with a heavy emphasis on software developers.
Story continues below this ad
Google also made a similar move on June 10, offering voluntary buyouts to employees across several of its teams, including Communications, Marketing, Research, Core, and Knowledge & Information. And it’s not just big tech — layoffs are happening across other industries as well, from media to FMCG, with corporate jobs being impacted the most.
AI replacing white-collar jobs
Once known for providing job security, better work-life balance, and extremely high pay, recent cuts have threatened the stability white-collar workers once enjoyed. There is increasing evidence that companies are eliminating positions held by trained and seasoned employees—either due to financial pressure or the elimination of certain job categories—and are using artificial intelligence tools to support the remaining workforce. Most of the cuts can be seen in Human Resources, marketing and sales, legal, accounting, and even coding.
Companies claim that AI isn’t replacing workers, but that may not be the case. (Image: Anuj Bhatia/ Companies claim that AI isn’t replacing workers, but that may not be the case. (Image: Anuj Bhatia/ The Indian Express
Amazon CEO Jassy’s memo, in which he said employees should figure out ‘how to get more done with scrappier teams,’ shows how AI will become a core part of daily work. Many of the tasks that previously required large teams can now be done with fewer people by automating certain functions — letting AI do the job.
Goldman Sachs CEO David Solomon recently stated that AI can draft 95 per cent of an IPO prospectus in minutes. According to him, the efficiency gains are significant, considering that the same task used to take a six-person team two weeks to complete. Meta CEO Mark Zuckerberg and Microsoft CEO Satya Nadella, in a fireside chat at Meta’s LlamaCon in April this year, said that 30 per cent of code within their companies is now written by AI.
Story continues below this ad Also Read | AI and future of jobs: Here’s what top tech CEOs Sam Altman, Jensen Huang are saying Klarna CEO Sebastian Siemiatkowski recently said that the fintech company has shrunk its head count by 40 per cent, in part due to investments in AI. Likewise, Shopify CEO Tobias Lütke told employees in April that they will have to prove why tasks can’t be performed by AI before asking for more workers and resources. And while companies claim that AI isn’t replacing workers, that may not be the case. Although the narrative suggests that workers familiar with AI tools have a higher chance of being retained, in many instances, they are replacing entire teams or employees with experience in a specific field. Middle-manager roles are being eliminated A new trend seems to be emerging in the corporate world: the elimination of middle managers. Large tech companies like Meta, Amazon, Google, Microsoft, and Salesforce are thinning out management roles — often referred to as ‘bossing’ — to enable faster and more effective decision-making. Take the case of Starbucks, which recently announced 1,100 corporate job cuts, or Nissan, which revealed a 20 per cent global reduction in its managerial workforce. In both big tech and startups, there has been a noticeable shift in mindset — everyone now wants to be a manager. Engineers increasingly prefer leadership roles over remaining individual contributors. As a result, top-notch developers often stop coding and move into management. But at a time when companies like Meta are actively seeking exceptional coders, these once-great developers end up spending their days micromanaging teams and workflows instead of writing code. Story continues below this ad During the first wave of layoffs, Meta was one of the tech companies that eliminated many middle management roles across the organisation. In fact, Meta CEO Mark Zuckerberg stated in an internal Q&A that he didn’t want ‘managers managing managers, managing managers, managing managers, managing the people who are doing the work. Data from McKinsey found that nearly half of middle managers devote less than a quarter of their working time to people management, and they aren’t contributing as individual contributors. If well-paid managerial jobs are being eliminated or reduced, it could significantly impact a worker’s chances of becoming a manager. The aspiration to become a manager drives many motivated individuals to pursue an MBA, aiming to quickly climb the corporate ladder, and eventually reach the C-suite. Not that being a manager is an easy job; a lack of middle managers altogether or operating at less capacity could make staff unhappy and put more pressure on them without an effective manager. Corporates have become choosy Today, the job market is brutal, and knowledgeable, experienced white-collar workers are competing for scarce roles. This isn’t to say that companies are not hiring at all — they are, but only for specialised roles. Even though the threat to white-collar jobs is historically high, companies are still hiring where they believe a candidate adds real value. Tech companies and large corporates are prioritising experience over training freshers. (Image: Anuj Bhatia/The Indian Express) Tech companies and large corporates are prioritising experience over training freshers. (Image: Anuj Bhatia/The Indian Express) This could be for an existing project where there’s a talent shortage within the team, or when the company has no choice but to bring in external talent, even at a higher compensation. Take the case of Meta CEO Mark Zuckerberg, who is assembling a top artificial intelligence team for its “superintelligence” AI lab and is willing to poach OpenAI employees with offers as high as $100 million. Meta also recently hired Scale AI founder Alexandr Wang as part of a $14 billion deal. Story continues below this ad Another truth is that jobs have become more complex and demand specialised skills, and for that, the talent pool is both rare and expensive. This is why companies are willing to spend millions on the right hires (at least, that’s how Silicon Valley has traditionally operated: pay whatever it takes to land a star software developer). Also Read | Is AI leading to reduced jobs? What it means for software engineers No one has the time to train employees and wait a year or more for a new recruit to match the skill level of the existing team. That’s why tech companies and large corporates are being extra cautious in their hiring. They are prioritising experience over training freshers, expecting candidates to step into roles already come with domain-level knowledge and skills.
| 2025-06-29T00:00:00 |
2025/06/29
|
https://indianexpress.com/article/technology/tech-news-technology/jobs-shrinking-ai-to-blame-specialised-expertise-10075634/
|
[
{
"date": "2025/06/29",
"position": 97,
"query": "AI layoffs"
}
] |
Entry-level jobs have 'dropped by a third since ChatGPT ...
|
Entry-level job numbers have 'dropped by a third since ChatGPT was launched'
|
https://www.dailymail.co.uk
|
[
"Tom Lawrence"
] |
Entry-level job numbers have 'dropped by a third since ChatGPT was launched' ... impact on their role. A 2024 survey of 16,000 workers found nearly half ...
|
The number of new entry-level jobs has fallen by nearly a third since ChatGPT was launched in November 2022, it was reported last night.
Openings for apprenticeships, graduate roles, internships and junior roles with no requirement for a degree fell by 31.9 per cent, according to The Times.
Research by jobs search website Adzuna found that entry-level vacancies only make up a quarter of the overall jobs market, which is down by nearly 4 per cent since 2022.
It comes as more companies outline their plans to use AI to reduce their headcount.
BT said in May 2023 that 10,000 jobs would be replaced by artificial intelligence by the end of the decade. The roles impacted include call handling and network diagnostics.
Its chief executive Allison Kirkby has claimed that advances in AI could result in even more job cuts at the company.
Dario Amodei, head of $61billion AI start-up Anthropic, last month warned that the technology could cut half of all entry-level white-collar jobs within five years.
He said this could increase unemployment by between up to 20 per cent.
The number of new entry-level jobs has fallen by nearly a third since ChatGPT was launched in November 2022
More companies are outlining their plans to use AI to reduce their headcount
James Neave, the head of data science at Adzuna, said AI was a major factor in the reduction of entry-level jobs.
‘If you can reduce your hiring at the entry level, that’s just going to increase your efficiency and improve cost savings,’ he said.
Businesses are facing increasing costs including rises in national insurance contributions and the national minimum wage. The number of entry-level roles fell again by 4.2 per cent in May.
