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Two-Fifths of U.S. Workers Now Use AI; Frontline Adoption Stalls ...
|
Two-Fifths of U.S. Workers Now Use AI; Frontline Adoption Stalls, Leadership Use Climbs Sharply
|
https://www.digitalinformationworld.com
|
[
"Irfan Ahmad"
] |
The number of employees who say they use AI tools at least a few times each year has nearly doubled, rising from just over one-fifth of the workforce in 2023 ...
|
Artificial intelligence has become a more familiar part of daily work life in the United States, with its use spreading quickly across offices and professional environments.Over the past two years, the number of employees who say they use AI tools at least a few times each year has nearly doubled, rising from just over one-fifth of the workforce in 2023 to around two-fifths in 2025. Within that same period, the proportion of workers engaging with AI on a weekly basis has almost doubled as well, while daily use has quietly increased from four to eight percent over the past year alone.The growth in AI use has been most visible in white-collar occupations, particularly in sectors such as technology, consulting, and financial services. In these industries, between one-third and one-half of employees now report using AI frequently in the course of their work. Among white-collar professionals more broadly, over one in four are now regular users of AI, a clear increase compared to the previous year.Outside office-based roles, however, the picture has remained mostly unchanged. For those working in frontline jobs or production-related positions, regular use of AI has not followed the same trend. In fact, the percentage of these workers who report using AI a few times a week or more has remained flat, showing only a slight dip since 2023. The contrast between sectors where AI is being embraced and those where it remains largely unused suggests a growing divide in workplace technology exposure.Among employees who manage other leaders or oversee larger teams, AI adoption appears to be advancing at a faster pace than among individual contributors. Roughly one in three of these senior leaders now report frequent AI use, which is about double the rate observed among non-managers. This suggests that those in strategic or supervisory roles may be more likely to explore or depend on AI-based tools in their decision-making processes.Despite these shifts, most workers have not changed their outlook on the risk AI may pose to job security. The proportion of employees who believe it is likely that automation or AI will eliminate their position within the next five years remains consistent with previous years, holding steady at around fifteen percent. However, this figure rises slightly in some fields, particularly among those working in technology, retail, and finance, where around one in five anticipate that their roles could eventually be replaced.Although more organisations are beginning to introduce AI into their operations, many have done so without offering clear guidance or structured support for their staff. While just under half of all employees now say that AI is being introduced into their workplace in some form, fewer than one in four say that their employer has provided a detailed strategy or communicated a clear plan about how AI should be used. Only three in ten say that their organisation has issued either broad guidelines or formal policies governing the use of AI tools. This means that many employees are encountering AI without knowing where it fits into the rules or priorities of their workplace.When asked about the challenges surrounding the use of AI, employees most often point to confusion about its purpose or relevance. Even among those who regularly use AI at work, only a small proportion strongly agree that the tools they are given are genuinely helpful for the tasks they perform. For others, especially those without first-hand experience, the usefulness of AI remains unclear.Where staff have used AI to support customer-facing tasks, feedback is more positive. Most workers with direct experience in this area say that AI has improved their interactions with customers. In contrast, those who have never used AI in this way are far less likely to believe it would make any difference, with fewer than one in five expecting a benefit.Research indicates that a clearer sense of direction from leadership may be key to expanding AI use across the workplace. Employees who say their organisation has shared a detailed plan are significantly more likely to feel both comfortable and well-prepared to work with AI tools. In fact, those with this level of communication are several times more likely to describe themselves as confident users, compared with peers who have received no guidance.If companies are serious about using AI more widely, it may not be enough to simply provide access to new tools. The evidence suggests that helping employees understand how AI fits into their role — and offering structured, practical support — is what makes the difference between curiosity and genuine adoption.H/T: Gallup . Read next: Researchers Link Browser Fingerprints to Ad Targeting, Undermining Online Privacy Promises
| 2025-06-20T00:00:00 |
https://www.digitalinformationworld.com/2025/06/two-fifths-of-us-workers-now-use-ai.html
|
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|
11 most in-demand AI jobs companies are hiring for - CIO
|
11 most in-demand AI jobs companies are hiring for
|
https://www.cio.com
|
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Organizations are optimistic about AI in the workplace, but rapid adoption has sparked the need for new hires to help design, develop, implement ...
|
Data scientist
As companies embrace AI, they need data scientists to help drive better insights from customer and business data using analytics and AI. For most companies, AI systems rely on large datasets, which require the expertise of data scientists to navigate them. Responsibilities include building predictive modeling solutions that address both client and business needs, implementing analytical models alongside other relevant teams, and helping the organization make the transition from traditional software to AI infused software. It’s a role that requires experience with natural language processing, coding languages, statistical models, and large language and gen AI models. According to the survey, 26% of respondents said they’ve hired data scientists to support gen AI, while 53% said they have plans to hire candidates.
AI researcher
AI is still new territory for businesses, and there’s a lot to discover, which is why they’re looking to hire AI researchers to help identify the best possible applications of AI within the business. AI researchers help develop new models and algorithms to improve the efficiency of gen AI tools and systems, and identify opportunities for how AI can be used to improve processes or achieve business needs. AI researchers need to understand data and automation infrastructure, ML models, AI tools and algorithms, data science, programming, and how to build AI models from scratch. According to the survey, 18% of respondents say they’ve already hired AI researchers to support gen AI, while 52% say they have plans to hire for the role.
Algorithm engineer
Algorithm engineers, sometimes referred to as algorithm developers, are tasked with building, creating, and implementing algorithms for software and computer systems to achieve specific tasks and business needs. The role of the algorithm engineer requires knowledge of programming languages, testing and debugging, documentation, and, of course, algorithm design. These engineers are responsible for solving complex computational problems in the organization, often working with large data sets to design intricate algorithms that address and solve business needs. Businesses rely on algorithm engineers to help navigate AI technology, relying on these experts to scale and deploy AI solutions, consider all the ethical and bias implications, and ensure they’re aligned with all compliance and regulatory requirements. According to the survey, 17% of respondents say they’ve already hired algorithm engineers to support gen AI, while 51% say they have plans to hire for the role.
| 2025-06-20T00:00:00 |
https://www.cio.com/article/655291/most-in-demand-generative-ai-jobs.html
|
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|
How Artificial Intelligence Is Changing Journalism - Modern Diplomacy
|
How Artificial Intelligence Is Changing Journalism: From Headlines to Deep Analysis
|
https://moderndiplomacy.eu
|
[] |
Journalists today don't only write down what they see – they also use algorithms, machine learning technologies, and ai humanizer that can write ...
|
Unless someone points it out, you probably won’t notice the difference, but newsrooms are starting to feel the effects of AI. It now lends a hand in crafting everything from quick weather alerts to detailed reports built on complex spreadsheets. But this change brings up critical considerations regarding the quality, ethics, originality, and human voice in news reporting.
Journalists today don’t only write down what they see – they also use algorithms, machine learning technologies, and ai humanizer that can write news in a matter of seconds. It’s both fun and hard.
Writing News using AI: Quick and Easy
The speed at which AI can make readable information is one of the most obvious advances in journalism. Tools like ChatGPT and Jasper can spin out short stories, crisp summaries, or even full articles as soon as the data hits the system. Because of that speed, news organizations can squeeze in far more updates, covering every score, stock dip, or breaking alert.
Still, many editors and writers worry that machine prose lacks warmth or a human touch. Enter helpers branded as AI humanizers. Make It Human, for example, tweaks an AIs draft so it reads like something a real person would say. It lets reporters, bloggers, and editors polish rough machine drafts in minutes, saving time without losing voice. The program tweaks tone, word choice, rhythm, and beat, walking the line between smart automation and real warmth. This is something that pure AI currently has trouble with.
What AI Does Well (and Not So Well)
Let’s take a closer look at what AI can do for journalism right now:
What AI Is Good At:
Speed: Today, the machine can bang out a short story in the blink of an eye, a trick newsrooms love when headlines shift by the minute.
Number-crunching: it hunts through spreadsheets, reports, and endless footnotes, spotting odd trends and overlooked red flags faster than any tired editor.
Translation: before the first human wordsmith has finished a single paragraph, the piece is already live in half a dozen languages.
SEO services: Programs suggest keywords, slug lines, and tags that make pages easier to find in crowded searches.
Where people are still needed:
People still know how to make sources, ask tough questions, and get to the bottom of things.
Imitation: An algorithm can mirror a style, yet it lacks genuine feeling behind the words. Fact-checking: Systems stumble when they draw from shaky sources or outdated databases.
Humans still set the rules about what is fair, balanced, and responsible to publish.
Headlines, Trends, and Making It Your Own
AI is transforming not only how tales are written, but also what stories are written. News websites now utilize algorithms to figure out what people click on, how long they remain on a page, and what they share. This information will affect what material is made in the future.
In some locations, AI is even allowed to test several headlines to see which performs better in real time. This can increase participation, but if not done properly, it can also result in clickbait.
On top of that, the same system tweaks each version to match a readers own taste. Someone who always chases tech scoops will wake up to one set of headlines; a fan of movie gossip will find a totally different look on the same screen.
What Do Human Journalists Do in an AI World?
You might be wondering what else human reporters can achieve with all this technology.
The answer is: a lot.
Content strategists are becoming more like journalists. They think about how to control AI technologies, pick sources, shape stories, and keep the truth and integrity safe. AI is a strong helper, not a substitute.
And sites like HumanizeAI.pro are helping to close the gap between automation and realness. Writers may now utilize AI to write a first draft in only a few minutes and then make it better so that it really connects with readers.
A Smarter Future, Not a Colder Future One
AI in journalism isn’t going away – it’s just getting started. That doesn’t mean journalism will lose its heart, though. Instead, smart technologies are giving writers more time and space to think about why the story matters, not just what it is.
AI will be a helpful partner as long as journalists are honest, caring, and can think for themselves. It will help us tell tales more quickly, more intelligently, and maybe even better.
But don’t forget: journalism is still about people.
| 2025-06-20T00:00:00 |
2025/06/20
|
https://moderndiplomacy.eu/2025/06/20/how-artificial-intelligence-is-changing-journalism-from-headlines-to-deep-analysis/
|
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How much of the layoffs are trully caused by AI? - Blind
|
Your Anonymous Workplace Community
|
https://www.teamblind.com
|
[] |
AI is impacting job formation, but most of the layoffs in tech at the moment are to free up resources to invest in AI. With that said, AI ...
|
notification
Oops! Something went wrong.Please try again later.If the problem continues, please contact our team.
| 2025-06-20T00:00:00 |
https://www.teamblind.com/post/how-much-of-the-layoffs-are-trully-caused-by-ai-nilg1c2j
|
[
{
"date": "2025/06/20",
"position": 20,
"query": "artificial intelligence layoffs"
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{
"date": "2025/06/20",
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"query": "artificial intelligence layoffs"
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{
"date": "2025/06/20",
"position": 20,
"query": "artificial intelligence layoffs"
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|
26 best AI marketing tools I'm using to get ahead in 2025
|
26 best AI marketing tools I'm using to get ahead in 2025
|
https://www.marketermilk.com
|
[
"Faith Storey",
"Freelance Marketer",
"Post By",
"Omid G",
"Growth Manager",
"Contrarian Thinking",
"Hi",
"I M Omid",
"A Marketer",
"Writer"
] |
... machine learning, the future of AI marketing software is bright. I've been constantly testing and using different AI tools in my marketing ...
|
Some of the biggest brands like Shopify, Instacart, and Airbnb are using AI marketing tools internally to gain a competitive edge. Through my network and my time running content marketing at Webflow, I’ve uncovered some of the best AI marketing tools on the market today (and listed them below).
It's pretty obvious that AI has taken not only marketing by storm, but the tech industry in general.
Is it all hype?
Will we see a bubble burst like we did 25 years ago?
It's tough to tell. But one thing I'm certain about — AI marketing is the future for how we connect with our target audiences.
While AI today is simply just complex machine learning, the future of AI marketing software is bright.
I've been constantly testing and using different AI tools in my marketing stack for the past 3 years, and every once in a while I come back to this article to update it with any new tools I find myself using often.
If you look at some other posts on this subject, they've been totally copying me and trying to feed you a bunch of results influenced by affiliate commissions.
But this post is different.
These are tools I ACTUALLY use. And if you watch my YouTube video below, you'll see the ones I use the most (and how). The last one in the video is the one I use the most.
Alright, let's go over some of my favorite tools and how I think AI can be applied to different areas of your marketing stack.
What is AI used for in marketing?
In 2025, marketing is all about data — information on your competitors, on market trends, and on what your customers (and potential customers) are saying about your product. There’s a lot of information out there but it’s hard to manually source. AI makes this process much simpler. It does quickly, and at scale, what would be onerous to achieve by hand.
Here are some ways my friends and clients are using AI in marketing:
Sentiment analysis on social media to aggregate positive and critical product reviews with tools like Gumloop.
Automating competitor intelligence reports to stay up to date with what rival brands are doing. You can improve the ROI of your marketing campaigns with better targeting.
AI workflows to write creative copy, helping you keep up with the internet’s incessant demand for content (SEO optimization).
Video editing and content creation workflows with tools like Midjourney and Crayo.
Automating and presenting report with things like Claude Artifacts.
Ad creation automation with tools like Arcads.
And a ton more we'll get into in this article.
It’s likely that you’ll use more than one AI-powered software solution. In fact, most data manipulation tools now use the power of machine-learning and automation to achieve impressive results at scale. In this rundown of some of the best AI-driven apps and platforms, I’ll explain exactly what each one does, what its benefits are, as well as any limitations it might have.
Prefer to watch my top favorite tools? Check out my video:
For those that like to read, keep scrolling.
What are AI marketing tools?
AI marketing tools are software platforms that integrate with LLMs and your existing marketing workflows, using MCP (Model Context Protocol), to help automate internal workflows for marketers. These tools can help you either create something new, using AI, or take your automation skills to the next level without needing to be an AI Engineer.
At first, many of these AI tools seemed to just be using regular machine learning algorithms that had nothing to do with modern day "AI". But now, many of them leverage LLMs like ChatGPT, Claude, Gemini, or Grok, to give your existing workflows a layer of intelligence we have never seen before. It's actually quite amazing.
There's now this wave of marketing automation platforms that is changing the way teams think about productivity. Even Tobi, CEO of Shopify, sent a memo saying that all employees need leverage AI tools in some way. So it's no longer something we can turn a blind eye too (even though I did for some time).
Okay, let's check out the tools!
26 best AI marketing tools to grow your business in 2025
Here are 25 AI marketing tools you need to try in 2025:
Okay, let’s dive a bit deeper into each one.
1. Gumloop (best for AI automations)
Gumloop is the most underrated AI tool on the market right now. Founded just a year ago by two Canadian prodigies, this AI automation tool has quickly won my heart.
They're used by teams at Webflow, Instacart, Shopify, and a ton more.
If you’re familiar with Zapier, this tool is like that but with an AI layer over it. It’s like if Zapier and ChatGPT had a baby.
Gumloop lets you connect any LLM model (like GPT-4, Claude, Grok, etc.) to your internal tools and workflows — without writing a single line of code.
The UI (user interface) is so tasteful and clean and it’s actually nice to look at and use. And the amazing thing too is that you don’t need your own OpenAI or Anthropic API keys — Gumloop gives you access to premium LLMs right out of the box and they eat the costs. It’s all baked in. And now with Gumloop's MCP launch, it's become one of the best AI tools for startups and marketing teams (hence why so many big tech companies are starting to use it).
I already wrote a full Gumloop review if you want a deeper dive. I also put it head-to-head with n8n (another popular AI automation tool) in this Gumloop vs n8n comparison, which breaks down exactly where each tool shines.
Here are a few reasons why I’ve been using Gumloop:
Built-in access to the latest AI models: No need for API keys or surprise billing.
No need for API keys or surprise billing. Beautiful interface: It’s like a modern Zapier, but with smoother UX and more flexibility for AI workflows.
It’s like a modern Zapier, but with smoother UX and more flexibility for AI workflows. Powerful web and app scraping: Easily scrape content from sites and add them to tools like Notion, Slack, or Google Sheets to feed into your workflows.
Easily scrape content from sites and add them to tools like Notion, Slack, or Google Sheets to feed into your workflows. Continuous AI agents: Set up automations that run continuously and act on new data in real-time. This is great for sales, research, or admin tasks.
If you’re looking for a real AI marketing tool, this is it. They’re not paying me to say this, but I reached out to Max, the CEO of Gumloop, and he gave me a 20% off coupon code to give to my readers (Code: MARKETERMILK).
I love the tool so much I went to San Francisco to meet the team and took this photo of myself in their office (lol).
Anyways, it's a great tool and the free plan is super generours. If you want to upgrade to get more credits, use code MARKETERMILK at checkout and you’ll get 20% off your monthly plan.
2. Surfer SEO (for content optimization)
Surfer SEO is a content optimization tool that helps you create copy for ranking on search engines — a worthy goal for any content strategy. While you do the writing, Surfer assesses and scores your content according to its keyword density, readability, length, use of headers, and other aspects which push content up the rankings.
To use Surfer SEO, first you choose your domain, niche, and target audience. The system will then give you actionable insights by highlighting the top-ranking keywords, suggest a content outline structure, and even define image density for your piece. You can work directly on Surfer SEO, which has its own text editor, or copy-paste for quick analysis. As you edit your work, you’ll see the SEO improving in real time.
Integrations are available with other content marketing tools like Jasper, WordPress, Google Docs, and more. Surfer SEO promises hit your organic growth metrics for Google search, and satisfied clients include FedEx, Shopify, Quantas, and Viacom.
Notion AI is a cool new feature that Notion recently added to their popular productivity platform. It uses AI to make getting stuff done in Notion a breeze. Basically, you can ask questions in plain English about anything in your Notion workspace — whether it's your notes, projects, docs or wikis — and Notion AI will automatically pull up the answer. It's like having a personal assistant built into the project management tool.
The AI can also help you write, brainstorm ideas, fill out tables automatically, and more. So it takes a lot of the manual busywork out of using Notion.
This feature costs either $8 or $10 per member per month depending on if you pay annually or monthly. It's available for any paid Notion plan, and can even be added to free plans.
Notion takes privacy and security seriously too. Your data is encrypted and they comply with data protection laws like GDPR. The AI doesn't use customer data to train itself unless you specifically opt-in to that.
You can try Notion AI free for a while, with the number of free responses you get depending on your workspace membership. The plan is for the AI integration to expand over time and add even more capabilities. Since it works seamlessly with Notion's existing text editor and features, it should feel like a natural upgrade.
The bottom line is that Notion AI makes it even easier to stay organized and work smarter using this popular tool. The AI handles a lot of tedious tasks so you can focus on getting meaningful work done.
The people behind Jasper, the best-known of the various AI-powered copywriting systems, quickly became a victim of their own success. Marvel sent them a cease-and-desist letter after they had secured more than 350,000 users. Their AI was previously known as Jarvis, cheekily inspired by Tony Stark (AKA Iron Man)’s virtual assistant. And so, Jasper was reborn.
Jasper, this human writer must grudgingly accept, is remarkably good at creating copy, in a range of tones and styles, on any topic you can throw at it. Its creators say it has “read” 10% of the internet. How well does Jasper work? Using a free trial, I asked Jasper to write 40 words about AI in business automation. It came up with:
AI is the next step in business automation. AI had been instrumental in improving business processes. AI can be deployed to an organization’s business process for a particular strategic purpose to increase efficiencies, cut costs and improve customer service.
This is certainly a decent start, although you still require human intervention to make sense of the flow of the copy, and there’s an element of repetition. Jasper’s natural language processing is perhaps best seen as a tool to create early drafts for later polishing by human copywriters.
Whether you’re looking to write copy for email campaigns, product descriptions for ecommerce products, blog posts, or landing page copy, Jasper can do it all.
It has a simple and intuitive dashboard, is inexpensive to implement, and will certainly speed up the content creation process. Jasper, which boasts over 5,000 5-star product reviews, won’t turn you into Tolstoy, but it will keep those vital SEO page scores high.
5. Lexica Art (for blog thumbnails)
Lexica Art is a high-quality AI image generator that's one of the best I've seen. It creates some of the most realistic AI images and you can generate marketing content for almost anything. I've personally used this generative AI-powered tool to create blog thumbnail images for my SEO (search engine optimization) clients. There are different prompts you can use and save so all the images it generates are "on brand" with whatever brand guidelines you have. Some brands even use it for their social media posts.
If you're looking to move away from standard stock images for your blog thumbnails, this is a tool you definitely need to check out.
On the surface, LALAL.AI looks like a tool for musicians not marketers. But this tool is actually great for anyone who records any audio for things like a podcast or YouTube video. If you live in a loud city like me, recording videos can get frustrating. With LALAL.AI I can record a video and then upload the audio file to this tool and it automatically removes all of the background nice — without lowering the quality of my voice (which is what most tools end up doing).
This is an amazing tool for video marketers and I definitely recommend you give it a try if you find yourself getting frustrated with background noises in your recordings.
If you're creating short form videos for TikTok, Instagram Reels, or YouTube Shorts, Crayo is a tool you definitely want to check out.
The platform was started by Musa and Daniel — two big YouTube creators who are known for generating millions from faceless YouTube channels (and for mentoring some of the biggest short-form video creators out there). The tool aims at streamlining the video creation process by helping you ideate, produce, and generate videos made to go viral.
If you have a marketing strategy around using voiceovers and graphics to tell stories your target audience would be interested in, Crayo could help you produce those videos a lot faster.
8. Brandwell (for generating SEO blog posts)
Brandwell (formerly Content at Scale) is a platform I've been experimenting with for the past few months and I have to say, I'm pretty impressed. Out of all the AI writing tools that I've used, this is one of the few that passes AI detectors. Any time I generate an article with this tool, and run it through an AI detector, it usually comes out at least 70% human-written — which is quite impressive.
The platform is still quite new and the UI can be a bit buggy. But the content it generates is some of the best I've seen when it comes to AI content generation. It's not as flexible like Surfer is in terms of being able to label H2 and H3 headings in your articles, but the actual content it generates is a bit more higher quality than that of Surfer and even Jasper. I definitely recommend playing around with this tool if you're looking to generate SEO blog posts. Of course, you always want a real human to review the final draft.
9. Originality AI (for AI content detection)
Originality AI is an AI content detector and plagiarism tool. I run almost every piece of content through this tool these days to make sure it passes has being written by a human. Of course, I won't run actual human writing through it. But I'll generally run AI generated content, from a tool like Content at Scale, through this just to double check what areas need some work.
This is also a good tool to run your content through if you're working with freelance writers and want to make sure they're not using ChatGPT to generate large portions of text. Of course, take these detectors with a grain of salt. There have been reports of it falsely accusing human writing as AI writing. But, out of most of the AI content detectors out there, I found this one to be one of the best.
10. Writer (content writing for teams)
First off, Writer has secured a high value URL, indicating lofty ambitions. They position their platform as a writer’s assistant for marketing teams. Writer is a collaborative efficiency tool which takes some of the features of a traditional text editor like Word and turbocharges them.
Features include autocorrect, autocomplete, grammar and clarity checks, and there are often-used snippets to paste in. There’s also a suite of intelligence tools to maintain house style, including a database of approved terminology (vital for tech, legal and financial firms). Their AI is light touch, sitting in the background making recommendations rather than rewriting block of copy.
When you have a virtual or hybrid team working with minimal in-person supervision, this AI writer could provide all the reassurance you need that your copy remains professional and accurate across all uses. Clients include Deloitte, Accenture, Twitter and Vistaprint.
11. Undetectable AI (for rewriting AI content)
Undetectable AI is another AI content detector similar to Originality AI. What makes this one different is that it can actually rewrite AI generate content from ChatGPT to make it sound like a human. I've tested this by creating a paragraph of text in ChatGPT, running it through Undetectable AI to rewrite it, then double checking it with Originality AI. To my surprise, it does a pretty good job.
Again, you want to take these AI detectors and rewriters with a grain of salt. Sometimes this tool will rewrite things that don't totally make sense. Or it will purposely mess up in terms of grammar. So, you'll still want to read everything it generates to make sure there are no errors.
12. ContentShake AI (for SEO blog writing)
ContentShake AI is an AI optimization tool for those who work in SEO and content marketing. What makes the tool unique compared to other content optimizations tools is that it combines the power of LLMs, and SEO data from Semrush, to help you create SEO optimized web pages.
The tool starts by giving you trending topics in your niche, then you can generate detailed SEO content outline, and from there you can write full blog posts in multiple languages — all within the same interface.
The main selling point is that it uses Semrush’s data to give you an optimization score that gives you tips on how to rank for more keywords in one blog post. It also helps you improve the readability of your content with one-click rewrite options.
What I also find impressive is how it handles brand voice. You can upload your writing samples, and ContentShake will create a tone that mirrors your style (or your brand’s). Whether you’re writing for a creator media company or a serious B2B company, it customizes the tone to match your persona.
Here are some of the tool highlights:
AI + SEO insights in one: Combines real Semrush keyword and competitor data with LLM-powered writing to help you create content that actually ranks.
Combines real Semrush keyword and competitor data with LLM-powered writing to help you create content that actually ranks. One-click SEO blog posts: Generate full-length, optimized articles (in 7 languages) from a single prompt.
Generate full-length, optimized articles (in 7 languages) from a single prompt. Brand voice customization: Upload writing samples or choose a persona to make sure every piece sounds like you (or your brand).
Upload writing samples or choose a persona to make sure every piece sounds like you (or your brand). Direct publishing & sharing: Push articles to Google Docs or publish straight to WordPress.
So ya, if you’re looking for a tool to help you write better SEO copy, this is one to definitely check out.
13. Fullstory (for digital experiences)
By digital experience, Fullstory mean the journey a site visitor goes through from their first visit to conversion (or dismissal). They make the valuable point that you can learn a huge amount from the unpredictable things users do, which couldn’t have been anticipated.
To make this level of insight possible, Fullstory employ an AI to track every cursor move, click, and page visit across a visitor’s journey to create their “story”. This can then be compared with thousands of other visitors’ stories to derive insight. Fullstory leverage the processing power and scalability of AI automation to discover opportunities and errors much more quickly than any human observer would.
Fullstory claim users will make cost savings, retain more customers, and improve the UX of their site significantly. Their current client roster includes GAP, Zipcar, Icelandair, and Forbes.
14. Zapier (for automating tasks)
Zapier is really the Lego of tech stack and process integration. It's the OG of AI agent platforms. Using it you can build connections and marketing automations between thousands of different systems, saving time, promoting efficiency, reducing repetitive tasks, and making cost savings. You build customized workflows to link actions in one system to automated processes in one or more others. The salient data is pulled from the right place each time.
These automations can be written without coding, and there are templates to speed things up. Zapier calls its automations zaps, and it features over 3,000 integrations at time of writing. You can even create branching workflows, dependent on logical criteria you set.
The AI is at work behind the scenes interpreting signals which trigger processes with a speed and efficiency no human team could master. Clients rave about the time savings these zaps create. There’s excellent support too, including a blog, webinars, online no-code community, and Zapier University for training.
15. Hemingway App (for content editing)
Even if you only want to use human writers to create your copy, AI can at least help edit it for maximum readability and clarity. Named after a writer who was famously sparing with words, Hemingway highlights aspects of “poor” style including overlong sentences, passive voice, and excessive adverb use.
Hemingway also awards a readability score, based upon US educational grades. To reach the largest audience, grade 9 or lower is considered ideal. It’s exceptionally easy to use — just copy and paste your text into the online app and hit return.
Best of all — it’s free! The app was created by Ben and Adam Long in emulation of their favourite writer. Although there’s a $20 version including PDF exports, offline usability and instant publish features, the free version is still immensely useful.
That said, a perfectly optimized Hemingway piece might feel too simplistic for some purposes, such as annual reports, white papers, opinion pieces and other types of writing where personal style carries more weight than raw readability.
Vital AI assistants or irritating nuisance — whatever you think of chatbots, they are here to stay. Of course, a chatbot’s usefulness depends upon how you build it, which is where Chatfuel comes in. Rather than buying an off-the-shelf solution, the platform allows you to create a bespoke virtual personality yourself, using an intuitive drag and drop interface.
Whether you’re looking to replace a mundane FAQ page or drive potential leads down the funnel by offering discount codes, Chatfuel’s bots are remarkably good at interpreting even misspelt or non-grammatical responses. The AI here is doing a lot of sophisticated linguistic processing and it can easily spot keywords which trigger appropriate and helpful responses.
They’re an official partner with Meta (formerly Facebook), which should provide some reassurance that their AI is top-flight.
17. Grammarly (for content editing)
Like Hemingway, Grammarly will also analyze your content for ways in which it can be improved. Unlike Hemingway, it doesn’t make so many assumptions about style, and focuses its attention instead on traditional rules of syntax and grammar.
One great feature is that you can use Grammarly whilst working in many different apps, including Gmail, Word, Twitter, Facebook and more. Its AI will highlight errors and suggest corrections, which you are free to adopt or ignore. Going beyond mere grammar and punctuation, Grammarly can spot redundant words, inconsistencies in style and offer word choice alternatives.
It works by highlighting and color-coding errors or potential improvements (similar to Hemingway) and has been featured in such august publications as the Wall Street Journal, the New York Times and Forbes.
Advertising is inherently hit-and-miss, or at least it was prior to the dawn of AI. Albert personalizes and optimizes ad content at scale, across social media and paid search platforms, including Facebook, YouTube, Google Ads, Bing and more. Albert call their methodology “data-powered creativity”, and founder Om Shani believes in using AI and automation to free up human creatives to make campaigns that connect on a human level.
Albert.ai functions as a laboratory for testing and tweaking campaigns to take advantage of unseen channel opportunities, unthought of demographics or new markets. It helps make ad campaigns more relevant and lest wasteful.
Albert’s adopters include Crabtree & Evelyn, Telenor, and Harley Davidson. The latter enjoyed a five-fold swell in site traffic and an enormous 2,930% increase in leads per month.
19. Headlime (for landing pages)
Landing page copy is vital — it’s the storefront of the digital realm. Headlime is an AI-powered content-writing system designed to perfect the art of the landing page.
Powered by the deep learning abilities of GPT-3 from OpenAI, Headlime uses machine learning to help predict and complete text you type, potentially saving significant time. It suggests high performing subject lines, optimizes word count, and can write copy in multiple tones and languages.
Like Jasper, it can write blog content, but it’s integrated with a simple landing page builder so you don’t have to copy-paste constantly. Most importantly, it’s constantly focused on the task at hand — optimizing time on page and conversions. With over 1,700 copy templates and 11 languages, you could have a global landing page up and running in no time.
At first Userbot might seem like just another chatbot but it’s much cleverer than that. When Userbot can’t parse a customer’s query, it hands over to a human operator but continues to monitor and learn from the rest of the conversation. Userbot then uses what it learns to improve and add the new user query to its repertoire.
Over time, therefore, Userbot should become more and more intuitive and effective, although you may still have to reply on human operators a fair bit when you first implement it. I tried it with the question “who are your top clients?” and it was unable to provide a meaningful response. For the record, they include Aboca, SSG, and Vivactis Group.
The system provides useful customer data, which you can use to monitor the effectiveness of your sales team or customer support department (it also integrates with many popular CRM platforms).
21. Browse AI (for scraping web pages)
Competitive Intelligence (CI) is one of the most powerful weapons in the digital marketer’s armory. It lets you to assess competitor brands and spot new trends, pricing strategies, reviews, and product launches. To do CI at scale, you need to use data scraping, employing algorithms (aka “spiders” or bots) which crawl competitor sites and extract useful data.
Browse AI allows you to quickly train a bot to source data for you, automatically filling in a spreadsheet with everything you need. You might get it to look for one- or two-star reviews of competitor products in order to spot possible product improvements, or check the current price of similar products on ecommerce sites, for instance.
Browse’s creators say their AI can mimic human behavior to fool Captcha and other bot-spotting protections. The product is used by over 2500 companies including Adobe, Amazon, Salesforce, and HubSpot.
22. Algolia (for search and recommendation APIs)
Search fields can either prove really helpful or endlessly frustrating. Rather than plug-in a “powered by Google” field, why not create a bespoke search facility of your own?
This is what Algolia enables, proving especially popular with entertainment companies or ecommerce firms with large inventories. The less time visitors have to spend fruitlessly scanning your catalogue the more likely they are to buy from you.
Create your own search filter to enable your customers to find exactly what they want at lightning speed. Algolia is already incorporated into the sales portals of Staples, Gymshark, NBCUniversal, Decathlon, Lacoste, and many more.
23. PhotoRoom (for removing image backgrounds)
Here’s a neat (and free) specialist tool — it selectively removes the background of any photo, leaving the human subject highlighted on a transparent background you can incorporate into other graphics. I tried it with several photos of my own and it worked beautifully.
This is a design tool which uses AI and machine learning to identify the subject of a portrait and separate it from the background. While it might previously have taken a designer ten minutes to patiently define the outline of an image, PhotoRoom does it in seconds. You can also drop in a colored background of your choice.
It’s an absolute blessing for anyone tasked with creating a “meet the team” page or creating an avatar to use in multiple locations. There’s a premium batch version, and an app for mobile users.
Constructing standard email responses are another marketing task which can quickly become repetitive and labor-intensive. Reply.io’s AI Sales Email Assistant aims to remove much of that drudgery. But it also has many different use cases, describing itself as a “sales engagement platform.”
While the conversion rate for email marketing campaigns may be a lowly 1.22%, that can translate to a lot of promising leads when you scale up. To make the most of this technique, which can be fully automated, you need an AI-powered email marketing tool such as Reply.io.
Build cold email drip campaigns across multiple channels and Reply will automate the rest, applying AI-powered response scoring to help identify leads which hold potential. There are a host of CRM integrations and predictive analytics tools to track the progress of your campaigns.
25. Brand24 (for media monitoring)
If you want to find out how your brand is being mentioned all over the net where do you start? Brand24 scours news sites, social media, blogs, forums, video, and other locations to aggregate mentions. It then applies sentiment analysis to identify topics of conversation and the underlying emotions of reviewers and users.
You can respond quickly to criticism and intervene with customer support issues, improving customer retention and potentially spotting product and service flaws before they become crises. Much more efficiently than a Google keyword search, Brand24 will highlight problematic mentions and great reviews, weeding out irrelevancies.
There’s a great hashtag trend-spotting feature and good customer support including blogs and masterclasses to sharpen your marketing strategy and customer service skills. Clients include Uber, Stanford University, and Intel.
26. Influencity (for influencer marketing)
The use of influencers in social media marketing has been a major trend in recent years and isn’t showing signs of slowing. Whether its hauls, product reviews, sponsorship or traditional advertising, social media influencers are big business for brands, especially those aimed at niche or younger demographics.
Influencity bills itself as the “most complete influencer marketing platform” on the market, and it’s used by such giants as WPP, Kellogg’s and Samsung. It helps brands assess and contact influencers, collaborate on campaigns and then track their effectiveness.
All the major social media platforms are covered. There are plenty of stats and the ability to work at scale across multiple brands, making this a great agency solution.
AI-powered marketing is here to stay
Given the many benefits that AI algorithms can provide — scalability, reach, efficiency, cost savings, decision making, analytic power, better customer experience, and more — it’s clear that we are still only at the dawn of this AI technology revolution. Marketers have more exciting tools at their fingertips than ever before, allowing the tiniest startup to compete for global success alongside the most established brands.
Many of the above tools have freemium versions available, so be open-minded, give them a try, and they may become your best friend for future marketing efforts.
| 2025-06-20T00:00:00 |
https://www.marketermilk.com/blog/ai-marketing-tools
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[
{
"date": "2025/06/20",
"position": 88,
"query": "machine learning job market"
}
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|
HR use of AI in recruiting in the U.S. 2024 - Statista
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AI use in recruiting in the U.S. 2024
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https://www.statista.com
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[
"Raphael Bohne",
"Jun"
] |
In 2024, the top way in which HR departments used artificial intelligence (AI) in recruiting, interviewing, and hiring in the United States was to generate job ...
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SHRM. (June 19, 2025). Use of artificial intelligence (AI) in recruiting, interviewing, and hiring according to Human Resources (HR) professionals in the United States in 2024 [Graph]. In Statista . Retrieved July 15, 2025, from https://www.statista.com/statistics/1535364/hr-use-of-ai-in-recruiting-us/
SHRM. "Use of artificial intelligence (AI) in recruiting, interviewing, and hiring according to Human Resources (HR) professionals in the United States in 2024." Chart. June 19, 2025. Statista. Accessed July 15, 2025. https://www.statista.com/statistics/1535364/hr-use-of-ai-in-recruiting-us/
SHRM. (2025). Use of artificial intelligence (AI) in recruiting, interviewing, and hiring according to Human Resources (HR) professionals in the United States in 2024 . Statista . Statista Inc.. Accessed: July 15, 2025. https://www.statista.com/statistics/1535364/hr-use-of-ai-in-recruiting-us/
SHRM. "Use of Artificial Intelligence (Ai) in Recruiting, Interviewing, and Hiring According to Human Resources (Hr) Professionals in The United States in 2024." Statista , Statista Inc., 19 Jun 2025, https://www.statista.com/statistics/1535364/hr-use-of-ai-in-recruiting-us/
SHRM, Use of artificial intelligence (AI) in recruiting, interviewing, and hiring according to Human Resources (HR) professionals in the United States in 2024 Statista, https://www.statista.com/statistics/1535364/hr-use-of-ai-in-recruiting-us/ (last visited July 15, 2025)
Use of artificial intelligence (AI) in recruiting, interviewing, and hiring according to Human Resources (HR) professionals in the United States in 2024 [Graph], SHRM, June 19, 2025. [Online]. Available: https://www.statista.com/statistics/1535364/hr-use-of-ai-in-recruiting-us/
| 2025-06-20T00:00:00 |
https://www.statista.com/statistics/1535364/hr-use-of-ai-in-recruiting-us/
|
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The AGI economy is coming faster than you think - Freethink
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The AGI economy is coming faster than you think
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https://www.freethink.com
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[] |
The uncomfortable truth is that many traditional jobs will be replaced by AI — but the emerging truth is that economically valuable complements ...
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Sign up for Rohit Krishnan’s Strange Loop Canon Substack Essays about innovation, progress, technology, business, science, and complex systems. Subscribe now
OpenAI CEO Sam Altman said in January that his company believes 2025 may be the year “the first AI agents ‘join the workforce’ and materially change the output of companies.”
In a recent interview with Axios, Dario Amodei — current CEO of AI startup Anthropic and former VP of research at OpenAI — made a bold prediction for how that AI integration could affect the people already in the workforce: In the next one to five years, AI could eliminate 50% of entry-level white-collar jobs and spike unemployment 10–20%.
Tech CEOs aren’t the only ones predicting that AI’s impact on the economy will be huge. Investors, financial institutions, and macro forecasters have all converged on the same basic storyline: AI’s impact is going to be big, it’s going to happen fast, and it’s going to be disruptive.
But how will the disruption play out?
Charting the disruption
We likely have four options, as shown in the table below. The horizontal axis represents how the gains from AI will be distributed: broadly or among a concentrated group. The vertical axis represents the speed of AI adoption: rapid or gradual.
Capital, labor markets, and policy all point us toward the rapid row:
Capital: Nvidia’s latest quarterly revenue cleared $148 billion, up 86% year‑on‑year, and there is still a waiting list for high‑end H100 boards. A single frontier model training run already costs roughly $500 million in hardware and power. The Big Four cloud computing companies plus Meta poured roughly $200 billion into AI/data center capex in 2024 alone.
Labor: The leading models solve bar exams, draft contracts, and write passable code. Employers are testing replacements for workers, not just systems to augment them. Amodei’s forecasts sound aggressive, but early deployment studies are directionally supportive. Standardized tests at big consulting firms show productivity gains in the 30–40% range when LLM copilots are switched on.
Policy: Brussels is writing rules for how AI can be used at work, but the European Union’s AI Act focuses on transparency and liability, not moratoria. In the US, the Trump Administration rescinded all previous AI policies in January 2025. China is accelerating its domestic accelerator stack to get around export bans. Everywhere, regulators want a slice of the upside and are wary of pushing firms offshore. That is a permissive environment by historical standards.
Put those pieces together, and you get rapid adoption. We’re looking at one to five years, not one to five decades.
The live question, then, is whether we land in the left or right column — broad or concentrated distribution of the gains — and the answer depends on three levers: compute concentration, energy supply, and the emergence of new “meta-work” that keeps humans complementary to AIs.
A grounded scenario for 2030
Suppose AI adds one percentage point to global productivity annually starting in 2027, as Goldman Sachs projects. Compound that and the world is ~6% richer by 2030. Call it a $6 trillion bump.
At the same time, entry‑level white‑collar employment shrinks by perhaps 30%. Some of the displaced exit through retirement. Others get absorbed into the new meta-work or traditional services. In the US, unemployment might peak in the high single digits among actual labor market participants. In parts of continental Europe, it hits the low teens. Wage dispersion might even widen: The incomes of earners in the 90th percentile increase by 15%, the median stays flat, and the bottom quartile decreases.
In such a scenario, international trade will reshuffle. Energy- and chip‑rich nations (e.g., the US, Taiwan, and the Gulf states) run surpluses in the sector. Traditional manufacturing exporters, such as Vietnam, see some economic losses as traditional importers start using automation and robotics to make on-shore manufacturing more cost effective. Service exporters (e.g., India, the Philippines, and Anglophone Africa) do well if they can rent the models cheaply and sell AI‑enhanced tasks abroad.