Experts predict a 50-50 chance machines could take over all our jobs within a century.
But a poll of 16,000 workers last year found many employees believe AI could do it already.
Nearly half admitted the technology can outperform them in 'routine tasks' – while also paying better attention to detail.
The 'jobs apocalypse' is expected to see admin and entry-level roles first – but will increasingly affect those higher paid as it becomes more sophisticated.
The Future of Work Report by jobs website Indeed found just one in three respondents were confident AI would have a positive impact on their role.
A 2024 survey of 16,000 workers found nearly half admit the technology can already outperform them in 'routine tasks'
The majority however – nine in ten – felt confident they would be able to adapt to the changes over the next five years.
Workers told how much of their day-to-day responsibilities were already ripe for automation – with three in five saying that AI can carry out data analysis better than humans.
Routine tasks (48%) and attention to detail (45%) were other tasks where workers felt AI had the upper hand.
While repetitive jobs are well-suited to AI, workers said they still felt confident they were better in critical thinking, creativity and emotional intelligence.
Asked which jobs are most likely to be untouched by AI in a decade's time, PricewaterhouseCoopers (PwC) Chief Economist, Barret Kupelian said people should look to traditional trades - with roles plumbers, electricians and decorators
He explained: 'It appears to me that jobs that require a quite a lot of manual labour...I don't think the technology is skilled there, in terms of augmenting those skills.'
The PwC spokesman said that roles that require 'a high degree of judgement and creativity' are also unlikely to be able to be automated any time soon because they require 'bespoke skills that are quite difficult to replicate on a digital basis.'
The IMF warned that, even where AI's effects are positive, computer automation is likely to drive wealth inequality.
A new study from the IMF found that AI could affect 60 per cent of all jobs in the UK and more than 40 per cent of jobs worldwide
Highly paid professions will see AI boost their wages while lower paid roles are at a significant risk of pay cuts and lay-offs.
A study by the IMF found that clerical workers such as secretaries and clerks are very likely to be replaced by AI because most of their could be done by machines.
However, it is clerical support workers and technical service roles that are most likely to be replaced by AI.
Professionals and managers, although they are very likely to be impacted by AI, are more likely to be impacted positively.
These findings echo a previous study from the Department for Education which found that white-collar professionals were most likely to be replaced by AI.
The study found that accountants, consultants, and psychologists were among the professions most likely to be pushed aside by computers.
Sports players, roofers, and steel erectors on the other hand were considered the least at risk from AI.
| 2025-06-30T00:00:00 |
2025/06/30
|
https://www.dailymail.co.uk/news/article-14859341/Entry-level-job-numbers-dropped-ChatGPT-launched.html
|
[
{
"date": "2025/06/29",
"position": 50,
"query": "ChatGPT employment impact"
}
] |
Digital Transformation and the Restructuring of Employment
|
Digital Transformation and the Restructuring of Employment: Evidence from Chinese Listed Firms
|
https://arxiv.org
|
[] |
... hiring by leveraging granular job posting data from major online ... data analytics, and automation, are profoundly reshaping labor markets globally.
|
(1)
Acemoglu and Restrepo (2018a) Acemoglu, D. and P. Restrepo , “Artificial Intelligence, Automation and Work,” Alfred P. Sloan Foundation Economic Research Paper Series , 2018.
Acemoglu and Restrepo (2018b) and , “The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment,” American Economic Review , 2018.
Acemoglu and Restrepo (2019) and , “Automation and New Tasks: How Technology Displaces and Reinstates Labor,” NBER Working Paper Series , 2019.
Acemoglu and Restrepo (2020) Acemoglu, Daron and P. Restrepo , “AI and Jobs: Evidence from Online Vacancies,” PSN: Technology (Topic) , 2020.
Arntz et al. (2017) Arntz, M., Terry Gregory, and U. Zierahn , “Revisiting the risk of automation,” Economics Letters , 2017, 159 , 157–160.
Autor (2013) Autor, David , “The "Task Approach" to Labor Markets: An Overview,” Journal for Labour Market Research , 2013, 46 (3), 185–199.
Autor (2014) , “Skills, education, and the rise of earnings inequality among the “other 99 percent”,” Science , 2014, 344 , 843 – 851.
Autor (2015) , “Why Are There Still So Many Jobs? The History and Future of Workplace Automation,” Journal of Economic Perspectives , September 2015, 29 (3), 3–30.
Autor and Salomons (2018) and A. Salomons , “Is Automation Labor-Displacing? Productivity Growth, Employment, and the Labor Share,” ERN: Capital; Investment; Capacity (Topic) , 2018.
Autor and A.Salomons (2020) and A.Salomons , “The fall of the labor share and the rise of superstar firms,” The Quarterly Journal of Economics , 2020, 135 (2), 645–709.
Autor and Dorn (2009) and David Dorn , “The Growth of Low Skill Service Jobs and the Polarization of the U.S. Labor Market,” NBER Working Paper Series , 2009.
Autor et al. (2003) , Frank Levy, and Richard J. Murnane , “The Skill Content of Recent Technological Change: An Empirical Exploration,” The Quarterly Journal of Economics , 2003, 118 (4), 1279–1333.
Bartel et al. (2005) Bartel, A., Casey Ichniowski, and K. Shaw , “How Does Information Technology Really Affect Productivity? Plant-Level Comparisons of Product Innovation, Process Improvement and Worker Skills,” Information Systems & Economics , 2005.
Benzell et al. (2019) Benzell, Seth G., Guillermo Lagarda, and Daniel Rock , “Do Labor Demand Shifts Occur Within Firms or Across Them? Non-Routine-Biased Technological Change, 2000-2016,” Labor: Human Capital eJournal , 2019.
Bloom and Van Reenen (2007) Bloom, Nicholas and John Van Reenen , “Measuring and explaining management practices across firms and countries,” The Quarterly Journal of Economics , 2007, 122 (4), 1351–1408.
Brynjolfsson and McAfee (2011) Brynjolfsson, Erik and Andrew P. McAfee , Race Against the Machine: How the Digital Revolution Is Accelerating Innovation, Driving Productivity, and Irreversibly Transforming Employment and the Economy , Digital Frontier Press, 2011.
Brynjolfsson et al. (2018) , Tom Michael Mitchell, and Daniel Rock , “What Can Machines Learn, and What Does It Mean for Occupations and the Economy?,” PsychRN: Organizational Behavior & Workplace Performance (Topic) , 2018.
Card and Dinardo (2002) Card, David and John E. Dinardo , “Skill-Biased Technological Change and Rising Wage Inequality: Some Problems and Puzzles,” Journal of Labor Economics , 2002, 20 , 733 – 783.
Felten et al. (2018) Felten, E., Manav Raj, and Robert C. Seamans , “A Method to Link Advances in Artificial Intelligence to Occupational Abilities,” AEA Papers and Proceedings , May 2018, 108 , 54–57.
Felten et al. (2019) , , and , “The Occupational Impact of Artificial Intelligence: Labor, Skills, and Polarization,” Ewing Marion Kauffman Foundation Research Paper Series , 2019.
Frey and Osborne (2017) Frey, C. and Michael A. Osborne , “The future of employment: How susceptible are jobs to computerisation?,” Technological Forecasting and Social Change , 2017, 114 , 254–280.