Meanwhile, inflation comes in two parts. Digital cognition falls toward zero marginal cost, but electricity, land near data centers, and the rare metals in GPUs are still costly. The agglomeration effects of wanting to live where the other geniuses live means cities continue to be the center of economic activity. The Consumer Price Index thus might tell a muddled story.
Left to itself, that bundle of facts lands us in the Oligarchic Boom quadrant of our table: rapid gains, captured by a few, with a political backlash brewing.
What drives the split between broad and concentrated gains?
Compute concentration is the first determinant.
Training budgets scale super‑linearly with capability: more capable AIs cost even more to train than their predecessors. There was a 2,000-fold jump in spend in the five years between GPT-2 to GPT-4, while capability went from “writes a coherent paragraph” to “aces college exams.” And it hasn’t stopped. That’s why OpenAI is spending tens of billions on Stargate. Unless open source keeps pace, the new “rail barons” will be whoever can afford to spend billions training AI. Talent follows the clusters. Meta is already dangling eight-figure compensation to senior AI engineers, while rescinding offers to entry‑level hires. Left unchecked, this dynamic pushes us straight toward Oligarchic Boom.
Energy is the second.
The International Energy Agency expects electricity demand for data centers to more than double to ~945 TWh — the current usage of Japan — by 2030, with AI largely driving the increase. Regions with a cheap supply of clean energy (e.g., Texas for wind, Québec for hydro, the Gulf Coast for nuclear) attract the clusters and run persistent current account surpluses. If electric grid expansion falls behind, adoption slows and the spoils remain locked in a few power‑rich enclaves, leading to Stalled Striation.
Human complements come last, and they are more malleable.
AGI still needs data, goals, and real‑world priors it cannot infer from pixels. If AGI eats cognitive tasks, what valuable human tasks are left? The answer is meta‑work: feeding, steering, and adjudicating the models. The right analogy is not the assembly line to service work, but agriculture to software: entire categories of work that existed in service to other lines of work will become industries in their own right once the cost curve changes.
That creates fresh roles. We could see model shepherds who curate synthetic fraud datasets for insurers, prompt‑pack designers in Nairobi who fine‑tune Midjourney outputs, or historians in California labs who flag hallucinated citations. None of these roles are glamorous, but they are all essential, and what they mostly resemble are the proto‑IT departments of 1965: clunky and over‑specialized, but seeds of much larger sectors. If education systems and gig platforms can scale these complements quickly, gains can diffuse more broadly.
Nudging the outcome toward Shared Upswing
Economist Tyler Cowen frequently emphasizes marginal thinking, asking questions like: “What institutional reforms are on the margin of being possible?” In terms of the impact of AI on the economy, three candidates could qualify:
Diffuse ownership of the capital stock. Equity sharing, data‑dividend trusts, or sovereign wealth stakes in frontier labs can spread the excess profits from compute. It is not socialism — it is railroads and telephony redux. If California can mandate film residuals, it can require model residuals. Speed‑focused re‑skilling. A compute excise tax of even 0.5% on AI companies could fund lifelong learning accounts for every worker in a G‑7 economy — transforming job destruction into task rebundling. Should it be done is unclear, but it’s why Altman has been discussing universal basic income from the largesse of the AI companies’ outputs. Energy‑capacity pacts. Match every new hyperscale data center permit to an equivalent amount of low‑carbon energy: wind, solar, small modular nuclear, whatever clears. That prevents AI growth from running into a power wall and keeps clusters geographically diversified.
Challenges could arise. If we get 4% real interest rates or more, it might neuter speculative capex, meaning no new investments in AI infrastructure or reskilling initiatives. A few high‑profile failures in AI might well provoke EU‑style brakes. Open-source efforts might fall a full generation behind closed labs — all while compute cost soars.
None of the steps above would be costless, either, but all three are politically plausible and would move the needle from Oligarchic Boom toward Shared Upswing.
The bottom line
Skeptics may ask: “If AGI does all cognitive tasks, what is left for humans?”
Historically, when the cost of an input collapses, new downstream goods appear. Electricity, for example, gave us aluminium smelting and MRI scanners. Cheap cognition can give us personalized tutors, automated drug design, neighborhood‑scale business intelligence, and yes, whole markets for evaluating and steering AI itself. These are not sci‑fi fantasies — venture capital is already funding them.
The uncomfortable truth is that many traditional jobs will be replaced by AI — but the emerging truth is that economically valuable complements are already visible. They need scale, norms, and capital, not magic. Whether they arrive in time to prevent the widespread unemployment that Amodei predicts is a management and policy challenge, not a technological one.
Whether you believe Amodei or not, his warnings should not be taken lightly. If what he and many others are saying is even somewhat true, the best-case scenario is an extraordinary disruption to the way we work — the kind that normally takes decades to unfold — over the next few years. Entirely new classes of jobs must emerge because the alternative is widespread unemployment and economic upheaval.
Ultimately, we seem to be headed toward a future where we spend an extraordinary chunk of our economy on data centers and AI infrastructure. That investment will then make space for new segments to flourish, but whether that means current industries will become more productive or entirely new sectors will emerge and quickly grow remains to be seen.
The correct response is not panic or complacency, but institutional hustle.
The economic die is not fully cast, but its weight is now measurable.
Rapid adoption looks close to inevitable, but the distribution of gains is still very much to be determined. If institutions manage to spread ownership, train complements, and build the necessary electric grid, 2030 could mark the start of a Shared Upswing: a messy but overall positive rerun of the 1990s internet boom with even larger numbers. If they fail, expect an Oligarchic Boom, which will create fertile ground for grievance politics and regulatory whiplash.
Either way, Amodei’s and Altman’s timelines are too short to ignore, and 27% of jobs are highly automatable. If 50% are automated — as Amodei warns they will be — they’ll be replaced by fractional gigs mediated by AI platforms instead of payroll departments. Skilled professionals who master AI toolchains could see wage increases. Incomes will go down for the rest.
The correct response is not panic or complacency, but institutional hustle.
In 1997, WIRED’s “Long Boom” envisioned 25 years of prosperity from PCs and networks, but even that bold forecast is a long shout from the double-digit GDP growth and capturing of “the light cone for all future value in the universe” that some now predict will follow in the wake of AI.
As we navigate this transition, we should remember two things. First, every wave of automation has created more work than it destroyed, but only after a painful transition period. Second, the more widely we spread the new tools, the greater the likelihood that happy recursion continues. That is as close to an iron law as economics ever gives us.
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].
| 2025-06-20T00:00:00 |
https://www.freethink.com/artificial-intelligence/agi-economy
|
[
{
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{
"date": "2025/06/20",
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},
{
"date": "2025/06/20",
"position": 85,
"query": "AI economic disruption"
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{
"date": "2025/06/20",
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"query": "AI economic disruption"
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] |
|
Bosses want you to know AI is coming for your job
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Bosses want you to know AI is coming for your job
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https://www.washingtonpost.com
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[
"Danielle Abril",
"Caroline O'Donovan",
"Dan Lamothe",
"Ellie Silverman",
"Tatum Hunter",
"Annie Gowen",
"John Muyskens",
"Arelis R. Hernández",
"Daniel Wolfe",
"Nicole Dungca"
] |
But there is evidence that workers across the United States are increasingly using AI in their jobs and the technology is starting to transform ...
|
SAN FRANCISCO — Top executives at some of the largest American companies have a warning for their workers: Artificial intelligence is a threat to your job. CEOs from Amazon to IBM, Salesforce and JPMorgan Chase are telling their employees to prepare for disruption as AI either transforms or eliminates their jobs in the future.
AI will “improve inventory placement, demand forecasting and the efficiency of our robots,” Amazon CEO Andy Jassy said in a Tuesday public memo that predicted his company’s corporate workforce will shrink “in the next few years.” He joins a string of other top executives that have recently sounded the alarm about AI’s impact in the workplace.
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Economists say there aren’t yet strong signs that AI is driving widespread layoffs across industries. But there is evidence that workers across the United States are increasingly using AI in their jobs and the technology is starting to transform some roles such as computer programming, marketing and customer service. At the same time, CEOs are under pressure to show they are embracing new technology and getting results — incentivizing attention-grabbing predictions that can create additional uncertainty for workers.
“It’s a message to shareholders and board members as much as it is to employees,” Molly Kinder, a Brookings Institution fellow who studies the impact of AI, said of the CEO announcements, noting that when one company makes a bold AI statement, others typically follow. “You’re projecting that you’re out in the future, that you’re embracing and adopting this so much that the footprint [of your company] will look different.”
Some CEOs fear they could be ousted from their job within two years if they don’t deliver measurable AI-driven business gains, a Harris Poll survey conducted for software company Dataiku showed.
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Tech leaders have sounded some of the loudest warnings — in line with their interest in promoting AI’s power. At the same time, the industry has been shedding workers the last few years after big hiring sprees during the height of the coronavirus pandemic and interest rate hikes by the Federal Reserve.
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At Amazon, Jassy told the company’s workers that AI would in “the next few years” reduce some corporate roles like customer service representatives and software developers, but also change work for those in the company’s warehouses.
IBM, which recently announced job cuts, said it replaced a couple hundred human resource workers with AI “agents” for repetitive tasks such as onboarding and scheduling interviews. In January, Meta CEO Mark Zuckerberg suggested on Joe Rogan’s podcast that the company is building AI that might be able to do what some human workers do by the end of the year.
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“We, at Meta as well as the other companies working on this, are going to have an AI that can effectively be sort of a mid-level engineer at your company,” Zuckerberg said. “Over time we’ll get to the point where a lot of the code in our apps … is actually going to be built by AI engineers instead of people engineers.”
Dario Amodei, CEO of Anthropic, maker of the chatbot Claude, boldly predicted last month that half of all white-collar entry-level jobs may be eliminated by AI within five years.
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Leaders in other sectors have also chimed in. Marianne Lake, JPMorgan’s CEO of consumer and community banking, told an investor meeting last month that AI could help the bank cut headcount in operations and account services by 10 percent. The CEO of BT Group Allison Kirkby suggested that advances in AI would mean deeper cuts at the British telecom company.
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Even CEOs who reject the idea of AI replacing humans on a massive scale are warning workers to prepare for disruption. Jensen Huang, CEO of AI chip designer Nvidia said last month, “You’re not going to lose your job to an AI, but you’re going to lose your job to someone who uses AI.”
Google CEO Sundar Pichai said at Bloomberg’s tech conference this month that AI will help engineers be more productive but that his company would still add more human engineers to its team. Meanwhile, Microsoft is planning more layoffs amid heavy investment in AI, Bloomberg reported this week. Other tech leaders at Shopify, Duolingo and Box have told workers they are now required to use AI at their jobs, and some will monitor usage as part of performance reviews.
Some companies have indicated that AI could slow hiring. Salesforce CEO Marc Benioff recently called Amodei’s prognosis “alarmist” on an earnings call, but on the same call chief operating and financial officer Robin Washington said that an AI agent has helped to reduce hiring needs and bring $50 million in savings.
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Despite corporate leaders’ warnings, economists don’t yet see broad signs that AI is driving humans out of work. “We have little evidence of layoffs so far,” said Columbia Business School professor Laura Veldkamp, whose research explores how companies’ use of AI affects the economy. “What I’d look for are new entrants with an AI-intensive business model, entering and putting the existing firms out of business.”
Some researchers suggest there is evidence AI is playing a role in the drop in openings for some specific jobs, like computer programming, where AI tools that generate code have become standard. Google’s Pichai said last year that more than a quarter of new code at the company was initially suggested by AI.
Many other workers are increasingly turning to AI tools, for everything from creating marketing campaigns to helping with research — with or without company guidance. The percentage of American employees who use AI daily has doubled in the last year to 8 percent, according to a Gallup poll released this week. Those using it at least a few times a week jumped from 12 percent to 19 percent.
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Some AI researchers say the poll may not actually reflect the total number of workers using AI as many may use it without disclosing it.
“I would suspect the numbers are actually higher,” said Ethan Mollick, co-director of Wharton School of Business’ generative AI Labs, because some workers avoid disclosing AI usage, worried they would be seen as less capable or breaching corporate policy. Only 30 percent of respondents to the Gallup survey said that their company had general guidelines or formal policies for using AI.
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OpenAI’s ChatGPT, one of the most popular chatbots, has more than 500 million weekly users around the globe, the company has said.
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It is still unclear what benefits companies are reaping from employees’ use of AI, said Arvind Karunakaran, a faculty member of Stanford University’s Center for Work, Technology, and Organization.
“Usage does not necessarily translate into value,” he said. “Is it just increasing productivity in terms of people doing the same task quicker or are people now doing more high value tasks as a result?”
Lynda Gratton, a professor at London Business School, said predictions of huge productivity gains from AI remain unproven.
“Right now, the technology companies are predicting there will be a 30% productivity gain. We haven’t yet experienced that, and it’s not clear if that gain would come from cost reduction … or because humans are more productive.”
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The pace of AI adoption is expected to accelerate even further if more companies use advanced tools such as AI agents and they deliver on their promise of automating work, Mollick said. AI labs are hoping to prove their agents are reliable within the next year or so, which will be a bigger disrupter to jobs, he said.
While the debate continues over whether AI will eliminate or create jobs, Mollick said “the truth is probably somewhere in between.”
| 2025-06-20T00:00:00 |
2025/06/20
|
https://www.washingtonpost.com/business/2025/06/20/ai-ceos-predict-kill-jobs/
|
[
{
"date": "2025/06/20",
"position": 95,
"query": "AI replacing workers"
}
] |
Navigating Labor's Response to AI: Proactive Strategies for ...
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Navigating Labor’s Response to AI: Proactive Strategies for Multinational Employers Across the Atlantic
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https://www.theemployerreport.com
|
[
"Caroline Burnett",
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"Rachel Farr",
"Matthias Köhler",
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In 2024, the Trade Union Congress proposed an AI and Employment Rights Bill aimed at regulating how high-risk AI is deployed in the workplace.
|
Listen to this post
As AI adoption accelerates across workplaces, labor organizations around the world are beginning to take notice—and action. The current regulatory focus in the US centers on state-specific laws like those in California, Illinois, Colorado and New York City, but the labor implications of AI are quickly becoming a front-line issue for unions, potentially signaling a new wave of collective bargaining considerations. Similarly, in Europe the deployment of certain AI tools within the organization may trigger information, consultation, and—in some European countries—negotiation obligations. AI tools may only be introduced once the process is completed.
This marks an important inflection point for employers: engaging with employee representatives on AI strategy early can help anticipate employee concerns and reduce friction as new technologies are adopted. Here, we explore how AI is emerging as a key topic in labor relations in the US and Europe and offer practical guidance for employers navigating the evolving intersection of AI, employment law, and collective engagement.
Efforts in the US to Regulate AI’s Impact on Workers
There is no specific US federal law regulating AI in the workplace. An emerging patchwork of state and local legislation (e.g. in Colorado, Illinois and New York City) address the potential for bias and discrimination in AI-based tools—but do not focus on preventing displacement of employees. In March, New York became the first state to require businesses to disclose AI-related mass layoffs, indicating a growing expectation that employers are transparent about AI’s impact on workers.[1]
Some unions have begun negotiating their own safeguards to address growing concerns about the impact that AI may have on union jobs. For example, in 2023, the Las Vegas Culinary Workers negotiated a collective bargaining agreement with major casinos requiring that the union be provided advance notice, and the opportunity to bargain over, AI implementation. The CBA also provides workers displaced by AI with severance pay, continued benefits, and recall rights.
Similarly, in 2023 both the Writers Guild of America (WGA) and Screen Actors Guild-American Federation of Television and Radio Artists (SAG-AFTRA) negotiated agreements with the Alliance of Motion Picture and Television Producers (AMPTP) that include safeguards against AI reducing or replacing writers and actors. WGA’s contract requires studios to meet semi-annually with the union to discuss current and future uses of generative AI—giving writers a formal channel to influence how AI is deployed in their industry. The SAG-AFTRA contract requires consent and compensation for use of digital replicas powered by AI.
The International Longshoremen’s Association (ILA) has taken a more aggressive approach. In October 2024, the ILA launched a 3-day strike that shut down all major East and Gulf Coast ports demanding, among other things, a complete ban on the automation of gates, cranes, and container-moving trucks. The ILA and US Maritime Alliance eventually reached agreement on the terms of a CBA a collective in early 2025, which includes a provision prohibiting the introduction of “fully automated” technology—equipment that operates without any human interaction. And any new tech implementation must be agreed upon by the union and employers; if they cannot reach consensus, the matter goes to arbitration.
Unions are also challenging the usage of AI before the National Labor Relations Board (NLRB). Recently, SAG-AFTRA filed an unfair labor practice charge to the NLRB against a video game maker, alleging the employer utilized AI-generated voices to replace bargaining unit work without providing the union with notice or the opportunity to bargain. The case is pending, and we are monitoring developments.
Across the pond, trade unions have been quick to react to the disruptive power of AI.
In Europe, AI is Emerging as a Key Topic with Trade Unions and Works Councils
In the EU, AI in the workplace is a particularly sensitive issue—especially when it comes to its impact on jobs. The landmark EU AI Act is currently in its phased implementation stage, with key provisions such as a ban on prohibited AI systems and obligations on AI literacy under the AI Act taking effect in February 2025, and rules for general-purpose AI models and governance structures set to take effect by August 2025. While the EU AI Act does not ban job displacement by AI outright, it does contain several employee protections. Employers must consult with works councils before implementing AI, and in some jurisdictions, obtain their agreement. The Act also empowers individual employees by giving them the right to be informed when AI is used in decisions that affect them, to request explanations about how AI influenced those decisions, and to challenge outcomes.
In France, a court recently underscored the importance of treading carefully with employee representation rights with respect to AI in the workplace, even during testing and experimentation phases. In an interim order from the Nanterre Court of Justice in February, the court ruled that a company’s early deployment of AI tools in a “pilot phase” occurred before the works council (CSE) consultation process had been completed. It therefore suspended the implementation until the consultation was completed and ordered the employer to pay damages to the CSE for the harm suffered.
In the UK, the conversation around AI and employment is gaining legislative traction. In 2024, the Trade Union Congress proposed an AI and Employment Rights Bill aimed at regulating how high-risk AI is deployed in the workplace. The bill would have required employers to consult workers before implementing such systems, ensure transparency, and provide personalized explanations for AI-driven decisions. Notably, the bill would classify dismissals based on unfair reliance on high-risk AI as “automatically unfair.” Though the bill did not advance, it signals growing momentum in the UK toward incorporating worker safeguards into the AI adoption process. The independent AI Opportunities Action Plan commissioned by the UK government, published in January 2025, recognizes the change that AI will bring to the labor market. The report acknowledges the importance of developing life skills and educational opportunities for development, and also of diversity in the talent pool working in AI and data science.
In Germany, the deployment of AI in the workplace is closely tied to works council co-determination. While there is currently no specific AI-related co-determination, political discussions are ongoing about expanding the works council’s authority in this area. In the meantime, existing IT co-determination standards apply. Under established case law, the works council has co-determination rights whenever an IT system is capable of monitoring employee behavior or performance—criteria met by most AI systems used in the workplace. Given this legal backdrop, employers are strongly advised to engage proactively with works councils and negotiate a framework agreement on AI which can help streamline co-determination procedures and provide legal certainty for future implementations.
Proactive Strategies for Multinational Employers
In both the US and in Europe, partnering early with unions and employee representative bodies on AI can help employers avoid costly disputes and disruptions, including strikes. Proactive employers looking to reduce reputational risk and promote constructive labor relations can keep these best practices in mind:
Have a very clear understanding of the company’s obligations under any applicable CBA and with respect to employee representative bodies . For US employers with unionized labor, implementation of technology (AI or otherwise) may be addressed in the CBA (whether in a management rights clause or elsewhere). Even if the CBA is not clear or does not explicitly address AI, partner with counsel to consider closely what the company’s obligations may be, as it is conceivable there is no obligation to bargain.
. For US employers with unionized labor, implementation of technology (AI or otherwise) may be addressed in the CBA (whether in a management rights clause or elsewhere). Even if the CBA is not clear or does not explicitly address AI, partner with counsel to consider closely what the company’s obligations may be, as it is conceivable there is no obligation to bargain. Engage with labor early and anticipate concerns. Employers need not wait for contract negotiations. By way of example, in 2023, a global tech company formed a first-of-its-kind partnership with a union to address the impact of AI on workers. The initiative involved training union members on AI fundamentals and gathering their feedback to inform AI development, as well as both parties advocating for policies supporting AI-related workforce training amid growing concerns about job displacement and AI-driven inequality. Getting out ahead can eliminate the fear of the unknown and go a long way in building trust on issues related to job security, retraining and perceived fairness.
Employers need not wait for contract negotiations. By way of example, in 2023, a global tech company formed a first-of-its-kind partnership with a union to address the impact of AI on workers. The initiative involved training union members on AI fundamentals and gathering their feedback to inform AI development, as well as both parties advocating for policies supporting AI-related workforce training amid growing concerns about job displacement and AI-driven inequality. Getting out ahead can eliminate the fear of the unknown and go a long way in building trust on issues related to job security, retraining and perceived fairness. Promote transparency. Proactively involve unions and employee representative bodies in discussions about AI adoption, including its purpose, scope, and potential impact on jobs. Be prepared to articular the opportunities at stake clearly, including how AI tools can optimize work and working conditions.
Proactively involve unions and employee representative bodies in discussions about AI adoption, including its purpose, scope, and potential impact on jobs. Be prepared to articular the opportunities at stake clearly, including how AI tools can optimize work and working conditions. Collaborate on guardrails. Work with unions and employee representative bodies to establish boundaries on AI use that the employer may be comfortable with—such as limits on surveillance, algorithmic management, and automation of core job functions—while also exploring how AI can enhance, not replace, human roles.
Work with unions and employee representative bodies to establish boundaries on AI use that the employer may be comfortable with—such as limits on surveillance, algorithmic management, and automation of core job functions—while also exploring how AI can enhance, not replace, human roles. Conduct AI impact assessments and ensure compliance with applicable law. Before deploying AI tools, obtain legal advice on the application of emerging AI laws. Consider the tools’ potential impact on job functions, employee rights and workplace dynamics. This can help identify areas where labor engagement is recommended.
Before deploying AI tools, obtain legal advice on the application of emerging AI laws. Consider the tools’ potential impact on job functions, employee rights and workplace dynamics. This can help identify areas where labor engagement is recommended. Reskill and upskill. Consider offering training programs and career transition support to help workers adapt to AI-driven changes. Jointly developing and investing in these initiatives with unions and employee representative bodies can ensure alignment with workers’ needs and alleviate fears of AI-related job displacement.
Consider offering training programs and career transition support to help workers adapt to AI-driven changes. Jointly developing and investing in these initiatives with unions and employee representative bodies can ensure alignment with workers’ needs and alleviate fears of AI-related job displacement. Be prepared to bargain. Depending on whether AI tools materially impact working conditions, plan ahead, work with experienced counsel and solidify communication strategies to be ready if it becomes necessary to bargain with unions or consult with works councils.
For support developing your AI adoption strategies, including anticipating labor’s response, please contact your Baker McKenzie employment lawyer.
[1] New York’s Worker Adjustment and Retraining Notification (WARN) online portal—used by employers with 50+ employees to submit the required 90-day notice of a mass layoff or plant closure—now includes a checkbox asking whether “technological innovation or automation” contributed to the job losses. If selected, employers are also asked to specify the type of technology involved, such as artificial intelligence or robotic machinery.
| 2025-06-21T00:00:00 |
2025/06/21
|
https://www.theemployerreport.com/2025/06/navigating-labors-response-to-ai-proactive-strategies-for-multinational-employers-across-the-atlantic/
|
[
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How the world is preparing the workforce for AI - UGA Today
|
Is AI education a priority for the U.S.?
|
https://news.uga.edu
|
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The United States was one of 23 countries that considered workforce training and AI education a medium priority, with a less detailed plan ...
|
Learning what other countries are doing could help the U.S. improve its own plans for workforce preparation in the era of AI, according to a new UGA study. (Getty Images)
Creating AI-focused curriculum and teaching employees how to use AI are priorities of many countries
Artificial intelligence is spreading into many aspects of life, from communications and advertising to grading tests. But with the growth of AI comes a shake-up in the workplace.
New research from the University of Georgia is shedding light on how different countries are preparing for how AI will impact their workforces.
According to previous research, almost half of today’s jobs could vanish over the next 20 years. But it’s not all doom and gloom.
Researchers also estimate that 65% of current elementary school students will have jobs in the future that don’t exist now. Most of these new careers will require advanced AI skills and knowledge.
Human soft skills, such as creativity, collaboration and communication cannot be replaced by AI.” —Lehong Shi, College of Education
To tackle these challenges, governments around the world are taking steps to help their citizens gain the skills they’ll need. The present study examined 50 countries’ national AI strategies, focusing on policies for education and the workforce.
Learning what other countries are doing could help the U.S. improve its own plans for workforce preparation in the era of AI, the researcher said.
“AI skills and competencies are very important,” said Lehong Shi, author of the study and an assistant research scientist at UGA’s Mary Frances Early College of Education. “If you want to be competitive in other areas, it’s very important to prepare employees to work with AI in the future.”
Some countries put larger focus on training, education
Shi used six indicators to evaluate each country’s prioritization on AI workforce training and education: the plan’s objective, how goals will be reached, examples of projects, how success will be measured, how projects will be supported and the timelines for each project.
Each nation was classified as giving high, medium or low priority to prepare an AI competent workforce depending on how each aspect of their plan was detailed.
Of the countries studied, only 13 gave high prioritization to training the current workforce and improving AI education in schools. Eleven of those were European countries, with Mexico and Australia being the two exceptions. This may be because European nations tend to have more resources for training and cultures of lifelong learning, the researcher said.
The United States was one of 23 countries that considered workforce training and AI education a medium priority, with a less detailed plan compared to countries that saw them as a high priority.
Different countries prioritize different issues when it comes to AI preparation
Some common themes emerged between countries, even when their approaches to AI differed. For example, almost every nation aimed to establish or improve AI-focused programs in universities. Some also aimed to improve AI education for K-12 students.
On-the-job training was also a priority for more than half the countries, with some offering industry-specific training programs or internships. However, few focused on vulnerable populations such as the elderly or unemployed through programs to teach them basic AI skills.
Shi stressed that just because a country gives less prioritization to education and workforce preparation doesn’t mean AI isn’t on its radar. Some Asian countries, for example, put more effort into improving national security and health care rather than education.
Cultivating interest in AI could help students prepare for careers
Some countries took a lifelong approach to developing these specialized skills. Germany, for instance, emphasized creating a culture that encourages interest in AI. Spain started teaching kids AI-related skills as early as preschool.
Of the many actions governments took, Shi noted one area that needs more emphasis when preparing future AI-empowered workplaces. “Human soft skills, such as creativity, collaboration and communication cannot be replaced by AI,” Shi said. “And they were only mentioned by a few countries.”
Developing these sorts of “soft skills” is key to making sure students and employees continue to have a place in the workforce.
This study was published in Human Resource Development Review.
| 2025-06-20T00:00:00 |
2025/06/20
|
https://news.uga.edu/planning-for-ai-in-workforce/
|
[
{
"date": "2025/06/20",
"position": 66,
"query": "AI education"
},
{
"date": "2025/06/20",
"position": 85,
"query": "AI education"
}
] |
How can we use AI responsibly in education?
|
How can we use AI responsibly in education? — EdTech Innovation Hub
|
https://www.edtechinnovationhub.com
|
[
"Rachel Lawler"
] |
As AI reshapes how educators teach, learn, and develop skills, the panel considers the potential risks of using AI in education and how these can be ...
|
As AI reshapes how educators teach, learn, and develop skills, the panel considers the potential risks of using AI in education and how these can be mitigated to ensure its power can still be used to improve outcomes.
Sian Cooke, Head of Education Technology Evidence and Adoption at the U.K.’s Department for Education (DfE), highlighted the recent resources published by the government on AI. The materials aim to help schools and colleges use AI safely and effectively.
“There is also a hardware challenge,” Cooke shared, noting that the DfE has put a lot of focus on “getting the basics right” such as access to wifi and laptops. “Teachers already have so much to worry about, they want technology that works,” she told delegates.
However, the DfE is also keen to promote the use of AI to increase efficiency. “We want to promote the use of this technology so teachers can focus on what they are best at,” Cooke explained. While she was hopeful that AI could unlock potential and help deliver great teaching for every child, she also shared fears that unequal access could create an increasing digital divide.
Professor Manolis Mavrikis, Professor in Artificial Intelligence in Education, at IOE - UCL's Faculty of Education and Society, told delegates that discussion on the use of new technologies in education have become polarized. “Even with positive use of EdTech we are seeing muddled arguments around screentime,” he explained.
Mavrikis argued that accumulating evidence supports the application of AI in the classroom. He also cautioned that there is a risk that students will continue to use the technology even if educators do not. “If we don’t show them the best way to use it then they will use it in a lazy way,” he explained, warning against its unregulated use.
Guadalupe Sampedro, Partner at law firm Cooley LLP, explained that any legal framework on the use of AI will be complicated to implement. “From a legal perspective, AI is very new and it’s constantly evolving,” she said. “We already have a very complete legal framework that is difficult to navigate for companies.”
With many companies struggling to train voice recognition for children due to data protection rules, Sampedro said some had found a workaround using synthetic data. “It’s not easy, but it’s doable,” she explained.
While Sampedro added many want reduced complexity, she explained that the EU’s General Data Protection Regulation (GDPR) and U.K. GDPR will make that difficult. That said, she admitted that legislation in the U.S. is currently “a bit of a Wild West” and called for consistency in the global approach.
Joshua Wohle, CEO and Co-Founder at learning technology platform Mindstone said that AI-powered technology is already here and being used. He felt it was important that organizations work with this reality, rather than trying to prevent it being used. “The worst case scenario is that you force employees to use personal accounts and data gets used in an unsafe way,” he explained. “We have to make employees feel that they can use it.”
However, he did acknowledge that there was a need for proper data to power AI tools effectively. “If you are scared to give it data, it won’t work,” Wohle added. “AI can only be as useful as the data you feed it.”
| 2025-06-20T00:00:00 |
https://www.edtechinnovationhub.com/news/how-can-we-use-ai-responsibly-in-education
|
[
{
"date": "2025/06/20",
"position": 52,
"query": "AI education"
}
] |
|
Home | EDSAFE AI
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EDSAFE AI
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https://www.edsafeai.org
|
[] |
EDSAFE AI Alliance leads work in AI education policy through the SAFE framework.
|
VISION
The EDSAFE AI Alliance, founded in 2020, is a global initiative led by InnovateEDU and powered by a coalition of organizations representing stakeholders across the education and workforce sector to provide global leadership for developing a safer, more secure, and more trusted AI education ecosystem through a focus on research, policy, and practice. We aim to build and develop an ecosystem that reflects the best practices for AI use in education.
By joining forces and complementing rather than competing with stakeholders in the space, we can address one of our time's most pressing educational policy, technology and practice challenges.
We've forged a unique alliance driven by a powerful mission: transforming education with human-centered AI to elevate learning outcomes. Our commitment is unwavering: to champion the responsible development and use of AI that is rigorously safe, accountable, fair, and effective in every classroom.
| 2025-06-20T00:00:00 |
https://www.edsafeai.org/
|
[
{
"date": "2025/06/20",
"position": 75,
"query": "AI education"
}
] |
|
30 Top San Francisco Bay Area AI Companies to Know
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30 Top San Francisco Bay Area AI Companies to Know
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https://www.builtinsf.com
|
[] |
These AI companies in San Francisco Bay Area are using artificial intelligence to innovate in a variety of industries.
|
When it comes to tech industry buzzwords, no term is thrown around more than “Artificial Intelligence.” No, AI isn’t all about evil robots hellbent on taking over the human race. Rather, these machines are helping to make human’s lives easier at every turn.
The way we shop online, how we receive healthcare and even how we consume media are all being positively affected by artificial intelligence. Unsurprisingly, the San Francisco Bay Area is playing a massive part in ushering in the next generation of this transformative technology.
Check out some San Francisco-based companies on the forefront of the AI revolution.
More Like ThisTop AI Tools on the Market Now
kea View Profile Industry: AI Founded: 2018 What they do: Kea provides restaurants with a unique solution to online and automated ordering, combining human capabilities with machine learning and natural language processing to create outstanding customer experiences. The platform’s voice capabilities increase capabilities with each use and is able to provide up-sell opportunities via customer order history, while human specialists process each call and work within the AI to improve its effectiveness. kea is Hiring | View All Jobs
Scale View Profile Industry: Image Recognition + Machine Learning Founded: 2016 What they do: Scale offers high quality data training and validation data for AI applications. The company’s API provides access to human-powered data on everything from video annotation for self-driving cars to sensor fusion segmentation for robotics and audio, and speech recognition for natural language processing tools. Scale’s API is currently being used by global innovators, like Pinterest, Lyft, Uber and Airbnb, to train their AI applications. Scale is Hiring | View All Jobs Industry: Retail Founded: 2017 What they do: Standard Cognition’s AI-powered computer vision enables brick & mortar stores to go checkout-free. With the platform, there’s no need for waiting in line for cashiers. Shoppers just walk in, grab what they want and walk out. The Standard Cognition deep learning machines add items nabbed throughout the store onto a running tab and will automatically charge a shopper’s account as they leave the store. The platform can also recognize shoplifting by monitoring a suspicious customer’s behavior and alerting store employees.
HouseCanary View Profile Industry: Real Estate Founded: 2013 What they do: HouseCanary’s real estate valuation platform uses AI to accurately predict home valuations for investors. The platform uses millions of data points (including historic price growth, neighborhood comparables and market forecasting) to accurately value home prices up with a remarkably low 2.9% Median Absolute Prediction Error. Additionally, HouseCanary’s Market Explorer gives investors insights into neighborhoods with data on rental returns, market demographics, future growth predictions and more. HouseCanary is Hiring | View All Jobs
Blueshift View Profile Industry: Marketing Tech + Software Founded: 2014 What they do: Blueshift’s platform offers AI-powered predictive content suggestions that helps marketing teams optimize their campaign efforts and increase conversions. The company’s platform lets marketers create hyper-personalized individual user experiences based on data that details a shopper’s style, brand and even content preferences. Blueshift has been used by global brands, from the BBC to Lendingtree, to optimize user experience and boost sales conversions. Blueshift is Hiring | View All Jobs
| 2025-06-20T00:00:00 |
https://www.builtinsf.com/articles/ai-companies-san-francisco-bay-area
|
[
{
"date": "2025/06/20",
"position": 26,
"query": "AI employers"
}
] |
|
Stories – Global Investigative Journalism Network
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Stories – Global Investigative Journalism Network
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https://gijn.org
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[] |
Exiled Russian media site IStories has shared with GIJN how it built an AI-powered database of Russian military war dead and missing, and why it was worth ...
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This investigation sought to answer key questions that no government could answer: What happens when someone goes missing at Europe’s borders? And how many burial sites are there across Europe?
| 2025-06-20T00:00:00 |
https://gijn.org/stories/?gijn_topic=data-journalism
|
[
{
"date": "2025/06/20",
"position": 94,
"query": "AI journalism"
}
] |
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Al Jazeera Journalism Review
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Al Jazeera Journalism Review
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http://institute.aljazeera.net
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[] |
How Much AI is Too Much AI for Ethical Journalism. As artificial intelligence transforms newsrooms across South Asia, journalists grapple with the fine line ...
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July 4 each year coincides with Liberation Day in Rwanda, which marks the end of the genocidal war against the Tutsi. This article explains the reasons behind the media’s neglect of the genocide and how the press failed to help prevent it. It also offers a critical perspective on how the same practices are being reproduced in coverage of the genocidal war on Palestine.
| 2025-06-20T00:00:00 |
http://institute.aljazeera.net/en/ajr
|
[
{
"date": "2025/06/20",
"position": 95,
"query": "AI journalism"
}
] |
|
AI Layoffs, Brain Drain & Bot Recruiters
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AI Layoffs, Brain Drain & Bot Recruiters
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https://www.fullstackhr.io
|
[
"Johannes Sundlo"
] |
CEO Andy Jassy told staff that new generative-AI agents will “reduce our total corporate workforce in the next few years.” Warehouse teams will also get more ...
|
Welcome to FullStack HR, and an extra welcome to the 102 people who have signed up since last edition.
If you haven’t yet subscribed, join the 9600+ smart, curious and like-minded future of work people by subscribing here:
This post gives you a concise selection of AI and future-of-work news. I’m Johannes Sundlo, an HR leader who tests AI every day and helps organisations put it to work.
Need a workshop or keynote that makes AI practical? Book me!
Coinbase details AI recruiting overhaul
Coinbase’s CPO L.J. Brock shows how in-house tools now screen résumés, run 15-minute AI phone interviews, auto-schedule panels and capture notes, with 85 percent of 320 pilot candidates calling the process “clear, conversational, and easy.” All eligible roles outside the EU/UK should be on the system by year-end 2025 so recruiters can focus on relationship-building.
Why it matters for HR: This is a live case of an end-to-end AI hiring funnel. It keeps humans in the scoring loop and logs every model decision, giving auditors a clear trail, yet still cuts manual work enough to lift candidate-satisfaction scores. Note that résumé screening skips EU and UK jobs, proof that regional rules can shape design choices, so map your own compliance constraints early. Treat Coinbase’s 85 percent approval as a baseline and track your own metrics; if speed gains let recruiters spend more time coaching candidates and hiring managers, update their KPIs to reward that higher-value work
Read more →
MIT study: ChatGPT may lower brain engagement
Published 10 June, MIT tested 54 volunteers writing essays with ChatGPT, Google Search or no tools. EEG scans showed the ChatGPT group had the weakest brain connectivity and recalled less of what they wrote.
Why it matters for HR:
I’m not impressed. The sample is tiny, yet it warns of possible cognitive costs.
But important to also highlight studies like this as well, especially as they are causing headlines that makes a lot of people go “I knew it. AI is bad.”
It’s not. Technology is both bad and good, it depends, as always on HOW you use it.
Read more →
Amazon CEO: AI will shrink corporate headcount
CEO Andy Jassy told staff that new generative-AI agents will “reduce our total corporate workforce in the next few years.” Warehouse teams will also get more robotics and predictive tools.
Why it matters for HR:
Start workforce-planning now. Map roles that are likely to disappear and list adjacent roles that need more people. Launch reskilling paths before the first cuts. Set clear talking points for managers so rumours do not fill the gap. Align talent acquisition targets with the new skills plan.
Read more →
HBR: organisations are not ready for agentic-AI risk
Ethicist Reid Blackman warned that autonomous agents can trigger actions no one can trace.
Why it matters for HR:
Write a policy that says which tasks agents may handle and when humans must step in. Add a RACI grid so staff know who owns an agent, who audits it and who shuts it off. Require audit logs for every people-facing action. Train teams to report malfunctions fast and without blame.
Read more →
Legal brief: AI in hiring brings Title VII, ADA and ADEA exposure
A 17 June National Law Review note lists bias audits, vendor due-diligence and privileged model reviews as baseline defences when AI touches hiring, promotion or pay.
Why it matters for HR:
Keep a live inventory of every model that screens applicants or employees. Run disparate-impact tests at least quarterly and store the results under legal privilege. Build accommodation workflows so candidates can opt out of automated tools. Update vendor contracts to spell out audit rights and liability sharing.
Read more →
Private-equity playbook: create value with AI, then exit
HBR authors Vikram Mahidhar and Thomas Davenport (16 June) show how PE firms lift EBITDA by dropping AI copilots into finance, sales and supply chains within 18 months of acquisition.
Why it matters for HR:
Expect demanding timelines. Pair each AI rollout with a change-management sprint that includes quick wins and clear metrics. Shift bonuses so leaders are paid for adoption, not just cost cuts. Sign retention deals for data and process experts who carry critical knowledge during the transition.
Read more →
Google Gemini now summarises PDFs and Google Forms
Rolling out from 12 June, Gemini shows summary cards in Drive and condenses form responses.
Why it matters for HR:
Recruiters can skim long CVs in seconds and draft interview questions on the spot. L&D teams can pull highlights from manuals or training feedback. Add a step where users compare the summary with the source before sharing to avoid errors. Check your data-handling rules so sensitive files stay in the right Drive folders.
Read more →
| 2025-06-20T00:00:00 |
https://www.fullstackhr.io/p/ai-layoffs-brain-drain-and-bot-recruiters
|
[
{
"date": "2025/06/20",
"position": 38,
"query": "AI layoffs"
}
] |
|
AI Will Shrink Corporate Workforce, Amazon CEO Warns
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AI Will Shrink Corporate Workforce, Amazon CEO Warns
|
https://www.shrm.org
|
[
"Roy Maurer"
] |
The company has already laid off 27,000 workers since 2022. Jassy positioned AI as transformative not just for Amazon but across industries. “It will change how ...
|
Designed and delivered by HR experts to empower you with the knowledge and tools you need to drive lasting change in the workplace.
Demonstrate targeted competence and enhance credibility among peers and employers.