Gathmann and Schönberg (2007) Gathmann, Christina and Uta Schönberg , “How General Is Human Capital? A Task-Based Approach,” Journal of Labor Economics , 2007, 28 , 1 – 49.
Goos et al. (2014) Goos, M., A. Manning, and A. Salomons , “Explaining Job Polarization: Routine-Biased Technological Change and Offshoring,” The American Economic Review , 2014, 104 , 2509–2526.
Goos et al. (2009) , Alan Manning, and A. Salomons , “Job Polarization in Europe,” The American Economic Review , 2009, 99 , 58–63.
Griliches (1969) Griliches, Z. , “Capital-Skill Complementarity,” The Review of Economics and Statistics , 1969, 51 , 465–468.
Gulati et al. (2025) Gulati, P., Arianna Marchetti, P. Puranam, and Victoria Sevcenko , “Generative AI Adoption and Higher Order Skills,” SSRN Electronic Journal , 2025.
Huo et al. (2024) Huo, Qingqing, Jing Ruan, and Yan Cui , ““Machine replacement” or “job creation”: How does artificial intelligence impact employment patterns in China’s manufacturing industry?,” Frontiers in Artificial Intelligence , 2024, 7.
Jensen and Meckling (1976) Jensen, Michael C. and William H. Meckling , “Theory of the firm: Managerial behavior, agency costs and ownership structure,” Journal of Financial Economics , 1976, 3 (4), 305–360.
Li and Zhang (2018) Li, Wei and Xiaohui Zhang , “Does digital technology improve governance efficiency? Evidence from China,” Journal of Comparative Economics , 2018, 46 (2), 450–468.
Liang et al. (2025) Liang, Hui, Jingbo Fan, and Yunhan Wang , “Artificial Intelligence, Technological Innovation, and Employment Transformation for Sustainable Development: Evidence from China,” Sustainability , 2025.
Lv et al. (2025) Lv, Yuanhao, Yifei Xie, and Zhenggang Song , “A Review of Research on the Employment Effects of China’s Digital Economy,” Scientific Journal of Economics and Management Research , 2025.
Manyika et al. (2017) Manyika, J., Michael Chui, Mehdi Miremadi, J. Bughin, Katy George, Paul Willmott, and Martin Dewhurst , “A Future That Works: Automation, Employment, and Productivity,” Technical Report, McKinsey Global Institute 2017. Accessed: 2025-06-04.
Marguerit (2025) Marguerit, David , “Augmenting or Automating Labor? The Effect of AI Development on New Work, Employment, and Wages,” SSRN Electronic Journal , 2025.
Mishra and Deichmann (2016) Mishra, Deepak and Uwe Deichmann , World Development Report 2016: Digital Dividends , World Bank Publications, 2016.
Murphy (1999) Murphy, Kevin J. , Executive compensation , Vol. 3, Elsevier, 1999.
Seamans and Raj (2018) Seamans, Robert C. and Manav Raj , “Ai, Labor, Productivity and the Need for Firm-Level Data,” Kauffman: Large Research Projects (Topic) , 2018.
Senftleben and Wielandt (2012) Senftleben, Charlotte and Hanna Wielandt , “The Polarization of Employment in German Local Labor Markets,” Working Paper, EconStor 2012.
Sun (2024) Sun, Yanru , “Analysis of the Impact of the Digital Economy on Employment in China,” Advances in Economics, Management and Political Sciences , 2024.
Wang (2024) Wang, Jing , “Exploring the Dual Impact of AI on Employment and Wages in Chinese Manufacturing,” SEISENSE Journal of Management , 2024.
Webb (2019) Webb, Michael , “The Impact of Artificial Intelligence on the Labor Market,” Economics of Innovation eJournal , 2019.
West (2015) West, James C. , “The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies.,” Psychiatry , 2015, 78 , 380 – 383.
Wu et al. (2025) Wu, Qinqin, Sikander Ali Qalati, Kayhan Tajeddini, and Haijing Wang , “The impact of artificial intelligence adoption on Chinese manufacturing enterprises’ innovativeness: new insights from a labor structure perspective,” Ind. Manag. Data Syst. , 2025, 125 , 849–874.
Wu et al. (2023) Wu, Yunxia, Neng Hao, and Yechi Ma , “The Effect of Digital Economy Development on Labor Employment: Empirical Evidence From Listed Companies in China,” J. Glob. Inf. Manag. , 2023, 31 , 1–27.
Zhang et al. (2022) Zhang, Xuan, Feiyang Lin, Yue Wang, and Mingliang Wang , “The impact of digital economy on employment polarization: an analysis based on Chinese provincial panel data,” Labor History , 2022, 63 , 636 – 651.
| 2025-06-29T00:00:00 |
https://arxiv.org/html/2506.23230v1
|
[
{
"date": "2025/06/29",
"position": 92,
"query": "job automation statistics"
}
] |
|
Gen Z Workers Secretly Use AI Despite Workplace ...
|
Gen Z Workers Secretly Use AI Despite Workplace Restrictions, Survey Finds -- Pure AI
|
https://pureai.com
|
[
"John K. Waters",
"About The Author"
] |
The study of 1,000 full-time Gen Z employees found that 39% have used AI to automate tasks behind their manager's back, while 57% run their work through AI ...
|
News
Gen Z Workers Secretly Use AI Despite Workplace Restrictions, Survey Finds
Nearly two in five Generation Z workers are using artificial intelligence to automate workplace tasks without their managers' knowledge, according to a new survey that reveals how the youngest employees are quietly transforming office practices.
The study of 1,000 full-time Gen Z employees found that 39% have used AI to automate tasks behind their manager's back, while 57% run their work through AI systems before presenting it to supervisors. The findings suggest a generational divide in how artificial intelligence is being adopted in American workplaces.
Generation Z, defined as those born between 1997 and 2012, appears to have integrated AI tools more deeply into daily work routines than many employers realize. The survey found that 60% of Gen Z workers say AI helps them complete tasks faster and with less effort, while 56% use it to determine how to communicate with bosses and colleagues.
The research, conducted by Resume Genius between April and May 2025, indicates that 18% of Gen Z workers would consider leaving their jobs if AI tools were banned in the workplace. The company, which has provided career services since 2009, surveyed participants across various demographics to understand AI adoption patterns among younger workers.
Widespread but Hidden Usage
The data reveals extensive AI usage across multiple workplace functions. Three-quarters of Gen Z workers use AI for brainstorming and generating creative ideas, while 68% employ it for writing and editing reports and emails. Additionally, 62% use AI for creating digital content and presentations, and 61% apply it to analyze large datasets.
However, the survey uncovered concerning patterns of undisclosed AI use. Twenty-eight percent of Gen Z workers have submitted AI-generated work as their own without disclosure, with 41% of those individuals indicating they would repeat this behavior. Male workers showed higher rates of such practices, with 40% admitting to passing off AI work as their own compared to 20% of women.
The gender divide extends across AI usage patterns. Men consistently reported higher usage rates across all categories, with 85% using AI for brainstorming compared to 67% of women. Male workers also showed greater willingness to violate company policies, with 52% automating tasks without approval versus 30% of women.
Mental Health Concerns Emerge
Despite productivity gains, the survey identified negative psychological impacts from AI adoption. Twenty-three percent of Gen Z workers reported that AI use has negatively affected their mental health, while 39% said frequent AI updates cause burnout.