Gain a deeper understanding and develop critical skills.
| 2025-06-20T00:00:00 |
https://www.shrm.org/topics-tools/news/technology/ai-will-shrink-corporate-workforce--amazon-ceo-warns
|
[
{
"date": "2025/06/20",
"position": 45,
"query": "AI layoffs"
}
] |
|
Microsoft to Lay Off Thousands as AI Push Shifts Sales Strategy
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Microsoft to Lay Off Thousands as AI Push Shifts Sales Strategy
|
https://www.techi.com
|
[] |
The tech giant is planning to cut jobs in the coming month, mainly from its sales and marketing teams. This comes just a month after Microsoft laid off ...
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The tech giant is planning to cut jobs in the coming month, mainly from its sales and marketing teams. This comes just a month after Microsoft laid off about 6,000 jobs. Details about the news are scanty, but Bloomberg said that it will be announced in the next month.
So, what’s going on? As of June 2024, Microsoft had 228,000 employees, 45,000 of them were in sales. According to Bloomberg, the previous layoff largely left the sales and marketing team untouched. Microsoft is moving in the AI race, as it’s planning to spend over $80 billion to support AI development in data centers. In April, Microsoft had already started informing employees that it plans to work with third-party firms for the marketing of to small and mid-sized customers.
This strategy will help Microsoft reduce operational costs by relying on gig workers for short-term campaigns instead of relying on full-time staff. On the flip side, Microsoft declined to comment on the report. It’s not only about Microsoft, other major firms like Amazon and Intel are also planning for layoffs. Companies are changing their tactics with Artificial intelligence.
AI is advancing faster than people can adapt, this much we know. While companies must evolve to stay competitive, what happens to the workers who helped build Microsoft’s success over the years? Tech leaders promise that new positions and roles will emerge, but what about employees who lack the time or resources to reskill? The tech industry focuses on future opportunities, yet the present reality for displaced workers remains unaddressed.
Microsoft has a chance here to set an example by prioritising humans over AI. Laying off may be a business decision, but supporting their employees is the right thing to do.
| 2025-06-20T00:00:00 |
2025/06/20
|
https://www.techi.com/microsoft-job-cuts-ai-strategy-sales-layoffs/
|
[
{
"date": "2025/06/20",
"position": 47,
"query": "AI layoffs"
}
] |
The Entire Generation of GenAI Won't Have Enough Jobs
|
The Entire Generation of GenAI Won’t Have Enough Jobs
|
https://analyticsindiamag.com
|
[
"Mohit Pandey",
"Mohit Writes About Ai In Simple",
"Explainable",
"Often Funny Words. He'S Especially Passionate About Chatting With Those Building Ai For Bharat",
"With The Occasional Detour Into Agi."
] |
The first generation raised on generative AI may also be the first to face structural unemployment before they even get a shot.
|
At just eight years old, many children are already using ChatGPT. By the time they turn 18, they’ll be stepping into a job market where AI is no longer just a tool—it’s the competition. In fact, several young kids in school are so eager to get ahead that they are skipping lunch to learn ‘vibe coding’, as noted by Anton Osika, founder of Lovable.
We often speak of generative AI as the future of work, with leaders offering a mix of optimism and concern. While some argue AI will create more jobs, others warn it will replace them. But for Gen Z and Gen Alpha, it could mean something more deep: the end of work as we know it, and possibly a rise of the gig economy.
Entry-level jobs—once the critical ramp for climbing the career ladder—are slowly being erased, not redefined. The first generation raised on generative AI may also be the first to face structural unemployment before they even get a shot.
Read: An Entire Generation is Studying for Jobs that Won’t Exist
Entry-Level Jobs are Dead
It’s already happening.
According to a survey by the Federal Reserve Bank of New York, the unemployment rate for recent college graduates has spiked to 5.8%, compared to a national average of 4%. This is more than double the rate for all college graduates (2.7%).
But where have the missing jobs gone? They’re not being handed to older workers—they’re disappearing altogether. They’ve been automated. At the same time, the latest generation is growing up immersed in generative AI.
In the UK, more than one in five children aged eight to 12 are already using generative AI tools like ChatGPT. That’s not a cute statistic—it’s a warning sign. These kids are growing up with tools that were never designed for them, learning from systems that don’t understand childhood, and adapting to technology that’s supposed to adapt to them.
Regardless, companies have rushed to implement AI-first strategies, often ignoring the fact that the next generation of workers is still learning the nascent technology. This has resulted in a pause in entry-level hires and shrinking internships.
Dario Amodei, CEO of Anthropic, has issued a bleak forecast: “AI could replace 50% of entry-level white-collar jobs within the next one to five years.” If that plays out, he added that unemployment could hit 20%, a level not seen outside major economic recessions.
The threat of AI taking over jobs is becoming increasingly real. Amazon CEO Andy Jassy recently told employees that as AI takes on more tasks in the coming years, the nature of work at Amazon will change, potentially reducing the number of corporate roles.
“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, and more people doing other types of jobs,” he said.
This shift is beginning to put tangible pressure on undergraduate students who are already worried about their job prospects.
A report from San Francisco-based venture firm SignalFire shows that major tech companies—including Google, Amazon, Apple, Meta, Microsoft, NVIDIA, and Tesla—have cut fresh graduate hiring by over 50% since 2022. The sharp decline has left many students anxious about their careers.
However, when it comes to software engineers, there is a high chance that there will be a need for more software engineers in the future.
Todd McKinnon, CEO of Okta, is one of the recent voices pushing back against the doomsday narrative. In an interview with Business Insider, McKinnon called the fear of declining engineering jobs “laughable”. He compared the rise of AI to past tech shifts like personal computing and mobile, which ultimately expanded job opportunities rather than eliminating them.
Read: We Will Need 10x More Software Engineers in 5 Years
‘Generation AI’ is Feeling the Heat
This isn’t an abstract threat for young professionals—it’s already a lived reality. According to Elite Recruitments, over 52% of people aged 18–24 fear that AI will negatively impact their future careers. Gen Z is 129% more likely than older generations to be worried about AI replacing them.
And the concern is valid. AI professor Tim Kapp revealed, “We’ve seen a drop of 27.5% recently in jobs in the developing world, especially entry-level jobs that are dropping extremely quickly.”
Even traditionally AI-resistant domains like writing and design aren’t safe. Freelance writing gigs have dropped by 30% since ChatGPT became mainstream.
Coding roles are down by 20%. Moreover, according to a report by CVL Economic, 2,04,000 jobs in the entertainment sector are projected to be significantly impacted by generative AI within just three years. That number doesn’t include freelancers or short-term contractors—the people most vulnerable and most invisible in labour data.
Two-thirds of business leaders now expect AI to consolidate or replace existing job titles by 2026. That’s not a trend. That’s an extinction event.
But Gen Z is Also Adapting
Ironically, while Gen Z fears the job market AI is shaping, they’re also the most fluent in using the technology. They’re not just using AI—they’re forming relationships with it.
Nearly half of Gen Z workers now prefer to ask AI tools for help rather than their managers or coworkers. About 51% of the Gen Z population sees AI not as a tool, but as a coworker or friend. It’s not surprising, then, that nearly 47% of them rely more on generative AI for workplace guidance than on human supervisors.
In many ways, they’re better prepared to work with AI than anyone else. But that might not be enough. Because the question isn’t if Gen Z can adapt—it’s whether the job market makes room for them at all?
The creative class thought it was immune. That was cute.
Today’s AI can generate ad copy, legal contracts, UI mockups, marketing strategies, product descriptions, and even rough film scripts. As a result, designers are becoming AI supervisors, writers are becoming prompt engineers, and producers are becoming editors of machine-generated content.
Seth Carpenter, global chief economist at Morgan Stanley, put the financial implications in stark terms: “Current generative AI technologies could affect as much as a quarter of the occupations that exist today…with associated labour costs that could reach at most $2.1 trillion.”
That’s the price tag of creative obsolescence.
There Will Be New Jobs—But Not for Everyone
The World Economic Forum tries to paint a rosier picture. Their Future of Jobs report predicts that 92 million jobs will be displaced by 2030, followed by 170 million new ones created, for a net gain of 78 million. The catch? These “new jobs” look nothing like the old ones.
Even access to AI isn’t equal. Children in private schools are three times more likely to use generative AI tools than those in public schools. This is the beginning of an AI fluency divide that will mirror, and possibly magnify, every other form of educational inequality.
To be fair, not everyone is sounding the alarm. Elon Musk, for instance, calls AI
the “most powerful tool for creativity that has ever been created”. According to him, it can potentially unleash a new era of human innovation.” In contrast, Sam Altman sounded an alarm on the nature of jobs of the future.
“We need to face the reality that mass job elimination is coming,” Amodei said. However, the generation of generative AI isn’t worried about whether AI will steal their jobs. They’re worried because AI is making sure they never get one in the first place.
| 2025-06-20T00:00:00 |
2025/06/20
|
https://analyticsindiamag.com/ai-features/the-entire-generation-of-genai-wont-have-enough-jobs/
|
[
{
"date": "2025/06/20",
"position": 27,
"query": "ChatGPT employment impact"
}
] |
I use these 3 ChatGPT prompts to work smarter and stay ...
|
I use these 3 ChatGPT prompts to work smarter and stay competitive — here’s how
|
https://www.yahoo.com
|
[] |
If you've been following the news, you've probably seen it: AI-driven layoffs are on the rise. From newsroom cuts to tech giants automating tasks once ...
|
When you buy through links on our articles, Future and its syndication partners may earn a commission.
Credit: Shutterstock
If you’ve been following the news, you’ve probably seen it: AI-driven layoffs are on the rise. From newsroom cuts to tech giants automating tasks once handled by entire teams, AI is getting smarter and changing the job market faster than anyone expected.
Whether you’re trying to protect your current job or looking for your next role, the uncertainty is real. Even though I test AI tools for a living, I found myself asking: Could AI replace me, too?
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That’s when I tried a simple exercise with ChatGPT — using just a few prompts to assess my career risk and figure out how to stay ahead of AI. Here’s exactly how you can do the same.
Step 1: Upload your resume into ChatGPT
Credit: Shutterstock
Start by copying and pasting your current resume into ChatGPT (or your preferred chatbot).
You can also upload it directly, just be sure you have removed all personal, confidential or sensitive information first.
If you don’t have a formal resume handy, you could use ChatGPT to write one, or you can also provide a summary of your current role, responsibilities, and major skills.
Step 2: Ask the hard question
Credit: ChatGPT
Once you’ve shared your background, type this prompt:
"Based on my resume and skills, how soon will AI take my job?"
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You might be surprised by the response. AI can provide a candid, and often eye-opening, assessment of how vulnerable your role is to automation — and which aspects of your job are still uniquely human.
It may flag parts of your skill set that are becoming less valuable in the current market. But, it may also give you reassurance based on your skills and ability to adapt.
This is also a good time to enter the description of a job you're hoping to land in the next few years. Will it even exist?
Step 3: Get your action plan
Credit: Shutterstock
Next, follow up with this prompt: "What skills do I need to learn to pivot and future-proof my career?"
The chatbot will typically generate a list of in-demand skills that can help you adapt, pivot to more secure roles or even transition into entirely new career paths.
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These often include areas where human expertise still has an edge — think creativity, emotional intelligence, leadership, strategy, problem-solving and relationship-building.
Step 4: Never stop learning
Credit: Shutterstock
Based on what the chatbot told you, go ahead and take your prompting a step further by asking ChatGPT: "What’s the best way for me to start learning these skills?"
In seconds, you’ll get suggestions for online courses, certifications, books, podcasts and communities that can help you upskill — often tailored to your current industry or experience level.
It never hurts to be prepared
This quick exercise won’t eliminate the risks of an AI-driven job market, but it will give you clarity and maybe even peace of mind as you discover new ways to use your skills.
These prompts turn an overwhelming question (will AI take my job?) into an actionable plan.
Advertisement Advertisement
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More importantly, it serves as a wake-up call: never stop learning. There are numerous ways you can elevate your human skillset and even develop skills to use AI to do your job better.
The best way to stay relevant is to continuously evolve your skills and, where possible, double down on the human qualities AI can’t easily replicate. That’s your edge in an AI-powered world.
Asking ChatGPT the tough questions is a habit I now recommend to anyone, in any industry.
| 2025-06-20T00:00:00 |
https://www.yahoo.com/lifestyle/articles/3-chatgpt-prompts-smarter-stay-110000577.html
|
[
{
"date": "2025/06/20",
"position": 90,
"query": "ChatGPT employment impact"
}
] |
|
Recruitment: top uses for AI 2024 - Statista
|
Recruitment: top uses for AI 2024
|
https://www.statista.com
|
[
"Raphael Bohne",
"Jun"
] |
In 2024, the top usage of AI in the recruiting process in North America was candidate matching. percent responded with job recommendations on career sites as ...
|
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Jobvite. (October 23, 2024). Top uses of artificial intelligence (AI) in the recruiting process in North America in 2024 [Graph]. In Statista . Retrieved July 15, 2025, from https://www.statista.com/statistics/1445356/recruitment-top-uses-for-ai/
Jobvite. "Top uses of artificial intelligence (AI) in the recruiting process in North America in 2024." Chart. October 23, 2024. Statista. Accessed July 15, 2025. https://www.statista.com/statistics/1445356/recruitment-top-uses-for-ai/
Jobvite. (2024). Top uses of artificial intelligence (AI) in the recruiting process in North America in 2024 . Statista . Statista Inc.. Accessed: July 15, 2025. https://www.statista.com/statistics/1445356/recruitment-top-uses-for-ai/
Jobvite. "Top Uses of Artificial Intelligence (Ai) in The Recruiting Process in North America in 2024." Statista , Statista Inc., 23 Oct 2024, https://www.statista.com/statistics/1445356/recruitment-top-uses-for-ai/
Jobvite, Top uses of artificial intelligence (AI) in the recruiting process in North America in 2024 Statista, https://www.statista.com/statistics/1445356/recruitment-top-uses-for-ai/ (last visited July 15, 2025)
Top uses of artificial intelligence (AI) in the recruiting process in North America in 2024 [Graph], Jobvite, October 23, 2024. [Online]. Available: https://www.statista.com/statistics/1445356/recruitment-top-uses-for-ai/
| 2025-06-20T00:00:00 |
https://www.statista.com/statistics/1445356/recruitment-top-uses-for-ai/
|
[
{
"date": "2025/06/20",
"position": 94,
"query": "artificial intelligence hiring"
}
] |
|
Concern of AI replacing jobs in the media U.S.2023
|
Concern of AI replacing jobs in the media U.S.2023
|
https://www.statista.com
|
[
"A. Guttmann",
"Jun"
] |
A survey held in the United States in April 2023 found that ** percent of respondents were concerned that artificial intelligence could replace news ...
|
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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
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Morning Consult. (April 24, 2023). Level of concern about artificial intelligence (AI) replacing humans in selected media and entertainment jobs in the United States as of April 2023 [Graph]. In Statista . Retrieved July 15, 2025, from https://www.statista.com/statistics/1402954/concern-ai-replacing-jobs-media-entertainment-us/
Morning Consult. "Level of concern about artificial intelligence (AI) replacing humans in selected media and entertainment jobs in the United States as of April 2023." Chart. April 24, 2023. Statista. Accessed July 15, 2025. https://www.statista.com/statistics/1402954/concern-ai-replacing-jobs-media-entertainment-us/
Morning Consult. (2023). Level of concern about artificial intelligence (AI) replacing humans in selected media and entertainment jobs in the United States as of April 2023 . Statista . Statista Inc.. Accessed: July 15, 2025. https://www.statista.com/statistics/1402954/concern-ai-replacing-jobs-media-entertainment-us/
Morning Consult. "Level of Concern about Artificial Intelligence (Ai) Replacing Humans in Selected Media and Entertainment Jobs in The United States as of April 2023." Statista , Statista Inc., 24 Apr 2023, https://www.statista.com/statistics/1402954/concern-ai-replacing-jobs-media-entertainment-us/
Morning Consult, Level of concern about artificial intelligence (AI) replacing humans in selected media and entertainment jobs in the United States as of April 2023 Statista, https://www.statista.com/statistics/1402954/concern-ai-replacing-jobs-media-entertainment-us/ (last visited July 15, 2025)
Level of concern about artificial intelligence (AI) replacing humans in selected media and entertainment jobs in the United States as of April 2023 [Graph], Morning Consult, April 24, 2023. [Online]. Available: https://www.statista.com/statistics/1402954/concern-ai-replacing-jobs-media-entertainment-us/
| 2025-06-20T00:00:00 |
https://www.statista.com/statistics/1402954/concern-ai-replacing-jobs-media-entertainment-us/
|
[
{
"date": "2025/06/20",
"position": 92,
"query": "artificial intelligence journalism"
}
] |
|
IATSE Joins AFL-CIO Call to Strike Reckless Ban on State ...
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IATSE Joins AFL-CIO Call to Strike Reckless Ban on State AI Policy from Budget Reconciliation Bill
|
https://iatse.net
|
[
"Iatse Communications"
] |
IATSE joined the AFL-CIO and 18 national labor organizations in urging the Senate to remove a dangerous provision from the budget reconciliation bill.
|
WASHINGTON, D.C — The International Alliance of Theatrical Stage Employees (IATSE) joined the AFL-CIO and 18 national labor organizations in urging the Senate to remove a dangerous provision from the budget reconciliation bill that bans states from enacting or enforcing artificial intelligence (AI) protections. Read the joint letter here.
So-called “red” states and “blue” states across the nation have been at the forefront of addressing critical threats posed by unregulated AI, such as worker surveillance, digital impersonation, discriminatory hiring practices, algorithmic job loss, and safety risks due to automation. These state-level efforts have created essential safeguards that protect workers and promote fairness in the workplace.
The proposed federal provision, however, would nullify these vital state-level protections for the next decade, leaving workers vulnerable to unchecked AI abuses and eliminating states’ authority to respond to emerging threats. By preempting state actions, this reckless policy would undermine ongoing bipartisan efforts and divert sole responsibility for policymaking to a historically gridlocked Congress.
IATSE members, including behind-the-scenes film, television, animation, gaming, and live event workers, continue to face significant risks to their livelihoods from irresponsible and unchecked AI deployment. Protecting these workers and their rights demands vigilant and responsive regulation, which states have actively pursued.
IATSE was among the first American unions to publicly oppose the provision in May. The union remains steadfast in advocating for robust AI protections to safeguard our members and all workers nationwide.
| 2025-06-20T00:00:00 |
2025/06/20
|
https://iatse.net/iatse-joins-afl-cio-call-to-strike-reckless-ban-on-state-ai-policy-from-budget-reconciliation-bill/
|
[
{
"date": "2025/06/20",
"position": 7,
"query": "artificial intelligence labor union"
}
] |
Artificial Intelligence (AI)
|
Artificial Intelligence (AI)
|
https://www.cfr.org
|
[
"Lindsay Maizland",
"Clara Fong",
"Olivia",
"Angelino",
"Thomas J. Bollyky",
"Ebenezer Obadare",
"With Carolyn Kissane",
"Irina A. Faskianos",
"With Michael W. Faulkender",
"Afsaneh Mashayekhi Beschloss"
] |
A battle for automation against AI, automation was won by labor. ... Employees International Union, to do some kind of innovative organizing in the South.
|
A. Michael Spence, distinguished visiting fellow at CFR, provides a global perspective on the changing landscape of labor and economic productivity. Sharon Block, professor of practice and executive director of the Center for Labor and a Just Economy at Harvard Law School, discusses this year’s strikes and the economic implications of increased collective labor activity in the United States. A question-and-answer session follows their opening remarks. TRANSCRIPT FASKIANOS: I’m Irina Faskianos, vice president for the National Program and Outreach here at CFR. We’re delighted to have over two hundred participants from forty-seven states and U.S. territories with us today. CFR is an independent and nonpartisan membership organization, think tank, and publisher focused on U.S. foreign policy. CFR is also the publisher of Foreign Affairs magazine. And, as always, CFR takes institutional positions on matters of policy. Through our State and Local Officials Initiative, CFR serves as a resource on international issues affecting the priorities and agendas of state and local governments by providing analysis on a wide range of policy topics. So, again, thank you all for joining us today. As a reminder, this webinar is on the record. The video and transcript will be posted on our website after the fact, at CFR.org. And we will circulate it to you as well. We are pleased to have Sharon Block and Michael Spence with us to talk about U.S. Strikes and Global Trends in Labor and Productivity. I will give a few highlights from their bios. Sharon Block is a professor of practice and executive director of the Center for Labor and a Just Economy at Harvard Law School. Recently, she served as a senior official in the Office of Information and Regulatory Affairs in the Biden administration. From 2017 to 2021, Professor Block led the Labor and Work Life Program at Harvard Law School, where she focused on labor law reforms to build a more equitable economy. Prior to that, she’s held various senior positions in government, including principal deputy assistant secretary for policy and senior counselor to the secretary of labor. Michael Spence is a distinguished visiting fellow at the Council on Foreign Relations and clinical professor of economics at Bocconi University in Milan. He is also a senior fellow at Stanford University’s Hoover Institution and the author of the book, The Next Convergence: The Future of Economic Growth in a Multispeed World. And in 2001, Dr. Spence was a co-recipient of the Nobel Prize in Economic Sciences. So thank you both for being with us. Sharon, I thought we could begin with you to give us a sense—give an overview of the increased collective labor activity in the U.S. that we’ve seen this year. If you could discuss the different strikes and the common threads, AI among them. BLOCK: Yeah, happy to. And thank you for having me. It is—I’m sure it will be a really interesting conversation. So just set the stage, this summer into fall, I think, was a season like no other in recent years in the U.S. labor movement. There were approximately half a million workers who went out on strike in 2023. And a lot of that activity, again, was concentrated in the later part of the year. Another way of thinking about that is more than four million workdays were spent on strike instead of working. And to put it in context, that’s double the number of workers who went out on strike in the U.S. in 2022. So really a big upswing. But, to sort of pull back and put it in even sort of longer historical context, it’s a much, much lower number than what we saw decades ago in the sort of the high point of union density in the United States. You had millions and millions of workers out on strike, and a much greater part—share of the economy would be affected by those strikes. But in terms of, like, say, the last twenty to thirty years, this was a very significant year. The biggest strike in the United States this year was the SAG-AFTRA strike. That’s 150,000 union members were on strike. That’s a little bit of a funny number because SAG-AFTRA members are obviously a little unusual. They don’t go to work—typically they don’t go to work every day. But they are a very big group that withheld their labor, along with the Writers Guild. So you had Hollywood shut down for a significant period of time. The next biggest strike this year was the strike at Kaiser Health Care. Those are mostly SEIU members. That was about 75,000 workers who were out for three days. And then the strike that got certainly the most attention and was, I think, the third-biggest strike this year, was the United Auto Workers and their sort of novel strike strategy vis-à-vis the big three auto companies. Now, they did not take all of their members out at one time. So that was about 50,000 workers. There are more members in the UAW than that. But it was still a very significant number of workers, even with this sort of staggered strategy. So in addition to those three very large strikes we also saw strikes in the hospitality sector, in Las Vegas at the casinos, also L.A. hotels, and then in higher education. So the most of these strikes were really centered in the private sector. But we did have University of California, graduate student workers went out on strike. That was a very large strike. And then Rutgers University faculty and staff went out on strike. Now I would add to this an almost-strike, if you really want to think about how dramatic this activity was in the United States. The UPS workers—the Teamsters at UPS didn’t actually go out on strike, but took a strike vote, came very—like, within hours of going out on strike, at which time they were able to reach an agreement with the company. But it’s a similar dynamic of the threat of a strike that led to that agreement. But say the theme among many of these strikes was that they existed—they happened between bargaining partners who have a very mature collective bargaining relationship. You think about the auto workers who have been unionized at the same three companies—you know, one of the companies has changed their name—but essentially organized at those three companies for almost a hundred years. These are not the kinds of bargaining relationships that have dominated sort of labor news over the past year or two, like Starbucks and Amazon, where you have new collective bargaining relationships. We didn’t see strikes among those workers. We saw them in these very established relationships. The other theme among these strikes, really almost universally, were very, very big wins for workers. They settled these strikes with agreements that, I think, were objectively viewed as very advantageous for workers. You saw very high levels of public support for the workers in almost all of these strikes. And then, to your point about AI, these are also strikes that happened, for the most part, in sectors that are in big transition. In some, because of the introduction of AI. That was obviously a very big theme, a big factor in the Hollywood strikes, but also other transitions. In the autoworkers strike you had the issue related to transition to an EV future played a big role, in healthcare that’s obviously an evolving field. So this idea of there being a big transition and workers using their power through their strike in order to get contracts that help them have more of a say in the future. And then I would say one last theme that was very prevalent in many of the strikes was the sort of rhetorical and motivating theme of workers wanting to have their fair share. You heard that phrase come up a lot. So we’re talking about sectors where the companies had had a recent history of very high profits, workers who were locked into collective bargaining agreements that they had negotiated sort of before the pandemic. So if you think about, like, UPS had very, very high profits during the pandemic. The Teamsters were working under a contract that didn’t anticipate that level of profits. You have—the auto companies were also coming off a couple of years of very high profits. And so you have this theme of workers really wanting to get their fair share of this increased revenue and profits that they saw coming into their—into their companies. The last thing I will say is just if you want to understand just sort of how positive this strike season was for workers, you just have to look at the UAW contracts. I mean, there are so many things about this strike that were just groundbreaking, or at least groundbreaking as of the past few decades. You saw wage increases of 25 percent for permanent workers and 150 percent for some of the temporary workers. You had really novel provisions in the collective bargaining agreement that they eventually signed to keep open or reopen auto plants. We’ve never really seen that before in a collective bargaining agreement. And workers preserving the right to strike over any other plant closures. As I said, you got this foothold in the EV future in agreements for the companies to recognize the union in these EV battery plants. And so, it was just a really remarkably positive contract that ended the strike in the auto sector, really transforming the UAW to be able to say, again, that a job in the auto sector equals a good middle-class job. And we’re seeing now the autoworkers taking that message to the nonunionized companies—Tesla and the transplant companies—to say, look what we got for workers at the big three. Wouldn’t you like to have this too? And you’re seeing actually these companies already responding by raising wages. So it’s also a strike that has had pretty significant ripple effects already. One thing to watch in 2024 is how far those ripple effects go, how successful they are. Will this season of successful strikes for workers actually lead other workers to want to organize a union in their own companies, in their own sectors, maybe even beyond the auto sector? And, again, we did have some groundbreaking provisions that came out of these strikes around AI. The Writers Guild, most significantly. You had agreements that AI can’t be used to undermine the writer’s credit, requirements for studios to disclose if they’re giving any material to writers that was generated by AI. But then also, in a sort of more positive embrace of AI, the right for writers to choose to use AI as a tool as part of an agreement with the studios. SAG-AFTRA, the actors also got provisions sort of protecting their images from AI replication without their consent. And the Las Vegas—the hospitality unions also got provisions guaranteeing them advanced warning of any new technology rollouts that were going to impact jobs and training for jobs that are altered by AI. And, really importantly, protections from certain types of AI that enables surveillance within the workplace, something that was very important to hotel workers who have been increasingly surveilled in their work. So there is a lot to dig into. I’m going to stop talking so we can get to some questions, because there’s really—could go on and on because it was such a fascinating period of time. FASKIANOS: Fantastic. Thank you so much, Sharon. Michael, let’s go to you to pull out a little bit and talk about the global trends you’re seeing, and the implications for the future workforce and labor movements. And you just recently authored an article in our magazine, Foreign Affairs, The Coming AI Economic Revolution, with James Manyika. So perhaps you could talk a little bit too about the AI piece of this as well. SPENCE: Well, thank you very much. And I’m, you know, like Sharon, very pleased to be with you. So let me approach these things, you know, at a sort of slightly different level. That three-decade period that Sharon referred to is a period in which a massive amount of productive capacity was introduced into the global economy, largely as a result of emerging economy growth. And that had one very large negative effect, which was it, you know, created options for, you know, labor arbitrage and decreased the power of American labor. So unions declined, you know, the middle class got hollowed out to some extent, and so on. That force is fading. It’s not over, but it’s fading. There’s lots of evidence of that. You know, for at least two decades, probably more than that, we lost employment in the manufacturing sector. That stopped in the last decade. And then—but then there’s some other trends that, you know, kind of reinforce this. So when I look, you know, I see aging populations. Seventy-five percent of the global GDP is produced in in countries that are aging rapidly. You know, the great financial crisis caused some of our older fellow citizens, like me—not to retire. Now they’re retiring in droves. You know, when I look at the American economy all—most of the big labor, you know, employment sectors have labor shortages, right? I mean, it’s clear that on the underlying economic fundamentals, labor’s power position vis-à-vis their employers has increased dramatically. Some of this shows up in unionization. Some of it just shows up and in bidding for, you know, talent in a way that basically companies didn’t have to before—or, employers in general. So I think this is basically a good development. I expect to see, you know, several attractive trends. A reversal, maybe not a dramatic one, in the trends in inequality on the income side, which would be very good thing because it had gotten pretty extreme over this three-decade period. You know, I think we will see productivity increases because when you’re short of labor it’s sort of natural to start looking—the incentives are much stronger to look for productivity-enhancing things. And if that’s done in a way that makes—you know, puts management and labor in a collaborative position, seeking for ways that are mutually beneficial to do it, that’s also a good thing. On the negative side, you know, this is—you know, for the first time, really, we live in a supply-constrained world. I just—you know, at the risk of telling people what they already know, after the great financial crisis we’ve had—and for a longer period than that—we’ve had essentially no sign of inflation whatsoever. And we had no sign of inflation, in spite of zero interest rates and massive infusions of liquidity into the economy to try to precipitate a recovery after the balance sheet damage that the great financial crisis caused. And as a result of that, people have kind of gotten used to the notion that, you know, the cost of capital isn’t very high. So for people who are operating in state and municipal governments, I think, you know, there’s—nobody knows for sure. And we have a big inflation fight on, led by the central banks. Not just in the United States but in the U.K., and in Europe, and in other places. China being a fairly dramatic exception to this. We’re likely, in my view, to emerge from this with higher real interest rates. I don’t have any doubt that the central banks will get the inflation eventually under control, because they’re determined to do it and their credibility depends on it. That’s their job. But when we come out, I think we’re going to have, you know, lower sustainable debt levels, higher cost of capital, lower multiples, lower valuations for many assets. This will have mixed effects. You know, the cost of funding, certain longer-term investments is going to be a little bit higher than it was before, maybe even more than a little bit higher. On the other hand, from a distributional point of view, you know, when—in the period—the decade after the great financial crisis, the one thing that just ballooned in value was the assets. And that favored people who, you know, own a lot of assets. So it didn’t do wonders for the distributional features. So I think on the whole, if you sort of look at—I mean, there’s a lot—a lot of other factors, you know, that are affecting this. The global supply chains are, you know, collapsing—or, being fragmented. We have a major strategic competition, you know, with China underway. Economic policy, from an international point of view, has tipped toward, you know, various kinds of security—national security prominently, but also economic security, here in Europe energy security, food security, and so on. And this is causing, you know, policy to reinforce a trend in the global economy that’s very visible now, which is diversification in pursuit of resilience. And the policy is reinforcing it and saying: We have to do some of this at home in a way that we didn’t pay attention to before. We lived for three decades, those three decades, in which the way global—the global economy was constructed was basically on the basis of economic efficiency and comparative advantage. And that’s no longer true. So we have homeshoring, friendshoring, nearshoring, et cetera. All of which are transforming the structure of the global economy. And for the most part, I think, in ways that favor, you know, domestic—our domestic fellow citizens, and especially labor. Briefly on AI. So, we’ve had a sequence of breakthroughs in AI that go back, you know, a decade or a bit more. Language recognition. You know, image recognition was a stunning set of breakthroughs that, you know, occurred roughly around 2015-2016. But the one that’s really gotten people’s attention is generative AI, the large language models and the like. So there’s several things to say about this. And I’ll try to be brief. One, we’re not at the end of this. These folks aren’t finished. So what’s coming next we don’t know. I suspect that we will see significant advances in robotics as a result of the fact that gen AI allows you to basically talk to machines in a way that they understand. The gen AI is distinctive in the sense—in two respects that I think are important. One, unlike any other previous version of AI, they switch domains easily. By that, I mean, you know, you can talk to it about the Italian Renaissance and then switch to math and then it’ll do computer coding, you know, and whatever, right? Now, there’s lots of quirks, you know. These systems so far have hallucinations. They make stuff up. And I mention that for a reason. You know, it’s not—when you look at it carefully, it’s not sensible to think that these things should be fully, you know, allowed to operate on their own, right? They’re just not that flawless. You know, there’s a famous story in America, you know, a lawyer, slightly incautiously, prepared a legal brief entirely using ChatGPT, and handed it in. Well, ChatGPT made up all the legal precedents. And this gentleman is, I think, in some serious trouble as a result with the courts. So the way I think about it, and I’m not alone in this. I mean, James and I wrote that paper. We think that the right model is powerful digital assistant or machine-human collaboration, right? And you have to work that out. But let me say, you know, right at the top, there’s just overwhelming evidence that whenever you mention, you know, AI, people think, automation. They think they’re coming for our jobs. A hospital administrator stands up and starts talking about AI—and, by the way, AI is going to be transformative in biomedical and life sciences, which is not our topic for today. But it’s just one of the many places where the footprint over time will be felt. We have to overcome this bias. So the implementation matters. You know, unions representing people and having a voice in which they participate in conversations about what the AI is supposed to be doing and how it will change the jobs, and which parts are acceptable or not. But I think in the course of it we can sort of get rid of this—what I call the automation bias. Erik Brynjolfsson at Stanford calls this the Turing trap. Alan Turing proposed that we evaluate our progress in AI by asking the question: Can we produce a machine that when a human being interacts with that machine, not looking at it but talking with it, it thinks it’s interacting with another human being? And so we haven’t got there yet, but we’re working on it. Second, one small step. Almost all AIs are benchmarked against human performance. So when they declare victory in image recognition, it’s when it passes the average human, and so on. It’s the next small step that’s dangerous, which is, you know, well, once the machine passes the human, why don’t we replace the human, right? That’s where the AI—the automation bias comes from. And it’s just a mistake. Now, there may be a time in the future when these machines are so good that automation is a more serious consideration. But right now, they’re powerful digital assistants. They can sometimes do things that humans can’t do. Sometimes they do them, you know, in a way that’s just on par. But they—but I think the promise here is if we do this right that we’ll have the potential—not next year, not the year after, but maybe by the end of the decade—we’ll start to see, you know, impacts of this and in terms of productivity that are actually, you know, enhancements to the way people work and how they view their employment. To get there, we got to get rid of the automation bias, which is very deep. And we need one other thing. We need access. So right now, we’re in a period of intense exploration and experimentation. Who’s doing this, right? The answer is the companies with the resources to do it, you know. But if we’re going to have this broadly beneficial in society, available to small businesses, to local governments, and so on, it has to diffuse widely and well beyond, you know, the kind of entities that have the capacity to invest tens of millions of dollars in it. There’s a role for government in this. And I want to conclude with this, because we’re talking to, you know, important government officials in our economy. There really is a role, you know, in ensuring diffusion and broad-based access to these tools once we’ve decided, you know, in rough and ready terms, you know, how we’re going to try to use them. It’s really important, both for the purpose of getting the productivity surge but also, you know, for preventing—you know, in past—there’s studies of this at the McKinsey Global Institute. In past, you know, episodes of digital, you know, transformation, they’ve studied adoption. So and what you see is a pattern of divergence. So the tech sectors way is way up top, and finance is not far behind, and then you drop down and find sectors that, you know, are lagging seriously in this respect. This is the pattern that we do not want to repeat on this round. So I think there’s huge potential. There’s some downside risks. James and I would say that, you know, it’s important to pay attention to the misuse of these things and the downside risks, just as there is with any powerful technology. I mean, gene editing is terrifying if used in the wrong way, just as AI is as well. But there’s the positive agenda as well. FASKIANOS: Thank you both very much. And now we’re going to go to all of you for your questions. We’ve got the first written question from Riley Nye: Hasn’t automation already replaced tons of manufacturing jobs? SPENCE: Sharon, do you want to take that, or? BLOCK: I mean, certainly there has been displacement. Earlier this year I visited a Ford auto plant. And it is very, very—a very, very different place than certainly historical documentation of what the manufacturing process looked like. There are a lot fewer workers. You see that also reflected in—just to stay with the auto sector—in the number of UAW members in that sector. The UAW has actually diversified their membership a great deal. They do a lot—as many people on the call may know if you’re involved with higher education—they represent now many, many graduate students and other employees of higher education institutions. So, yes, that has happened. But the displacement conversation is obviously not over. And there is, I think, concern about additional displacement of workers if robotics and those kinds of productivity enhancements, or whatever the right euphemism is, continue. But I do think in the shorter term, the bigger concern actually should be for workers is the way that automation is being used in workplaces to enhance not just productivity but also employer domination of workers. These surveillance issues you’re seeing, especially if you follow, like, the logistics sector. The intensification of work that is enabled by the kind of productivity tracking that AI has enabled. I think these are the changes in the workplace that people are feeling already, even before we get to this question of whether AI is ever going to—or when it’s going to be good enough to replace more workers. And so that’s a place where I think the regulatory attention really needs to be paid. And if you look at what the EU just did—we don’t know the details yet of the AI Act that the EU Parliament just passed—but there is a lot of attention to those issues. And, in fact, the workplace is designated in that legislation is a high-risk forum for the introduction of AI, not because of the displacement issues but because of the intrusion into sort of personal privacy spheres for working people, and this potential for new safety and health issues to arise from a misuse of AI in the workplace. FASKIANOS: Thank you. I’m going to go next to Justin Freeman, who is the director of community affairs for New York State Assembly: Could you share more about how today’s strike actions compare to before, say, thirty, forty years ago? You mentioned four million strike days. BLOCK: Yeah. So, again, we haven’t had a year with four million strike—it’s actually more than four million at this point. That doesn’t capture the full range of the UAW strike days. But I just couldn’t find a more recent calculation. That’s a little bit of a hard calculation to do. We haven’t seen a four million strike day year in a long time. So, say, ten to fifteen years ago. But if you look at, like, in the 1930s, so the period as we were legislating the right to join unions, you would have—there were years in the 1930s, early 1940s, where you had thousands of strikes in the United States. And, you know, it’s hard to compare numbers because our economy is obviously so much bigger now. Our workforce is so much bigger. But if you could imagine thousands of strikes. It was really a completely different scale. I mean, if I could show you a graph from, like, the ’40s to today, you would see a line that just really dramatically falls off as we entered this period, you know, that we’ve been talking about, like the past thirty years of a real decrease in the strength of the labor movement. You saw a commensurate decrease in the number of strikes. FASKIANOS: OK, thank you. Shawn has asked a question. China was mentioned. How big of a threat do you feel China is, with their housing, population, and debt crisis? SPENCE: OK. So I think everybody knows that China, you know, has had kind of a pretty impressive forty-year run. It was one of the poorest countries in the world in 1980. It has exhibited growth rates of, you know, 7, 8, 9 percent on a sustained basis that, you know, causes, you know, the size of the economy and incomes to double faster than every decade. That’s not something an advanced country can do. I think China is now in a very difficult sort of position in terms of transformation. And the economy is in trouble. So they have major, major excess capacity in real estate, and a lot of non-performing loans, and whatnot. This directly affects the Chinese economy because while this is, to some extent, true in other places, the household balance sheet—meaning wealth—is heavily dependent on real estate, right? Once they started buying houses and so on, they just owned more real estate and less kind of other kinds of assets than almost anywhere else in the world. And so when the real estate values decline, or there’s some uncertainty, or it gets shaky, or, you know, the apartment that you bought in advance doesn’t get built, it causes a major shakeup in confidence. The fiscal system needs major reform in China. The municipal governments are essentially flat-broke. They do not have the normal sources of revenue that our municipal governments do. And they are responsible for delivering services that are in excess of their capacity to finance it. There’s no more land. They used to do it by selling land. There’s no more land to sell, or not enough to finance themselves. But I think the really sort of serious challenge, in addition, in China is that the pattern of off again/on again and fairly aggressive regulation, which you can see in the tech sector but it’s broader than that, has caused a loss of confidence among investors. And by that, I don’t mean foreign investors. I mean, everybody, including the domestic investors. And so with the household spending, you know, a little bit on hold, and the private sector investment, you know, kind of on hold because they’re not sure what their place in the sun is, that, you know, there’s a significant slowdown. The numbers in China will look OK because the previous year was a disaster. So when you’d show up growth numbers, you know, when they were in zero-COVID, it was, you know, unimpressive. So the numbers look better than the actual situation. Having said that, you know, it is in many ways—you know, in human capital, in science and technology, and whatnot—they’ve made huge investments in it. So I don’t want to leave the impression that this is a kind of, you know, permanent disaster at all. They