The technology appears to create both dependency and anxiety among young workers. Thirty-seven percent said AI makes them feel replaceable, while 49% expressed concern about AI leading to unfair or biased workplace decisions. These concerns were particularly pronounced among male workers, with 50% saying they need AI to manage their workload compared to 30% of women.
Resume Genius, which has been featured in major publications including The New York Times and Forbes, found that women were more likely to experience emotional fatigue from AI adoption, with 41% reporting burnout from constant updates compared to 35% of men.
Communication Replacement
The survey revealed that Gen Z workers increasingly turn to AI instead of human colleagues for workplace guidance. Fifty-six percent use AI for advice on communicating with managers or coworkers, while 55% employ it to interpret workplace messages and communications.
This trend extends to career development, with 53% using AI for career decisions including salary negotiations and promotion discussions. Half of respondents use AI to understand company policies rather than consulting human resources departments.
The reliance on AI for communication appears to reflect broader workplace relationship challenges. Fifty-one percent of Gen Z workers use AI to navigate workplace conflicts, suggesting that artificial intelligence has become a substitute for traditional mentorship and guidance relationships.
Resistance to Restrictions
When asked about potential workplace AI bans, Gen Z workers showed significant resistance. Only 52% said they would support such restrictions, while 48% indicated opposition. More concerning for employers, 51% said they would continue using AI on personal devices outside work hours if banned, and 33% admitted they would violate workplace prohibitions by continuing to use AI on company equipment.
The survey found that 18% of Gen Z workers believe they would need to change jobs entirely if AI were banned, suggesting deep integration of these tools into their work processes. Male workers showed greater resistance to restrictions, with only 46% supporting AI bans compared to 57% of women.
Implications for Employers
The findings suggest that many organizations may be unknowingly benefiting from AI-enhanced productivity while maintaining policies that restrict such usage. The disconnect between official policies and actual practices could create compliance risks and management challenges as AI adoption continues to expand.
The survey indicates that companies face a choice between acknowledging and managing AI adoption or risk losing younger talent to organizations with more permissive policies. The research suggests that Gen Z workers view AI restrictions as barriers to efficiency rather than necessary ethical safeguards.
The study was conducted using Pollfish's Random Device Engagement methodology to ensure representative sampling across gender and age groups within the Gen Z demographic. Data analysis was completed using Python Pandas programming tools.
| 2025-06-29T00:00:00 |
2025/06/29
|
https://pureai.com/articles/2025/06/29/gen-z-workers-secretly-use-ai-despite-workplace-restrictions.aspx
|
[
{
"date": "2025/06/29",
"position": 11,
"query": "workplace AI adoption"
}
] |
Civil Rights Council Secures Approval for Regulations to Protect ...
|
Civil Rights Council Secures Approval for Regulations to Protect Against Employment Discrimination Related to Artificial Intelligence
|
https://calcivilrights.ca.gov
|
[
"State Of California"
] |
Automated-decision systems — which may rely on algorithms or artificial intelligence — are increasingly used in employment settings to ...
|
SACRAMENTO – The California Civil Rights Council today announced securing final approval for regulations to protect against potential employment discrimination as a result of the use of artificial intelligence, algorithms, and other automated-decision systems. The newly approved regulations provide increased clarity on how existing antidiscrimination laws apply to the use of artificial intelligence in employment decisions.
“As a member of the California Civil Rights Council who had the opportunity to work on this important effort, I want to extend our sincere thanks to the numerous stakeholders — from the business community, nonprofit sector, and many other associations — whose valuable participation and input in over 40 public comment letters and over the past few years have helped shape these regulations,” said Civil Rights Councilmember Hellen Hong. “We are proud to update these rules to better protect Californians from potential employment discrimination posed by the widespread use of automated decision-making systems.”
“These rules help address forms of discrimination through the use of AI, and preserve protections that have long been codified in our laws as new technologies pose novel challenges,” said Civil Rights Councilmember Jonathan Glater.
“California is a world leader when it comes to new technologies and innovation,” said Civil Rights Department Director Kevin Kish. “These new regulations on artificial intelligence in the workplace aim to help our state’s antidiscrimination protections keep pace. I applaud the Civil Rights Council for their commitment to protecting the rights of all Californians.”
Why Are Regulations Needed Now?
Automated-decision systems — which may rely on algorithms or artificial intelligence — are increasingly used in employment settings to facilitate a wide range of decisions related to job applicants or employees, including with respect to recruitment, hiring, and promotion. While these tools can bring myriad benefits, they can also exacerbate existing biases and contribute to discriminatory outcomes. Whether it is a hiring tool that rejects women applicants by mimicking the existing features of a company’s male-dominated workforce or a job advertisement delivery system that reinforces gender and racial stereotypes by directing cashier ads to women and taxi jobs to Black workers, there are numerous challenges that may arise with the use of artificial intelligence in the workplace.
What’s the Process for Issuing Regulations?
Under California law, the California Civil Rights Department (CRD) is charged with enforcing many of the state’s robust civil rights laws, including in the areas of employment, housing, businesses and public accommodations, and state-funded programs and activities. As part of those efforts, the Civil Rights Council — which is supported by CRD staff — develops and issues regulations to implement state civil rights laws, including when it comes to new and emerging technologies. With respect to automated-decision systems, the Civil Rights Council’s final regulations are the result of a series of public hearings and careful consideration of input from experts and the public, as well as federal reports and guidance. After review by the Office of Administrative Law, the regulations were approved on June 27, 2025 and are set to go into effect on October 1, 2025.
What Do These Regulations Do?
The regulations clarify the application of existing antidiscrimination laws in the workplace in the context of new and emerging technologies, like artificial intelligence. Among other changes, the Civil Rights Council’s regulations aim to:
Make it clear that the use of an automated-decision system may violate California law if it harms applicants or employees based on protected characteristics, such as gender, race, or disability.
Ensure employers and covered entities maintain employment records, including automated-decision data, for a minimum of four years.
Affirm that automated-decision system assessments, including tests, questions, or puzzle games that elicit information about a disability, may constitute an unlawful medical inquiry.
Add definitions for key terms used in the regulations, such as “automated-decision system,” “agent,” and “proxy.”
If you or someone you know has experienced employment discrimination, CRD may be able to assist you through its complaint process. The department also provides general information and factsheets online about civil rights protections for members of the public.
The full text of the regulations and additional information on the Civil Rights Council is available here.
| 2025-06-30T00:00:00 |
2025/06/30
|
https://calcivilrights.ca.gov/2025/06/30/civil-rights-council-secures-approval-for-regulations-to-protect-against-employment-discrimination-related-to-artificial-intelligence/
|
[
{
"date": "2025/06/30",
"position": 70,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/30",
"position": 66,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/30",
"position": 70,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/30",
"position": 100,
"query": "AI regulation employment"
},
{
"date": "2025/06/30",
"position": 65,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/30",
"position": 72,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/30",
"position": 29,
"query": "AI regulation employment"
},
{
"date": "2025/06/30",
"position": 68,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/30",
"position": 30,
"query": "AI regulation employment"
},
{
"date": "2025/06/30",
"position": 66,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/30",
"position": 2,
"query": "AI regulation employment"
},
{
"date": "2025/06/30",
"position": 71,
"query": "artificial intelligence employers"
},
{
"date": "2025/06/30",
"position": 32,
"query": "AI regulation employment"
},
{
"date": "2025/06/30",
"position": 67,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/30",
"position": 20,
"query": "AI regulation employment"
},
{
"date": "2025/06/30",
"position": 70,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/30",
"position": 31,
"query": "AI regulation employment"
},
{
"date": "2025/06/30",
"position": 64,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/30",
"position": 3,
"query": "AI regulation employment"
},
{
"date": "2025/06/30",
"position": 2,
"query": "AI regulation employment"
},
{
"date": "2025/06/30",
"position": 66,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/30",
"position": 31,
"query": "AI regulation employment"
},
{
"date": "2025/06/30",
"position": 53,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/30",
"position": 31,
"query": "AI regulation employment"
},
{
"date": "2025/06/30",
"position": 83,
"query": "artificial intelligence employers"
},
{
"date": "2025/06/30",
"position": 59,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/30",
"position": 89,
"query": "AI regulation employment"
},
{
"date": "2025/06/30",
"position": 4,
"query": "AI regulation employment"
},
{
"date": "2025/06/30",
"position": 25,
"query": "artificial intelligence employment"
}
] |
The Future of Labor Unions: Advocating for Workers in an AI-Driven ...
|
The Future of Labor Unions: Advocating for Workers in an AI-Driven Landscape
|
https://www.linkedin.com
|
[] |
Traditional union models were built around stable, full-time employment. But the rise of AI is fueling more dynamic work arrangements: gig work, ...
|
For over a century, labor unions have served as powerful advocates for workers’ rights negotiating fair wages, securing workplace protections, and shaping the policies that define modern employment. But in the face of AI-driven disruption, automation, and algorithmic management, unions are confronting a rapidly shifting terrain. The very nature of work is being redefined, and with it, the role of organized labor.
How can unions remain relevant and effective in a world where many decisions are made by code, and human workers increasingly share space with intelligent machines?
New Challenges in Representation
Traditional union models were built around stable, full-time employment. But the rise of AI is fueling more dynamic work arrangements: gig work, contract-based roles, and platform-mediated labor. In these ecosystems, workers are dispersed, work asynchronously, and often interact more with software than supervisors.
This fragmentation makes collective bargaining more difficult but also more urgent. As workers lose bargaining power in the face of opaque algorithms and productivity-tracking tools, they need new kinds of representation. Unions must adapt to advocate not just for factory or office workers, but for coders, remote freelancers, warehouse pickers, and even data labelers in AI supply chains.
Fighting Algorithmic Exploitation
One of the most critical frontiers for unions is algorithmic management. In many workplaces, decisions about workload distribution, performance reviews, and even termination are now made or heavily influenced by AI systems. These systems often lack transparency, and workers have little recourse to challenge them.
Unions can step in as watchdogs demanding algorithmic accountability, negotiating for transparency, and ensuring that workers are not subjected to hidden biases or inhumane productivity targets. They can lobby for the right to explanation in automated decision-making and ensure that human oversight remains a requirement in critical workforce decisions.
A Seat at the Digital Table
To remain effective in the AI era, unions must engage directly with the technologies shaping the workplace. This means developing internal expertise in data science, AI ethics, and digital policy. Unions should be present not only in negotiation rooms but also in advisory committees shaping corporate AI strategies and public policy frameworks.
Labor organizations that embrace digital tools themselves using AI to analyze workplace patterns, predict labor disruptions, or mobilize support will be better positioned to meet their members' evolving needs.
Collaborating with Tech Allies
Forward-thinking unions are already forming alliances with civil rights groups, digital advocacy organizations, and academic institutions to address broader concerns around digital labor. These collaborations allow unions to punch above their weight shaping narratives, influencing regulation, and pushing for a more equitable future of work.
In a world where AI can decide who works, when, and how, unions remain one of the last lines of defense for worker dignity. But to survive and thrive, they must evolve. Their future lies not in resisting AI, but in shaping how it is deployed and ensuring that technological progress doesn’t come at the cost of human rights.
#LaborUnions #AIandWork #DigitalLaborRights #AlgorithmicManagement #CollectiveBargaining #FutureOfWork
| 2025-06-30T00:00:00 |
https://www.linkedin.com/pulse/future-labor-unions-advocating-workers-ai-driven-xzjvc
|
[
{
"date": "2025/06/30",
"position": 17,
"query": "AI labor union"
},
{
"date": "2025/06/30",
"position": 76,
"query": "AI labor union"
},
{
"date": "2025/06/30",
"position": 74,
"query": "AI labor union"
},
{
"date": "2025/06/30",
"position": 73,
"query": "AI labor union"
},
{
"date": "2025/06/30",
"position": 76,
"query": "AI labor union"
},
{
"date": "2025/06/30",
"position": 76,
"query": "AI labor union"
},
{
"date": "2025/06/30",
"position": 22,
"query": "AI labor union"
}
] |
|
Facing the AI Future: A Call to Action for Union Leaders
|
Facing the AI Future: A Call to Action for Union Leaders
|
https://awf.labortools.com
|
[] |
Swanson stressed the importance of unions being proactive in shaping AI implementation to protect workers, communities and institutions from ...
|
Troy Swanson, legislative chair of the Cook County College Teachers Union, joined the America's Work Force Union Podcast to discuss his report "Facing the AI Future: A Call to Action for Union Leaders." Swanson explored the potential impact of AI on jobs, the need for union preparedness and strategies to protect workers during this technological transition.
Swanson emphasized the urgency for unions to address AI's impact on the workforce. He cited predictions that up to 30 percent of current work hours could be automated within five years, potentially affecting both blue-collar and white-collar jobs. Swanson stressed the importance of unions being proactive in shaping AI implementation to protect workers, communities and institutions from further economic inequality.
The report outlines several strategies for unions to address AI challenges. These include advocating for "human in the loop" requirements to ensure key decisions are made by people, negotiating for retraining programs and securing advance notice of AI implementation in workplaces. Swanson highlighted successful legislative action in Illinois mandating that only human faculty can award course credits in community colleges, demonstrating the potential for unions to shape AI policy.
Swanson called for a broader conversation within the labor movement about AI's impact. He emphasized the need for union leaders at all levels to envision how work might change and to develop strategies for negotiating these changes. Swanson urged unions to help shape AI's implementation rather than allowing tech billionaires to dictate its future. He stressed the opportunity to create more meaningful work while protecting jobs.