can pull this out. And it’s an economy—it’s a very large economy, the second-largest one in the world. And it will be, if they right the ship on these—what I think of as short- and medium-run challenges—it’s a, depending on how you think of it, a powerhouse and potential major competitor. FASKIANOS: And, Michael, just to follow up on that, a question from Alan Schneider, who is legislative director in the Office of Maryland Delegate Chao Wu: You know, given the relationship changes between the U.S. and China, how are the changes affecting wage, A1, and inflation here in the United States? SPENCE: Very good question. So in terms of, you know, the—we are in—our national security, you know, driven policies are bringing more stuff home. And in addition, China is now an economy with a per capita income of $13,000. You’re not going to make, you know, the cheapest labor-intensive, process-oriented manufacturing and assembly stuff in China for very much longer. There is no real substitute for China. There are other countries. And some of them are benefiting—Vietnam, Bangladesh, you know, Mexico has a major opportunity as China sort of, A, gets into kind of conflict with us and, B, you know, we move both businesses and governments in behind with policy to move stuff away. I think on the whole it’s slightly inflationary. But it’s good for, you know, labor—meaning, our labor. FASKIANOS: Terrific. Let’s go to—sorry. Going to sell in Selin Zorer: What proactive steps should federal and state legislators take to ensure that the emergence of AI benefits the public? SPENCE: Sharon, do you want—do you want— BLOCK: I can—I can start. I mean, you know, I think one way to ensure that it benefits public—I mean, most of the public has to go to work every day. And so thinking about the ways to protect workers from some of these abuses and excesses is really important. The other—I think the other area where I’m really interested is while we see some paralysis at the federal level in terms of legislating around the introduction of AI into the workplace, I think there is much more of an opportunity for state and local governments to step in. California is obviously very engaged in their legislature in thinking about guardrails for AI in the workplace and in other domains. But it’s really important that as this regulatory forum moves to state and local levels, that there is an attention to making sure that the people who are going to be most affected, that working people have an opportunity to have a voice in how this regulation develops. And so whether that’s bringing in the labor movement, finding other ways to ensure that working people are participating in these really important conversations, I think is going to be critical. And I hope we’ll see sort of interesting and innovative approaches as more states feel compelled to get into the game. Because we are probably not going to see, you know, significant federal regulation or legislation in this space. FASKIANOS: Thank you. Next— SPENCE: Irina, could I— FASKIANOS: Go ahead, Michael, absolutely. SPENCE: This is—I don’t want to repeat myself but, you know, there’s a positive agenda. You know, a lot of the, you know, management that affects people’s lives is done at the state and local level. Not, you know, the kind of stratosphere where some parts of the federal government operate. And, you know, I think, you know, thinking carefully about where we’re going with these technologies and how you help people, you know, become comfortable with them, productive with them, and so on, is a hugely important part of the agenda. And I can’t think of more important entities than the state and local governments, you know, the community colleges. You know, the education system as a whole seems to me to be, you know, where the conversation needs—you know, a fair amount of the conversation needs to occur. So, again, I don’t want to, you know, minimize the importance of preventing downside risks and misuse and so on. But I think walking into the world, you know, without a coherent set of programs to help people—you know, if we are going to have these transformations in one form or another. That it’s way too powerful, these technologies. So I think the challenge is to do it right, rather than resist them. FASKIANOS: Fantastic. I’m going to go next to Justin Freeman, director of community affairs at the New York State Assembly: Is there any correlation between interest rates and strike actions? Can strikes be anticipated through economic indicators? SPENCE: Go ahead. FASKIANOS: You can take it. Who wants to start? BLOCK: I think Michael mentioned the most important factor, which is a tight labor market. I mean, that is clearly connected to this upsurge in labor activity, both in the strike activity and then also in this renewed commitment to organizing. There’s just—there’s a lot of risk under our legal system. There’s a lot of risk to workers who try to organize a union, who go out on strike. We have a law that’s really deficient in terms of protecting workers who engage in that kind of labor activity. And so a tight labor market gives workers the confidence that if they are retaliated against for taking this kind of activity, that they can find other jobs. And it’s really as simple as that as to why you see that correlation between a tight labor market and increased union activity. So I think that’s the most important factor. I think the issue of interest rates is just whether the Fed was going to raise interest rates enough to start driving that unemployment rate up and creating slack in the labor market, which then would have taken some of this dynamic—diluted this dynamic so that workers didn’t have that same confidence in their ability to find other jobs when they take the risk of organizing or striking. FASKIANOS: Michael. SPENCE: Yeah, I mean, essentially the same. I mean, so we—you know, the supply side of our economy, and the global economy has just changed dramatically, right? So it used to be almost infinitely elastic. You could have a surge in demand and, you know, somewhere somebody produced enough to meet it. That’s just not true anymore. That’s why we have labor shortages, as Sharon says. That’s why labor power is increasing. And as for inflation, you know, the trigger, you know, as we came out of the pandemic with a predictable surge in demand, and the supply side constrained by, you know, aging—you know, all the things we talked about. You know, we had a demand and supply imbalance. It was the trigger for inflation. Now, inflation can develop a life of its own, you know, once it goes on for long enough. But, you know, the economists look at this and say: When have we seen interest rates go up this fast and this high and not seen, you know, labor market problem? We just—you can go back a long way and try to find out an example of this. So, you know, this—what this tells you is that, you know, we have fundamental structural changes underway in the economy. And they—and the relationship between the labor markets and the inflation is that, you know, it triggered the inflation because the supply side couldn’t keep up. Now, what’s going on now, and I’ll just end with this, is, you know, the central banks, you know, can’t operate on the supply side of the economy. So they’re basically raising interest rates largely to reduce aggregate demand and get rid of that imbalance. And so far, they managed to do it without, you know, producing unemployment increases of any significant magnitude because there are labor shortages—short version. FASKIANOS: Great. Thank you. I’m going to go next to Aaron Tebrinke, who’s legislative assistant to Leader Koehler of the Illinois Senate: After 148-day strike, Hollywood screenwriters secured significant guardrails against the use of AI in one of the first major labor battles over generative AI in the workplace. A battle for automation against AI, automation was won by labor. But what protections will workers have to keep up with AI tools in the marketplace that are not regulated for privacy? SPENCE: Sorry, can I—the concern of the writers was that, you know, they were going to get displaced, you know, by the use of, you know, the kind of generative AI, the large language models. That was, like, I don’t—that’s a bit of automation, but the underlying concern was copyright, right? Which is a major issue, right? Because it—you know, gen AI is trained on the entire internet. They just go read everything, you know, at speeds that exceed human capacities. So the question is, well, what’s the relationship between that and all the imaginative content that these and other people have produced that the AIs just hoover up? So that strike had multiple dimensions to it, and not all of them had to do with automation, for sure. FASKIANOS: Sharon, anything to add? BLOCK: Yeah, I think that that’s right. Obviously, we’re seeing litigation by content creators, many of whom are members of the Writers Guild, in order to get at this issue of their intellectual property rights vis-à-vis the use of these—the use of that content by the large language models. So I think we are going to continue to see many different fronts in the introduction of AI into the workplace, and as it impacts workers in different ways. So but to just to answer the, the part of the question about privacy, we have a very, very weak privacy regime vis-à-vis the workplace in the United States. And so you really—in the private sector. Now, that’s different in the public sector because you have a constitutional dimension to privacy in the workplace with public sector employers. So some of this might sound—might sound different than your own—than your experience, since folks on this call are from the public sector. But in the private sector, we don’t really have an institution of privacy protections—as we now have AI surveillance of things like, you know, your email. There are employers now who very easily can just scrape every email that you write to find out all kinds of things about you, and you probably don’t even know it. That can watch you through the camera on your laptop when you’re working from your home. So I think these privacy concerns aren’t new in the workplace. But I think they’re going to be appreciated by, I hope, policymakers, but also by workers in a new way, as we see different uses of AI in the workplace. FASKIANOS: Great, thank you. I’m going to go next to Nate Belcher, who is a fiscal analyst for Arizona Joint Legislative Budget Committee: UAW included a thirty-two-hour workweek with no pay reduction as one of their bargaining points in their recent negotiations. Do you think that reducing the length of the workweek will become a more popular demand from labor in the coming years? BLOCK: Yes. I think—I mean, I think we’re seeing it already. I mean, I would say just a few years ago there was almost no serious discussion of a four-day workweek. That is now an issue that is on the table. I don’t know of any workers who have secured a four-day workweek through collective bargaining. There are certainly employers who, of their own volition, are experimenting with shorter workweeks, sometimes with four-day workweeks. You know, I don’t think that many people thought that the UAW contract at the end of the day would actually include a thirty-two-hour workweek. I think it was put on the table as just another way to discuss hours. I mean, what was really an issue in the UAW strike I think around hours was the fact that many, many workers were being forced to work a lot of overtime. And even if they were getting paid for that overtime, it was having such an impact on their quality of life that it was really an entree to talk about what it is like to have those kinds of time demands, and what workers want in terms of having some kind of balance in their lives to be able to do with their time what they want. But I think the thirty-two-hour workweek is a conversation we’re going to continue to see bubbling up. FASKIANOS: Thank you. Next question from Paul Egnatuk, who is the legislative aide in the office of the Michigan State Representative Jim Haadsma: I’ve heard recently of brick-and-mortar type investments stalled because investors are enamored with AI ventures. Can you recommend sources of research on the impact of private capital going toward AI development and/or where capital may be short for other pressing needs? SPENCE: Right, this is complicated. I mean, so, you know, there’s a massive amount of money going into AI. So some of the valuations are probably a little bit off the chart and, you know, that’ll get corrected over time. Some of us will remember the internet bubble, which had some of the similar characteristics. But that doesn’t mean there’s nothing there. But, you know, if you look at, I mean, vis-à-vis the previous subject, you know, hybrid working is becoming a very prominent feature of a subset of the economy where you can do that, right? And, you know, if you go into New York now and go into an office on Friday—you know, you’re very likely not to find anybody there. I mean, my friends tell me, don’t even bother. You know, so that doesn’t mean the work week is shorter, but it means, you know, that there’s substantial changes in the real estate sector and, you know, excess capacity of one kind, people—economic activity is moving around. I mean, on the whole, I would say the investment situation in the United States is reasonably healthy. You know, for the first time we have sort of major investments in infrastructure, you know, that have been funded by the government. And the CHIPS and Science Act has some more major investments, some of it designed to bring activity at home. And then we have the Inflation Reduction Act, which is designed to put, you know, funds into the energy transition in pursuit of sustainability. So when I look at the whole—I mean, there’s imbalances all over the place because of these structural transformations. And I’m sure we could find places where there’s significant deficits. But on the whole, I think the investment program, you know, or the investment situation looks moderately healthy. You are going to see just huge investments in the digital technology side as people pursue this set of opportunities. FASKIANOS: Sharon. BLOCK: Yeah, I don’t think I have anything to add. I mean, it is—it does feel like we are seeing more manufacturing jobs. I think we’re all—having come out of the Biden administration, I’m really excited to see sort of the full implementation of the Inflation Reduction Act and the CHIPS and Science Act. We just—I think, last week the president visited a site of the first—like, one of the first major investments. So I think that might balance out, you know, the kinds of trends that the questioner was raising. FASKIANOS: Emily Walker, who’s legislative director for Pennsylvania Senator Katie Muth, asked: Can you talk a little bit about the wave of organizing that’s been taking place in southern United States recently? BLOCK: Yeah, happy to. It’s a very interesting dynamic. So a couple of different trends. There has been a concerted effort, particularly driven by SEIU, Service Employees International Union, to do some kind of innovative organizing in the South. You know, the South is a very challenging place for the labor movement. Has been for a long time. And so there’s been a push to not do traditional union organizing but just try to get as many workers engaged in collective activity without necessarily using the traditional model of an NLRB election for majority exclusive representation within their workforce. You know, the South now is pretty much universally right to work, which just makes it a very challenging environment for traditional union organizing. So I think we’re going to continue to see these kinds of innovative campaigns. They’re really more like campaigns than organizing drives. The counter to that, though, is, like in the Starbucks organizing, there’ve been about more than 300 Starbucks stores that have unionized, and a number of those are in southern states. The South has not been able to sort of put up that wall to union organizing, at least among the Starbucks organizing, that they have in terms of a lot of other sectors. But the other dynamic, which it’s too early to know whether it’s going to be successful or not, but is what I raised at the outset about the UAW’s intent now to organize the transplant car companies. Almost—not all of which, but which predominantly have located their manufacturing in the South. And we also have—Ford is building the Blue Oval Plant, which is going to be, I think, one of the largest auto manufacturing plants in the country, if not the world. And they have now made a commitment to not try to stop the union from coming into Blue Oval. So that’s in Mississippi. That is going to be a union plant. That’s a big deal. But then the big question is going to be whether the UAW can organize other car companies that are not union in this. And I’ll note, they’re not union in this country. Most of these companies have unionized workers everywhere else in the world. And they seem to figure out a way to make money in plants in other countries with unionized workforces. They come here, and they fight the UAW sort of tooth and nail to keep the union out of their plants here, again, which are mostly located in the South. So, you know, we’ll see. I think after this most recent UAW strike, underestimating the new president Shawn Fain is not a good idea. He did things in this strike that nobody thought he would be able to pull off. So I think, again, one of the big stories in 2024 is going to be whether we’re going to see inroads for labor in the South, particularly through these auto companies. FASKIANOS: Thank you. And I’m going to sneak in one last question from Charisse Childers, director for Arkansas Division of Workforce Services: Michael stated it is not possible to think that robots can operate on their own. Do we have employment data on jobs that were added solely in conjunction with added technology? In the same vein, jobs lost solely in conjunction with technology, meaning robots? SPENCE: So, I mean, this a little bit nerdy, but, I mean, robot—human beings, you know, especially people who actually make things and, you know, do things in a physical environment, have, you know, an extraordinary capacity that robots don’t have. Which is an ability to absorb a rapidly evolving, you know, external environment, you know, visual and other signals, essentially with no latency. Robots aren’t even remotely close to that. And if you want evidence of it, look at the, you know, challenges facing the autonomous vehicles. You know, they do fine in highly structured environments, you know, where, you know, you’ve painted all the lines on the road, or you’re in a parking lot, or something like that. And then you put them in sort of an unusual situation, and they drive into a pile of cement or, you know, the emergency responders don’t know how to deal with them, and so on. You know, in other words, in unstructured environments, you know, the robots basically need help navigating around, even if they have the mobility and, you know, manual dexterity, and other things that are other dimensions of robotics. There’s people working on this problem, but I think, you know, this is an example—you know, one of the many—in which I think robotics and people are going to work together. You know, and you’re not going to see full automation. Maybe in structured environments. I mean, you see some of it—you look at—it’s not just manufacturing. You look at a, you know, major distribution center, an Amazon distribution center, there’s—you know, there’s a lot of robots. And this isn’t very snazzy technology. They just don’t bump into each other and they go collect things and bring them to the people who pick and pack them, scan them, and so on. So, you know, there’ll be progress in this. But my—having spent some time talking with AI people, I think that, you know, full automation, except in highly structured environments, is a fairly long way away. And we’re going to see mostly human—you know, human-machine kind of collaboration and those environments. And there are a lot of them. I mean, you know, if you go outside distribution centers and manufacturing things, and highly structured, you know, roadways and whatnot, pretty much everything else is unstructured, right? Hospitals, et cetera, so. FASKIANOS: Thank you. Well, unfortunately, we are out of time. But this was a terrific discussion. So thank you, Sharon Block and Michael Spence. We appreciate it. And to all of you, for your questions. We will be sending a link to the webinar recording and transcript, as well as some of the other resources that were mentioned. You can follow Dr. Spence’s work on CFR.org and Professor Block on X, formerly known as Twitter, at @SharBlock. And, as always, we encourage you to visit CFR.org, ForeignAffairs.com, and ThinkGlobalHealth.org for the latest developments and analysis on international trends and how they are affecting the United States. Of course, please do share your suggestions with us for future webinars and any ideas on how we can help you in the work that you are doing in your communities. You can email [email protected] . We wish you all a happy holiday season. And we look forward to reconvening this series in fiscal year—or, actually 2024, which is right around the corner. So, again, thank you both. We really appreciate it. SPENCE: Thank you. Thank you. (END)
| 2025-06-20T00:00:00 |
https://www.cfr.org/artificial-intelligence-ai?page=5
|
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Salary for Skill: Artificial Intelligence (AI) - Payscale
|
Artificial Intelligence (AI) Salary
|
https://www.payscale.com
|
[] |
$141k / year / hour Avg. Base Salary (USD) Find out what you should be paid. Use our tool to get a personalized report on your market worth.
|
Use our tool to get a personalized report on your market worth. What's this?
Find out what you should be paid
| 2025-06-21T00:00:00 |
https://www.payscale.com/research/US/Skill=Artificial_Intelligence_(AI)/Salary
|
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Closing the AI Skills Gap - AI Think Tank Podcast
|
Closing the AI Skills Gap
|
https://aithinktankpodcast.com
|
[
"Ai Think Tank Podcast"
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Bridging the AI skills gap isn't a philanthropic side-project; it's industrial hygiene. Every knowledge worker, coder, nurse, line-manager, city ...
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We use cookies to analyze website traffic and optimize your website experience. By accepting our use of cookies, your data will be aggregated with all other user data.
| 2025-06-21T00:00:00 |
https://aithinktankpodcast.com/articles/f/closing-the-ai-skills-gap
|
[
{
"date": "2025/06/21",
"position": 65,
"query": "AI skills gap"
},
{
"date": "2025/06/21",
"position": 57,
"query": "AI skills gap"
},
{
"date": "2025/06/21",
"position": 57,
"query": "AI skills gap"
},
{
"date": "2025/06/21",
"position": 57,
"query": "AI skills gap"
},
{
"date": "2025/06/21",
"position": 57,
"query": "AI skills gap"
},
{
"date": "2025/06/21",
"position": 62,
"query": "AI skills gap"
},
{
"date": "2025/06/21",
"position": 56,
"query": "AI skills gap"
},
{
"date": "2025/06/21",
"position": 59,
"query": "AI skills gap"
},
{
"date": "2025/06/21",
"position": 57,
"query": "AI skills gap"
},
{
"date": "2025/06/21",
"position": 58,
"query": "AI skills gap"
},
{
"date": "2025/06/21",
"position": 57,
"query": "AI skills gap"
},
{
"date": "2025/06/21",
"position": 59,
"query": "AI skills gap"
}
] |
|
Amazon CEO Andy Jassy says company will cut jobs amid AI boom ...
|
Amazon CEO Andy Jassy says company will cut jobs amid AI boom. It's already happening at Microsoft.
|
https://finance.yahoo.com
|
[
"Sat",
"Jun",
"Min Read"
] |
Amazon slashed over 27,000 jobs between 2022 and 2023, just as Jassy was touting its AI efforts. The company laid off another 100 workers in May ...
|
Amazon (AMZN) CEO Andy Jassy said the company will reduce its workforce in the coming years, and Microsoft (MSFT) is reportedly planning thousands of layoffs, just as the two companies invest billions in artificial intelligence efforts.
Microsoft is expected to announce the cuts, primarily aimed at its sales teams, early next month, according to Bloomberg, which cited anonymous sources.
Microsoft declined to confirm the layoffs to Yahoo Finance. “As they typically do year-round, teams evaluate business priorities and ensure they are aligning to the right opportunities for strategic growth,” a spokesperson said.
The news came after Amazon’s Jassy said on Tuesday that AI will lead to job cuts at his own company.
“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, and more people doing other types of jobs,” Jassy said in a memo to employees.
“It’s hard to know exactly where this nets out over time, but in the next few years, we expect that this will reduce our total corporate workforce as we get efficiency gains from using AI extensively across the company.”
Jassy said Amazon is “using Generative AI broadly across our internal operations” for tasks like inventory management and demand forecasting in its delivery system.
The CEO said, because of AI, “We’ll be able to focus less on rote work and more on thinking strategically about how to improve customer experiences and invent new ones.” The comments were met with backlash from employees.
Some of Amazon's corporate employees are facing an order to relocate closer to their managers and teams, Bloomberg reported on Thursday. The mandate would require many of them to move across the US to Seattle, Washington DC and other hubs, its sources said.
Meanwhile, Amazon and Microsoft have been spending billions to advance their AI efforts. Amazon has consistently reported higher capital expenditures than its fellow Big Tech “hyperscalers” over the past several years, driven by its investments in AI infrastructure. In 2025, that trend is set to continue.
Amazon has projected it will spend roughly $105 billion, much higher than its peers, with the vast majority going to AI infrastructure for its cloud segment, Amazon Web Services. Microsoft is set to spend $80 billion in 2025 to build out AI data centers.
Amazon and Microsoft have both announced layoffs in recent years. Microsoft laid off 3% of its workforce in May after an upbeat earnings report. Amazon slashed over 27,000 jobs between 2022 and 2023, just as Jassy was touting its AI efforts. The company laid off another 100 workers in May amid the CEO's aggressive effort to cut middle management while looking to run Amazon like “the world’s largest startup.”
| 2025-06-21T00:00:00 |
https://finance.yahoo.com/news/amazon-ceo-andy-jassy-says-company-will-cut-jobs-amid-ai-boom-its-already-happening-at-microsoft-213847151.html
|
[
{
"date": "2025/06/21",
"position": 52,
"query": "AI layoffs"
},
{
"date": "2025/06/21",
"position": 68,
"query": "AI layoffs"
},
{
"date": "2025/06/21",
"position": 49,
"query": "AI layoffs"
},
{
"date": "2025/06/21",
"position": 64,
"query": "AI layoffs"
},
{
"date": "2025/06/21",
"position": 50,
"query": "AI layoffs"
},
{
"date": "2025/06/21",
"position": 49,
"query": "AI layoffs"
},
{
"date": "2025/06/21",
"position": 49,
"query": "AI layoffs"
},
{
"date": "2025/06/21",
"position": 72,
"query": "AI layoffs"
},
{
"date": "2025/06/21",
"position": 47,
"query": "AI layoffs"
},
{
"date": "2025/06/21",
"position": 49,
"query": "AI layoffs"
},
{
"date": "2025/06/21",
"position": 48,
"query": "AI layoffs"
},
{
"date": "2025/06/21",
"position": 50,
"query": "AI layoffs"
},
{
"date": "2025/06/21",
"position": 45,
"query": "AI layoffs"
},
{
"date": "2025/06/21",
"position": 72,
"query": "AI layoffs"
}
] |
|
Intel to outsource marketing to Accenture and AI, resulting ...
|
Intel to outsource marketing to Accenture and AI, resulting in more layoffs
|
https://www.tomshardware.com
|
[
"Anton Shilov",
"Contributing Writer",
"Elusive Ruse",
"Social Links Navigation"
] |
Intel is outsourcing much of its marketing work to Accenture, aiming to cut costs and automate tasks using AI, which will reshape the company's longtime ...
|
Employees at Intel's marketing division were informed that many of their roles will be handed over to Accenture, which will use AI to handle tasks traditionally done by Intel staff, reports OregonLive. The decision is part of a company-wide restructuring plan that includes job cuts, automation, and streamlining of execution.
The marketing division has been one of Intel's key strengths since the company began communicating directly with end users with the launch of its "Intel Inside" campaign in 1991. However, it looks like the company will drastically cut its human-driven marketing efforts going forward, as it plans to lay off many of its marketing employees, believing that Accenture's AI will do a better job connecting Intel with customers. The number of positions affected was not disclosed, but Intel confirmed changes will significantly alter team structures, with only 'lean' teams remaining. Workers will be told by July 11 whether they will remain with the company.
Among other things, the aim of the restructuring is to free up internal teams to focus on strategic, creative, and high-value projects, rather than routine functions. Therefore, Intel intends to use Accenture's AI in various aspects of marketing, including information processing, task automation, and personalized communications.
Intel has acknowledged the shift to Accenture and explained that this will not only cut costs but will modernize its capabilities and strengthen its brand. How exactly the usage of AI instead of real people can reinforce the brand hasn't been explained yet.
"As we announced earlier this year, we are taking steps to become a leaner, faster and more efficient company," a statement by Intel published by OregonLive reads. "As part of this, we are focused on modernizing our digital capabilities to serve our customers better and strengthen our brand. Accenture is a longtime partner and trusted leader in these areas and we look forward to expanding our work together."
In messages to staff published by OregonLive, Intel indicated that part of the restructuring may involve existing employees training Accenture contractors by explaining how Intel's operations work. This knowledge transfer would occur during the transitional phase of the outsourcing plan, although it is unclear how long this phase will take.
Follow Tom's Hardware on Google News to get our up-to-date news, analysis, and reviews in your feeds. Make sure to click the Follow button.
| 2025-06-21T00:00:00 |
2025/06/21
|
https://www.tomshardware.com/pc-components/cpus/intel-to-outsource-marketing-to-accenture-and-ai-resulting-in-more-layoffs
|
[
{
"date": "2025/06/21",
"position": 35,
"query": "AI layoffs"
}
] |
IBM laid off 8000 employees to replace them with AI—what ...
|
IBM laid off 8,000 employees to replace them with AI—what they didn’t expect was having to rehire as many due to AI
|
https://glassalmanac.com
|
[
"Brian Foster"
] |
In 2023, IBM made headlines with the announcement of nearly 8,000 layoffs, primarily from support roles such as Human Resources. The goal?
|
Share this Post: WhatsApp Share
In 2023, IBM made headlines with the announcement of nearly 8,000 layoffs, primarily from support roles such as Human Resources. The goal? To replace these workers with artificial intelligence (AI), automating repetitive tasks and increasing efficiency. However, just months later, the company found itself doing something it hadn’t anticipated: rehiring many of those workers【¹】.
IBM’s AI Experimentation: The Plan to Cut Costs
IBM’s announcement to reduce its workforce was bold. As a longtime technology pioneer, the company believed that up to 30% of repetitive tasks in HR and other support functions could be automated with AI. The aim was clear: boost productivity and reduce costs. This move came amid a wider trend in the tech industry, with companies like Google and Spotify also trimming staff, often citing AI and automation as key drivers of these cuts【²】.
However, IBM took this plan a step further. The company developed “AskHR,” an AI-driven chatbot designed to handle up to 94% of HR-related tasks. From processing leave requests to managing payroll and employee documentation, AskHR was a game-changer, freeing up employees to focus on more valuable tasks. By automating these processes, IBM saved an impressive $3.5 billion across 70 different roles, demonstrating the efficiency gains AI could provide【³】.
The Unexpected Result: Rehiring and Redirection
But here’s the twist: despite these significant savings, IBM’s workforce actually grew after the layoffs. Arvind Krishna, the CEO, explained to the Wall Street Journal that while AI had helped streamline operations, it also allowed the company to reinvest in other areas. Rather than eliminating jobs permanently, IBM found that the freed-up resources were being directed towards higher-value roles.
IBM began hiring engineers, salespeople, and marketing specialists—positions that require creativity, critical thinking, and human interaction—skills that AI cannot replace. While AI took over routine, repetitive tasks, the demand for human talent in strategic, high-impact areas grew substantially【⁴】.
A New Era of Work: How AI Is Creating Jobs, Not Just Replacing Them
IBM’s experience offers a glimpse into the future of work. Far from being a job-killer, AI is creating new opportunities—though these opportunities require different skills. As automation takes over repetitive tasks, the demand for professionals who can design, manage, and sell AI solutions is surging【⁵】.
This trend is not unique to IBM. Companies like Duolingo and certain customer service platforms have also experimented with replacing workers using AI tools like chatbots. However, in some instances, the results have been less than expected, leading to a return to hiring human specialists who can better manage the limitations of automation【⁶】.
The success of IBM’s AI-driven automation strategy lies in how effectively the company reinvested the savings into areas that required human expertise. For example, AskHR handled over 11.5 million interactions in 2024. Customer satisfaction jumped from a negative Net Promoter Score (NPS) of -35 to a positive +74, showcasing the value of both AI efficiency and human oversight. Yet, only 6% of requests still required human intervention, demonstrating that some tasks will always require a human touch.
What’s Next? The Future of Jobs in the Age of AI
IBM’s story raises important questions about the future of work in an AI-driven world. According to the World Economic Forum, nearly 92 million jobs could be displaced by automation by 2030. However, the same report also highlights the emergence of new roles that require expertise in AI and other high-tech sectors.
The challenge for both companies and workers will be navigating this transformation. Businesses must adapt to the changing demand for skills, while workers will need to invest in continuous learning and reskilling. The key to thriving in this new landscape will be embracing change and preparing for a future where AI doesn’t just replace jobs but reshapes entire industries.
IBM’s journey illustrates that AI is not just about cutting costs—it’s about evolving business models, reallocating human resources, and reinventing the nature of work itself【⁷】.
Footnotes:
“IBM 2023 layoff announcement,” BBC News, 2023. Available at: https://www.bbc.com/news/technology “How IBM’s AI-driven chatbot transformed HR,” The Guardian, 2024. Available at: https://www.theguardian.com/technology “The World Economic Forum’s 2023 job displacement report,” World Economic Forum, 2023. Available at: https://www.weforum.org/reports “Duolingo’s chatbot experiment,” TechCrunch, 2023. Available at: https://techcrunch.com/ “AI’s impact on job creation and automation,” Harvard Business Review, 2023. Available at: https://hbr.org/ “IBM’s automation strategy: A success story,” Wall Street Journal, 2024. Available at: https://www.wsj.com/ “Automation and Human Workforce Synergy,” Financial Times, 2024. Available at: https://www.ft.com/
Similar Posts
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| 2025-06-21T00:00:00 |
2025/06/21
|
https://glassalmanac.com/ibm-laid-off-8000-employees-to-replace-them-with-ai-what-they-didnt-expect-was-having-to-rehire-as-many-due-to-ai/
|
[
{
"date": "2025/06/21",
"position": 61,
"query": "AI layoffs"
}
] |
Will AI Replace Humans in The Workplace?
|
Will AI Replace Humans in The Workplace?
|
https://www.cekindo.com
|
[
"Pt Cekindo Business International",
"Indah Ramadhanti"
] |
10 Jobs AI Might Replace · Assembly line workers · Data entry clerks · Taxi drivers (with the rise of self-driving cars) · Telemarketers · Cashiers (with self- ...
|
As AI (Artificial Intelligence) perception shifted from a threat to a supportive tool, it has significantly transformed the business world. As a result, AI and digitalization have become increasingly indispensable in the workplace, raising the question, “Will AI replace humans in the workplace?”
What is Artificial Intelligence (AI)?
Artificial intelligence (AI) may be used for any computer science in which machines are programmed to exhibit human-like capabilities. These include critical thinking, decision-making, and the ability to improve efficiency.
AI development is fueled by human understanding. By breaking down complex tasks into manageable steps, we enable machines to perform them from the most basic to the most complicated.
AI and Its Growing Presence in The Workplace
According to Gartner, the number of companies investing in AI increased by 270% between 2015 and 2019. As a result, the global AI market will be valued at over $136 billion in 2022 and is estimated to grow by 38% in 2023.
These statistics highlight the significant transformation of the workplace, indicating a stark contrast to how it looked a decade ago. As a result, companies are investing heavily in AI, which has become a critical tool in human functions, making them more efficient and accurate.
AI technology has transformed the workplace, providing data-backed insights on employee performance and streamlining workflow processes, leading to better and faster decision-making. This often raises the question: will AI replace humans in the future?
AI has revolutionized learning and development programs with personalized content matching and coaching chatbots. It empowers workers to innovate workflow processes and perform better with reliable, up-to-date, error-free data.
The Potential Impact of AI on Employment
The fear and concerns regarding AI and automation are understandable, but history has shown that they are ultimately unwarranted as technological change creates more jobs than it eliminates.
Furthermore, AI and automation can eliminate tedious tasks and free humans to pursue more satisfying and challenging careers.
AI can also potentially eliminate disease and world poverty, as it is already driving advances in medicine and healthcare and helping to identify where help is needed most through the AI and Global Development Lab.
However, skeptics still question this movement due to AI’s limitations and the negative impact it may have on the existing workforce, which is gradually becoming redundant.
Here’s a breakdown of potential changes and an address to the question, “Will AI replace human jobs?”:
Automation of Tasks: AI digitizes and automates many repetitive tasks, often without human intervention. New Opportunities: AI opens up new career fields like digital engineering, even as traditional jobs decline. Economic Growth: Proper use of AI boosts productivity and economic growth, improving living standards. Role of Work: Work in the AI era fulfills deeper needs for involvement and creativity. Automated tasks should be replaced with roles that offer similar personal expression. Creativity and Innovation: With AI handling routine tasks, people can focus more on innovation and problem-solving.
While concerns about AI’s impact on jobs are valid, its benefits and the new opportunities it creates suggest a positive, transformative change.
AI and the Future of Jobs
AI might automate some tasks, but it’s also creating new opportunities. In the debate of AI vs human jobs, here’s a breakdown of potential changes:
10 Jobs AI Might Replace
Assembly line workers
Data entry clerks
Taxi drivers (with the rise of self-driving cars)
Telemarketers
Cashiers (with self-checkout becoming more common)
Loan processors
Bookkeepers
Paralegals (for some routine legal tasks)
Sports referees (with the use of automated officiating systems)
Factory workers (in repetitive manufacturing tasks)
10 Jobs AI Can’t Replace
Artists, writers, and other creative professionals
Therapists, counselors, and social workers
Teachers and educators
Nurses, doctors, and other healthcare professionals
Salespeople and customer service representatives
Managers and leaders
Scientists and researchers
Engineers and architects
Entrepreneurs and business owners
Skilled tradespeople (like electricians and plumbers)
READ MORE: The Future Landscape of AI in Business
The Benefits of AI in The Workplace
AI has been extensively implemented across various industries, with some sectors utilizing it more than others. Notably, the following industries have adopted AI to a greater extent:
Transportation
AI is used to find shorter transportation routes, minimize waiting time, and keep all available fleet drivers busy. The role of AI in transportation is predicted to grow in the next few years as companies such as Google and Tesla develop self-driving vehicles.
Healthcare
AI in healthcare automates repetitive tasks, giving doctors more time to help patients. By analyzing massive amounts of patient data, AI also helps improve the development of new drugs and treatments.
Marketing
AI in marketing tracks consumer habits makes predictions, and improves content creation. It can also track the interests of every individual user and present the correct type of content to increase sales and enhance the overall customer experience.
Finance
AI can analyze much more data than humans and make highly accurate predictions. As a result, AI is becoming an efficient financial advisor, as it can help thousands of customers with a one-time payment.
AI’s capability to swiftly analyze vast volumes of data makes it the most powerful method for investing and trading.
Entertainment
AI is used in the entertainment industry to provide personalized suggestions for individuals. Each individual’s preference is tracked, and AI further utilizes it to curate similar suggestions.
What Can AI Be Used For?
With AI’s shorter time to write codes and perform significant work, this innovation reduces the need for managerial talent. However, the requirement for workers to perform groundwork in lower parts of the organization remains integral.
While AI has many uses, one way to make the change smoother and minimize the negative result of this movement is by restructuring the education system to provide necessary skills to people entering the workforce and also provide means for re-skilling the existing force.
The education system should not focus on formal methods; instead, it should train students’ soft skills to adapt to the ever-changing world that requires constant learning and re-skilling. This way, the workforce can work alongside AI without worrying about their jobs being at stake.
Companies looking to explore this possibility and rearrange their workforce should contact InCorp Indonesia (an Ascentium Company) for HR & Recruitment. In addition, InCorp Indonesia also provides supplementary services with Employment Law Services.
Guide to Doing Business in Jakarta
Can Humans be Replaced by Artificial Intelligence?
The most anticipated question of the century is whether AI will replace humans. While AI may replace some jobs, it will also create new ones. Therefore, individuals and organizations need to adapt to the changing nature of work and develop new skills to thrive in the future.
The synergy between AI and human intelligence will be crucial, as leveraging both can enhance problem-solving, creativity, and innovation across industries.
However, the rise in the use of AI does not mean a replacement for humans but rather a tool that can enhance human capabilities and lead to greater productivity and innovation.
The collaboration between human-AI systems can drive advancements across various fields, blending human creativity and decision-making with AI’s efficiency and data processing power.
In conclusion, the workforce won’t be replaced; rather, there will be a collaboration between the two to increase organizations’ productivity.
| 2023-03-16T00:00:00 |
2023/03/16
|
https://www.cekindo.com/blog/will-ai-replace-humans
|
[
{
"date": "2025/06/21",
"position": 55,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/21",
"position": 47,
"query": "future of work AI"
},
{
"date": "2025/06/21",
"position": 99,
"query": "job automation statistics"
}
] |
Bosses want you to know AI is coming for your job
|
Bosses want you to know AI is coming for your job
|
https://illuminem.com
|
[
"Https",
"Illuminem.Com Illuminemvoicesprofile Illuminem-Briefings",
"About The Author"
] |
Top CEOs say AI will shrink their workforces — is it posturing or prescience?
|
illuminem summarises for you the essential news of the day. Read the full piece on The Washington Post or enjoy below:
🗞️ Driving the news: Top CEOs from major companies like Amazon, IBM, and JPMorgan Chase are warning employees about the growing threat of artificial intelligence (AI) to job security
• These executives predict that AI will not only transform but also reduce the workforce in certain sectors, from customer service to software development, urging workers to adapt to the upcoming disruptions
🔭 The context: Despite claims of AI-driven job losses, there is little evidence of widespread layoffs at present
• However, the technology is increasingly influencing job roles, particularly in fields such as computer programming and marketing, where AI tools are now commonplace
• CEOs are signaling their commitment to embracing AI while also managing the potential risks of significant workforce reductions, especially in a competitive tech market
🌍 Why it matters for the planet: AI’s role in reshaping labor markets will have a lasting impact on the economy, potentially displacing many workers while creating new opportunities in tech and automation
• The debate centers around whether AI will truly improve productivity or merely speed up existing job displacement
• While AI has the potential to increase efficiency, its long-term effects on global employment, income inequality, and economic growth remain uncertain
⏭️ What's next: As AI adoption accelerates, companies are likely to continue downsizing while integrating AI tools into their operations
• However, the full extent of AI's impact on job markets will depend on how quickly businesses adopt the technology and whether it leads to net job creation in new sectors or further disruption in traditional industries
• Economists predict that the next few years will be critical in understanding the technology's true effects on the labor force
💬 One quote: “You’re not going to lose your job to an AI, but you’re going to lose your job to someone who uses AI,” — Jensen Huang, CEO of Nvidia
📈 One stat: The percentage of U.S. employees using AI daily has doubled in the past year, reaching 8%, according to a Gallup poll
Click for more news covering the latest on corporate governance and green tech
| 2025-06-21T00:00:00 |
https://illuminem.com/illuminemvoices/bosses-want-you-to-know-ai-is-coming-for-your-job
|
[
{
"date": "2025/06/21",
"position": 74,
"query": "artificial intelligence employment"
}
] |
|
Conference | INMA Media Tech and AI Week 2025
|
INMA Media Tech and AI Week 2025
|
https://www.inma.org
|
[] |
The inaugural INMA Media & AI Conference at KQED in San Francisco will bring the fast-moving world of artificial intelligence and machine learning onto a ...
|
The inaugural INMA Media & AI Conference at KQED in San Francisco will bring the fast-moving world of artificial intelligence and machine learning onto a single stage – packaged for up-to-the-minute take-home practicalities.
Across a rapid-paced two days, INMA will boil down what news organisations need to know now about the disruption of search, the smart emergence of answer engines, and the AI-fueled rise of voice, tech, and video. INMA will pivot from analysis to action as we explore AI business efficiencies, producing more with less, and the value of content.
An underlying theme throughout the conference: A guide to platforms and partnerships for news organisations.
| 2025-06-21T00:00:00 |
https://www.inma.org/modules/event/2025MediaTechAIWeek/conference.html
|
[
{
"date": "2025/06/21",
"position": 71,
"query": "artificial intelligence journalism"
}
] |
|
Exa | Web Search API, AI Search Engine, & Website Crawler
|
Exa
|
https://exa.ai
|
[
"Exa Labs"
] |
Real-time AI search engine with web crawling API, SERP API, and deep research tools ... Find companies and people that fit hyper-specific criteria. Sales ...
|
Web Search API — LOW COMPUTE FAST
Fast, controllable, and accurate web search API powered by neural and keyword ranking. Get the most relevant URLs and their contents in milliseconds.
| 2025-06-22T00:00:00 |
https://exa.ai/
|
[
{
"date": "2025/06/22",
"position": 100,
"query": "AI employers"
}
] |
|
My AI exploration use for journalism experience
|
‘My AI exploration use for journalism experience’
|
https://mediacareerng.org
|
[
"Lekan Otufodunrin",
"Dayo Emmanuel",
"Media Career Development Network",
"Elizabeth Osayande",
"Kehinde Adegboyega",
"Justina Asishana",
"Abimbola Oluwakemi"
] |
Niger State Correspondent of The Nation, Justina Asishana who has been exploring the use of artificial intelligence for her editorial work shares her ...
|
Niger State Correspondent of The Nation, Justina Asishana who has been exploring the use of artificial intelligence for her editorial work shares her experience other journalists can learn from in this account shared below.
My AI exploration began two years ago when the usage of the tools was becoming well-known. Though at that time, I was not aware of Chat GPT and other generative AI tools, but for transcription, creation of animated videos and graphics, and editing my reports, I was able to use AI, and it worked well for me. Especially transcription, the hours I used to take in transcribing interviews were cut short, which was very helpful to me.
Then came the turnaround, which happened between last year and this year. So many tools came up. I discovered better transcription tools that could transcribe, and then you can interact with your transcription, looking for a better angle to tell your story.
Video editing got better as the tools I was using were upgraded to perform and edit better. Now, I can add captions to my videos without typing them word by word. My graphics tool, Canva, also got upgraded, and I could also edit videos, turn text to images, create talking heads, turn my texts into animated texts, and other features.
The video creation tool, Lumen5, included voice and got sleeker, while I discovered other video creation tools where I could turn text to videos like Video AI, Hydra, King AI, and others. And tools that can turn texts into images. Then, generative AI like ChatGPT and Gemini helped me fine-tune my writing.
I used to be very poor in writing headlines. I could write the whole story completely and struggle with coming up with appropriate headlines, but this has been solved. When I see myself struggling with headlines, I just copy my whole story and place it on Chat GPT and Gemini and ask them to generate the headlines for me, then I go through what was generated and select the one that fits my report best. Grammarly has helped my writing come out refined. I use it to edit my work as it suggests better phrases or words to use and indicates areas you need to put or remove punctuation marks or work on my Grammar. These tools have been very helpful.
I keep being amazed at the endless creativity one can achieve with these tools.
With my busy schedule, most people wonder how I get time to explore these tools, and I let them know that I use like an hour every night before I sleep to explore a tool. I learnt that if you can dedicate an hour every day to a skill or task, in a year, you would be knowledgeable in it, and that’s what I have been trying to do.
One thing we need to know about these tools is that you need to know how to write prompts well. Prompts are the keys to a good output you wish to get. Without an accurate prompt, these tools will give you anything. But using an explanatory prompt, you get exactly what you want. Also, giving these tools, especially the generative AI like Chat GPT and Gemini, a role will help you get the refined response that you need.
Another thing is that these tools are great to brainstorm with and if you give it a role to be a critical partner who has to critically analyse what you are suggesting, you will be surprised to see yourself arguing with a professor who will poke a lot of holes in your idea, and make you think critically too.
To help me keep abreast with new trends in the AI world, I follow a lot of people on TikTok and YouTube, where they teach how to use most of these tools and any new feature or tool that comes up. When I see anyone who interests me, I save them and practice them later. I have learnt so many things from these people and discovered several features that I didn’t know in the tools I use.
In all, I see using and exploring AI as having fun while learning on the way, and I wonder why some journalists are not yet utilizing what AI brings. I will say they are missing a lot.
| 2025-06-22T00:00:00 |
2025/06/22
|
https://mediacareerng.org/my-ai-exploration-use-for-journalism-experience/
|
[
{
"date": "2025/06/22",
"position": 48,
"query": "AI journalism"
}
] |
HKFP's commitment to human-powered journalism
|
HKFP & AI: Our commitment to human-powered journalism
|
https://hongkongfp.com
|
[] |
HKFP readers can always be assured that our output is the work of our dedicated journalists and freelancers. AI guidelines. The 2025 Reuters Institute Digital ...
|
Hong Kong Free Press is committed to remaining a human-powered newsroom in the AI era. Whilst others in the local news sector are experimenting, readers can be assured that none of HKFP’s news content has been – or will be – AI generated.
An AI tool cannot ask Hongkongers for reactions, pick up the phone, attend a court hearing or press event, keep sources safe, or understand the nuances of a rapidly-changing city and press freedom landscape. Quality journalism needs boots on the ground.
News stories written with generative AI have been proven to introduce undeclared errors or “hallucinated” content, as well as produce biased, outdated or plagiarised content.
Few AI tools include proper sourcing or attribution information, therefore HKFP does not, and will not, adopt generative AI for any news writing, news image generation or fact-checking.
HKFP readers can always be assured that our output is the work of our dedicated journalists and freelancers.
AI guidelines
The 2025 Reuters Institute Digital News Report also revealed scepticism among audiences when it comes to the use of AI in newsrooms. Only 19 per cent of those surveyed in the US, and just 15 per cent of Europeans, were comfortable with AI taking the lead in news production, even if it had some human oversight. According to the report, respondents accepted that AI could make news cheaper to produce, and more timely, but a significant proportion believed AI would have a detrimental effect on transparency, accuracy and trustworthiness.
Journalists in Hong Kong. File photo: GovHK.
Last year, we were among the first news outlets to adopt AI guidelines, adding a section to our Ethics Code which restricted its use to tasks such as transcription, research and translation assistance, summarisation and data crunching.
Read more about our commitment to accurate, fair and ethical journalism.
| 2025-06-20T00:00:00 |
2025/06/20
|
https://hongkongfp.com/hkfp-powered-by-humans-not-ai/
|
[
{
"date": "2025/06/22",
"position": 62,
"query": "AI journalism"
}
] |
Companies Introduce AI With the Threat of Layoffs
|
Companies Introduce AI With the Threat of Layoffs
|
https://sfg.media
|
[
"Sfg Media"
] |
CEOs of major companies are simultaneously alarming employees and pressuring them to embrace AI tools. On the one hand, they warn that new technologies will ...
|
Executives at major corporations are speaking more openly about integrating neural networks—and less inclined to hide the fact that this will mean job cuts. Gone are the reassuring forecasts, replaced by blunt warnings: either learn to work with AI or make way for the algorithm. This approach may seem pragmatic, but decades of management research suggest otherwise: fear rarely accelerates change. On the contrary—it fuels anxiety, erodes trust, and ultimately undermines the very transformation it’s meant to drive.
CEOs of major companies are simultaneously alarming employees and pressuring them to embrace AI tools. On the one hand, they warn that new technologies will render a significant portion of the workforce obsolete; on the other—they demand the immediate integration of neural networks into daily operations.
This contradictory messaging breeds unease. Managing through fear is a well-known but questionable tactic: at its extremes, it risks slowing down employees’ adaptation to AI rather than speeding it up.
In a recent statement, Amazon CEO Andy Jassy devoted fourteen paragraphs to the impressive potential of generative AI—and in the fifteenth, acknowledged that the transformation will "likely reduce the overall size of our corporate workforce." A similar tone came from JPMorgan’s head of consumer operations, who assured investors that AI would help cut staffing by 10% . Some companies have already cited "the impact of neural networks" to justify layoffs, while studies and surveys continue to forecast the disappearance of entire professions.
The reasons behind this harsh tone vary. Some leaders genuinely believe employees underestimate the scale of change. As consultant Brian Elliott notes, some prefer a "more balanced message"—for example, slowing hiring while encouraging colleagues to adopt AI more actively. Shopify CEO Tobi Lütke took this approach: in a letter to staff, he called the use of neural networks "the new normal" and required managers to prove that vacancies couldn’t be filled by algorithms before opening recruitment. Later, Lütke made this letter public.
Other top executives set the informational tone to appear candid and to soften the impact of upcoming layoffs. As Yale School of Management professor Jeffrey Sonnenfeld puts it, such warnings act like a "vaccine," reducing subsequent trauma.
There is also the motive of attracting investors: blunt statements signal to Wall Street that the company is "on trend," and the stock market traditionally welcomes cost-cutting. The "push" from AI vendors plays a role too—they need to free up resources for hardware and specialists, thus fueling the sense of inevitability around large-scale deployments.
However, decades of research show that managing through fear carries toxic consequences: creativity is stifled, teamwork suffers, and the risk of burnout rises. "Many employees think, ‘This is my future robot replacement. Why should I help train the tool that will take my job?’" observed U.S. Deputy Labor Secretary Keith Sonderling at a recent conference.
| 2025-06-22T00:00:00 |
https://sfg.media/en/a/companies-introduce-ai-with-the-threat-of-layoffs/
|
[
{
"date": "2025/06/22",
"position": 92,
"query": "AI layoffs"
}
] |
|
Half of today's jobs could vanish—Here's how smart ...
|
Half of today’s jobs could vanish—Here’s how smart countries are future-proofing workers
|
https://www.sciencedaily.com
|
[] |
AI is revolutionizing the job landscape, prompting nations worldwide to prepare their workforces for dramatic changes. A University of Georgia study ...
|
Artificial intelligence is spreading into many aspects of life, from communications and advertising to grading tests. But with the growth of AI comes a shake-up in the workplace.
New research from the University of Georgia is shedding light on how different countries are preparing for how AI will impact their workforces.
According to previous research, almost half of today's jobs could vanish over the next 20 years. But it's not all doom and gloom.
Researchers also estimate that 65% of current elementary school students will have jobs in the future that don't exist now. Most of these new careers will require advanced AI skills and knowledge.
"Human soft skills, such as creativity, collaboration and communication cannot be replaced by AI." -- Lehong Shi, College of Education
To tackle these challenges, governments around the world are taking steps to help their citizens gain the skills they'll need. The present study examined 50 countries' national AI strategies, focusing on policies for education and the workforce.
Learning what other countries are doing could help the U.S. improve its own plans for workforce preparation in the era of AI, the researcher said.
"AI skills and competencies are very important," said Lehong Shi, author of the study and an assistant research scientist at UGA's Mary Frances Early College of Education. "If you want to be competitive in other areas, it's very important to prepare employees to work with AI in the future."
Some countries put larger focus on training, education
Shi used six indicators to evaluate each country's prioritization on AI workforce training and education: the plan's objective, how goals will be reached, examples of projects, how success will be measured, how projects will be supported and the timelines for each project.
Each nation was classified as giving high, medium or low priority to prepare an AI competent workforce depending on how each aspect of their plan was detailed.
Of the countries studied, only 13 gave high prioritization to training the current workforce and improving AI education in schools. Eleven of those were European countries, with Mexico and Australia being the two exceptions. This may be because European nations tend to have more resources for training and cultures of lifelong learning, the researcher said.
The United States was one of 23 countries that considered workforce training and AI education a medium priority, with a less detailed plan compared to countries that saw them as a high priority.
Different countries prioritize different issues when it comes to AI preparation
Some common themes emerged between countries, even when their approaches to AI differed. For example, almost every nation aimed to establish or improve AI-focused programs in universities. Some also aimed to improve AI education for K-12 students.
On-the-job training was also a priority for more than half the countries, with some offering industry-specific training programs or internships. However, few focused on vulnerable populations such as the elderly or unemployed through programs to teach them basic AI skills.
Shi stressed that just because a country gives less prioritization to education and workforce preparation doesn't mean AI isn't on its radar. Some Asian countries, for example, put more effort into improving national security and health care rather than education.
Cultivating interest in AI could help students prepare for careers
Some countries took a lifelong approach to developing these specialized skills. Germany, for instance, emphasized creating a culture that encourages interest in AI. Spain started teaching kids AI-related skills as early as preschool.
Of the many actions governments took, Shi noted one area that needs more emphasis when preparing future AI-empowered workplaces. "Human soft skills, such as creativity, collaboration and communication cannot be replaced by AI," Shi said. "And they were only mentioned by a few countries."
Developing these sorts of "soft skills" is key to making sure students and employees continue to have a place in the workforce.
This study was published in Human Resource Development Review.
| 2025-06-25T00:00:00 |
2025/06/25
|
https://www.sciencedaily.com/releases/2025/06/250622030429.htm
|
[
{
"date": "2025/06/22",
"position": 97,
"query": "artificial intelligence employment"
}
] |
Will AI Replace Cybersecurity Jobs?
|
Will AI Replace Cybersecurity Jobs?
|
https://purplesec.us
|
[
"Tom Vazdar",
"Tom Is An Expert In Ai",
"Cybersecurity With Over Two Decades Of Experience. He Leads The Development Of Advanced Cybersecurity Strategies",
"Enhancing Data Protection",
"Compliance. Tom Currently Serves As The Chief Artificial Intelligence Officer At Purplesec."
] |
A 2023 Goldman Sachs report predicts that by 2030, generative AI will put about 300 million full-time jobs at risk of automation. That's a huge number, ...
|
A 2023 Goldman Sachs report predicts that by 2030, generative AI will put about 300 million full-time jobs at risk of automation.
That’s a huge number, and it’s got people asking:
Will AI replace cybersecurity jobs?
Take CrowdStrike’s move in May 2025—they cut 500 jobs to focus on AI-powered solutions.
Then there’s the Reddit post from March 2025 about an 80-person cybersecurity team being replaced by artificial intelligence after training it for two years.
Scary stuff, right?
But hold on—don’t hit the panic button yet.
| 2025-06-23T00:00:00 |
2025/06/23
|
https://purplesec.us/learn/ai-replacing-cybersecurity-jobs/
|
[
{
"date": "2025/06/22",
"position": 35,
"query": "job automation statistics"
}
] |
How AI Is Changing the Job Market Forever | Lifehack
|
How AI Is Changing the Job Market Forever
|
https://vocal.media
|
[] |
Data Entry AI software can now overlook and reuse documents briskly than any person. According to some studies, millions of jobs could be automated in the ...
|
Artificial Intelligence( AI) is no longer just a futuristic conception it’s formerly changing the world we live in. From voice sidekicks like Siri and Alexa to hurt robots in manufactories, AI is getting part of our everyday lives. One of the biggest areas where AI is making a huge impact is the job request. The way we work is changing. Some jobs are fading, others are changing, and entirely new places are being created. In this composition, we’ll explore how AI is transubstantiating the job request ever, the challenges it brings, and how workers can prepare for the future.
--- 1. What Is Artificial Intelligence? Before we dive into its goods, let’s snappily explain what AI is. Artificial Intelligence is the capability of machines to perform tasks that typically bear mortal intelligence. This includes effects like understanding language, feting images, working problems, and learning from data. AI systems use complex algorithms and massive quantities of data to make opinions, frequently briskly and more directly than humans. This makes them precious in numerous diligence, from healthcare and finance to transportation and retail.
--- 2. Jobs at Risk The Rise of robotization One of the biggest enterprises about AI is robotization. This means using machines or software to perform tasks that were formerly done by people. numerous routine and repetitious jobs are now being automated. exemplifications of jobs affected by robotization Manufacturing Robots are erecting buses and electronics briskly than mortal workers. Retail Self- checkout systems are replacing cashiers in stores. client Service Chatbots are answering questions and working issues without a mortal agent. Data Entry AI software can now overlook and reuse documents briskly than any person. According to some studies, millions of jobs could be automated in the coming decade. This does n’t mean all jobs will vanish, but numerous will change or move to different sectors.
--- 3. AI Is Also Creating New Jobs While AI can replace some jobs, it also creates numerous new openings. In fact, AI is helping produce a new kind of pool — one that works with AI rather of being replaced by it. exemplifications of new and growing job places AI Specialists and Data Scientists People who make and train AI systems. Machine Learning masterminds inventors who design systems that learn from data. AI Ethicists Experts who insure AI is used fairly and responsibly. Cybersecurity Judges guarding systems and data from pitfalls is more important than ever. Robotics Technicians Skilled workers who maintain and repair automated machines. Indeed in fields like marketing, design, education, and healthcare, AI tools are creating new ways of working and adding productivity.
--- 4. Changing Chops What Workers Need to Know As AI becomes more common, the chops demanded to succeed in the job request are changing. Workers must be ready to acclimatize and learn new effects. crucial chops for the AI- driven world Digital knowledge Knowing how to use computers, apps, and digital tools. Problem working Being suitable to suppose critically and break new challenges. Creativity Coming up with new ideas and working with AI in creative ways. Emotional Intelligence Chops like empathy and communication are still hard for AI to replicate. Lifelong literacy The capability to keep learning and reskilling throughout your career. Governments, seminaries, and companies must work together to help workers learn these chops through education and training programs.
--- 5. diligence Being converted by AI Let’s look at how AI is transubstantiating different diligence Healthcare AI helps croakers descry conditions briskly, develop new treatments, and indeed perform surgeries with the help of robotic tools. executive tasks are also being automated, letting healthcare workers concentrate more on cases. Finance Banks and fiscal companies use AI to descry fraud, assess loan pitfalls, and automate trading. AI helps give faster, more individualized service to guests. Transportation tone- driving buses and delivery drones are being tested across the world. AI helps optimize business, delivery routes, and line operation. Education AI tools are helping preceptors epitomize assignments for scholars, automate grading, and ameliorate learning through interactive apps and platforms. Retail andE-commerce AI recommends products, manages force, and predicts client geste . individualized shopping gests are powered by data and smart systems.
--- 6. Challenges and enterprises While AI brings numerous benefits, there are also some real challenges we need to address Job relegation numerous people worry about losing their jobs due to robotization. Inequality Not everyone has the same access to digital tools or education. Bias in AI If not designed precisely, AI systems can make illegal or prejudiced opinions. sequestration Issues AI systems collect large quantities of particular data, which must be defended. Governments and companies must produce programs to manage these issues and insure a fair transition to an AI- powered world.
--- 7. How to Prepare for the AI Future The stylish way to face the future is to be visionary. Then’s how workers can get ready for the changes AI is bringing Stay Curious Keep learning about technology and how it affects your field. Take Online Courses Platforms like Coursera, Udemy, and LinkedIn Learning offer affordable training. Get Hands- On Try using AI tools or apps in your diurnal work to make confidence. Network Connect with others in your assiduity to partake knowledge and stay streamlined. Stay Flexible Be open to changing places or learning new chops as the request evolves.
--- Conclusion A New Era of Work AI is changing the job request ever but it does n’t have to be commodity to sweat. Like once technological revolutions, it brings both challenges and openings. While some jobs will be lost or converted, numerous further can be created. The key to success in the AI period is rigidity. By learning new chops, staying informed, and working with AI rather than against it, people can make meaningful careers in a changing world.
| 2025-06-22T00:00:00 |
https://vocal.media/lifehack/how-ai-is-changing-the-job-market-forever
|
[
{
"date": "2025/06/22",
"position": 94,
"query": "job automation statistics"
}
] |
|
Is AI changing or threatening to take your job? Tell us about it here
|
Is AI changing or threatening to take your job? Tell us about it here
|
https://www.cnn.com
|
[
"Clare Duffy"
] |
And last week, Amazon CEO Andy Jassy told his employees that AI agents would reduce the company's workforce in the near future. Those comments ...
|
New York CNN —
Some of Silicon Valley’s top leaders have warned in recent weeks that artificial intelligence is coming for people’s jobs — and fast.
Anthropic CEO Dario Amodei warned last month that AI could cause as much as 20% unemployment in the next one to five years. And last week, Amazon CEO Andy Jassy told his employees that AI agents would reduce the company’s workforce in the near future.
Those comments have made it a stressful and uncertain time for human workers. But experts are split on just how quickly and drastically AI will upend the job market. Some skeptics believe these warnings are largely marketing hype from executives trying to sell a product.
So, we want to hear from you. Is AI already changing the way you work, or taking over tasks at your company? If you’ve adopted AI at work, is it making you more productive? And as you think about the future of your career, is AI making you excited, anxious or a bit of both?
Tell us about it in the form below, and please leave your contact information. No named commentary will be used without following up with you, and we can discuss providing anonymity if you’re concerned about speaking on the record about work.
| 2025-06-23T00:00:00 |
2025/06/23
|
https://www.cnn.com/2025/06/23/tech/ai-impact-on-jobs-callout
|
[
{
"date": "2025/06/23",
"position": 89,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/23",
"position": 84,
"query": "AI employment"
},
{
"date": "2025/06/23",
"position": 57,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 86,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/23",
"position": 91,
"query": "AI employment"
},
{
"date": "2025/06/23",
"position": 62,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 85,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/23",
"position": 72,
"query": "AI replacing workers"
},
{
"date": "2025/06/23",
"position": 54,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 72,
"query": "AI replacing workers"
},
{
"date": "2025/06/23",
"position": 72,
"query": "AI replacing workers"
},
{
"date": "2025/06/23",
"position": 87,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/23",
"position": 92,
"query": "AI employment"
},
{
"date": "2025/06/23",
"position": 79,
"query": "AI replacing workers"
},
{
"date": "2025/06/23",
"position": 60,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 94,
"query": "AI employment"
},
{
"date": "2025/06/23",
"position": 58,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 77,
"query": "AI replacing workers"
},
{
"date": "2025/06/23",
"position": 9,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 77,
"query": "AI replacing workers"
},
{
"date": "2025/06/23",
"position": 86,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/23",
"position": 78,
"query": "AI replacing workers"
},
{
"date": "2025/06/23",
"position": 87,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/23",
"position": 54,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 78,
"query": "AI replacing workers"
},
{
"date": "2025/06/23",
"position": 88,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/23",
"position": 57,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 75,
"query": "AI replacing workers"
},
{
"date": "2025/06/23",
"position": 75,
"query": "AI employment"
},
{
"date": "2025/06/23",
"position": 22,
"query": "AI replacing workers"
},
{
"date": "2025/06/23",
"position": 56,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 64,
"query": "AI replacing workers"
},
{
"date": "2025/06/23",
"position": 76,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/23",
"position": 73,
"query": "AI replacing workers"
},
{
"date": "2025/06/23",
"position": 89,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/23",
"position": 53,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 72,
"query": "AI replacing workers"
},
{
"date": "2025/06/23",
"position": 51,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 77,
"query": "AI replacing workers"
},
{
"date": "2025/06/23",
"position": 76,
"query": "AI replacing workers"
},
{
"date": "2025/06/23",
"position": 80,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/23",
"position": 96,
"query": "AI employment"
},
{
"date": "2025/06/23",
"position": 76,
"query": "AI replacing workers"
},
{
"date": "2025/06/23",
"position": 56,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 86,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/23",
"position": 56,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 68,
"query": "AI replacing workers"
},
{
"date": "2025/06/23",
"position": 85,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/23",
"position": 99,
"query": "AI employment"
},
{
"date": "2025/06/23",
"position": 58,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 76,
"query": "AI replacing workers"
},
{
"date": "2025/06/23",
"position": 85,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/23",
"position": 59,
"query": "AI replacing workers"
},
{
"date": "2025/06/23",
"position": 74,
"query": "AI replacing workers"
},
{
"date": "2025/06/23",
"position": 79,
"query": "AI impact jobs"
}
] |
AI's impact on the job market is 'inevitable,' says workforce expert
|
AI's impact on the job market is ‘inevitable,’ says workforce expert: 'It's going to hurt for certain parts of the population'
|
https://www.cnbc.com
|
[
"Sophie Caldwell"
] |
Earlier this year, a World Economic Forum report found that 48% of U.S. employers plan to reduce their workforce because of AI. While not all ...
|
For those concerned about AI's impact on the job market, Amazon CEO Andy Jassy's recent announcement may add even more fuel to the fire.
In a memo to Amazon employees on June 17, Jassy shared that the company plans to cut down their corporate workforce in the next few years due to "efficiency gains" from using AI.
"As we roll out more Generative AI and agents, it should change the way our work is done," Jassy wrote. "We will need fewer people doing some of the jobs that are being done today, and more people doing other types of jobs."
Earlier this year, a World Economic Forum report found that 48% of U.S. employers plan to reduce their workforce because of AI.
While not all recent job cuts have been directly linked to AI, several other major tech companies are also looking to reduce their headcount: in May, Microsoft announced that they plan to cut 3% of their workforce, and Google recently offered another round of buyouts through their "voluntary exit program" to employees across the company.
Klarna has reduced its workforce by about 40% due to AI, CEO Sebastian Siemiatkowski told CNBC in May, and Shopify CEO Tobi Lütke told employees in an April memo that they can't make new hires unless they can prove artificial intelligence isn't capable of doing the job.
Here's what AI gains could mean for the job market, according to an expert.
| 2025-06-23T00:00:00 |
2025/06/23
|
https://www.cnbc.com/2025/06/23/ais-impact-on-the-job-market-is-inevitable-says-workforce-expert.html
|
[
{
"date": "2025/06/23",
"position": 62,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 63,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 61,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 66,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 64,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 13,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 53,
"query": "AI job losses"
},
{
"date": "2025/06/23",
"position": 63,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 6,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 39,
"query": "AI job losses"
},
{
"date": "2025/06/23",
"position": 64,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 9,
"query": "AI job losses"
},
{
"date": "2025/06/23",
"position": 63,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 66,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 64,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 69,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 7,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 72,
"query": "artificial intelligence layoffs"
},
{
"date": "2025/06/23",
"position": 58,
"query": "generative AI jobs"
},
{
"date": "2025/06/23",
"position": 70,
"query": "artificial intelligence layoffs"
},
{
"date": "2025/06/23",
"position": 57,
"query": "generative AI jobs"
},
{
"date": "2025/06/23",
"position": 85,
"query": "artificial intelligence layoffs"
},
{
"date": "2025/06/23",
"position": 59,
"query": "generative AI jobs"
},
{
"date": "2025/06/23",
"position": 10,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 9,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 72,
"query": "artificial intelligence layoffs"
},
{
"date": "2025/06/23",
"position": 57,
"query": "generative AI jobs"
}
] |
Will AI create or take over jobs? Here's what AI leaders are saying.
|
Will AI Create or Replace Jobs? Here's What AI Leaders Say.
|
https://www.businessinsider.com
|
[
"Jack Sommers",
"Robert Scammell"
] |
Tech leaders are divided on AI's job impact, with some concerned it'll take over jobs and spike unemployment, and others saying it'll create ...
|
Jensen Huang said he disagreed with Dario Amodei's view on how AI would impact jobs.
Jensen Huang said he disagreed with Dario Amodei's view on how AI would impact jobs. JULIEN DE ROSA/AFP via Getty Images / Chesnot/Getty Images / Justin Sullivan/Getty Images
Jensen Huang said he disagreed with Dario Amodei's view on how AI would impact jobs. JULIEN DE ROSA/AFP via Getty Images / Chesnot/Getty Images / Justin Sullivan/Getty Images
This story is available exclusively to Business Insider subscribers. Become an Insider and start reading now.
AI leaders are split on whether AI will take over jobs or create new roles that mitigate disruption.
It's a long-running debate — but one that has been heating up in recent months. While tech leaders seem to agree that AI is shaking up jobs, they are divided over timelines and scale.
From Jensen Huang to Sam Altman, here is what some of the biggest names in tech are saying about how AI will impact jobs.
| 2025-06-23T00:00:00 |
https://www.businessinsider.com/will-ai-replace-take-over-create-jobs-debate-tech-leaders-2025-6
|
[
{
"date": "2025/06/23",
"position": 89,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 97,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 88,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 71,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 94,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 93,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 93,
"query": "AI impact jobs"
},
{
"date": "2025/06/23",
"position": 56,
"query": "AI impact jobs"
}
] |
|
Employers Are Buried in A.I.-Generated Résumés
|
Employers Are Buried in A.I.-Generated Résumés
|
https://www.nytimes.com
|
[
"Sarah Kessler"
] |
... hiring time by 75 percent. HireVue, a popular A.I. video interview platform, offers recruiters an option to have A.I. assess responses and ...
|
We invited Anderson to discuss how D.S.O. is playing out, two years in, with Aimee Groth, an expert in decentralized organizations. Groth documented Zappos’s effort to flatten its org chart in her 2017 book, “The Kingdom of Happiness,” and has been following the movement ever since, including briefly as a consultant. Their conversation has been edited and condensed.
Groth: Many large companies are flattening hierarchies to cut costs. Bayer aims to save over $2 billion by 2026. What makes this more than just an efficiency play?
Anderson: Most corporate change programs take out heads but not the work. That’s why companies end up doing them every few years. They eliminate a layer — usually just one — and leave everything else the same. People are back two years later because the work still has to get done.
What we’re doing is taking out five layers of management. But that’s just surface-level stuff. We’re also replacing things like the annual budget process. Instead of spending three to five months a year doing this big bureaucratic exercise, people now spend one day every 90 days asking: How did we do in the last 90? What are the most important objectives for the next 90? Do we have the right team? Do we need to add or move people? Then we work for 89 days and do it again. That’s one reason we call it Dynamic Shared Ownership — every 90 days, 10 to 15 percent of people shift what they’re doing.
What’s working so far? Any examples that stand out?
In contraception, we had lost the business of one of the largest health care providers in the world. The local team said: “We’ve got to win it back.” They made all the resource and structural decisions — brought in a contract reimbursement specialist, added a medical liaison to speak with academic medical centers. None of it went through any management layers. Aside from compliance, all those decisions happened at the edge. In most companies, those decisions would go up 10 layers.
| 2025-06-21T00:00:00 |
2025/06/21
|
https://www.nytimes.com/2025/06/21/business/dealbook/ai-job-applications.html
|
[
{
"date": "2025/06/23",
"position": 87,
"query": "AI hiring"
},
{
"date": "2025/06/23",
"position": 4,
"query": "artificial intelligence employers"
},
{
"date": "2025/06/23",
"position": 87,
"query": "AI hiring"
},
{
"date": "2025/06/23",
"position": 88,
"query": "AI hiring"
},
{
"date": "2025/06/23",
"position": 2,
"query": "artificial intelligence employers"
},
{
"date": "2025/06/23",
"position": 60,
"query": "AI hiring"
},
{
"date": "2025/06/23",
"position": 65,
"query": "AI hiring"
},
{
"date": "2025/06/23",
"position": 3,
"query": "AI employers"
},
{
"date": "2025/06/23",
"position": 65,
"query": "AI hiring"
},
{
"date": "2025/06/23",
"position": 4,
"query": "artificial intelligence employers"
}
] |
Rethinking AI in journalism with global cooperation
|
Rethinking AI in journalism with global cooperation
|
https://dig.watch
|
[] |
As AI rapidly transforms journalism, a diverse group of global experts and grassroots voices came together in Norway to rethink how media ...
|
23 Jun 2025
Rethinking AI in journalism with global cooperation
At the Internet Governance Forum 2025 in Lillestrøm, Norway, a vibrant multistakeholder session spotlighted the ethical dilemmas of AI in journalism and digital content. The event was hosted by R&W Media and introduced the Haarlem Declaration, a global initiative to promote responsible AI practices in digital media.
Central to the discussion was unveiling an ‘ethical AI checklist,’ designed to help organisations uphold human rights, transparency, and environmental responsibility while navigating AI’s expanding role in content creation. Speakers emphasised a people-centred approach to AI, advocating for tools that support rather than replace human decision-making.
Ernst Noorman, the Dutch Ambassador for Cyber Affairs, called for AI policies rooted in international human rights law, highlighting Europe’s Digital Services and AI Acts as potential models. Meanwhile, grassroots organisations from the Global South shared real-world challenges, including algorithmic bias, language exclusions, and environmental impacts.
Taysir Mathlouthi of Hamleh detailed efforts to build localised AI models in Arabic and Hebrew, while Nepal’s Yuva organisation, represented by Sanskriti Panday, explained how small NGOs balance ethical use of generative tools like ChatGPT with limited resources. The Global Forum for Media Development’s Laura Becana Ball introduced the Journalism Cloud Alliance, a collective aimed at making AI tools more accessible and affordable for newsrooms.
Despite enthusiasm, participants acknowledged hurdles such as checklist fatigue, lack of capacity, and the need for AI literacy training. Still, there was a shared sense of urgency and optimism, with the consensus that ethical frameworks must be embedded from the outset of AI development and not bolted on as an afterthought.
In closing, organisers invited civil society and media groups to endorse the Harlem Declaration and co-create practical tools for ethical AI governance. While challenges remain, the forum set a clear agenda: ethical AI in media must be inclusive, accountable, and co-designed by those most affected by its implementation.
Track all key moments from the Internet Governance Forum 2025 on our dedicated IGF page.
| 2025-06-23T00:00:00 |
2025/06/23
|
https://dig.watch/updates/rethinking-ai-in-journalism-with-global-cooperation
|
[
{
"date": "2025/06/23",
"position": 54,
"query": "AI journalism"
},
{
"date": "2025/06/23",
"position": 52,
"query": "AI journalism"
},
{
"date": "2025/06/23",
"position": 52,
"query": "AI journalism"
},
{
"date": "2025/06/23",
"position": 51,
"query": "AI journalism"
},
{
"date": "2025/06/23",
"position": 54,
"query": "AI journalism"
},
{
"date": "2025/06/23",
"position": 52,
"query": "AI journalism"
},
{
"date": "2025/06/23",
"position": 52,
"query": "AI journalism"
},
{
"date": "2025/06/23",
"position": 52,
"query": "AI journalism"
},
{
"date": "2025/06/23",
"position": 56,
"query": "AI journalism"
},
{
"date": "2025/06/23",
"position": 54,
"query": "AI journalism"
},
{
"date": "2025/06/23",
"position": 52,
"query": "AI journalism"
},
{
"date": "2025/06/23",
"position": 56,
"query": "AI journalism"
}
] |
ADM-143 Use of Artificial Intelligence Policy - Lebanon, NH
|
ADM-143 Use of Artificial Intelligence Policy
|
https://lebanonnh.gov
|
[
"Government Websites"
] |
ADM-143 Use of Artificial Intelligence · 4.1 Transparency and Accountability. City employees must be transparent and accountable when using AI ...
|
3.1 Algorithmic Discrimination occurs when automated systems contribute to unjustified different treatment or impacts disfavoring people based on their race, skin color, national or ethnic origin, cultural group, language, gender identity or expression, sexual orientation, mental or physical ability, age, religious or political opinion or activity, economic status, immigration status, or housing status.
3.2 Artificial Intelligence (AI) is a type of computer science which deals with computer systems that perform tasks which usually require human intelligence, such as reasoning, problem solving, perception, and language.
3.3 Bing AI is AI software that allows individuals to chat with an intelligent chatbot and generate various types of content. Bing AI is part of Microsoft’s search engine.
3.4 Chatbot is AI software that seeks to mimic human conversation through interactions via text or voice.
3.5 ChatGPT stands for Chat Generative Pre-trained Transformer. It is a complex machine learning model that is able to carry out natural language generation (NLG) tasks with such a high level of accuracy that the model can pass a Turing Test. It is based on the "GPT (Generative Pre-training Transformer) architecture, which is a type of neural network designed for natural language processing tasks.” ChatGPT is an AI chatbot that uses natural language processing to create humanlike conversational dialogue. The language model can respond to questions and compose various written content, including articles, social media posts, essays, code and emails. ChatGPT-3, ChatGPT-3.5, and ChatGPT-4 are the current models available to the public to use.
3.6 Generative AI uses both computer algorithms and large volumes of data to create new content, such as audio, code, images, and videos.
3.7 Sensitive Data or Personally Identifying Information (PII) (as defined in ADM-450 Securing Sensitive Information) is information that is private and must be protected.
3.8 Technology Review Committee (TRC) – This committee consists of the Cyber Services Director, Chief Innovation Officer, and Asset Manager. The committee works across all departments to review and audit any technology, including but not limited to software, technology, and AI.
| 2025-06-23T00:00:00 |
https://lebanonnh.gov/1737/AI-Policy
|
[
{
"date": "2025/06/23",
"position": 72,
"query": "government AI workforce policy"
},
{
"date": "2025/06/23",
"position": 70,
"query": "government AI workforce policy"
},
{
"date": "2025/06/23",
"position": 94,
"query": "government AI workforce policy"
}
] |
|
Gen Z job ladder isn't breaking because of AI—but it's evolving, says ...
|
Gen Z job ladder isn’t breaking because of AI—but it’s evolving, says LinkedIn COO Dan Shapero
|
https://fortune.com
|
[
"Massimo Marioni"
] |
With generative AI rewiring how work gets done, the future of entry-level employment hangs in the balance. But Dan Shapero, chief operating ...
|
With generative AI rewiring how work gets done, the future of entry-level employment hangs in the balance. But Dan Shapero, chief operating officer at LinkedIn, isn’t ready to declare the bottom rung of the career ladder broken—at least not yet.
“Navigating the transition to an AI economy is probably going to be the issue of the next decade,” Shapero told Fortune in a recent conversation at Cannes Lions. “Not just for companies, but for individuals.”
Shapero acknowledges that there are already anecdotal signs that finding that all-important first job out of college is becoming tougher, as noted by his colleague and LinkedIn’s chief economic opportunity officer, Aneesh Raman, in a recent op-ed for the New York Times.
But unlike previous waves of technology that tended to target specific functions or industries, AI is “a very pervasive shift in how the world of work is happening,” he said.
Rather than eliminating jobs wholesale, Shapero sees the nature of entry-level work evolving.
“I remember when I was at Bain, a lot of the time I spent was making slides and going to the library to figure out research reports. All of that is now automated,” he said.
“Bain still hires scores of recent graduates. They just do different parts of the process.
“If you talk to the partners and ask them what they did when they first joined, they were cutting out squares with a scalpel to make slides on a piece of colored paper because PowerPoint didn’t exist then.”
One of the most significant changes Shapero anticipates in the job market over the next five years is the rise of AI fluency as a core hiring attribute.
“If you talk to companies trying to deploy AI, they’ll talk about how varied the adoption is,” he said. “You’ll have some people using it all day long and others that are slowing down the process because they’re concerned about what it might mean for them.”
Job candidates, he predicts, will increasingly be asked to prove they’re comfortable with AI—not just as users, but as agents of change.
“There’s going to be a lot of pressure to build AI into your operating model, and the bottleneck is unlikely to be the tech,” Shapero said. “The bottleneck is going to be how you teach people how to do it. That’s a talent challenge, not a tech challenge.”
Internally, LinkedIn talks about hiring for “AI fluency and agency”—the former being the ability to use the tools, and the latter being the initiative to find new solutions rather than relying strictly on prescribed processes.
Changing the game in recruitment
LinkedIn itself is leaning into AI to transform the machinery of recruitment.
Shapero described a vision of recruiting where AI handles the repetitive work—generating job specs, matching candidate skills, screening for eligibility—and recruiters focus on the human elements: persuasion, relationship-building, and judgment.
“If you map out what a recruiter does, half the week is automatable tasks that are also the things they like the least,” he said. “The other half is time with candidates. We hear from recruiters: automate what can be automated, and let me focus on the human part.”
LinkedIn’s new “Hiring Assistant,” rolled out to recruiters and early corporate customers last fall, automates much of that front-end process.
“They’re seeing candidates they wouldn’t have seen otherwise,” Shapero noted, pointing out that AI can broaden rather than narrow talent pools. “Every recruiter has habitual search criteria. They exclude a whole bunch of candidates who might actually be a great fit.”
In other words, AI may be more inclusive than the humans it augments.
A hybrid future
Still, none of this automation spells the end of human judgment. If anything, it makes it more valuable. “The right endpoint will be more tech and more human,” Shapero said. “But we’re still a long way from that place.”
Even as AI rewires hiring and flattens the traditional career path, Shapero remains optimistic that people will adapt—if they’re willing to keep learning.
“You don’t necessarily need to be the one that invents the new way to do something,” he said. “But you do need to be aware of what others are doing, what the best practices are, and then be comfortable changing your habits.”
| 2025-06-23T00:00:00 |
2025/06/23
|
https://fortune.com/2025/06/23/linkedin-dan-shapero-job-ladder-ai-gen-z-recruitment/
|
[
{
"date": "2025/06/23",
"position": 92,
"query": "generative AI jobs"
},
{
"date": "2025/06/23",
"position": 88,
"query": "generative AI jobs"
},
{
"date": "2025/06/23",
"position": 89,
"query": "generative AI jobs"
},
{
"date": "2025/06/23",
"position": 93,
"query": "generative AI jobs"
},
{
"date": "2025/06/23",
"position": 93,
"query": "generative AI jobs"
},
{
"date": "2025/06/23",
"position": 94,
"query": "generative AI jobs"
},
{
"date": "2025/06/23",
"position": 94,
"query": "generative AI jobs"
},
{
"date": "2025/06/23",
"position": 89,
"query": "generative AI jobs"
},
{
"date": "2025/06/23",
"position": 97,
"query": "generative AI jobs"
}
] |
AI Will Likely Increase Hiring, Tech Leaders Say - Business Insider
|
AI Will Likely Increase Hiring, Tech Leaders Say
|
https://www.businessinsider.com
|
[
"Tim Paradis"
] |
In a recent survey, nearly seven in 10 tech leaders said they planned to increase the number of people on their teams because of the expansion ...
|
Nearly seven in 10 tech leaders said in a survey that they expect to add to their teams because of generative AI.
Nearly seven in 10 tech leaders said in a survey that they expect to add to their teams because of generative AI. Cravetiger/Getty Images
Nearly seven in 10 tech leaders said in a survey that they expect to add to their teams because of generative AI. Cravetiger/Getty Images
This story is available exclusively to Business Insider subscribers. Become an Insider and start reading now.
Tech workers, take heart — artificial intelligence might actually be good for your job prospects.
In a recent survey, nearly seven in 10 tech leaders said they planned to increase the number of people on their teams because of the expansion of generative AI.
The possibility of increased demand for tech talent is welcome news after years of industry layoffs and following recent comments from high-profile tech CEOs, including Amazon's Andy Jassy, who warn that AI is coming for some jobs.
The newly released findings from Deloitte are based on a March survey of some 600 chief information officers, CTOs, and other tech leaders. In it, 69% of tech leaders said they planned to boost their team's size because of GenAI.
Such plans are a sign that many leaders are going to step back and think about the expertise they'll need as AI makes rapid advances in its capabilities, Anjali Shaikh, a managing director at Deloitte, told Business Insider.
She said that will mean, among other things, asking what types of skills will be needed as AI takes on more work.
Other questions will include how roles might evolve to incorporate AI. For example, people working in cybersecurity could see their day-to-day activities change as AI absorbs more duties related to fortifying digital infrastructure.
Beyond that, Shaikh said, many new roles are likely to combine technical chops with so-called soft skills.
Workers, build your skills
The prospect of a workplace crowded with tech like GenAI and AI agents — autonomous software programs — has, at times, raised uncomfortable questions about how many human employees will still be needed. That's particularly true with desk jobs that are likely easier to automate than the work of a plumber or an electrician.
More CEOs are talking about the possible fallout. OpenAI chief Sam Altman said this month that AI was already producing work similar to that of junior employees. Salesforce CEO Marc Benioff has said he tells fellow chief executives that future generations of leaders will oversee both people and agents.
Related stories Business Insider tells the innovative stories you want to know Business Insider tells the innovative stories you want to know
Getting or keeping a job in tech as AI takes on a bigger role within organizations isn't guaranteed, of course. In many cases, people will need to build their skills in order to remain competitive.