Listen to the full episode to hear more about Swanson's thoughts on AI and the labor movement's response.
| 2025-06-30T00:00:00 |
https://awf.labortools.com/listen/facing-the-ai-future-a-call-to-action-for-union-leaders
|
[
{
"date": "2025/06/30",
"position": 26,
"query": "AI labor union"
},
{
"date": "2025/06/30",
"position": 67,
"query": "AI labor union"
},
{
"date": "2025/06/30",
"position": 64,
"query": "AI labor union"
},
{
"date": "2025/06/30",
"position": 60,
"query": "AI labor union"
},
{
"date": "2025/06/30",
"position": 65,
"query": "AI labor union"
},
{
"date": "2025/06/30",
"position": 62,
"query": "AI labor union"
},
{
"date": "2025/06/30",
"position": 67,
"query": "AI labor union"
},
{
"date": "2025/06/30",
"position": 93,
"query": "AI labor union"
},
{
"date": "2025/06/30",
"position": 60,
"query": "AI labor union"
},
{
"date": "2025/06/30",
"position": 29,
"query": "AI labor union"
},
{
"date": "2025/06/30",
"position": 68,
"query": "AI labor union"
},
{
"date": "2025/06/30",
"position": 66,
"query": "AI labor union"
}
] |
|
AI talent wars lead to superstar salaries for top tech staff
|
AI talent wars lead to superstar salaries for top tech staff
|
https://www.ft.com
|
[] |
While some top AI engineers are being paid more than $10mn a year, typical pay packages were between $3mn and $7mn — representing a rise of ...
|
Join FT Edit Only $49 a year
Get 2 months free with an annual subscription at was $59.88 now $49. Access to eight surprising articles a day, hand-picked by FT editors. For seamless reading, access content via the FT Edit page on FT.com and receive the FT Edit newsletter.
| 2025-06-30T00:00:00 |
https://www.ft.com/content/d48e7cfe-7b04-4cdd-8769-c88c83522118
|
[
{
"date": "2025/06/30",
"position": 30,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 54,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 86,
"query": "artificial intelligence wages"
},
{
"date": "2025/06/30",
"position": 61,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 33,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 51,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 78,
"query": "artificial intelligence wages"
},
{
"date": "2025/06/30",
"position": 28,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 86,
"query": "artificial intelligence wages"
},
{
"date": "2025/06/30",
"position": 47,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 85,
"query": "artificial intelligence wages"
},
{
"date": "2025/06/30",
"position": 73,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 83,
"query": "artificial intelligence wages"
},
{
"date": "2025/06/30",
"position": 87,
"query": "artificial intelligence wages"
},
{
"date": "2025/06/30",
"position": 64,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 87,
"query": "artificial intelligence wages"
},
{
"date": "2025/06/30",
"position": 64,
"query": "artificial intelligence wages"
},
{
"date": "2025/06/30",
"position": 34,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 67,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 90,
"query": "artificial intelligence wages"
},
{
"date": "2025/06/30",
"position": 60,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 53,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 41,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 90,
"query": "artificial intelligence wages"
},
{
"date": "2025/06/30",
"position": 56,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 88,
"query": "artificial intelligence wages"
},
{
"date": "2025/06/30",
"position": 61,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 59,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 85,
"query": "artificial intelligence wages"
}
] |
|
31 Honest AI Engineer Salaries - CBT Nuggets
|
31 Honest AI Engineer Salaries
|
https://www.cbtnuggets.com
|
[
"Danielle Antosz",
"Josh Burnett",
"Ross Heintzkill"
] |
In this guide, we'll break down what AI engineers actually do, how much they earn across the U.S., and what factors influence their pay. We'll ...
|
AI isn’t just powering your favorite chatbot—it’s reshaping entire industries. Behind the scenes of this revolution are AI engineers, the specialists turning machine learning models into real-world solutions. As demand for AI skyrockets, so does the competition for top talent, and the salaries are keeping pace.
In this guide, we’ll break down what AI engineers actually do, how much they earn across the U.S., and what factors influence their pay. We’ll also cover the tools, certifications, and career moves that can help you climb the salary ladder even faster.
What is an AI Engineer?
An AI engineer is a software engineer who designs, builds, and deploys artificial intelligence models. These professionals combine data science, machine learning, and software development to create systems that can mimic human intelligence, whether they understand language, recognize images, or make predictions based on patterns in data.
Day to day, an AI engineer might clean and organize datasets, train machine learning models, test different algorithms, or integrate those models into a larger application. Their work doesn’t stop once a model is built; they’re also responsible for evaluating its performance, fine-tuning it over time, and ensuring it runs reliably at scale.
To do all this, AI engineers rely on a deep understanding of programming, statistics, and machine learning frameworks. They often use tools like TensorFlow, PyTorch, and scikit-learn, and they need to be comfortable working with cloud platforms and containerized environments.
Job titles in this space can vary, and you might see job listings with names like:
Machine learning engineer
Deep learning engineer
NLP engineer
Applied AI scientist
These roles might have slightly different focuses, but they are all rooted in the same core skill set.
31 Honest Salaries for AI Engineers
AI engineering is one of the most in-demand and well-compensated tech roles in today’s market. But how much you can actually earn depends on more than just your title. Location, experience level, and specialization all play a role in shaping your paycheck.
According to ZipRecruiter, AI engineers make around $101,000 nationwide. But the range is large, from $76,000 to $200,000+.
To give you a clear, no-fluff picture of what AI engineers really make, we compiled salary data from Glassdoor, Levels.fyi, and ZipRecruiter. We focused on base salary ranges for individual contributor roles, not inflated figures from executive positions or stock-heavy comp packages.
Below is a breakdown of low, average, and high-end salaries for AI engineers in 31 U.S. cities. This data reflects 2025 estimates and assumes full-time employment.
City / State Low-End Salary Average Salary High-End Salary San Francisco, CA $145,000 $187,000 $225,000 San Jose, CA $140,000 $180,000 $220,000 Seattle, WA $135,000 $175,000 $210,000 New York, NY $130,000 $170,000 $205,000 Boston, MA $125,000 $165,000 $200,000 Los Angeles, CA $120,000 $160,000 $195,000 Washington, DC $118,000 $158,000 $192,000 San Diego, CA $115,000 $155,000 $190,000 Austin, TX $110,000 $150,000 $185,000 Chicago, IL $108,000 $148,000 $182,000 Denver, CO $105,000 $145,000 $178,000 Atlanta, GA $102,000 $142,000 $175,000 Portland, OR $100,000 $140,000 $172,000 Charlotte, NC $98,000 $138,000 $170,000 Dallas, TX $95,000 $135,000 $168,000 Philadelphia, PA $94,000 $134,000 $167,000 Minneapolis, MN $93,000 $133,000 $165,000 Raleigh, NC $92,000 $132,000 $163,000 Salt Lake City, UT $90,000 $130,000 $160,000 Phoenix, AZ $89,000 $128,000 $158,000 Tampa, FL $87,000 $126,000 $155,000 Miami, FL $86,000 $125,000 $153,000 Pittsburgh, PA $85,000 $124,000 $152,000 Cincinnati, OH $83,000 $122,000 $150,000 Columbus, OH $82,000 $121,000 $148,000 Indianapolis, IN $81,000 $120,000 $147,000 St. Louis, MO $80,000 $118,000 $145,000 Detroit, MI $79,000 $117,000 $143,000 Cleveland, OH $78,000 $116,000 $142,000 Kansas City, MO $77,000 $115,000 $140,000 Orlando, FL $76,000 $114,000 $138,000
There’s no doubt that location has a major impact on AI engineer salaries. Cities with lots of tech companies and a high cost of living, like San Francisco, San Jose, and Seattle, top the charts. In these hubs, average salaries often exceed $170,000, with high-end roles hitting $200K+.
On the flip side, cities in the Midwest and Southeast tend to offer lower salaries, but they also have lower costs of living. For example, Cleveland and Kansas City report average salaries around $115,000 to $120,000, which can still go a long way considering the average rent for a studio apartment in those cities is $1,306 and $1,198, respectively.