That's a point that Amazon's Jassy and other leaders have been making as they've implored workers to level up their AI abilities to avoid risking obsolescence. Jassy said that while AI will take over some jobs, the technology will likely lead to the addition of other roles — an idea echoed in the results of the Deloitte survey.
For many, experimentation is key
Shaikh said the takeaway for most workers is to learn AI and what it can and can't do. She said technical skills might be needed in some cases, though Shaikh doesn't think most workers need to get hung up on that.
"The experimentation, the understanding of what the technology can and cannot do, is probably most fundamental," she said.
Shaikh said that as AI becomes more self-sustaining within organizations, there will be a greater need for human skills to propel adoption further and maximize the technology.
She said that means workers will often need to deploy their most human abilities: empathy, emotional intelligence, and curiosity. They'll also need to rely on critical thinking, problem solving, logical reasoning, and written and verbal communication, Shaikh said.
"You're going to need people who understand how to use it," she said. "That's going to require some of those human skills."
| 2025-06-23T00:00:00 |
https://www.businessinsider.com/tech-leaders-genai-increased-hiring-teams-2025-6
|
[
{
"date": "2025/06/23",
"position": 94,
"query": "AI hiring"
},
{
"date": "2025/06/23",
"position": 96,
"query": "AI hiring"
},
{
"date": "2025/06/23",
"position": 95,
"query": "AI hiring"
},
{
"date": "2025/06/23",
"position": 94,
"query": "AI hiring"
},
{
"date": "2025/06/23",
"position": 92,
"query": "AI hiring"
}
] |
|
New Collaborative Aims to Tackle Questions About AI in ...
|
New Collaborative Aims to Tackle Questions About AI in Education
|
https://www.everylearnereverywhere.org
|
[
"Emilie Cook",
"Author",
"Trisha Turner"
] |
The Intentional Futures (iF) AI Education Collaborative will gather education and technology professionals in research, development, and funding.
|
A new initiative from Intentional Futures will facilitate conversation toward thoughtful responses to emerging questions about using artificial intelligence (AI) in education.
The Intentional Futures (iF) AI Education Collaborative will gather education and technology professionals in research, development, and funding. Alison Gazarek, iF’s Principal, Education, says the goal of the collaborative is to find common solutions and guiding principles for the innovative development, guidance, and use of AI in education.
“This is an incredible opportunity, especially at the pace with which AI is developing, to pause and ask how we are using this moment to really ensure we are re-envisioning what teaching and learning could and should be,” she says. “This technology has the potential to revolutionize what’s possible.”
The collaborative originated from the realization that in the many conversations about AI the iF team has had with its partners, they are seeking answers to a similar set of questions. The lack of alignment around ways forward revealed the need for a project that brought together a variety of voices. So iF, an Every Learner Everywhere network partner, is convening groups to consider common questions and to inform procedures and policies.
Beginning in mid-summer 2025, the AI Education Collaborative will convene in online sessions to explore questions such as:
Are we building AI systems that merely digitize our broken educational models?
Who benefits from AI in education — students, or the companies that design these systems?
How do we redistribute intellectual and financial capital from tech developers to the young people we serve?
What radical educational futures might we create with AI that currently seem impossible?
How can tech developers and policymakers embrace their responsibility to build ethical systems from the start?
Sharing insight
Although iF works with partners in strategy, education technology, and design, its role in the AI Education Collaborative is convenor and facilitator. It isn’t developing predetermined answers, and it will be up to participants to find common solutions.
“These groups will start investigating some of these questions, to ask whether they’re digitizing what currently exists or innovating for what’s possible,” Gazarek says.
While discussion will begin with small groups, the collaborative also will offer public presentations with panels that bring in insight from educators, funders, developers, and attendees. These will emphasize AI’s potential for education at large, on students, and on those who work with them.
The AI Education Collaborative also will include a quarterly call for additional input from the wider education community.
The result, according to iF’s plans for the project, will be a set of guiding principles for using AI in education and a call to action for implementing them.
Building momentum
Gazarek hopes these efforts represent just one phase of the AI Education Collaborative’s efforts, with no set end to its work. Building on the momentum of the discussions, the initiative could take on additional programs. These might include:
Hosting convenings centered around key questions
Producing reports with insights and recommended solutions
Assembling a community of practice
Leading new programs or pilots
“There will always be ways to better leverage AI for students,” she says. “Could we leverage a couple of really specific innovative pathways, and then, in a year or two, come back and say, ‘We found a solution for that’? This is the kind of work our partners are asking for.”
Offering guidance
These plans for addressing AI in education build on existing services from iF:
AI readiness and opportunity assessments: Identifying an organization’s strengths, gaps, and potential use cases for AI
Identifying an organization’s strengths, gaps, and potential use cases for AI Mission-aligned AI strategy sprints: Defining a guiding vision, ethical guardrails, and a practical roadmap for adoption
Defining a guiding vision, ethical guardrails, and a practical roadmap for adoption Future-of-AI briefings and market landscapes: Understanding where the field is headed and how an organization can lead
Understanding where the field is headed and how an organization can lead Tech-enabled futures: Exploring future potential through demos or user journeys of existing AI and edtech tools that draw on the right vision, investment, or design decisions
Exploring future potential through demos or user journeys of existing AI and edtech tools that draw on the right vision, investment, or design decisions Responsible AI rubrics and frameworks: Developing decision-making tools to guide ethical and impactful AI use
Gazarek, a former teacher herself, says she’s particularly excited about the ideas and guidance the AI Education Collaborative will produce.
“I’m passionate about students and education, and I feel invigorated by what’s possible,” she says. “Instead of asking, ‘What are we reacting to, and how do we adapt?’ we’re asking, ‘What are we developing, and what are we going to create?’”
| 2025-06-09T00:00:00 |
2025/06/09
|
https://www.everylearnereverywhere.org/blog/new-collaborative-aims-to-tackle-questions-about-ai-in-education/
|
[
{
"date": "2025/06/23",
"position": 28,
"query": "AI education"
}
] |
Enterprise AI is changing education
|
Enterprise AI is changing education
|
https://www.eschoolnews.com
|
[
"Laura Ascione"
] |
AI can help educators spend more time teaching as they strive to create a more engaging, personalized experience for students.
|
Key points:
AI is poised to reshape education, impacting everything from administrative tasks and assessments to how students navigate research and develop critical thinking skills.
While AI seems like a relatively new development, it’s been around for quite some time, and is changing very quickly within the education space.
“We’re keeping an eye on usage in the U.S., where it’s happening, and how we can leverage that for teaching and learning,” said Kellie Ady, Senior Director of Education Strategy and Government Relations for PowerSchool.
It’s critical to think about how to better support educators who are using AI, including creating AI policies and guidelines in schools and districts.
Connected data system are also important for AI. “AI relies upon data, and if we have data living in different systems, it makes it a challenge for AI to do what it can do and do it well,” Ady said. “If we can remove data silos and make sure AI is leveraging a really powerful set of data, that changes the story of what it can do.”
Colorado Springs School District 11 is leveraging PowerSchool’s AI-powered solution, PowerBuddy for Learning, to help educators spend more time teaching to create a more engaging, personalized experience for students.
Take a deep dive into the district’s experience and discover how PowerBuddy for Learning:
Delivers scalable, enterprise-grade AI tailored specifically for K-12 districts
Saves teachers time and enhances instructional materials, enabling greater focus on student needs
Supports a more interactive and individualized learning environment with an always-available AI assistant
| 2025-06-23T00:00:00 |
2025/06/23
|
https://www.eschoolnews.com/digital-learning/2025/06/23/enterprise-ai-is-changing-education/
|
[
{
"date": "2025/06/23",
"position": 84,
"query": "AI education"
}
] |
Welcome to Axel Springer
|
https://www.axelspringer.com
|
[] |
Our guiding principle is: “We shape and lead the future of AI empowered media in the free world ... journalism and media marketing. BILD, BUSINESS INSIDER ...
|
Our guiding principle is: “We shape and lead the future of AI empowered media in the free world.” That is exactly the idea Axel Springer had when he founded the company around 80 years ago: to shape the future of journalism in the free world. For him at the time, the free world was the young Federal Republic of Germany. For us today, it is more than that.
We are a transatlantic media company with strong brands in Europe and the US. Our ambitions go further, and POLITICO, for example, offers excellent growth opportunities.
What has changed is the structure of Axel Springer. After forty years, we are once again entirely privately owned. Our investments in Stepstone and Aviv, AS Classifieds, secure our position and give us scope for our core business, journalism and media marketing. BILD, BUSINESS INSIDER, POLITICO, WELT, Emarketer, MORNING BREW, Idealo, and Bonial are a great portfolio with high potential.
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With the changed structure, we are concluding successful phases that first led Axel Springer to the stock market and then to partnerships with KKR and CCP Investments. These years have enabled us to digitally transform our brands and internationalize our business. And, let’s not forget, to double the company’s value. The story of this furious ride can be read on these pages – told by contemporary witnesses, in interviews, a new chronicle, and texts on the history of Axel Springer over the past decades.
But more than the past, said Albert Einstein, I am interested in the future, because that is where I intend to live.
But we want even more: we want to shape the future. The challenges are clear. Artificial intelligence is changing our world in the same way that digitalization did twenty years ago. We must radically seize all the opportunities that AI offers us and merge them with our human intelligence. The results will exceed anything we can imagine.
At the same time, we must regain what journalism has lost in many areas: credibility. To do this, we need transparency, including with regard to our values. Only those who say what they stand for will be trusted. But within the value system, friction is necessary. That is what distinguishes us from ideologues.
These guidelines are essential for us. They form our value system, but they are not rigid dogmas. At this point in the company’s history, we have slightly adjusted them again. They now reflect not only the German perspective of our values, but also the transatlantic perspective. You can find everything you need to know on this page, which will continue to grow over the coming weeks.
Feel free to check back often! We promise: things never get boring at Axel Springer. Welcome!
| 2025-06-23T00:00:00 |
https://www.axelspringer.com/en/welcome-to-axel-springer
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[
{
"date": "2025/06/23",
"position": 78,
"query": "AI journalism"
}
] |
||
Amazon's AI Layoff Wave: CEO's Email Sparks Outrage
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Amazon’s AI Layoff Wave: CEO’s Email Sparks Outrage — Why SVPs Stay Safe While Workers Get the Axe?
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https://blog.stackademic.com
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[
"Dylan Cooper"
] |
On June 18, Amazon CEO Andy Jassy sent out a bluntly worded internal memo to all employees: with AI being rapidly deployed at scale and driving “efficiency ...
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Amazon’s AI Layoff Wave: CEO’s Email Sparks Outrage — Why SVPs Stay Safe While Workers Get the Axe? Dylan Cooper 5 min read · Jun 23, 2025 -- 77 Share
“What an inspiring way to start your Tuesday — being told you’ll be replaced by AI in a few years!”
— A sarcastic comment from an Amazon employee in a company Slack channel.
Behind this biting remark lies a major event that has stirred heated debate among Amazon’s rank-and-file employees. On June 18, Amazon CEO Andy Jassy sent out a bluntly worded internal memo to all employees: with AI being rapidly deployed at scale and driving “efficiency gains,” the company anticipates a reduction in workforce over the next few years.
As expected, the announcement did little to ease concerns about AI-driven disruption. Instead, it acted as a spark, triggering a wave of venting across multiple internal Slack channels.
Some employees questioned whether the company’s vision had shifted to a “cost-cutting-first” mentality. Others voiced frustration more directly:
“Why is it that AI-driven layoffs never seem to reach the SVP level?”
01 CEO All-Hands Letter: Generative AI Is Transforming Amazon
In this all-hands letter, Andy Jassy first outlined the extensive deployment and impact of AI within the…
| 2025-06-23T00:00:00 |
2025/06/23
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https://blog.stackademic.com/amazons-ai-layoff-wave-ceo-s-email-sparks-outrage-why-svps-stay-safe-while-workers-get-the-axe-baf81baa8458
|
[
{
"date": "2025/06/23",
"position": 46,
"query": "AI layoffs"
}
] |
Global employees attempting to use ChatGPT at work 2023
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Global employees using ChatGPT at work 2023
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https://www.statista.com
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[
"Ani Petrosyan",
"Jun"
] |
As of June 2023, it was reported that **** percent of employees of worldwide companies have tried using ChatGPT in the workplace at least once.
|
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Cyberhaven. (June 18, 2023). Share of company employees worldwide using ChatGPT in work environments from February to June 2023 [Graph]. In Statista . Retrieved July 15, 2025, from https://www.statista.com/statistics/1378709/global-employees-chatgpt-se/
Cyberhaven. "Share of company employees worldwide using ChatGPT in work environments from February to June 2023." Chart. June 18, 2023. Statista. Accessed July 15, 2025. https://www.statista.com/statistics/1378709/global-employees-chatgpt-se/
Cyberhaven. (2023). Share of company employees worldwide using ChatGPT in work environments from February to June 2023 . Statista . Statista Inc.. Accessed: July 15, 2025. https://www.statista.com/statistics/1378709/global-employees-chatgpt-se/
Cyberhaven. "Share of Company Employees Worldwide Using Chatgpt in Work Environments from February to June 2023." Statista , Statista Inc., 18 Jun 2023, https://www.statista.com/statistics/1378709/global-employees-chatgpt-se/
Cyberhaven, Share of company employees worldwide using ChatGPT in work environments from February to June 2023 Statista, https://www.statista.com/statistics/1378709/global-employees-chatgpt-se/ (last visited July 15, 2025)
Share of company employees worldwide using ChatGPT in work environments from February to June 2023 [Graph], Cyberhaven, June 18, 2023. [Online]. Available: https://www.statista.com/statistics/1378709/global-employees-chatgpt-se/
| 2025-06-23T00:00:00 |
https://www.statista.com/statistics/1378709/global-employees-chatgpt-se/
|
[
{
"date": "2025/06/23",
"position": 32,
"query": "ChatGPT employment impact"
}
] |
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AI shows little impact on worker well-being despite self ...
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AI shows little impact on worker well-being despite self-reported job satisfaction concerns
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https://phys.org
|
[
"University Of Pittsburgh"
] |
No significant average effects of AI exposure on job satisfaction, life satisfaction, or mental health. · Small improvements in self-rated physical health and ...
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This article has been reviewed according to Science X's editorial process and policies . Editors have highlighted the following attributes while ensuring the content's credibility:
Credit: Matheus Bertelli from Pexels
As artificial intelligence reshapes workplaces worldwide, a new study provides early evidence suggesting AI exposure has not, thus far, caused widespread harm to workers' mental health or job satisfaction. In fact, the data reveals that AI may even be linked to modest improvements in worker physical health, particularly among employees with less than a college degree.
But the authors caution: It is way too soon to draw definitive conclusions.
The paper, "Artificial Intelligence and the Wellbeing of Workers," published June 23 in Scientific Reports, uses two decades of longitudinal data from the German Socio-Economic Panel. Using that rich data, the researchers—Osea Giuntella of the University of Pittsburgh and the National Bureau of Economic Research (NBER), Luca Stella of the University of Milan and the Berlin School of Economics, and Johannes King of the German Ministry of Finance—explored how workers in AI-exposed occupations have fared in contrast to workers in less-exposed roles.
"Public anxiety about AI is real, but the worst-case scenarios are not inevitable," said Professor Stella, who is also affiliated with independent European bodies the Center for Economic Studies (CESifo) and the Institute for Labor Economics (IZA).
"So far, we find little evidence that AI adoption has undermined workers' well-being on average. If anything, physical health seems to have slightly improved, likely due to declining job physical intensity and overall job risk in some of the AI-exposed occupations."
Yet the study also highlights reasons for caution.
The analysis relies primarily on a task-based measure of AI exposure—considered more objective—but alternative estimates based on self-reported exposure reveal small negative effects on job and life satisfaction. In addition, the sample excludes younger workers and only covers the early phases of AI diffusion in Germany.
"We may simply be too early in the AI adoption curve to observe its full effects," Stella emphasized. "AI's impact could evolve dramatically as technologies advance, penetrate more sectors, and alter work at a deeper level."
Key findings from the study include:
No significant average effects of AI exposure on job satisfaction, life satisfaction, or mental health.
Small improvements in self-rated physical health and health satisfaction, especially among lower-educated workers.
Evidence of reduced physical job intensity, suggesting that AI may alleviate physically demanding tasks.
A modest decline in weekly working hours, without significant changes in income or employment rates.
Self-reported AI exposure suggests small but negative effects on subjective well-being, reinforcing the need for more granular future research.
Due to the data supply, the study focuses on Germany—a country with strong labor protections and a gradual pace of AI adoption. The co-authors noted that outcomes may differ in more flexible labor markets or among younger cohorts entering increasingly AI-saturated workplaces.
"This research is an early snapshot, not the final word," said Pitt's Giuntella, who previously conducted significant research into the effect of robotics on households and labor, and on types of workers.
"As AI adoption accelerates, continued monitoring of its broader impacts on work and health is essential. Technology alone doesn't determine outcomes —institutions and policies will decide whether AI enhances or erodes the conditions of work."
More information: Artificial intelligence and the wellbeing of workers, Scientific Reports (2025). DOI: 10.1038/s41598-025-98241-3 Journal information: Scientific Reports
| 2025-06-23T00:00:00 |
https://phys.org/news/2025-06-ai-impact-worker-job-satisfaction.html
|
[
{
"date": "2025/06/23",
"position": 51,
"query": "ChatGPT employment impact"
},
{
"date": "2025/06/23",
"position": 92,
"query": "artificial intelligence employment"
}
] |
|
Does generative AI actually enhance creativity in the ...
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Does generative AI actually enhance creativity in the workplace?
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https://mitsloan.mit.edu
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[
"Mit Sloan Office Of Communications"
] |
The researchers also found that ChatGPT helped employees gain cognitive job resources — including access to information and knowledge, and the opportunity to ...
|
facebook
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linkedin
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New research from MIT Sloan finds generative AI boosts employee creativity — but only for those who actively reflect on and adapt how they use it.
CAMBRIDGE, Mass., June 23, 2025 – Businesses and organizations worldwide are increasingly integrating generative AI tools like ChatGPT into their workflows, hoping that these tools will fuel innovation and boost creativity. But results have been mixed thus far. For example, a large-scale, nationally representative survey conducted by Gallup found that only 26% of employees using generative AI reported improved creativity.
This raised a crucial question: Does generative AI actually enhance creativity in the workplace? The answer is yes — but only for employees who have strong metacognitive strategies, according to new research from MIT Sloan School of Management associate professor Jackson G. Lu , Tulane University associate professor Shuhua Sun, Renmin University lecturer Angelina Zhuyi Li, Nanyang Technological University professor Maw Der Foo, and Rice University professor Jing Zhou.
“Generative AI isn’t a plug-and-play solution for creativity,” said Lu. “To fully unlock their creative potential, employees must know how to engage with AI — to drive the tool, rather than letting the tool drive them.”
“Metacognition — thinking about your thinking — is the missing link between simply using AI and using it well. It allows people to ask better questions, recognize knowledge gaps, and extract real value from AI tools." Jackson G. Lu Sloan School Career Development Associate Professor of Work and Organization Studies Share
The study, titled “How and For Whom Using Generative AI Affects Creativity: A Field Experiment,” published in the Journal of Applied Psychology, tested how AI affected creativity in real-world organizational settings through a field experiment at a technology consulting firm in China.
The researchers randomly assigned 250 employees to either use ChatGPT to assist with their work or not. Employees with access to ChatGPT were rated as more creative by both their supervisors and external evaluators — but only if they had high levels of metacognitive strategies, which involved analyzing tasks and their own thought processes, planning, self-monitoring, and revising strategies. For example, employees with strong metacognitive skills could reflect on what information they lacked, keep track of how effective their approach is and reassess their approach when noticing a lack of progress, and refine their AI prompts accordingly — behaviors that could help them use AI more effectively to enhance creativity.
“Metacognition — thinking about your thinking — is the missing link between simply using AI and using it well,” said Lu. “It allows people to ask better questions, recognize knowledge gaps, and extract real value from AI tools instead of relying on them passively.”
The researchers also found that ChatGPT helped employees gain cognitive job resources — including access to information and knowledge, and the opportunity to switch between tasks and take mental breaks — which can foster creativity . However, only employees with strong metacognitive strategies could fully take advantage of these benefits.
Importantly, the researchers emphasized that metacognitive strategies are not fixed traits — they can be taught. Cost-effective interventions like brief training modules, social-psychological exercises, or even multi-day workshops can help employees enhance their metacognitive capabilities — and, in turn, their creativity.
“Even the most powerful AI won’t boost creativity if employees don’t know how to use it effectively,” said Lu. “Organizations should pair AI deployment with metacognition training to maximize the creative benefits.”
About the MIT Sloan School of Management
The MIT Sloan School of Management is where smart, independent leaders come together to solve problems, create new organizations, and improve the world. Learn more at mitsloan.mit.edu.
| 2025-06-23T00:00:00 |
2025/06/23
|
https://mitsloan.mit.edu/press/does-generative-ai-actually-enhance-creativity-workplace
|
[
{
"date": "2025/06/23",
"position": 68,
"query": "ChatGPT employment impact"
}
] |
Impact of AI on Employment Discrimination - Symmetra
|
Impact of AI on Employment Discrimination
|
https://symmetraglobal.com
|
[] |
AI has for years now, been used extensively in recruitment, evaluation, transfer, promotion and dismissal in the workplace.
|
Symmetra wrote very recently about the profound impact which the implementation of AI tools in various aspects of employment will have on issues of discrimination [link here] but since then the landscape in this area has changed significantly.
The US National Artificial Intelligence Act defines AI as “machine-based system that can, for a given set of human-defined objectives, make predictions, recommendations or decisions influencing real or virtual environments “
AI has for years now, been used extensively in recruitment, evaluation, transfer, promotion and dismissal in the workplace but the pace at which AI systems have advanced in just the last six months has had oversight and regulatory bodies scrambling to respond. Can existing legal and internal disciplinary models cope with the new technology?
Examples of AI systems producing biased or skewed results are well- documented. In 2018 Amazon famously abandoned the use of AI in its recruitment program because it selected males over females. Many other examples have been noted such as facial-recognition cameras evidencing bias when identifying people with dark skin.
Amongst the bodies sounding the alert is the UN Human Rights Council. Its resolution on 14, July, 2023 calls for the” adequate explainability “of AI-supported decisions…” taking into account human rights risks arising from these technologies “
Also, in the past month three regulatory bodies in the US (Financial protection bureau, Justice Department and Federal Trade Commission) have issued a joint statement “… On Enforcement Efforts Against Discrimination and Bias in Automated Systems “. It ends as follows: “We. pledge to vigorously use our collective authorities to protect individual rights regardless of whether legal violations occur through traditional means or advanced technologies. “
New York City (Local Law 144), now in force is the first attempt globally to legislate in this area- laying down certain pre-requisites in using AI for recruitment. These are (i) conduct a bias audit prior to use of the tool; (ii)notify candidates that the tool is in use; (iii) outline to candidates the qualifications and characteristics that the tool will use. These are useful baseline points for employers anywhere in the world using AI tools to observe.
Most importantly is the need for organisations, public and private to make it clear both internally and externally that they are being pro-active in their commitments to a workplace characterized by DEI. AI tools can be useful for cutting down laborious sifting tasks but at the end of the day human oversight is required to ensure that potentiality for unlawful discrimination is minimized whenever decisions are made affecting recruitment, advancement and employee evaluation.
| 2023-07-21T00:00:00 |
2023/07/21
|
https://symmetraglobal.com/impact-of-ai-on-employment-discrimination
|
[
{
"date": "2025/06/23",
"position": 99,
"query": "artificial intelligence employment"
}
] |
Overview on the Sustainable and Responsible Educational ...
|
Overview on the Sustainable and Responsible Educational Technology Efforts Using Artificial Intelligence for the Workers of the Future
|
https://wap.hapres.com
|
[
"Zita Kaszalik",
"Viktória Gősi Kövecses",
"Márta Konczos Szombathelyi"
] |
... artificial intelligence, educational technology, ESG, and the labor market were examined. ... International Labor Organization. Global Employment Trends ...
|
Article
Received: 23 Jan 2025; Accepted: 28 May 2025; Published: 24 Jun 2025
The purpose of the research is to review how artificial intelligence is integrated into the education of employees, emphasizing that the rapid application of artificial intelligence significantly affects the development of the workforce and the achievement of sustainability goals. The European Commission also continuously monitors changes in the field of digitization and artificial intelligence. Among other things, the European Union uses ESG (environmental, social, governance) aspects to measure sustainability performance, relying on domestic and international literature to reveal how education, investments and international cooperation can lead to social development and market competitiveness. As a research method, we use the analysis of annual reports, training and conference reports, company websites, and databases on corporate ESG commitment, employee development, and digitalization. Based on the decision of the European Commission, the continuous and rapid progress of the development of digitization and artificial intelligence is an issue to be monitored with reporting obligations. Analyzes of ESG reports help to understand the sustainability practices and environmental effects of a given organization, help to reveal social responsibility, interpret the company's long-term value creation potential and risks, measure and compare the sustainability performance of different companies and organizations. Analyzing ESG reports is key to promoting transparency and responsible business practices. Based on the developments, in addition to the economic results, the realization of the sustainability goals is becoming more and more tangible in the context of the ESG framework, the investigation of digitalization and artificial intelligence, as well as the labor market and education.
ABBREVIATIONS AI, artificial intelligence; ESG, environmental, social, governance; OECD, Organization for Economic Co-operation and Development; EU, European Union; SME, small and medium-sized enterprises; SDG, sustainable development goals; CSRD, corporate sustainability reporting directive; CSR, corporate social responsibility; EdTech, education technology; CAGR, compound annual growth rate; AR, augmented reality; VR, virtual reality; GDPR, general data protection regulation; MOOC, massive open online course; UNESCO, United Nations Educational, Scientific and Cultural Organization; ESRS, European Sustainability Reporting Standards; STEM, science, technology, engineering and mathematics; LLM, large language models; Cedefop, European Centre for the Development of Vocational Training
INTRODUCTION The study does not contain an in-depth analysis of a single company or event, nor does it focus exclusively on market and economic data. Rather, an exploratory scientific study combines data and perspectives from multiple sources, formulates research questions, draws conclusions, and makes suggestions for future research directions. The study examines companies’ compliance with social sustainability for the sake of future employees, in relation to digitized education and the application of artificial intelligence (AI). The rapid development of AI has a clear impact through the workforce factor on economic results and the realization of sustainability goals [1]. Due to the reporting obligations imposed by the decision of the European Commission, the realization of sustainability goals, digitalization and the application of AI have become factors designated for monitoring [2]. The perspectives of ESG as the means of measuring sustainability are increasingly prestigious evaluation criteria for investors and financial actors during risk analysis studies, and education for the sake of development, investments and international cooperation overall motivate the social development and market competitiveness [3–5]. Legislation is a central element in addition to financial capital, it is a base for changing lifestyles, increasing opportunities for equal opportunities, and combined with education, it has a significant impact on the development of the workforce [6]. Based on the expectations, the growth of educational investments and the transformation of traditional classrooms can be predicted, instead of the further training of the own workforce, retraining is manifested due to the shortened time interval, and international partnership can also help to catch up with the results achieved in the field of the knowledge-based society [7]. AI has emerged as a fundamental element of knowledge sharing, a chance to increase productivity and improve living standards [8]. The purpose of the study is to explore educational technology efforts embedded in sustainable and responsible AI applications used by companies, which represent a new path for future workers [9]. The study focuses on AI applications, as this technological development can provide a solution for further productivity growth, efficiency gains, and positive financial performance in the future. AI is now a systemic transformational force, identified as a catalyst for its profound labor market shaping impact, automation potential, personalized learning opportunities, efficiency-enhancing potential, and both risk and opportunity potential [10]. The Research method is based on analyses of annual reports, training and conference reports, company websites, and company ESG reports on employee development, digitalization and AI database analyzes [11–17]. The World Economic Forum, Eurostat, OECD, European Commission, UNESCO reports are complemented by statements from Audi, Bosch, IBM, BDO, Piac&Profit, Eurofound, Cedefop, Grand View Research, W3Tech, WebTechnology Surveys, typically covering the period 2019–2024. During the data collection, 18 company analyses, 12 international policy studies and 6 statistical databases were processed. The quantitative research approach was also assisted by database research and index research. The companies were selected based on size, sector and level of AI application in order to compare SMEs and large companies. Company reports can also be used for marketing purposes, so unfortunately, positive distortion of the data cannot be ruled out. Based on the decision of the European Commission, digitalization and the use of AI are part of the reporting obligation of companies. The analysis of ESG reports is authoritative from the point of view of promoting transparency and responsible business practices, based on the developments, economic results and the realization of sustainability goals can be verified [18,19]. According to the 1987 report of the World Commission on Environment and Development, we must meet the needs of the present so that the next generation can their own needs. Based on this, the companies are compared objectively not from a financial and economic point of view, but from a sustainability point of view [20]. In 2015, the basic idea of the United Nations was added to the objectives of the European Union (EU) to be achieved by 2030 through the formulation of 17 sustainable development goals, together with the discussion of the issues of innovation, equal opportunities, job creation and education, the universality of “leaving no one behind” following its principle [18,21,22]. Based on Hungarian surveys, 83% of the surveyed companies claim that ESG will be important to them because of their reputation and expectations. 40% of the respondents would spend more, 50% would spend the same amount. Energy efficiency appears as the most frequented area (77%), in the case of SMEs, employee welfare, education, training and human rights are more prominent [23]. Solution diversities can provide an opportunity to avoid the homogenizing effect of institutional pressure on organizations [24]. In order to strengthen environmental awareness, based on the EU’s corporate sustainability reporting directive (CSRD), since January 2023, companies have been obliged to publish and report on the fulfillment of the standards based on reporting standards (European Sustainable Reporting Standards—ESRS) [25]. The reporting of non-financial information applies to all large companies and SMEs present in the markets, and supports the measures of the European Green Deal aimed at overcoming the climate crisis [15,26]. Corporate social responsibility (CSR) can generate decisive advantages for collaborators due to competitiveness. Based on the 2011 CSR strategy of the European Commission, cooperation is integrated into the basic strategies in social, environmental, ethical, human rights and consumer issues [27]. CSR practices can become suitable for raising the company’s reputation, attracting high-quality workforce and young talents, so organizations should pay special attention to this area [28]. Throughout history, the acceptance of new technologies, innovation, and the acquisition of new knowledge have always appeared as defining issues, which is how the issue of education was included among the 17 sustainability goals [29]. Responsible educational technology steps include the development of educational systems, the search and recognition of possible learning bases, and their transmission to students [30]. Sustainable and responsible educational technology efforts and AI work together effectively for the benefit of the workforce of the future. According to Bill Gates’ forecast, AI will induce significant changes even in everyday life within five years, but the IMF is concerned about the rapid evolution of AI, according to which approximately 40% of jobs may be affected by the extremely rapid development. It is clear that successful economies cannot exist without the widespread diffusion of digital capabilities. According to the founder of Microsoft, similar to the increase in agricultural productivity in the 1900s, AI can represent a chance to improve the standard of living, also for education, it can help remedy the shortage of teachers, it can start the process of realizing equal opportunities, but in the opinion of the doubters, it contributes even more to the increase of inequalities [31,32]. Research questions: What opportunities can digitalization bring to achieve sustainability goals? How do the labor market and education respond to this AI breakthrough? What impact does AI-based educational technology have on the skill level of employees? How sustainability is reflected in educational technology ESG reports? What factors influence the success of AI implementation in labor market-oriented education [11,12]?
MATERIALS AND METHODS A mixed methodological approach was applied during the research, combining qualitative and quantitative analysis techniques. A multi-stage criteria system was followed when analyzing the data sources. Regarding the relevance of the study, only company websites that are directly related to the topics of artificial intelligence, educational technology, ESG, and the labor market were examined. In terms of temporal validity, the analyzed documents originate from the period 2019–2024, thus providing an up-to-date picture of current trends. From a geographical perspective, the sources focus primarily on Europe, including Hungary, Germany, and the Nordic countries, but international comparisons were also made when examining OECD, UNESCO, and EU documents. We used two basic theoretical models for the analytical framework. The TAM (Technology Acceptance Model) was applied to examine the application of AI in education, with particular attention to the factors influencing acceptance (usefulness, usability, attitude), while SDG4 goal (Quality Education) was used to measure the contribution to the sustainable development goals. In order to ensure methodological rigor in data analysis, triangulation and comparison of multiple types of data sources were carried out when examining statistics from international organizations, corporate ESG reports, market research studies, and academic articles. Index-based analysis was performed to compare ESG performances. We applied filtered database analysis based on structured data collection tables, in which we used key indicators, such as the extent of education investments, the level of AI use, and digital skills development strategies. We also took into account the marketing biases of corporate reports and the reliability limitations of publicly available sources. An overview of sustainable and responsible educational technology efforts with the application of AI research for the workers of the future reveals the most important educational technology and labor market opportunities and results in order to realize them. As a market-leading solution in the field of education, the study discusses the opportunities offered by products associated with cloud services, machine learning and natural language processing, the implementations are completed with the help of cooperative learning and healthy collaboration. The exploration of educational technology innovations is justified by the intense industry competition, where the strengthening of traditional education with the position of distance education, the knowledge of emerging content languages, and the use of AI position the chances of competitiveness to a significantly higher level. The labor market and education represent a common line of sustainability, in which the most dynamically growing elements are technology, digitization and sustainability. How would companies change their ESG spending in the future? The future of work is the acquisition of new technologies, the correction of expected basic skills through education, lifelong learning, improving the employment rate of young people, and the practical application of AI. The explosive expansion of the study’s research area means research limitations, so data is not yet available in some areas. The findings of mixed-method research are valid within the time interval of the research and require continuous updating, as AI, digitalization, and educational technology are rapidly changing fields. However, the conclusions drawn from the available data are useful, especially for identifying trends and defining primary frameworks. The study communicates these limitations transparently, which increases its scientific credibility. The study analyzes the introduction of AI in the educational context using the Technology Acceptance Model (TAM) and the SDG framework. In addition to the government reports, the data of the educational technology studies are independent technological reports of the service providers Grand View Research, W3Techs, Web Technology Surveys, International Labor Organization, and BDO Hungary, secondary sources are other educational technology and labor market documents and publications. The collected data were explored to identify educational technology and labor market trends and opportunities. The formulation of the market, the normalization of the data, and the data representation were made only based on validated data. The purpose of sharing the reports is to understand the dynamics of the educational technology and labor market and global market forecasts. The individual regional prospects required a short-term, up to 2030, and long-term forecast interpretation, primarily compared to the AI and sustainability segment prospects. The limited database of reports may result in a percentage deviation of the results, but it is suitable for detecting market trends. The validity of the trends is limited at the time of writing the study; the data require continuous updating in case of further research. Although the limited data, geographical and organizational limitations of the research require future expansion of the research, even in its current state it can serve as a basis for comparison in an international context. Due to the broad outlook, triangulation was applied by involving scientific and policy sources (Figure 1). FIGURE 1 Figure 1. Methodological logic scheme of the research. (Source: Compilation of authors.)
RESULTS AND DISCUSSION Answering the research question, the first one is: What opportunities can digitalization bring to achieve sustainability goals? In order to eliminate inequalities, the 2030 development framework tries to use all innovation tools to achieve the 17 development goals. In order to achieve the goals, lifelong learning is necessary for the individual, which will become available in the future with new educational technology solutions, e-books, micro-training, intelligent classroom training and other developments that are still in their infancy [3]. Innovation tools pervade the examined modernized education system and changes in the labor market, their development is also supported by official follow-up reports [33,34]. The possible distortion of the results of the empirical research, which is the basis of the study, stems from the depth of immersion and the limitations of data availability, so the reference to various reports serves to illuminate and strengthen the data in several directions. The fourth Development Goal, the process of realizing quality education, is supported by market expansion in the field of education, the appearance of typically North American development-led digital classrooms, and the latest game-based learning [9]. AI has already appeared in the field of personalized education and catch-up. By using quality educational basic data, it is able to provide assistance in the segment of education and the labor market connection and in order to achieve sustainability goals. The use of this support significantly affects the reputation and economic results of the given company, especially in the case of SMEs, the issue of education and the appropriate fulfillment of employee expectations is emphasized [23]. Based on the summary report of Cedofop [7], the joint work of vocational training, quality education, and educational technology developers generates catch-up in the knowledge-based society. According to the report of the World Economic Forum [35], the use of AI in the relationship between workplaces and the future of work is the key to increasing efficiency and competitiveness, as it is suitable, among other things, for the immediate sharing of technological knowledge. From the corporate reports of BDO, Audi Hungaria, IBM and NOKIA, it is possible to report on already implemented ESG steps and digitalization experiences, in which the importance of new essential employee skills, retraining, innovations, and the injection of the industrial application of AI with conditions can be seen [13,16,23,26]. In Europe, the evaluation of the workplace is an extremely important workplace expectation. The emergence of AI also significantly influenced the need for workplace stability. With the fourth industrial revolution, the direction of automation, the application of AI, new types of work appear, the rapid acquisition of which can be achieved with quality education, adaptability, a positive employee attitude, and retraining. AI still poses certain risks for the industrial environment, it needs further development, but it can also serve as a future solution to labor shortages. European Commission reports [15,36–38] report on EU ESG activities, steps taken in ESG ratings, reveal a coordinated plan for artificial intelligence, and convey a strategy for the transition to a sustainable economy. The results show that training platforms integrated with AI significantly support lifelong learning and corporate tracking of ESG objectives [39]. The W3Techs database, as a reliable source of information independent of service providers, presents us with a new emerging order of server usage, in which the leading role of English is not threatened now, but in addition to Spanish, German and Japanese, Russian and French also appear as content languages of increasing importance [40]. Many corporate ESG reports paint an overly optimistic picture of AI integration in education and retraining. These reports often emphasize innovation and productivity while neglecting ethical and equal opportunities challenges, or even practical application challenges, while current OECD and UNESCO reports highlight digital divides, algorithmic biases, and access barriers in low-income regions. These divergent realities highlight the gap between corporate ambitions and actual readiness. Education Technology How do the labor market and education respond to this AI breakthrough? What factors influence the success of AI implementation in labor market-oriented education? In the near future, EdTech (education technology) will undergo a complete transformation under the influence of AI, skills and competencies essential for the labor market will change [41]. Its success precludes short-term thinking during digitization processes, cooperative cooperation and a unified collaborative intention are emphasized expectations [42]. Among the market-leading solutions in the education technology of the future are products associated with cloud services, machine learning, and natural language processing [43]. Learning the benefits of flexibility, digital routine, personalized, motivating education, and group, cooperative learning is justified. We need transformative competences and the ability to compromise. In a knowledge-based economy, the acceptance of lifelong learning, even with the use of micro training, is essential for systemic thinking [44]. Cloud services, machine learning and natural language processing are becoming the number one application among the tools that support education, and accordingly, a vigorous increase in value can be forecast in the field of the educational technology market. The market worth 123.40 billion dollars in 2022 and 142.37 billion dollars in 2023 is expected to grow at a compound annual growth rate (CAGR) of 13.6% between 2023–2030 and reach 348.41 billion dollars by 2030 [45]. The popularity of e-books is also increasing, as they are available anywhere, can be translated into different languages, and the possibility of tutoring online is becoming more and more popular [46]. The Texthelp Ltd.’s new development result—documents available in OrbitNote-pdf format with voice notes, also available for the visually impaired—represents an opportunity to create equal opportunities [32]. The “Intelligent Classroom” project is a digitization experiment, during which new technologies are used with virtual learning. The development and impact of interactive parts, augmented reality (AR) and virtual reality (VR), as well as AI and IoT (Internet of Things) are motivating. The concentration of the educational technology market and the prominence of its characteristics are illustrated in Figure 2, which shows the high level of innovation and the significant impact of technology on the change of education, as it can already serve individual needs. There is an increase in investment in the sector, and traditional classrooms are being transformed. The business share rate in the area is high, reaching 68.55% of global revenue. Concentration, partnerships between institutions and content developers represent new potential for digitization, industry competition in the field of educational technology market is becoming more intense [45] (Figure 2). FIGURE 2 Figure 2. Educational Technology Market—Industry Competition. (Own editing, based on [45].) A problematic point, the data protection of the students participating in the training, is also guaranteed by law, due to EU regulations, EdTech is subject to the GDPR (General Data Protection Regulation). During the Smart Classroom project, advanced technologies based on virtual learning are used [45]. The use of AI in education raises several ethical and data protection issues, such as excessive collection of student data, algorithmic bias, and lack of transparency in automated decision-making. Although the EU GDPR regulation contains strict requirements, many EdTech systems do not fully comply with these principles. The ownership and management of data collected by AI is a particularly sensitive issue, which also affects student rights and equal opportunities in education [46,47]. Open online courses (MOOC—Massive Open Online Course) that provide the opportunity for mass participation are mostly free and may require registration. These interactive forums appeared in the Anglo-Saxon areas in 2008 and spread from there in the field of distance education. The MOOC became really popular in 2012, and the reason for this is the quality of the material covered, the commitment of the instructors and the interaction between the participants in the training, but the issue of ethical use and free access is becoming an increasing problem [45,48,49] (Figure 3). FIGURE 3 Figure 3. Traditional education—distance-learning position. (Compilation of authors, based on [45].) As a result of digitization, digital classrooms play an increasingly important role in the education segment. In 2022, 36.64% of the profits of the EdTech sector were controlled by North America and according to the forecasts, it will maintain its primacy, the new trend will be game-based learning [45]. EdTech investors came from China, the United States, Europe and the United Kingdom, and the amount of their investments already reached 20 billion dollars in 2021 [48,50]. Since the server is essential for digitization, the popularity of server locations will also affect the technical development of the given country. According to the popularity ranking based on server usage, in 2024, 1st is the United States with 33.8%, second Germany with 11.3%, and 3rd France with a value of 5.5%. Where the most popular content languages are tied? Based on the February 2024 survey of the World Wide Web Technology Surveys, among the content languages, 1st English 51.2%, 2nd Spanish 5.6%, 3rd German 5.0%, 4th Japanese 4.6%, and 5th Russian with a usage value of 4.4%. The fastest growing content language since February 1, 2024 is German. As of June 1, 2024, French replaced Russian in the 5th place [40] (Table 1). TABLE 1 Table 1. Emerging content languages. The intersection of education and AI has countless possibilities, including personalized education and catch-up, but the risk factors are currently unknown [51]. Visualization according to individual needs can be created with the help of the Education Databot AI-enhanced data visualization tool, which uses SDG 4 data in order to present educational data with a higher quality. The data visualization of OpenAI GPT-3.5 Turbo and Azure OpenAI API is also specially based on UNESCO statistical data, using the data of the fourth sustainability goal (quality education) during its operation [52]. According to international research, educational technology developments related to SDG 4 objectives have produced a number of measurable results. In countries where AI-based, personalized learning platforms have been introduced to develop basic skills, students’ reading comprehension and mathematics performance have improved by up to 12%–20% compared to traditional teaching methods [53]. Another positive result is that distance-learning programs supported by digital tools, for example in Nigeria, have increased access to education for disadvantaged students, thereby reducing learning inequalities [54]. These results show that well-designed EdTech interventions actually contribute to the global advancement of quality education. Although market research data (e.g., Grand View Research, W3Tech) predict rapid growth in the sector, they do not sufficiently address the issue of regulatory and pedagogical integration. There is little information available on how these technologies will actually be implemented in educational practice, or how their impact will be measured beyond financial indicators. Despite the goal of quality education, studies on educational innovation rarely address ESG frameworks, while sustainability-focused research does not address the technological and pedagogical aspects of AI-based education. This is a significant interdisciplinary gap and may support the need for integrated models. The importance of SDG4 is emphasized by many sources, but few studies discuss the long-term risks, such as the decline of the teacher role, the lack of transparency in data collection for educational purposes, or even the suppression of critical thinking. These undervalued aspects reinforce the need to evaluate technological developments according to normative, value-based criteria, not just economic performance. Labor Market-Employees What impact does AI-based educational technology have on the skill level of employees? How sustainability is reflected in educational technology ESG reports? The intertwining of education and the labor market is not new, the formulation of a common sustainability direction is essential. The sustainable financing package adopted by the European Commission in 2021 is ESG tries to capture non-financial risks and opportunities through reporting obligations [37]. The EU's Corporate Sustainability Reporting Directive, which entered into force in 2023, and the Sustainability Reporting Standards, which govern reporting requirements, require companies to regularly disclosing information on the environmental and social impacts of their activities, sustainability operations and performance [55]. According to a survey conducted by BDO Hungary's financial consulting group, companies in the region believe that ESG points of view cannot be avoided either, but compliance is still in its infancy, although 83% of the surveyed companies predict that it will have a major impact on their business results and reputation. 40% of the regionally surveyed companies would be happy to spend even more money to achieve ESG goals. 77% of large companies focus on energy and green energy investments, SMEs focus more on social areas and 15% more consider education and further training to be more important areas [23] (Figure 4). FIGURE 4 Figure 4. How would companies change their ESG spending in the future? (Own editing, based on [23].) AI tools suitable for sharing the latest knowledge have also become unavoidable from the point of view of the labor market. ChatGPT is already suitable for increasing global GDP. The rate of growth can reach up to 7%, since ChatGPT can simultaneously replace up to 300 million full-time workers. AI greatly threatens the jobs of employees in higher positions, while previous forecasts clearly predicted the mechanization of physical jobs. Automation can appear only as a supplement to the workforce, it can increase demand and generate jobs, and the increase of capital and workforce stimulates modernization. Technical scientific possibilities are not equivalent to technological reality, the quantified value of human work will be determined by the entry limits of the given role, which are generated by education and training [56]. The AI designed by Artisian AI is already able to integrate into the work of human teams, and in the future, the “Ava” development, which is an improved version of Chatbots, is suitable for replacing what people call boring jobs, including sales jobs [57]. Market competitiveness can only be improved by rapid adaptation to new trends. In a world dominated by AI, interpersonal skills, empathic and creative skills are becoming more and more important, making the given employee valuable. Christopher Pissarides [17] in connection with the research of science, technology, engineering and mathematics (STEM) subjects warns that the summarization, comparison and innovative application of data will make AI even more advanced, so that developers will soon become indispensable for the first time. With the development of AI, the need to fill areas that cannot be replaced by AI may increase, since creativity, managerial approach; empathy cannot be replaced with technical solutions [55,58]. In order to create a competent layer of employees in the workplace, a quick reaction is necessary, further training is replaced by retraining, which requires a much shorter time [59]. Retraining must be included in the company's strategy, since efficiency and productivity can be increased together with raising the qualification level of the workforce. During mentoring, Generation Z expects individual talent management and challenges during international projects, research, and professional internships [60]. The management of the process, which is also a compulsion for employees, can only be achieved through effective cooperation between the state apparatus, companies, businesses and the education sector [61]. According to experience, company managers most often ask employees about workplace development, training, and digitalization through surveys and questionnaires [62]. Based on the results of the surveys, the company's commitment to the development of its employees becomes measurable, possible shortcomings and areas to be developed in the adaptation of new technologies are also revealed. Staff training and development programs, their efficiency and participation rate in the field of new technologies can be monitored. Most of the information can be found on the companies' websites, in their annual reports, in reserved places. It is of informational value what kind of training, training or other development opportunities companies offer to their employees in the fields of innovation, and it is also worth considering the opinions and research of industry analysts and experts [63]. According to Randstad's market survey (Employer Brand Research), the most important employee expectations in 2024 are wages and other benefits, work-life balance, workplace stability, workplace atmosphere, fairness initiatives, fair development and career opportunities. Based on the data, the content of the work and the general perception of the company are more important in Europe than in Hungary [64]. The transformation of the labor market is indicated by the fact that, as a result of the application and advance of the fourth industrial revolution, AI, every fifth job will disappear in the future. This tendency must be responded to quickly due to the macroeconomic trends, the increase in the cost of living, the lack of supply, rising input costs and the process of slow economic growth. It can be a solution that the most dynamically growing function is performed by technology, digitalization and sustainability [65]. By 2025, almost 50% of jobs will be automated if the given conditions are created, and 65% of students still studying in the education system today will work in a new type of work [35] (Figure 5). FIGURE 5 Figure 5. The future of work. (Compilation of authors, based on [35].) In the future, due to the important role of mastering new technologies and the skill defect of the workforce, a 10% increase in the education division can be forecasted in vocational education and in the university and higher education segment. Analytical and creative thinking, flexibility, motivation and self-awareness, curiosity and lifelong learning will become indispensable for the employees of the future. Adaptability, reliability, analyzing details, technical literacy, cooperation with others, empathy, leadership and quality control complete the top 10 list of expected basic skills, the level of the most important skills can be improved with education. Developing the workforce and attracting talent are definitely management tasks. The role of young workers in the economy would show enhanced value, but currently their potential lack of employment can be monitored. Negative values can still be detected in Eastern Europe, while a positive shift is already visible in Northern, Southern and Western Europe [65]. Compared to 2019, the employment deficit in Northern, Southern and Western Europe improved from −5.5% in 2020 to 1.0% in 2022, and in Eastern Europe, it changed from −7.2% to −5.3% in 2020. The above data are estimates until 2021 and forecasts for 2022. Young people represent the age group 15–24. The values show a favorable process, but the improvement is not yet at a sufficient level [66] (Table 2). TABLE 2 Table 2. Employment deficit of young people (15–24 years old) compared to 2019, 2020–2022, by region of Europe. According to the latest forecasts, the earth's population is expected to peak at 9.73 billion people by 2064, by 2100 it will decrease to 8.79 billion people, and by 2050, a third of the 15–24-year-olds will be of African origin, who will enter the labor market as employees [67]. Productivity is declining worldwide, which the use of AI can improve. Due to the aging of the population, the peculiarity of young people, the fluid intelligence necessary for creative problem solving, is also decreasing, digitization can be the solution to replacing the workforce and increasing efficiency [68]. In the past, aging already played a 35% role in the use of robots, especially in the extremely aging societies of Germany, South Korea and Japan, because demographic changes entail faster technological change [69]. Currently, AI may emerge as a strategic solution to alleviate labor shortages and sustain economic growth. There are regional differences in the impact of AI on the labor market. In North America, AI has been rapidly adopted, dominated by technology companies, and the survival of intellectual jobs is at a higher risk, while in Europe, the pace of AI adoption is slower and is implemented in a regulated environment. In China and Asia, AI operates with strong state support and plays a major role in manufacturing and education, while in the Global South and developing regions, the introduction of AI has been mostly delayed, and we can only talk about digital remote work [70–72]. The adoption of technological development fundamentally affects workplaces. Based on the analyzes of the Future of Jobs Survey, by 2023–2027 Digital platforms and applications are likely to be used by 86.4%, Education and workforce development technologies 80.9%, Big-data analysis 80%, and Artificial intelligence 74.9%, based on feedback [65]. The technological transformation of the workplace is not a future possibility, but a rapidly approaching reality. For companies and workers, technological adaptation is becoming an inevitable competitive factor, redefining the way work is done, organizational structures, and the skills required. The appearance of large language models (LLMs), is the next significant innovation change. Generative artificial intelligence (genAI), which will be important for businesses with new data generated based on previously created data, can increase productivity, but many people feel it is dangerous for society. According to Jensen Huang, the CEO of Nvidia, the development of artificial intelligence is reaching such a scale that within five years it will be able to pass tests that correspond to human thinking [73]. ChatGPT 4.5 may even surpass humans in the near future [74]. According to Nobel Prize-winning economist Christopher Pissarides, previously urbanization, then the entry of women into work, and now, on the threshold of the fourth industrial revolution, the emergence of a new resource (AI) are once again generating changes. First the power of steam, then electricity, the advent of computers and now automation, AI, which affects the transformation of the labor market. At the moment, robots cause an improvement in productivity, so the most sought-after employees will need IT skills, they must understand data processing, operations, logistics, and have engineering expertise. The reliable, creative employee who has sufficient self-discipline, but at the same time critical thinking, and thanks to his good communication skills can easily share his opinion with his colleagues and managers, continuous development and learning are valued, the love of new technology becomes indispensable [17,75]. Based on the interpretation of this forecast, education definitely forms the basis of economic growth due to higher productivity, innovation skills, and the diffusion of innovation, but a diploma is an increasingly less desirable condition. The attitude, ability to perform, potential inherent in the person, which is authoritative [76]. The application of AI in practice is no longer just a modernization tool, but a strategic tool for solving the most complicated problems [36]. Currently, however, AI is not yet suitable for the standards of industrial control systems (OT—operational technology), as it is not always accurate, which can be particularly risky for the industrial environment. Nokia’s MX Workmate, an industrial AI application developed for this problem, is able to perform an interpreter function, where, using the Generative AI Large Language Model technology, it will be able to translate technical language into common language and vice versa, colloquial expressions can also become suitable for control with its help, employees they will be able to control more complex systems even with lower professional knowledge. This factor can become one of the solutions to the labor shortage [16]. Although AI could potentially displace millions of jobs, it is more likely to play a primarily complementary role, as its introduction may be associated with high costs, social resistance, and ethical dilemmas. The issue of youth employment also requires significant regional studies based on the assumption of heterogeneous competence levels and employee diversity.
CONCLUSIONS The primary aim of this study was to examine sustainable and responsible educational technology efforts and the cooperation of artificial intelligence for the sake of future workers. The study helps to introduce new thinking frameworks, even if it does not offer strong statistical analysis. The empirical foundation was strengthened through a comparison of ESG strategies among Hungarian, German and Nordic companies. According to the results of this research, digital transformation fundamentally transforms the labor market. This is supported by Audi Hungaria’s annual report [13], which identifies flexibility, openness to new knowledge, lifelong learning, and the ability to adapt quickly as the most valued employee attributes in the production sector. In the organizational system, development is stimulated by employees who train themselves from internal motivation and motivate their environment, the role of retraining and further training is enhanced compared to traditional educational frameworks. Several practical proposals aim to stimulate development: the introduction of modular, micro-accredited training systems (e.g., EU DigComp, IBM SkillsBuild); AI-assisted learning path planning (Skill Navigator); the integration of technological and cultural practices (Tech+Humanity Labs); learning through practical experience (e.g., AI coaching), joint innovation incubators bridging education and industry (dual-innovation labs); AI mentoring programs for young people and early-career professionals; and the implementation of digital portfolio-based assessment (e.g., project work, blogs). The transformation of the educational technology market is also fundamentally influenced by regulations. Recognizing the influencing factors in the transformation is the company’s responsibility by creating organizational charts, using organizational network analysis, interactive joint work, and corporate synergies. As practical implications we can conclude, that the key to competitiveness is the ability to innovate, improve the portfolio, control efficiency, community engagement, and continuous motivation. Diversity is a key element of sustainability, and successful transformation requires flexibility, lifelong learning, the practical application of knowledge, and effective recruitment strategies within organizational development. It is in the self-interest of companies that wish to maintain their competitiveness to think about recruitment, primarily to develop with the help of dual training, even in the field of adult training and higher education, but important factors are the development of retraining, professional competences, soft skills, and shortened training programs. Universities are primarily looking for solutions and development results from a scientific point of view, while companies prioritize economic and industrial aspects. According to the research results, the theoretical process of digitization, AI, can make previous automated processes more efficient. From 2025, the report on ESG indicators will be verified by external auditors for compliance with CSRD. If the CSRD data is connected with the financial and production data, the formulation of correlations and directions in the primary stage will be successful. With the use of ESG data, it becomes necessary to localize the data points, connect the data, use AI, and then integrate the conclusions and measurement results into the planning processes. The most important research result of the study is that the fourth goal of the SDG (Quality Education), is compared with the latest educational technology, labor market, and AI-related current issues and the answers are supported by the latest practical data. The study provides evidence, supported by statistical data that the educational technology market is growing dynamically, the labor market is undergoing significant transformation, training is becoming shorter and more digitalized, and soft skills are gaining value. However, these developments alone are not sufficient. The literature review reveals additional challenges, such as the impact of AI on the workforce, the role of ESG in education, data limitations, regulatory lags, gaps in provision, skill shortages driven by AI, the digital divide, the ongoing need for educational reform, and new directions for research. The limitations of the research are that the results of the analyzes are specific to a narrow geographical area and only to specific organizations, and the data revealed for processing can accordingly only affect a small segment of the investigated areas. While the primary data reflect Central European trends, they can form the basis for broader comparative international studies. The future research direction is to expand the geographical boundaries of the research and the number of studied organizations in order to establish the most well founded conclusions. If we compare the test results with the existing literature, the novelty and the theoretical implication of the research is that the role of digitization is supported by a new, unique justification, which includes further innovative thinking and development ideas. AI is becoming an integral part of everyday life, but its use must be underpinned by responsible and ethical conduct from both developers and society. In the spirit of preparation for approaching full employment, effective competitiveness requires digitization developments, as well as the effective cooperation of innovative companies, educational institutions, and government agencies [60]. Developments designed to increase production volume are replaced by the management of labor shortages and the reduction of energy costs, the shift towards technological innovations, and the importance of retraining increases. Productivity within production can also provide a motivating force. Following the possession of system data suitable for the industrial use of AI, conclusions can be drawn and injected into the management process. Efforts concerning sustainable and responsible educational technology and labor market supply can become effective in cooperation with the use of artificial intelligence for the benefit of the workers of the future [11]. Future research should explore the long-term effects of AI on educational equity and corporate responsibility in different regions. In 2024, AI systems accounted for approximately 1%–1.3% of global electricity consumption, a figure projected to rise to 3% by 2030. This underscores the needs to explore energy efficiency and develop green AI strategies [77]. The study’s interdisciplinary approach to the future of education and he labor market transformation aims to address an existing research gap. Empirically, the critical comparison of secondary sources and the mapping of the literature all contribute to setting the direction of future research and point out the existing theoretical and practical shortcomings, according to which the full-scale introduction of AI has regional, industry, ethical, technological, and budgetary limitations, and the introduction of young people into the labor market may have varying results despite appropriate mentoring due to employee diversity and different levels of competence.
DATA AVAILABILITY All data generated from the study are available in the manuscript.
AUTHOR CONTRIBUTIONS Conceptualization and methodology, ZK, VGK and MKS writing—original draft preparation, ZK; writing—review and editing, VGK and MKS; visualization, ZK; supervision, VGK and MKS; All authors have read and agreed to the published version of the manuscript.
| 2025-06-24T00:00:00 |
2025/06/24
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https://wap.hapres.com/htmls/JSR_1750_Detail.html
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[
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"date": "2025/06/23",
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"query": "artificial intelligence labor union"
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Artificial Intelligence and Human Responsibility | SDSU
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Artificial Intelligence and Human Responsibility
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https://cal.sdsu.edu
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... artificial intelligence (AI) technologies in an ethical and sustainable manner. ... work but also when, whether, and why they should be employed, and how to ...
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Define your future in a tech-driven world.
Artificial Intelligence is transforming the world. At SDSU, we invite you to be at the forefront — not just as a coder or a data scientist, but as a critical thinker, a global citizen, and an ethical innovator. This pioneering degree blends technical expertise, ethical insight, and human-centered analysis to prepare you for careers in technology, policy, research, and public engagement.
The Bachelor of Science degree in Artificial Intelligence and Human Responsibility equips you with the knowledge and skills to understand and evaluate artificial intelligence (AI) technologies in an ethical and sustainable manner.
By integrating technical literacy with insights from the social sciences and humanities, this degree will prepare you to navigate the complex landscape of AI use, creating graduates who can think expansively about not only how such technologies work but also when, whether, and why they should be employed, and how to realize their significant benefits while mitigating their dangerous potential for harm.
Why Choose This Degree?
| 2025-06-23T00:00:00 |
https://cal.sdsu.edu/programs/ai
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[
{
"date": "2025/06/23",
"position": 81,
"query": "artificial intelligence labor union"
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Artificial Intelligence: a blueprint for unions and telecom ...
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Artificial Intelligence: a blueprint for unions and telecom companies (joint declaration)
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https://www.uni-europa.org
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Artificial Intelligence: a blueprint for unions and telecom companies (joint declaration) ... employment and social cohesion. + More + Link to documents. 15.
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| 2025-06-23T00:00:00 |
https://www.uni-europa.org/news/artificial-intelligence-a-blueprint-for-unions-and-telecom-companies-joint-declaration/
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[
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"date": "2025/06/23",
"position": 85,
"query": "artificial intelligence labor union"
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The Future of Work Is a Liminal Space
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The Future of Work Is a Liminal Space
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https://www.aei.org
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[
"Sarah Jeddy",
"Brent Orrell"
] |
In the short term, then, AI will tend to transform tasks, increase efficiency, and move workers up the value chain, freeing human labor to focus on higher-order ...
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It’s been another breathless week in the business of projecting how artificial intelligence will reshape the US (and global) labor markets. Following Anthropic CEO Dario Amodei’s warnings of an AI “bloodbath,” several major tech companies announced plans to make significant workforce reductions, citing AI efficiencies as the reason.
LinkedIn co-founder and Netflix board member Reid Hoffman stepped into the conversation in an interview on the Rapid Response podcast with a more measured take on the short- and medium-term future. Hoffman pushed back on the idea that artificial intelligence is driving us toward a white-collar jobs apocalypse. The principal effect of AI, he argues, is job transformation, rather than job destruction. This insight fits well with emerging research that focuses on AI’s effects on tasks—moment-to-moment worker activities—rather than whole jobs.
It’s helpful to think about AI as another chapter in the long story of automation trends: shifting workers away from acting like machines—toiling on information assembly lines, in this case—and toward roles that are creative, strategic, and analytical. The immediate effects will be to boost efficiency in a wide variety of knowledge economy roles that, before the advent of AI, were necessary to help organizations and businesses serve customers and understand their own operations: scheduling, repetitive data entry, internal knowledge management, and research. In these areas, AI can be faster, cheaper, and more accurate.
But almost all jobs are made up of bundles of tasks, some of which are automatable and others not. In the short term, then, AI will tend to transform tasks, increase efficiency, and move workers up the value chain, freeing human labor to focus on higher-order thinking, judgment, and creativity.
Sounds dandy, doesn’t it? The problem with taking too rosy a view of how AI will improve work lies in some of its ancillary effects. First, getting incumbent workers upskilled for their reconfigured jobs isn’t going to be cheap or easy. Retraining will impose financial burdens on companies and cognitive burdens on workers. These are both likely to slow the transition to AI, giving us some breathing room to make adjustments to education, training, and workforce development. Second, by fractionally changing jobs to increase efficiency, companies will eventually have to consolidate their workforces—keeping the most talented and adaptable workers while laying off those who, for whatever reason, are not suited to the new AI-infused tasks.
This raises significant public policy challenges. As we’ve seen with deindustrialization, it is entirely possible, perhaps likely, that government and social responses will lag economic transformation and add to the anxiety and feeling of dislocation workers experience. This suggests that what is most needed right now is a close examination of “what if” scenarios to help policymakers think through transition dynamics and map out frameworks for response. For those workers who find themselves on the losing side of this equation, we need to consider what kinds of economic assistance and workforce support might be needed to help them retool and ensure they are not left feeling adrift in the liminal space of the AI transition with no clear path to finding a new place in the economy.
| 2025-06-23T00:00:00 |
2025/06/23
|
https://www.aei.org/domestic-policy/the-future-of-work-is-a-liminal-space/
|
[
{
"date": "2025/06/23",
"position": 10,
"query": "future of work AI"
}
] |
Artificial Intelligence Archives
|
Artificial Intelligence Archives
|
https://futureofworkexchange.com
|
[
"Christopher J. Dwyer",
"John Yuva"
] |
Companies are using generative AI to better manage their workforce and respond to changing job market conditions. The technology analyzes large amounts of ...
|
June 14, 2022. Harvard Club, Boston, MA. 6:17am.
I sit nervously in the lobby, watching a sunny Tuesday come to fruition while the bustling Boston workday begins to awaken. It’s been over two years since I last attended a conference, let alone spoke at a corporate event (you know, the pandemic). And now, with the members of the Ardent Partners team either already in the building or on their way into the venue, I’m about to kick off the very first Future of Work Exchange LIVE executive roundtable event. Under a year ago, we launched the Future of Work Exchange destination site, a go-to, everyday source of workforce, talent, HR, technology, and Future of Work news, resources, insights, and intelligence. Deep breaths.
June 10, 2025. Harvard Club, Boston, MA. 6:43am.
Wow…this is the FOURTH iteration of this event. Let’s rock!
Consider this your Rolling Stone-style prologue to a very special recap of the fourth annual Future of Work Exchange LIVE executive roundtable. The reflections above? They’re not just scene-setting—they’re genuine moments from two very different mornings that bookended something extraordinary.
As I sit here replaying the day—the powerful conversations, the handshakes and hugs, the unforgettable Harvard Club lunch (yes, the Sacchetti purses!), and the unmistakable feeling that something real happened—I can’t help but smile.
So, with that spirit in mind… let’s dive in.
The Future of Work, Established 2025
The anchor of the day’s discussions was unveiled during the welcome address. It has become clear that we’re entering a transformational era—one defined by adaptability, AI-driven collaboration, and reimagined talent strategies. Here’s how I kicked off the event:
🔹 Leadership for the Age of Agility (and Adaptability). Today’s workforce demands leaders who embrace fluidity. The conversation underscored that agility isn’t just a buzzword; it’s a leadership imperative. Organizations that foster adaptable cultures will be best positioned to thrive.
🤖 AI: The Ultimate Workforce Partner. AI is not here to replace human ingenuity—it’s here to elevate it. Thought leaders explored AI’s role as a trusted ally in talent acquisition, workforce planning, and productivity enhancement, reinforcing that strategic adoption is the key to unlocking its full potential.
🔄 Talent Tech Ecosystems (Reimagined). The event highlighted a fundamental shift in how companies build and integrate talent technologies. The ecosystem approach is replacing fragmented solutions, enabling seamless collaboration between platforms, recruiters, and workforce leaders.
🚀 Talent as a Dynamic Asset. Gone are the days of static workforce models. Talent today is fluid, multifaceted, and deeply integrated into business growth. The session reinforced the importance of viewing talent through a dynamic, evolving lens rather than conventional job descriptions.
AI in Talent Tech: Enabling a New Era of Hiring
And, not only that, AI is the perfect complement to two major hiring movements today: skills-based hiring and direct sourcing. Opptly CEO Lori Hock and Beeline SVP of Global Customer Success Craig Coe teamed up for a morning panel that focused on the implications of AI, how businesses can trust artificial intelligence, and why AI is the foundational form of automation that will supercharge recruitment, hiring, extended workforce management innovation, etc.
Expert Panel Key Takeaway: Trust AI, deploy AI, leverage AI, and consider it the ultimate workforce partner…in time.
Yes, Direct Sourcing is For Real
For many organizations, direct sourcing is like Santa Claus: some believe wholeheartedly, others remain skeptical, and a few have yet to truly grasp its potential. But one thing is clear—it’s no longer a theoretical strategy; it’s a proven force in modern workforce planning. nextSource’s Deb Bergevine and Adam Klaucke, along with TalentProcure’s Denise Stalker, discussed why direct sourcing is emerging as an essential pillar in workforce agility. And for those still on the fence? The conversation made it clear—embracing direct sourcing isn’t about chasing trends; it’s about future-proofing how organizations attract, deploy, and retain top talent.
Expert Panel Key Takeaway: Direct sourcing is taking longer than anticipated to come to fruition, however, the companies that enable a deliberate approach towards implementing it and using it will reap the rewards.
The Time for Change? Right Now
One of the many highlights of last week’s event was the incredible dynamic between AMS’s Matthew Rodger and RSM’s Lizzie Parnell, who tackled the very-relevant topic of extended workforce management evolution. Matthew spoke about how CW programs must change given the impact and power of the extended workforce (along with why the talent technology ecosystem must also evolve), while Lizzie discussed her vast experience running extended workforce programs and the work, effort, and strategy required to spark a new era of change.
Expert Panel Key Takeaway: With the extended workforce comprising upwards of 50% of the total enterprise talent pool, businesses must act now to push their programs into a new era of value, impact, and innovation.
The Future of Work Awaits
As I wrapped up the day, I couldn’t help but take one final look around the room. What began as a nervous wait in the Harvard Club lobby back in 2022 has blossomed into something far more meaningful than an event series. Future of Work Exchange LIVE has become a movement—a space where ideas ignite, strategies evolve, and leaders connect over a shared ambition to shape what’s next. If this year taught us anything, it’s that the Future of Work isn’t on the horizon—it’s here, unfolding in every thoughtful conversation, every handshake, every bold commitment to rethink what’s possible. Until next year… keep driving the change. Keep leading forward. The future needs us. Now.
(And, to all of those wondering: Sawyer, the Chief Puppy Officer of Ardent Partners and the Future of Work Exchange, was not allowed entry into this year’s event…but we’re working on Harvard Club rules for next year.)
| 2025-06-23T00:00:00 |
https://futureofworkexchange.com/tag/artificial-intelligence/
|
[
{
"date": "2025/06/23",
"position": 42,
"query": "future of work AI"
}
] |
|
AI Archives
|
The Future of Work Exchange
|
https://futureofworkexchange.com
|
[
"Christopher J. Dwyer",
"John Yuva"
] |
Companies are using generative AI to better manage their workforce and respond to changing job market conditions. The technology analyzes large amounts of ...
|
June 14, 2022. Harvard Club, Boston, MA. 6:17am.
I sit nervously in the lobby, watching a sunny Tuesday come to fruition while the bustling Boston workday begins to awaken. It’s been over two years since I last attended a conference, let alone spoke at a corporate event (you know, the pandemic). And now, with the members of the Ardent Partners team either already in the building or on their way into the venue, I’m about to kick off the very first Future of Work Exchange LIVE executive roundtable event. Under a year ago, we launched the Future of Work Exchange destination site, a go-to, everyday source of workforce, talent, HR, technology, and Future of Work news, resources, insights, and intelligence. Deep breaths.
June 10, 2025. Harvard Club, Boston, MA. 6:43am.
Wow…this is the FOURTH iteration of this event. Let’s rock!
Consider this your Rolling Stone-style prologue to a very special recap of the fourth annual Future of Work Exchange LIVE executive roundtable. The reflections above? They’re not just scene-setting—they’re genuine moments from two very different mornings that bookended something extraordinary.
As I sit here replaying the day—the powerful conversations, the handshakes and hugs, the unforgettable Harvard Club lunch (yes, the Sacchetti purses!), and the unmistakable feeling that something real happened—I can’t help but smile.
So, with that spirit in mind… let’s dive in.
The Future of Work, Established 2025
The anchor of the day’s discussions was unveiled during the welcome address. It has become clear that we’re entering a transformational era—one defined by adaptability, AI-driven collaboration, and reimagined talent strategies. Here’s how I kicked off the event:
🔹 Leadership for the Age of Agility (and Adaptability). Today’s workforce demands leaders who embrace fluidity. The conversation underscored that agility isn’t just a buzzword; it’s a leadership imperative. Organizations that foster adaptable cultures will be best positioned to thrive.
🤖 AI: The Ultimate Workforce Partner. AI is not here to replace human ingenuity—it’s here to elevate it. Thought leaders explored AI’s role as a trusted ally in talent acquisition, workforce planning, and productivity enhancement, reinforcing that strategic adoption is the key to unlocking its full potential.
🔄 Talent Tech Ecosystems (Reimagined). The event highlighted a fundamental shift in how companies build and integrate talent technologies. The ecosystem approach is replacing fragmented solutions, enabling seamless collaboration between platforms, recruiters, and workforce leaders.
🚀 Talent as a Dynamic Asset. Gone are the days of static workforce models. Talent today is fluid, multifaceted, and deeply integrated into business growth. The session reinforced the importance of viewing talent through a dynamic, evolving lens rather than conventional job descriptions.
AI in Talent Tech: Enabling a New Era of Hiring
And, not only that, AI is the perfect complement to two major hiring movements today: skills-based hiring and direct sourcing. Opptly CEO Lori Hock and Beeline SVP of Global Customer Success Craig Coe teamed up for a morning panel that focused on the implications of AI, how businesses can trust artificial intelligence, and why AI is the foundational form of automation that will supercharge recruitment, hiring, extended workforce management innovation, etc.
Expert Panel Key Takeaway: Trust AI, deploy AI, leverage AI, and consider it the ultimate workforce partner…in time.
Yes, Direct Sourcing is For Real
For many organizations, direct sourcing is like Santa Claus: some believe wholeheartedly, others remain skeptical, and a few have yet to truly grasp its potential. But one thing is clear—it’s no longer a theoretical strategy; it’s a proven force in modern workforce planning. nextSource’s Deb Bergevine and Adam Klaucke, along with TalentProcure’s Denise Stalker, discussed why direct sourcing is emerging as an essential pillar in workforce agility. And for those still on the fence? The conversation made it clear—embracing direct sourcing isn’t about chasing trends; it’s about future-proofing how organizations attract, deploy, and retain top talent.
Expert Panel Key Takeaway: Direct sourcing is taking longer than anticipated to come to fruition, however, the companies that enable a deliberate approach towards implementing it and using it will reap the rewards.
The Time for Change? Right Now
One of the many highlights of last week’s event was the incredible dynamic between AMS’s Matthew Rodger and RSM’s Lizzie Parnell, who tackled the very-relevant topic of extended workforce management evolution. Matthew spoke about how CW programs must change given the impact and power of the extended workforce (along with why the talent technology ecosystem must also evolve), while Lizzie discussed her vast experience running extended workforce programs and the work, effort, and strategy required to spark a new era of change.
Expert Panel Key Takeaway: With the extended workforce comprising upwards of 50% of the total enterprise talent pool, businesses must act now to push their programs into a new era of value, impact, and innovation.
The Future of Work Awaits
As I wrapped up the day, I couldn’t help but take one final look around the room. What began as a nervous wait in the Harvard Club lobby back in 2022 has blossomed into something far more meaningful than an event series. Future of Work Exchange LIVE has become a movement—a space where ideas ignite, strategies evolve, and leaders connect over a shared ambition to shape what’s next. If this year taught us anything, it’s that the Future of Work isn’t on the horizon—it’s here, unfolding in every thoughtful conversation, every handshake, every bold commitment to rethink what’s possible. Until next year… keep driving the change. Keep leading forward. The future needs us. Now.
(And, to all of those wondering: Sawyer, the Chief Puppy Officer of Ardent Partners and the Future of Work Exchange, was not allowed entry into this year’s event…but we’re working on Harvard Club rules for next year.)
| 2025-06-23T00:00:00 |
https://futureofworkexchange.com/tag/ai/
|
[
{
"date": "2025/06/23",
"position": 53,
"query": "future of work AI"
}
] |
|
AI and Junior Talent: Building the Workforce of the Future
|
AI and Junior Talent: Building the Workforce of the Future
|
https://mthree.com
|
[] |
As artificial intelligence continues to reshape industries worldwide, the need for forward-thinking workforce strategies has never been greater.
|
As artificial intelligence continues to reshape industries worldwide, the need for forward-thinking workforce strategies has never been greater. Companies are under pressure to stay ahead of rapid technological evolution, but many find themselves constrained by outdated hiring models and skills shortages. The workforce of the future isn’t just about advanced tools or machine learning algorithms; it’s about people. Specifically, it's about equipping junior talent with the AI literacy and hands-on experience they need to make meaningful contributions from day one. That’s where models like Hire Train Deploy (HTD) come in. In this blog, we’ll explore how mthree’s HTD model helps organisations embed junior talent into their AI strategies, close skills gaps, and build ethical, future-ready teams.
> The rise of AI in the workplace AI is no longer a distant vision or niche field. It’s embedded in everything from data analytics and cybersecurity to customer service and supply chain optimisation. According to a 2024 McKinsey report, more than 50% of organisations have already adopted AI in at least one function, and this number is expected to continue growing. But while interest is high, implementation remains uneven, often bottlenecked by the lack of talent capable of understanding, deploying, and iterating AI tools. This is especially true in junior-to-mid-level roles, where a blend of foundational tech skills and AI fluency is becoming critical. These individuals will be responsible for integrating automation into daily processes, maintaining AI-driven systems, and adapting to emerging technologies. They represent the backbone of scalable digital transformation.
> Why junior talent matters more than ever Traditionally, companies have focused on hiring senior professionals when introducing new technologies like AI. While that approach brings immediate experience, it is not scalable or sustainable in the long term. Salaries are high, the talent pool is limited, and cultural fit can vary. For example, someone coming from a startup may struggle to adapt to the pace and structure of a highly regulated enterprise environment. Junior talent, on the other hand, can be trained to align with your organisation’s specific tech stack, values, and working style from the outset. In contrast, junior talent offers several strategic advantages: Adaptability : Early-career professionals are more open to learning and working in dynamic environments.
Longevity : Training junior staff enables organisations to develop and retain talent as they progress through the ranks.
Diversity : Programmes focused on developing junior talent can be designed to enhance representation across gender, socioeconomic backgrounds, and geographic areas.
Cost-efficiency: Investing in junior talent offers a more sustainable financial model. Developing entry-level hires is typically more cost-effective than recruiting senior AI specialists, whose salaries and market competition continue to rise. By investing in junior professionals now, organisations lay the groundwork for a resilient, future-ready workforce.
> Hire-Train-Deploy: A smarter model for AI workforce development The hire-train-deploy model is gaining traction as a strategic solution for building internal tech and AI capabilities. It flips the script on traditional hiring by focusing on potential over pedigree. Here’s how it works: Hire: Candidates are selected based on aptitude, motivation, and alignment with the company’s long-term needs. Train: They undergo intensive training tailored to the hiring organisation’s specific tech stack, AI tools, and workflows. Deploy: Graduates are placed directly into teams where they can apply their new skills immediately. Unlike general bootcamps or university programmes, HTD provides a customised bridge between education and employment. It ensures that junior talent enters the workforce not only job-ready but company-ready.
> Tailored AI training for real-world application For organisations adopting AI, off-the-shelf training isn’t enough. What’s needed is role-specific, context-aware learning that mirrors the organisation’s actual tech environment. With Hire Train Deploy, companies can work with providers like mthree to create training programmes that: Cover foundational AI concepts such as supervised vs. unsupervised learning, NLP, and model evaluation
Incorporate hands-on projects using the company's real or simulated datasets
Teach junior professionals how to integrate AI into DevOps, software development, data engineering, or business analysis workflows
Reinforce responsible AI principles, including bias mitigation, explainability, and compliance This approach ensures that AI doesn’t remain siloed in R&D departments but instead becomes part of the everyday operational DNA.
> The long-term payoff: from junior to mid-level impact One of the biggest workforce challenges companies face today is the mid-level talent gap. These are the individuals who combine a few years of hands-on experience with deep organisational knowledge. They are key to driving strategic initiatives, mentoring new hires, and leading agile product teams. By reskilling and nurturing junior professionals from the start, companies create a reliable internal pipeline of future mid-level leaders. HTD models accelerate this process by ensuring those individuals start their careers with a solid technical foundation and a strong understanding of the business context. Moreover, junior employees trained in AI from the outset are better equipped to keep up with its rapid evolution. They are more likely to embrace ongoing learning and contribute to the continuous improvement loops that define successful AI adoption.
> Partnering with mthree for workforce transformation At mthree, we specialise in hire-train-deploy programmes that align emerging talent with the real needs of global employers. Our AI-aligned tracks are designed in collaboration with hiring teams to deliver immediate value and long-term growth. From building pipelines of diverse candidates to customising curricula around company-specific AI workflows, we help organisations future-proof their workforce from the ground up. Whether you’re launching new AI initiatives or scaling existing ones, mthree's approach ensures your teams have the people, skills, and mindset to thrive. The future of work is not just AI-powered; it’s people-powered. And the best way to prepare for it is by building and investing in the next generation of junior talent.
> Conclusion: future-proofing starts today The convergence of AI and workforce transformation isn’t a challenge to solve in the future; it’s an opportunity to seize now. By adopting forward-looking models like hire-train-deploy and partnering with workforce development experts like mthree, companies can train junior talent not just to adapt to change, but to drive it. In doing so, they unlock a competitive edge rooted in agility, innovation, and inclusivity, one that will carry them confidently into the future of work powered by AI. If you're ready to invest in the future of your workforce through AI and junior talent, we're here to help. Learn more about our AI offerings.
| 2025-06-23T00:00:00 |
https://mthree.com/insights/ai-and-junior-talent-building-the-workforce-of-the-future/
|
[
{
"date": "2025/06/23",
"position": 76,
"query": "future of work AI"
}
] |
|
Proportion of jobs at high risk of automation by 2030 ...
|
Proportion of jobs at high risk of automation by 2030 by select country
|
https://www.statista.com
|
[
"Jose Sanchez",
"Jun"
] |
This statistic shows the share of jobs at risk of automation by early 2030 in the United States and in the United Kingdom, according to three studies ...
|
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PwC. (March 2, 2017). Share of jobs at high risk of automation by early 2030 in select countries worldwide, by study, as of 2017 [Graph]. In Statista . Retrieved July 15, 2025, from https://www.statista.com/statistics/716847/worldwide-proportion-of-jobs-at-high-risk-of-automation/
PwC. "Share of jobs at high risk of automation by early 2030 in select countries worldwide, by study, as of 2017." Chart. March 2, 2017. Statista. Accessed July 15, 2025. https://www.statista.com/statistics/716847/worldwide-proportion-of-jobs-at-high-risk-of-automation/
PwC. (2017). Share of jobs at high risk of automation by early 2030 in select countries worldwide, by study, as of 2017 . Statista . Statista Inc.. Accessed: July 15, 2025. https://www.statista.com/statistics/716847/worldwide-proportion-of-jobs-at-high-risk-of-automation/
PwC. "Share of Jobs at High Risk of Automation by Early 2030 in Select Countries Worldwide, by Study, as of 2017." Statista , Statista Inc., 2 Mar 2017, https://www.statista.com/statistics/716847/worldwide-proportion-of-jobs-at-high-risk-of-automation/
PwC, Share of jobs at high risk of automation by early 2030 in select countries worldwide, by study, as of 2017 Statista, https://www.statista.com/statistics/716847/worldwide-proportion-of-jobs-at-high-risk-of-automation/ (last visited July 15, 2025)
Share of jobs at high risk of automation by early 2030 in select countries worldwide, by study, as of 2017 [Graph], PwC, March 2, 2017. [Online]. Available: https://www.statista.com/statistics/716847/worldwide-proportion-of-jobs-at-high-risk-of-automation/
| 2025-06-23T00:00:00 |
https://www.statista.com/statistics/716847/worldwide-proportion-of-jobs-at-high-risk-of-automation/
|
[
{
"date": "2025/06/23",
"position": 14,
"query": "job automation statistics"
}
] |
|
Robots Aim to Tackle the Hardest Job in Warehousing
|
Robots Aim to Tackle the Hardest Job in Warehousing
|
https://www.eweek.com
|
[
"Megan Crouse",
"Written By",
"Megan Crouse Has A Decade Of Experience In Business-To-Business News",
"Feature Writing",
"Including As First A Writer",
"Then The Editor Of Manufacturing.Net. Her News",
"Feature Stories Have Appeared In Military",
"Aerospace Electronics",
"Fierce Wireless",
"Techrepublic"
] |
Multiple companies have sold robots for one of the most difficult warehouse jobs to automate: loading and unloading trucks. According to the Wall Street Journal ...
|
eWEEK content and product recommendations are editorially independent. We may make money when you click on links to our partners. Learn More.