A few more things stand out:
Wider salary bands in top cities suggest more variability based on specialization and seniority.
Secondary tech markets like Austin, Denver, and Charlotte continue to offer strong compensation and growing opportunities.
Remote roles aren’t listed here specifically, but many employers benchmark remote salaries against major hubs, especially if the company is headquartered there.
Ultimately, the city you live in (or work remotely for) shapes your earning potential, but it’s just one piece of the puzzle. Next, we’ll look at other factors that can impact your salary as an AI engineer.
Salary Considerations for AI Engineers
AI engineering is a specialized field, and salaries can swing wildly depending on what you bring to the table. Beyond geography, here are some of the most significant factors that impact the salary of an AI engineer.
Specialization Matters: Engineers working in deep learning, natural language processing (NLP), or computer vision often earn more than those focused on general machine learning. Niche expertise in areas like generative AI or reinforcement learning can command an even higher rate.
Academic Background Can Boost Pay: While not required, a master’s or PhD in artificial intelligence, computer science, or a related field can open doors to higher-paying roles, especially in research-heavy organizations or emerging tech startups.
Industry Plays a Huge Role: Tech companies tend to pay well, but they’re not alone. AI engineers in finance, defense, healthcare, and autonomous vehicles also earn top dollar thanks to the complexity and impact of their work.
Project Maturity Makes a Difference: If you’re helping deploy production-ready AI systems that directly affect business operations or revenue, you’re likely to earn more than someone focused on research or early-stage prototyping.
Ethical AI Is in Demand: As concerns grow around AI bias, fairness, and explainability, engineers who understand how to build responsible systems are becoming increasingly valuable—and that value often shows up in their paychecks.
How Experience Impacts Salary
Like most tech roles, AI engineering salaries grow significantly with experience. Here's how compensation typically scales over time:
Entry-Level (0–2 Years)
Entry-level AI engineers can expect to earn between $90,000 and $120,000. At this stage, most are focused on supporting model development, preparing datasets, and assisting with experimentation. They’re usually learning from more experienced colleagues and building foundational skills.
Mid-Level (3–5 Years)
With a few years under their belts, mid-level engineers earn around $120,000 to $155,000. These professionals can independently build and deploy machine learning models, mentor junior staff, and contribute to product development. They often take on more strategic or cross-functional responsibilities.
Senior-Level (6+ Years)
Senior AI engineers typically earn $155,000 to $200,000 or more. They lead complex projects, design AI architectures, and interface with leadership to align AI initiatives with business goals. At this level, soft skills like communication, leadership, and strategic thinking matter just as much as deep technical expertise.
It's also worth noting that the AI industry is in its infancy, so the salary and job responsibilities might change as the industry matures. Still, this is a solid starting point for understanding how experience can impact your salary!
Must-Know Tools for AI Engineers
AI engineers work across a broad and ever-evolving tech stack. Mastery of these tools not only boosts productivity but it can also directly influence earning potential. While the stacks might vary by industry and company, here are the main types of tools you'll want to be familiar with.
Programming and Modeling
Python is the go-to language for most AI engineers, thanks to its rich ecosystem and ease of use. R, C++, and Java also come into play, especially in roles that involve statistical modeling, performance tuning, or integration with larger systems.
Machine Learning and Deep Learning Frameworks
Popular libraries like TensorFlow, PyTorch, Keras, and scikit-learn power most machine learning workflows. These tools help engineers build, train, and evaluate models efficiently and at scale.
NLP and Computer Vision
For language tasks, libraries like Hugging Face Transformers and spaCy are essential. In computer vision, OpenCV remains a staple for image processing and analysis.
Cloud and DevOps
AI applications often need to scale, and cloud platforms make that possible. Tools like AWS SageMaker, Azure ML, and GCP AI Hub help engineers manage model training, deployment, and monitoring. On the DevOps side, Docker and Kubernetes support reproducibility and scalability.
Experiment Tracking and Versioning
Engineers rely on tools like MLflow, DVC (Data Version Control), and Weights & Biases to manage model iterations and track results over time. These platforms are especially valuable in collaborative environments and production pipelines.
Must-Have Certifications for AI Engineers
Certifications aren’t mandatory in the AI world, but they can absolutely boost your credibility, especially if you're trying to stand out in a competitive job market or pivot into AI from another tech role. The best certifications validate your skills with cloud platforms, machine learning frameworks, and real-world AI applications.
Top certifications for AI engineers include:
While not specific to AI, these can still strengthen your resume depending on your career path:
PMP (Project Management Professional) : Valuable if you’re moving into a leadership or AI architect role.
Certified Data Scientist (DASCA) : More general, but helpful if your role includes heavy analytics work.
CompTIA Data+: Good for those earlier in their data or AI careers, especially if transitioning from other IT roles.
How to Increase Your Salary as an AI Engineer
There’s no magic button to boost your income instantly, but there are clear moves that can help you climb the pay scale faster. Whether you're early in your career or looking to break into six-figure territory, these strategies can make a real difference.
Develop Deep Specialization in High-Value Areas
Expertise in trending fields like generative AI, large language models (LLMs), or time-series forecasting can set you apart. Companies are willing to pay a premium for engineers who can lead innovation in these complex, high-demand domains.
Gain MLOps and Deployment Experience
Knowing how to build models is one thing. Knowing how to deploy, monitor, and scale them in production is another. Engineers who can bridge the gap between modeling and operations (MLOps) are incredibly valuable—and often better paid.
Lead Projects With Measurable Business Impact
Want to stand out? Lead or contribute to projects that clearly move the needle—whether that’s through automation, cost savings, or new revenue streams. Being able to connect your work to bottom-line results makes you more promotable and negotiation-ready.
Build Your Reputation Through Research or Open Source
Publishing research, presenting at conferences, or contributing to open-source tools in the AI ecosystem helps establish you as a thought leader. It also builds credibility, which can lead to better offers or consulting opportunities.
Align Certifications with Your Tech Stack
Certifications from AWS, Google Cloud, or Microsoft Azure can increase your value, especially if they match the platform your employer or clients already use. Pick certs that reinforce your existing strengths and fill in any gaps.
Step Into Leadership Roles
If you’re ready, consider transitioning into an AI architect, lead engineer, or technical manager role. These positions often come with higher pay and greater influence, especially in organizations where AI is central to strategy.
Conclusion
AI engineers are among the most in-demand professionals in tech today, and the salary data proves it. Whether you're just starting out or aiming for a senior role, your earning potential depends on more than just location. Specialization, hands-on experience, and the ability to deploy production-ready systems all play a major role.
To stay competitive (and keep climbing the pay ladder), it’s essential to keep your skills sharp. That means staying current with the latest AI tools, earning relevant certifications, and continuing to learn as the field evolves.
CBT Nuggets offers training on everything from Python and machine learning fundamentals to cloud platforms and certification prep.
| 2025-06-30T00:00:00 |
https://www.cbtnuggets.com/blog/career/career-progression/honest-ai-engineer-salaries
|
[
{
"date": "2025/06/30",
"position": 31,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 31,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 26,
"query": "artificial intelligence wages"
},
{
"date": "2025/06/30",
"position": 30,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 30,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 26,
"query": "artificial intelligence wages"
},
{
"date": "2025/06/30",
"position": 31,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 27,
"query": "artificial intelligence wages"
},
{
"date": "2025/06/30",
"position": 32,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 32,
"query": "artificial intelligence wages"
},
{
"date": "2025/06/30",
"position": 22,
"query": "artificial intelligence wages"
},
{
"date": "2025/06/30",
"position": 30,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 31,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 30,
"query": "artificial intelligence wages"
},
{
"date": "2025/06/30",
"position": 26,
"query": "artificial intelligence wages"
},
{
"date": "2025/06/30",
"position": 30,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 30,
"query": "artificial intelligence wages"
},
{
"date": "2025/06/30",
"position": 17,
"query": "artificial intelligence wages"
},
{
"date": "2025/06/30",
"position": 30,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 31,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 11,
"query": "artificial intelligence wages"
},
{
"date": "2025/06/30",
"position": 27,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 30,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 23,
"query": "artificial intelligence wages"
},
{
"date": "2025/06/30",
"position": 27,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 27,
"query": "artificial intelligence wages"
},
{
"date": "2025/06/30",
"position": 32,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 31,
"query": "AI wages"
},
{
"date": "2025/06/30",
"position": 28,
"query": "artificial intelligence wages"
}
] |
|
60+ Organizations Sign White House Pledge to Support America's ...
|
60+ Organizations Sign White House Pledge to Support America’s Youth and Invest in AI Education
|
https://www.whitehouse.gov
|
[
"The White House"
] |
Together, the Pledge will help make AI education accessible to K-12 students across the country, sparking curiosity in the technology and ...
|
Articles 60+ Organizations Sign White House Pledge to Support America’s Youth and Invest in AI Education
WASHINGTON, DC – Today, over 60 organizations are the first signers of the White House’s Pledge to America’s Youth: Investing in AI Education, which promises to support the goals and mission of President Trump’s executive order Advancing Artificial Intelligence Education for America’s Youth.
The organizations “pledge to make available resources for youth and teachers through funding and grants, educational materials and curricula, technology and tools, teacher professional development programs, workforce development resources, and/or technical expertise and mentorship” over the next four years, working alongside the White House Task Force on Artificial Intelligence Education. Together, the Pledge will help make AI education accessible to K-12 students across the country, sparking curiosity in the technology and preparing the next-generation for an AI-enabled economy.
“Fostering young people’s interest and expertise in artificial intelligence is crucial to maintaining American technological dominance. These initial pledges from American organizations will help create new educational and workforce development opportunities for our students. We invite other organizations to join the pledge as we look forward to furthering these partnerships to introduce more of America’s youth to AI,” said Michael Kratsios, Director of the White House Office of Science and Technology Policy and Chair of the White House Task Force on AI Education.
“We are thrilled that so many organizations have signed the Pledge to America’s Youth. It is clear there is a lot of energy about AI and how it can be used responsibly in education. The resources and tools that have been pledged through this initiative will help our teachers and learners leverage AI in classrooms and communities across America,” said Secretary of Education Linda McMahon.
“AI is reshaping our economy and the way we live and work, and we must ensure the next generation of American workers is equipped with the skills they need to lead in this new era,” said Secretary of Labor Lori Chavez-DeRemer. “By uniting behind this pledge to provide critical resources for students and educators, I’m encouraged to see these organizations are committed to helping young Americans build the skills they need in AI literacy to drive innovation and become empowered leaders of tomorrow.”
“To secure America’s future, the United States must win the AI race,” said U.S. Secretary of Energy Chris Wright. “That’s why President Trump is investing in the next generation of American innovators and providing students and teachers the tools to lead in this emerging industry. With this President’s bold leadership and the future leaders of America dialed in, America stands to dominate.”
“The U. S. National Science Foundation is proud to support the White House’s Pledge to America’s Youth: Investing in AI Education. Equipping young people with the tools to understand and shape artificial intelligence is not only a matter of national competitiveness—it is an investment in a more innovative, prosperous and informed future,” said Brian Stone, performing the duties of the NSF director. “NSF has long recognized the importance of nurturing early interest in science and technology. Through our ongoing efforts to fund cutting-edge research, support teacher development, and expand access to STEM education in every corner of the country, we are committed to ensuring that all students have the opportunity to engage with and contribute to the future of AI. We applaud the organizations that have joined this pledge and look forward to collaborating with our partners to deliver the contributed resources to America’s youth and inspire the next generation of AI innovators, researchers, and technology leaders.”
“President Trump is bringing America into a new Golden Age by harnessing the best tools and innovations America has to offer. At USDA, we are working to give students the opportunities and mentorship they need to continue the legacy of American ingenuity. Our efforts involve leveraging specific training and grant opportunities for students and teachers that encourage the use and development of artificial intelligence in agriculture. Under President Trump’s leadership, this task force is empowering teachers to integrate artificial intelligence into their curriculum as they prepare their students for the future,” said U.S. Secretary of Agriculture Brooke L. Rollins.
Stay tuned as the Trump Administration works with these and other organizations to announce specific new grants, programs, and technologies towards the Pledge throughout the year ahead. Visit our website for more information on joining the Pledge to America’s Youth, and stay up to date with the latest pledge signers and initiatives.
###
| 2025-06-06T00:00:00 |
2025/06/06
|
https://www.whitehouse.gov/articles/2025/06/60-organizations-sign-white-house-pledge-to-support-americas-youth-and-invest-in-ai-education/
|
[
{
"date": "2025/06/30",
"position": 60,
"query": "AI education"
},
{
"date": "2025/06/30",
"position": 65,
"query": "AI education"
},
{
"date": "2025/06/30",
"position": 65,
"query": "AI education"
},
{
"date": "2025/06/30",
"position": 25,
"query": "AI education"
},
{
"date": "2025/06/30",
"position": 26,
"query": "AI education"
},
{
"date": "2025/06/30",
"position": 65,
"query": "AI education"
},
{
"date": "2025/06/30",
"position": 65,
"query": "AI education"
},
{
"date": "2025/06/30",
"position": 63,
"query": "AI education"
},
{
"date": "2025/06/30",
"position": 66,
"query": "AI education"
},
{
"date": "2025/06/30",
"position": 68,
"query": "AI education"
},
{
"date": "2025/06/30",
"position": 28,
"query": "AI education"
},
{
"date": "2025/06/30",
"position": 1,
"query": "AI education"
}
] |
Artificial intelligence will provide better hiring and training for good ...
|
The heart of the internet
|
https://www.reddit.com
|
[] |
AI is already being used to hire. A lot of filtering of applications are being done by AI instead of humans. They will likely increasingly move ...
|
I believe because humans are capable of poor judgement of others, I believe hiring managers need to be obsolete. I've seen so many bad workers come and go at my job and it always looks like managers miss details about a certain employee. Worse, they can't train anyone to save a life; they are always reclusing in their office and not on the floor looking at every aspect of the job so they can't be capable of training. While AI will take most of the grunt work jobs like warehousing, there probably are things humans need to do to keep it running properly. AI could train humans better. Ai is more patient and unemotional.
Idk.
| 2025-06-30T00:00:00 |
https://www.reddit.com/r/ArtificialInteligence/comments/1loe4wt/artificial_intelligence_will_provide_better/
|
[
{
"date": "2025/06/30",
"position": 68,
"query": "artificial intelligence hiring"
}
] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.