Multiple companies have sold robots for one of the most difficult warehouse jobs to automate: loading and unloading trucks.
According to the Wall Street Journal, loading and unloading is the “Holy Grail of warehouse logistics.” These breakthroughs became feasible only after the development of newer vision sensors, smarter AI algorithms, and lightning-fast image-processing capabilities.
Which companies are involved?
The Journal profiled several companies:
Ambi Robotics : Creator of the AmbiStack robotic stacking system, designed to assess weight, fragility, and center of gravity for optimal palletization.
: Creator of the AmbiStack robotic stacking system, designed to assess weight, fragility, and center of gravity for optimal palletization. Boston Dynamics : Developer of Stretch, a large robotic arm equipped with a vacuum-grip suction hand for handling packages.
: Developer of Stretch, a large robotic arm equipped with a vacuum-grip suction hand for handling packages. Dexterity : Supplies truck-loading robots to FedEx, contributing automation to the courier giant’s logistics operations.
: Supplies truck-loading robots to FedEx, contributing automation to the courier giant’s logistics operations. Fox Robotics : Manufacturer of autonomous forklifts that handle both loading and unloading tasks with minimal human input.
: Manufacturer of autonomous forklifts that handle both loading and unloading tasks with minimal human input. DHL: Already using seven Stretch robots in its warehouses and has signed a contract for 1,000 more, highlighting a strong commitment to automation.
Why is loading and unloading trucks difficult for robots?
While these companies are making strides, the task remains one of the toughest to automate in warehouse logistics. Automating the loading and unloading of trucks remains a challenge because it requires a broad range of motion and necessitates decision-making regarding package placements.
The worker, or robot, must navigate into the deepest corners of a trailer. Loading packages also involves stacking the heaviest boxes at the bottom to prevent damage, while also considering how to leverage all available space.
For example, the AmbiStack system analyzes an item’s weight, fragility, and center of gravity to determine optimal placement on a pallet. It also aims to pack the highest possible number of boxes per pallet.
Even the most advanced of the robots still face limitations. The Stretch model cannot pick up soft-sided bags and struggles with thin or irregularly shaped packages.
As in other fields, warehouse workers have expressed concern about potential job displacement. However, proponents of automation argue that loading and unloading trucks is physically demanding work, especially in extreme weather conditions, such as winter or summer.
While challenges remain, the growing involvement of robotics in truck loading signals a turning point in how humans and machines share the warehouse floor.
Read about Foxconn’s efforts to use humanoid robots to assemble advanced AI chips in US factories.
| 2025-06-23T00:00:00 |
2025/06/23
|
https://www.eweek.com/news/robotics-automated-loading-unloading-warehouse/
|
[
{
"date": "2025/06/23",
"position": 8,
"query": "robotics job displacement"
}
] |
Four Actions to Elevate Your Workforce with AI
|
Four actions to elevate your workforce with AI
|
https://kpmg.com
|
[] |
Real-world examples of workforce AI adoption ... believe that automation will provide them with new career opportunities. ... say their organizations have shared ...
|
A quiet shift is happening in workplaces across America. After years of concern and unease, something hopeful is taking shape—employers and employees are finally finding common ground. Together, they’re accepting and embracing AI adoption and its benefits, reshaping how we work, collaborate, and succeed.
Here’s what the most forward-thinking companies already know: When you’re honest about automation and invest in your people’s growth, something remarkable happens. Employees stay. Teams innovate. Futures get brighter. Want to be part of this change?
Four simple but powerful actions are helping businesses like yours build a workforce transformation that’s both stronger and more strategic. Let’s explore them together.
| 2025-06-17T00:00:00 |
2025/06/17
|
https://kpmg.com/us/en/articles/2025/four-key-actions-elevate-workforce-ai.html
|
[
{
"date": "2025/06/23",
"position": 50,
"query": "workplace AI adoption"
}
] |
Adoption of AI in organizations 2022-2023, by region
|
AI adoption in companies 2022-2023, by region
|
https://www.statista.com
|
[
"Bergur Thormundsson",
"Jun"
] |
The adoption of artificial intelligence (AI) by organizations worldwide has increased about **** percent from 2022 to 2023.
|
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Stanford University. (April 15, 2024). Adoption share of artificial intelligence (AI) by organizations worldwide from 2022 to 2023, by region [Graph]. In Statista . Retrieved July 15, 2025, from https://www.statista.com/statistics/1472617/ai-adoption-companies-by-region/
Stanford University. "Adoption share of artificial intelligence (AI) by organizations worldwide from 2022 to 2023, by region." Chart. April 15, 2024. Statista. Accessed July 15, 2025. https://www.statista.com/statistics/1472617/ai-adoption-companies-by-region/
Stanford University. (2024). Adoption share of artificial intelligence (AI) by organizations worldwide from 2022 to 2023, by region . Statista . Statista Inc.. Accessed: July 15, 2025. https://www.statista.com/statistics/1472617/ai-adoption-companies-by-region/
Stanford University. "Adoption Share of Artificial Intelligence (Ai) by Organizations Worldwide from 2022 to 2023, by Region." Statista , Statista Inc., 15 Apr 2024, https://www.statista.com/statistics/1472617/ai-adoption-companies-by-region/
Stanford University, Adoption share of artificial intelligence (AI) by organizations worldwide from 2022 to 2023, by region Statista, https://www.statista.com/statistics/1472617/ai-adoption-companies-by-region/ (last visited July 15, 2025)
Adoption share of artificial intelligence (AI) by organizations worldwide from 2022 to 2023, by region [Graph], Stanford University, April 15, 2024. [Online]. Available: https://www.statista.com/statistics/1472617/ai-adoption-companies-by-region/
| 2025-06-23T00:00:00 |
https://www.statista.com/statistics/1472617/ai-adoption-companies-by-region/
|
[
{
"date": "2025/06/23",
"position": 73,
"query": "workplace AI adoption"
}
] |
|
AI vs. Human Workforce: Job Displacement and Creation Stats
|
AI vs. Human Workforce: Job Displacement and Creation Stats
|
https://patentpc.com
|
[
"Bao Tran",
"Patent Attorney"
] |
But with every advancement comes the concern—will AI take jobs away from people? Or will it create more opportunities? The reality is a mix of ...
|
Artificial Intelligence (AI) is transforming industries worldwide. It’s automating tasks, increasing efficiency, and even taking on roles once thought to be uniquely human. But with every advancement comes the concern—will AI take jobs away from people? Or will it create more opportunities? The reality is a mix of both. Some jobs will disappear, others will evolve, and entirely new roles will emerge.
1. AI automation could displace 85 million jobs globally by 2025
AI is automating many tasks once performed by humans. In sectors like manufacturing, customer service, and finance, companies are increasingly relying on AI-powered tools to boost productivity.
How to prepare:
If you’re in a repetitive or routine-based job, now is the time to upskill.
Learn how to work alongside AI rather than compete with it.
Explore career paths that require creativity, emotional intelligence, or hands-on work—areas where AI still struggles.
2. 97 million new jobs could be created by AI-driven automation by 2025
While AI eliminates certain roles, it also creates demand for new skills. AI engineers, cybersecurity experts, and data analysts are all in high demand.
How to take advantage:
Consider reskilling in AI-related fields, even if you’re not in tech.
Look into certifications in AI, cloud computing, or data science.
Stay flexible—many future roles haven’t even been invented yet.
3. By 2030, up to 800 million jobs could be lost to automation worldwide
This is a massive shift that will affect nearly every industry. Blue-collar jobs in manufacturing and logistics will be impacted the most, but even white-collar roles in finance, legal, and healthcare will see AI-driven changes.
What to do now:
Identify how your industry is changing.
Stay updated on AI developments in your field.
Build transferable skills that work across different industries.
4. AI is expected to replace 16% of all U.S. jobs by 2030
Automation is coming faster than many people realize. Businesses are using AI for everything from customer support chatbots to medical diagnoses.
How to stay relevant:
If your job involves repetitive tasks, start learning skills that require judgment, creativity, or interpersonal skills.
Consider roles that involve managing AI rather than being replaced by it.
5. 30% of all jobs could be automated by the mid-2030s
AI is getting better at tasks traditionally performed by humans, from driving trucks to writing reports. Many routine-based professions will see a shift toward automation.
Smart moves:
Adapt by learning to work with AI tools in your industry.
Start thinking about how AI can complement your work rather than replace it.
6. 60% of all occupations have at least 30% of tasks that could be automated
Most jobs won’t disappear completely, but they will change. AI can take over routine parts of a job, allowing employees to focus on more complex tasks.
How to prepare:
Find ways to integrate AI tools into your daily work.
Develop problem-solving and decision-making skills, which AI struggles with.
7. AI could increase global GDP by $15.7 trillion by 2030
AI isn’t just about replacing jobs—it’s about driving economic growth. Industries using AI are becoming more productive and efficient.
How to benefit:
Business owners should explore AI tools to improve efficiency.
Employees should learn AI-driven tools used in their industries.
8. The AI industry could generate 97 million new high-skill jobs globally by 2025
Jobs like AI ethics specialists, AI trainers, and automation engineers didn’t exist a few years ago but are now in high demand.
Steps to take:
If you’re interested in tech, explore careers in AI-related fields.
Even in non-tech jobs, understanding AI can make you more valuable.
9. 14% of the global workforce may need to switch occupations by 2030 due to AI
Automation will force millions of workers to change careers.
How to stay ahead:
Start looking at career transitions now instead of waiting until it’s too late.
Be open to learning new skills and moving into adjacent industries.
10. Over 50% of companies expect automation to lead to net job creation
Many companies see AI as an opportunity to expand rather than replace workers.
What this means for you:
Keep an eye on how your company is using AI.
Look for roles that involve AI implementation and oversight.
11. 75 million jobs may be displaced, but 133 million new roles could emerge by 2022
While AI will replace some jobs, it will also create new opportunities.
Smart move:
Look at job postings to see which skills are in demand.
12. AI adoption in the workplace could add $13 trillion to the global economy by 2030
Businesses investing in AI will have a competitive advantage.
If you’re a business owner:
Start integrating AI tools into your operations now.
13. Up to 45% of paid activities could be automated using current technology
AI can take over tasks in industries like retail, transportation, and customer service.
How to stay valuable:
Work on skills that require human judgment, such as leadership and strategy.
14. AI and automation could create a demand for 58 million new jobs in the next few years
AI isn’t just eliminating jobs—it’s shifting the workforce toward new roles.
What to do:
Consider pivoting into fields where AI is expanding opportunities.
15. AI-related job postings increased by 32% between 2019 and 2022
AI jobs are growing rapidly.
Actionable step:
If you’re job hunting, look for roles related to AI and automation.
16. AI could automate 20% of current human tasks by 2025
Automation is coming faster than most expect.
What this means for you:
Start learning how to work with AI rather than against it.
17. AI-driven automation could replace 40% of jobs that require repetitive tasks
Jobs involving routine, predictable work—such as data entry, assembly line work, and basic administrative tasks—are at the highest risk of automation. AI-driven software and robots can complete these tasks faster and with fewer errors than humans.
How to stay relevant:
If your job involves repetitive tasks, explore ways to automate parts of your work so you can focus on higher-value activities.
Learn new skills that require human judgment, creativity, or emotional intelligence, which AI struggles to replicate.
18. The healthcare industry could see AI replace 30% of administrative roles
Healthcare administration involves a lot of paperwork, scheduling, and data entry—all tasks AI can handle efficiently. Hospitals and clinics are increasingly adopting AI to manage medical records, insurance claims, and patient scheduling.
How healthcare professionals can adapt:
Administrative staff should consider upskilling in healthcare IT and AI-driven software to stay relevant.
Medical professionals should embrace AI-powered diagnostic tools rather than resist them, as they can enhance efficiency and accuracy.
19. AI is expected to increase the productivity of workers by up to 40%
AI doesn’t just replace jobs; it also enhances human productivity. Many professionals are using AI to analyze data, generate reports, and automate routine processes, freeing them up for more strategic work.
How to leverage AI for productivity:
Learn how AI tools like ChatGPT, automation software, and data analytics platforms can help streamline your workflow.
Focus on tasks that require human creativity, strategic thinking, and relationship-building.
20. Robotic Process Automation (RPA) could replace 230 million knowledge worker jobs
RPA is an AI-powered software that mimics human actions in digital systems. It’s already replacing routine office work in banking, insurance, and customer service.
Steps to take:
If you work in an industry with high automation potential, develop skills in problem-solving and decision-making.
Consider learning how to implement and manage RPA solutions rather than being replaced by them.
21. By 2025, 50% of all work tasks will be handled by machines
Businesses are rapidly implementing AI-driven automation, meaning half of all workplace activities could soon be AI-powered.
What you can do:
If you’re an employee, learn to work with AI rather than fear it.
If you’re a business owner, start integrating AI tools now to stay competitive.
22. AI could eliminate 6% of U.S. jobs in the next five years
Certain industries will be hit harder than others. Manufacturing, customer support, and administrative roles are at the highest risk.
How to safeguard your career:
Develop a growth mindset and be willing to adapt to change.
Stay informed about how AI is being used in your field.
23. AI-related job openings have grown by over 450% since 2013
AI is creating jobs at a rapid pace, especially in tech-related fields like data science, machine learning, and cybersecurity.
How to break into AI-driven roles:
Take online courses in AI and data science, even if you’re in a non-technical field.
Look for opportunities in AI implementation within your industry.
24. 35% of businesses are already using AI in some form for workforce management
AI is helping businesses optimize scheduling, hiring, and performance tracking. Companies use AI-driven HR tools to improve hiring decisions and employee engagement.
How workers can adapt:
If you’re in HR, learn how AI-powered recruitment and employee engagement tools work.
If you’re an employee, understand how AI influences hiring and performance evaluations in your industry.
25. Companies adopting AI expect revenue increases of up to 38% by 2035
Businesses that successfully integrate AI can expect significant financial growth due to increased efficiency and better decision-making.
How to prepare:
Business owners should start investing in AI-driven solutions now.
Employees should develop skills in AI-assisted decision-making and analytics.
26. 70% of employers believe AI will create more jobs than it eliminates
Despite concerns about job losses, many business leaders believe AI will lead to net job growth by improving efficiency and creating new opportunities.
What this means for you:
Instead of fearing AI, look for ways to work alongside it.
Stay adaptable and be willing to learn new skills.
27. AI could replace up to 85% of customer service interactions by 2025
Chatbots and virtual assistants are already handling a large portion of customer service inquiries. AI can resolve basic issues, reducing the need for human representatives.
How to stay competitive in customer service:
Develop skills in handling complex customer issues that AI cannot resolve.
Focus on personalizing customer interactions, an area where AI still falls short.
28. AI adoption could contribute up to 26% increase in GDP for local economies
Cities and regions that embrace AI will see economic growth. Businesses that adopt AI early will have a significant advantage.
What businesses should do:
Invest in AI-powered tools to improve efficiency.
Train employees to work with AI rather than against it.
29. Automation could impact 375 million workers worldwide by 2030
Millions of workers will need to adapt as AI changes the job market. The impact will be uneven, with some industries benefiting more than others.
How to future-proof your career:
Stay updated on AI trends in your field.
Build skills that AI cannot easily replicate, such as leadership, communication, and creativity.
30. Over 40% of HR professionals believe AI will be a key driver of workforce transformation
AI is revolutionizing hiring, training, and workforce management. HR departments are using AI to streamline recruitment, predict employee performance, and improve engagement.
How to adapt if you’re in HR:
Learn how AI-driven HR tools work.
Focus on soft skills like employee engagement and company culture, which AI cannot replace.
wrapping it up
AI is no longer a futuristic concept—it is here, transforming industries at an unprecedented rate. The workforce is evolving, and the way we work will never be the same.
While automation will replace certain jobs, it will also create new opportunities that didn’t exist before. The key takeaway is that AI isn’t just about job loss—it’s about job transformation.
For employees, the best approach is to adapt, reskill, and embrace AI rather than resist it.
Jobs that rely on repetitive, routine tasks are at the highest risk of automation, so professionals in these roles must develop new skills that leverage creativity, emotional intelligence, and problem-solving—areas where AI still struggles.
| 2025-07-02T00:00:00 |
2025/07/02
|
https://patentpc.com/blog/ai-vs-human-workforce-job-displacement-and-creation-stats
|
[
{
"date": "2025/06/24",
"position": 62,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/24",
"position": 79,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/24",
"position": 68,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/24",
"position": 61,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/24",
"position": 64,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/24",
"position": 65,
"query": "AI job creation vs elimination"
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"date": "2025/06/24",
"position": 62,
"query": "AI job creation vs elimination"
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Navigating Labor's Response to AI | Insight - Baker McKenzie
|
Navigating Labor's Response to AI
|
https://www.bakermckenzie.com
|
[] |
Some unions have begun negotiating their own safeguards to address growing concerns about the impact that AI may have on union jobs. For example ...
|
As AI adoption accelerates across workplaces, labor organizations around the world are beginning to take notice—and action. The current regulatory focus in the US centers on state-specific laws like those in California, Illinois, Colorado and New York City, but the labor implications of AI are quickly becoming a front-line issue for unions, potentially signaling a new wave of collective bargaining considerations. Similarly, in Europe the deployment of certain AI tools within the organization may trigger information, consultation, and—in some European countries—negotiation obligations. AI tools may only be introduced once the process is completed.
This marks an important inflection point for employers: engaging with employee representatives on AI strategy early can help anticipate employee concerns and reduce friction as new technologies are adopted. Here, we explore how AI is emerging as a key topic in labor relations in the US and Europe and offer practical guidance for employers navigating the evolving intersection of AI, employment law, and collective engagement.
Efforts in the US to regulate AI's impact on workers
There is no specific US federal law regulating AI in the workplace. An emerging patchwork of state and local legislation (e.g., in Colorado, Illinois and New York City) address the potential for bias and discrimination in AI-based tools—but do not focus on preventing displacement of employees. In March, New York became the first state to require businesses to disclose AI-related mass layoffs, indicating a growing expectation that employers are transparent about AI's impact on workers.1
Some unions have begun negotiating their own safeguards to address growing concerns about the impact that AI may have on union jobs. For example, in 2023, the Las Vegas Culinary Workers negotiated a collective bargaining agreement with major casinos requiring that the union be provided advance notice, and the opportunity to bargain over, AI implementation. The CBA also provides workers displaced by AI with severance pay, continued benefits, and recall rights.
Similarly, in 2023 both the Writers Guild of America (WGA) and Screen Actors Guild-American Federation of Television and Radio Artists (SAG-AFTRA) negotiated agreements with the Alliance of Motion Picture and Television Producers (AMPTP) that include safeguards against AI reducing or replacing writers and actors. WGA's contract requires studios to meet semi-annually with the union to discuss current and future uses of generative AI—giving writers a formal channel to influence how AI is deployed in their industry. The SAG-AFTRA contract requires consent and compensation for use of digital replicas powered by AI.
The International Longshoremen's Association (ILA) has taken a more aggressive approach. In October 2024, the ILA launched a three-day strike that shut down all major East and Gulf Coast ports demanding, among other things, a complete ban on the automation of gates, cranes, and container-moving trucks. The ILA and US Maritime Alliance eventually reached agreement on the terms of a CBA a collective in early 2025, which includes a provision prohibiting the introduction of "fully automated" technology—equipment that operates without any human interaction. And any new tech implementation must be agreed upon by the union and employers; if they cannot reach consensus, the matter goes to arbitration.
Unions are also challenging the usage of AI before the National Labor Relations Board (NLRB). Recently, SAG-AFTRA filed an unfair labor practice charge to the NLRB against a video game maker, alleging the employer utilized AI-generated voices to replace bargaining unit work without providing the union with notice or the opportunity to bargain. The case is pending, and we are monitoring developments.
Across the pond, trade unions have been quick to react to the disruptive power of AI.
In Europe, AI is emerging as a key topic with trade unions and works councils
In the EU, AI in the workplace is a particularly sensitive issue—especially when it comes to its impact on jobs. The landmark EU AI Act is currently in its phased implementation stage, with key provisions such as a ban on prohibited AI systems and obligations on AI literacy under the AI Act taking effect in February 2025, and rules for general-purpose AI models and governance structures set to take effect by August 2025. While the EU AI Act does not ban job displacement by AI outright, it does contain several employee protections. Employers must consult with works councils before implementing AI, and in some jurisdictions, obtain their agreement. The Act also empowers individual employees by giving them the right to be informed when AI is used in decisions that affect them, to request explanations about how AI influenced those decisions, and to challenge outcomes.
In France, a court recently underscored the importance of treading carefully with employee representation rights with respect to AI in the workplace, even during testing and experimentation phases. In an interim order from the Nanterre Court of Justice in February, the court ruled that a company's early deployment of AI tools in a "pilot phase" occurred before the works council (CSE) consultation process had been completed. It therefore suspended the implementation until the consultation was completed and ordered the employer to pay damages to the CSE for the harm suffered.
In the UK, the conversation around AI and employment is gaining legislative traction. In 2024, the Trade Union Congress proposed an AI and Employment Rights Bill aimed at regulating how high-risk AI is deployed in the workplace. The bill would have required employers to consult workers before implementing such systems, ensure transparency, and provide personalized explanations for AI-driven decisions. Notably, the bill would classify dismissals based on unfair reliance on high-risk AI as "automatically unfair." Though the bill did not advance, it signals growing momentum in the UK toward incorporating worker safeguards into the AI adoption process. The independent AI Opportunities Action Plan commissioned by the UK government, published in January 2025, recognizes the change that AI will bring to the labor market. The report acknowledges the importance of developing life skills and educational opportunities for development, and also of diversity in the talent pool working in AI and data science.
In Germany, the deployment of AI in the workplace is closely tied to works council co-determination. While there is currently no specific AI-related co-determination, political discussions are ongoing about expanding the works council's authority in this area. In the meantime, existing IT co-determination standards apply. Under established case law, the works council has co-determination rights whenever an IT system is capable of monitoring employee behavior or performance—criteria met by most AI systems used in the workplace. Given this legal backdrop, employers are strongly advised to engage proactively with works councils and negotiate a framework agreement on AI which can help streamline co-determination procedures and provide legal certainty for future implementations.
Proactive strategies for multinational employers
In both the US and in Europe, partnering early with unions and employee representative bodies on AI can help employers avoid costly disputes and disruptions, including strikes. Proactive employers looking to reduce reputational risk and promote constructive labor relations can keep these best practices in mind:
Have a very clear understanding of the company's obligations under any applicable CBA and with respect to employee representative bodies. For US employers with unionized labor, implementation of technology (AI or otherwise) may be addressed in the CBA (whether in a management rights clause or elsewhere). Even if the CBA is not clear or does not explicitly address AI, partner with counsel to consider closely what the company's obligations may be, as it is conceivable there is no obligation to bargain.
For US employers with unionized labor, implementation of technology (AI or otherwise) may be addressed in the CBA (whether in a management rights clause or elsewhere). Even if the CBA is not clear or does not explicitly address AI, partner with counsel to consider closely what the company's obligations may be, as it is conceivable there is no obligation to bargain. Engage with labor early and anticipate concerns. Employers need not wait for contract negotiations. By way of example, in 2023, a global tech company formed a first-of-its-kind partnership with a union to address the impact of AI on workers. The initiative involved training union members on AI fundamentals and gathering their feedback to inform AI development, as well as both parties advocating for policies supporting AI-related workforce training amid growing concerns about job displacement and AI-driven inequality. Getting out ahead can eliminate the fear of the unknown and go a long way in building trust on issues related to job security, retraining and perceived fairness.
Employers need not wait for contract negotiations. By way of example, in 2023, a global tech company formed a first-of-its-kind partnership with a union to address the impact of AI on workers. The initiative involved training union members on AI fundamentals and gathering their feedback to inform AI development, as well as both parties advocating for policies supporting AI-related workforce training amid growing concerns about job displacement and AI-driven inequality. Getting out ahead can eliminate the fear of the unknown and go a long way in building trust on issues related to job security, retraining and perceived fairness. Promote transparency. Proactively involve unions and employee representative bodies in discussions about AI adoption, including its purpose, scope, and potential impact on jobs. Be prepared to articular the opportunities at stake clearly, including how AI tools can optimize work and working conditions.
Proactively involve unions and employee representative bodies in discussions about AI adoption, including its purpose, scope, and potential impact on jobs. Be prepared to articular the opportunities at stake clearly, including how AI tools can optimize work and working conditions. Collaborate on guardrails. Work with unions and employee representative bodies to establish boundaries on AI use that the employer may be comfortable with—such as limits on surveillance, algorithmic management, and automation of core job functions—while also exploring how AI can enhance, not replace, human roles.
Work with unions and employee representative bodies to establish boundaries on AI use that the employer may be comfortable with—such as limits on surveillance, algorithmic management, and automation of core job functions—while also exploring how AI can enhance, not replace, human roles. Conduct AI impact assessments and ensure compliance with applicable law. Before deploying AI tools, obtain legal advice on the application of emerging AI laws. Consider the tools' potential impact on job functions, employee rights and workplace dynamics. This can help identify areas where labor engagement is recommended.
Before deploying AI tools, obtain legal advice on the application of emerging AI laws. Consider the tools' potential impact on job functions, employee rights and workplace dynamics. This can help identify areas where labor engagement is recommended. Reskill and upskill. Consider offering training programs and career transition support to help workers adapt to AI-driven changes. Jointly developing and investing in these initiatives with unions and employee representative bodies can ensure alignment with workers' needs and alleviate fears of AI-related job displacement.
Consider offering training programs and career transition support to help workers adapt to AI-driven changes. Jointly developing and investing in these initiatives with unions and employee representative bodies can ensure alignment with workers' needs and alleviate fears of AI-related job displacement. Be prepared to bargain. Depending on whether AI tools materially impact working conditions, plan ahead, work with experienced counsel and solidify communication strategies to be ready if it becomes necessary to bargain with unions or consult with works councils.
For support developing your AI adoption strategies, including anticipating labor's response, please contact your Baker McKenzie employment lawyer.
--
1 New York's Worker Adjustment and Retraining Notification (WARN) online portal—used by employers with 50+ employees to submit the required 90-day notice of a mass layoff or plant closure—now includes a checkbox asking whether "technological innovation or automation" contributed to the job losses. If selected, employers are also asked to specify the type of technology involved, such as artificial intelligence or robotic machinery.
| 2025-06-24T00:00:00 |
https://www.bakermckenzie.com/en/insight/publications/2025/06/navigating-labors-response-to-ai
|
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|
UK MHRA leads safe use of AI in healthcare as first country in new ...
|
UK MHRA leads safe use of AI in healthcare as first country in new global network
|
https://www.gov.uk
|
[] |
... artificial intelligence (AI) in healthcare. The move puts the Medicines and Healthcare products Regulatory Agency (MHRA) at the centre of ...
|
The UK has today (24 June) become the first country in the world to join a new global network of health regulators focused on the safe, effective use of artificial intelligence (AI) in healthcare.
The move puts the Medicines and Healthcare products Regulatory Agency (MHRA) at the centre of global efforts to get trusted AI tools safely into clinics faster – supporting earlier diagnosis, cutting NHS waiting times, and backing growth in the UK’s health tech sector.
By joining the HealthAI Global Regulatory Network as a founding ‘pioneer’ country, the MHRA will work with regulators around the world to share early warnings on safety, monitor how AI tools perform in practice, and shape international standards together – helping make AI in healthcare safer and more effective for patients around the world. Other countries are expected to join in the coming months.
The MHRA will draw on its leading work at home to help shape the network from the ground up. That includes AI Airlock, a global leading example of a regulatory sandbox for AI medical devices – which lets companies test new tools with the regulator before wider NHS roll-out. Early examples include AI models to help GPs spot lung conditions sooner and AI to support more personalised cancer care.
The MHRA has updated guidance and begun reforming medical device safety regulations, and continues to adapt them for fast-developing areas such as adaptive and generative AI. The MHRA is also working with researchers, National Institute for Health and Care Excellence (NICE) and the NHS to strengthen real-world evidence on how these tools perform in practice.
A signing ceremony to mark the UK’s membership took place today at Westminster with Science Minister Lord Vallance, MHRA Chief Executive Lawrence Tallon and Dr Ricardo Baptista Leite, CEO of HealthAI.
Health and Social Care Secretary Wes Streeting said:
“I’m delighted that the UK has been invited to become a Pioneer Country in HealthAI’s Global Regulatory Network.
“This recognition underscores our commitment to being at the forefront of responsible AI innovation in healthcare. As we implement our 10 Year Health Plan, cutting-edge technology will be crucial to transforming patient care and NHS efficiency.
“Working with international partners through this network will ensure we harness AI’s incredible potential, while maintaining the highest standards of safety and ethics.”
Science and Tech Secretary Peter Kyle said:
“The UK is leading the way in making sure AI delivers real-world benefits – from better care for patients to new opportunities for growth.”
“By shaping global standards and breaking down unnecessary regulatory barriers at home, we’re helping innovators to get trusted tools into the NHS faster, improving treatments for patients while growing our economy in support of our Plan for Change.”
MHRA Chief Executive Lawrence Tallon said:
“AI has huge promise to speed up diagnoses, cut NHS waiting times and save lives – but only if people can trust that it works and is safe. That’s why we’re proud to be leading the way, shaping how this powerful technology is used safely in healthcare here and around the world. From our AI Airlock testbed to new guidance on fast-moving tech like generative AI, we’re backing smart innovation that works for patients – and makes the UK the best place in the world to develop it.”
Dr Ricardo Baptista Leite, CEO of HealthAI, - The Global Agency for Responsible AI in Health, said:
“We are proud of this landmark collaboration with the UK Government and the MHRA. The UK has long been a trailblazer at the intersection of artificial intelligence and health, and we are honoured to welcome it as the first of ten pioneer countries in the HealthAI Global Regulatory Network, fostering global collaboration and shared learning in the regulation and scaling of AI for health. We believe the UK will both strengthen its leadership in this critical field and offer invaluable expertise to its peers, accelerating global progress toward equitable, AI-powered health systems that ultimately contribute to improving quality of life and well-being for all.”
Notes to editors
| 2025-06-24T00:00:00 |
https://www.gov.uk/government/news/uk-mhra-leads-safe-use-of-ai-in-healthcare-as-first-country-in-new-global-network
|
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|
Bonus Episode: The AI Pivot: Seagate's Workforce Transformation in ...
|
Bonus Episode: The AI Pivot: Seagate’s Workforce Transformation in the Age of AI (with Patricia Frost & Ruslan Tovbulatov)
|
https://www.myhrfuture.com
|
[
"David Green"
] |
Bonus Episode: The AI Pivot: Seagate's Workforce Transformation in the Age of AI (with Patricia Frost & Ruslan Tovbulatov). What happens when ...
|
[0:00:00] David Green: Attend any conference and the key theme you'll hear rolling throughout will be about building a future-ready workforce. But what does that really look like when the pace of change outstrips traditional planning cycles? For Seagate technology, it meant making a decisive shift, pausing external hiring in favour of unlocking the potential already within, and it meant giving employees more than a platform. It meant giving them a map, a mindset, and the means to move.
I'm David Green, and in this episode of the Digital HR Leaders podcast, I'm joined by Patricia Frost, Chief People and Places Officer at Seagate, and Ruslan Tovbulatov, Chief Marketing Officer at Gloat, the platform partner helping to enable this shift. Together, we explore the story behind Seagate's internal talent marketplace, TalentLink, how they built trust and transparency across the organisation, and what it really takes to embed AI in ways that resonate with the workforce, not just leadership. This is a conversation about technology, yes, but more importantly about trust, purpose and building the conditions for people to thrive in a world of constant reinvention. So, what does it take to future-proof your talent strategy in a time of disruption, and how do you bring your people with you on that journey? Join us as we explore the answers together.
Patricia, Rus, welcome to the Digital HR Leader podcast and Rus, welcome back for the second time. To kick things off, please can each of you share with listeners an introduction about yourselves and your respective roles at Seagate and Gloat. Patricia, I'll come to you first.
[0:01:53] Patricia Frost: Oh, well, thank you, David. And first and foremost, just a little bit about myself. I would describe myself as a people leader. I'm a mum, an army veteran, outdoor enthusiast. That's where I get my passion, is being outside. And I have had the honour to lead people at all levels, all team sizes for over 40 years, and 32 of that being, of course, in the army. And now, I get the honour of leading at Seagate Technology. For those that don't know what Seagate Technology is, it's a global manufacturing company. We actually develop and produce hard disk drives. So, think mass capacity storage. Also think about external storage to your laptop or desktop. So, we pretty much probably touch everyone listening on this call, whether personally or professionally, because it's the world's data. So, just very excited to be here. And my role actually encompasses HR, communications, culture, community, occupational health and safety, environmental health and safety, sustainability, security. It's kind of anything that touches people, as soon as you walk in the door, or whether you're a remote worker, and it's just a fascinating job to have.
[0:03:06] David Green: Rus, if you'd like to give an introduction to yourself to listeners as well, that'd be great.
[0:03:11] Ruslan Tovbulatov: Yeah, thank you for having me again, David, and really great to be with you, Patricia. So, yeah, Ruslan Tovbulatov, I run the marketing here at Gloat. And not only do I have the privilege of telling Gloat's story, but I have the even bigger privilege of working with some of our top partners and some of the most forward-thinking companies on the planet, I would say, like Seagate and Patricia and all the work they're doing, and Gloat. And we've been really trying to help organisations navigate change through years, almost a decade now of disruptions that we, as enterprises, have to think about and endure and thrive through. In a way, started with COVID in a big way, where a lot of companies needed to redeploy talent, drive internal mobility, figure out how do we adapt to the changing environments and needs of a COVID in a post-pandemic world. Then, we went through the great resignation, helping companies retain talent and skills and grow that talent, so they can make sure they were prepared for the future. And now, increasingly the conversation is about the AI transformation that every company has to endure. And it's been a lot of fun, but also a huge challenge, obviously, every step of the way. How do we help enterprises like Seagate, and partner with them very closely, both from a technology and a change management standpoint, to thrive through all of these changes? So, we'll get into all of that, but I'm really excited for the conversation.
[0:04:31] David Green: Yeah, thanks, Ruz, thanks, Patricia. And actually, you've teed that up perfectly, Rus, because as you just talked about really, over the last six or seven years really, through the pandemic, immediately prior to the pandemic and then since, it's been a huge time of transformation and change, and obviously a lot of conversations around skills-based workforce planning. Internal mobility is a big focus, particularly as the labour market pool starts to shrink. They've taken centre stage and now obviously, as you said, the advancement of technology, AI, agentic AI, we're seeing more organisations really start to prioritise this. Patricia, I'd love to hear your take. What sparked the transformation that you've undertaken at Seagate?
[0:05:12] Patricia Frost: So, mine was, you come into a new position and you do an evaluation, and I was doing lots of listening sessions. And the number one thing that was being mentioned across our global company, and this was about five years ago, was a lack of transparency on requisitions that were open at Seagate. And Seagate managers tended to go externally first. And my objective was that I wanted our employees to be the first to see a requisition open. But we know, it's human nature, if an employee is looking for a new opportunity, they're already on LinkedIn, especially here in the United States, looking. So, I needed a platform where it was them looking within Seagate first. So, I wanted a platform that could kind of be our LinkedIn. And so, they could see their career, which is why we called it Career Discovery in its first phase, so they could discover career opportunities at Seagate. And managers had to be willing to allow them to depart their organisation to have that opportunity. That's another challenge.
But it really was to be transparent. And I had the support of our CEO and we had a mandate for how many days a requisition had to sit on the internal platform before a manager could even go externally. And I also knew that our employees, they knew our business processes, they knew our culture. They also knew we're a pretty large company, so they had teammates. And so, they knew how to get things done. If you bring in someone externally, yes, they'll bring new skills, new talent, but their learning curve is pretty steep, 90 to 120 days. So, just let's truly focus on the team we have and give them that opportunity first. So, that was my goal when we first rolled out the platform. And we went all in. Many companies did only projects first. We did projects and open positions. And we said, "If we're going to do it, we're opening the whole thing up. And we want everyone to see everything from projects to mentorship, to positions that were available".
[0:07:27] David Green: It's crazy, isn't it, that it's easier in some companies to get a job if you're an external candidate than it is if you're internal to the organisation and you've got a track record of success over a number of years. And I guess that your objective was to flip that effectively. And there's enough research out there that tells you that not only is it cheaper to hire internally, but the time to productivity, as you highlighted, Patricia, is less. These people are already embedded in the culture as well. Russ, I presume this is a common story that you heard from the companies that you've worked with at Gloat?
[0:08:04] Ruslan Tovbulatov: Yeah, Patricia has given me many quotes over the years that I proudly steal, but one of them, and I'm going to steal your thunder here, is that, "You have to win with the team you have". And you can hopefully share some of that story of where you got that quote, I won't steal your thunder on that. But it's just so core to the belief system that we have at Gloat. And I really believe that as a manager and a people leader myself. I think so many times, we think that we can solve the problems by some kind of external solution, whether that's a hire or a platform, or in the marketing world, it's always more technology. But in reality, it actually starts within. You have to really take advantage of the people and the technology increasingly that you already have. And that's the question, are we getting the most out of that?
So, for us, that's one of the reasons this relationship has worked so well, is I think from the beginning, Patricia really understood the value of not chasing some shiny object externally, but let's look at the people around us. Let's look at not even the skills they already have, but what skills are they willing to have? What are their passions and interests? And what is the capacity of those people? And we'll get into some of those conversations, but I think that philosophy almost has to underpin everything. I think even as we transition to the AI era, I actually think that becomes even more important, to make sure that our people are as equipped as possible to do their best work.
[0:09:24] David Green: That's really good. And Patricia, I'm going to let you expand on that story, because I think it sounds like definitely one our listeners will want to hear. So, I'll ask the next question as a two-part question, really. Please, obviously, expand on the win with the team you have; and then, maybe a wider, a big part of enhancing internal mobility is transparency. What are some of the barriers that you needed to break down to make that happen and win more with the team that you have; and how did your partnership with Gloat help that change?
[0:09:53] Patricia Frost: Right. So, it goes from being in the military. And in the military, you have to know the team you have. And we're going to talk about the next phase of Gloat and Mosaic. I'm so excited with where they're going and the opportunities. But to really know, managers have to know their team. They have to know the strengths of their team, they have to know what gaps they need to fill, and those gaps can be filled normally within the company itself. So, if you go to an army, platoon, company, battalion, we don't get to externally hire and say, "Oh, I'm missing a rifleman, I'm missing a sniper". No, you have to go train for that skill. That's not something you just throw someone into the mix.
So, you go to war with the team you have, I've been to combat several times, and you win with the team you have. And you're going to build on the strengths of that team. And that's signs of a good leader, that you're developing, you're growing, you're looking for those opportunities. Yes, you may have to pull people from different units, but you're still pulling from within the same organisation, the same company. Like, I could reach across to another function and pull someone with that skillset I need, but it's still from within seeking. And so, that's really powerful. And your team appreciates it when they know you're looking internally first, that you recognise their skills. Now, it does require you, as an individual, to want to upskill, to continue to be that learner, be curious, be challenged. That's what we're going to hit in this new era of AI, are you willing to learn a new way to work? It's not taking away your job, you're going to evolve how you do work.
So, for managers in the very beginning, if you focus on internal mobility, it is that kind of, "I want to hoard my talent. I have the best team, therefore, I don't want to let any of my team members go". But at the end of the day, your talent is, for us, it's Seagate's most precious asset. It's what makes us unique, the talent, the skills, the innovation, the hundreds of PhDs that we have in the company, those that don't even have the paper, but they're actually at the same skill set of someone with a PhD because they've done that learning through experience. I mean, you have to value your people. And I think if you get managers to let go and realise they will still be successful and you're actually helping the company grow by allowing that person to move, because if you don't, Seagate is going to lose that person. Not only you, the manager, are going to lose that person because they're going to go externally to the opportunity they're looking for, but Seagate's going to lose that person, your company's going to lose that person.
So, I think just getting managers to let go and realising that every time you bring on a new team member, gives you an opportunity to maybe lead a little differently.
[0:12:57] David Green: That's a shifting culture from maybe what you had before, where people would look outside. And obviously, as you said, for individuals, make them curious, make them focus on continual learning so they can develop their careers within the organisation. Within managers, it's to enable that and to not hoard talent, as you said. How did Gloat help you make that change?
[0:13:18] Patricia Frost: So, it gives you a platform to actually see your people. You can actually search. It does matching. So, it's already prompting individuals to say, "Hey, there's an opportunity, there's a project, there's a position". It allows managers to actually see it. And it's doing it where it's not just that paper resumé. There are things that if an employee puts in the information correctly in their profile, they can talk about passion. I could have an HR business partner who actually does Python programming in their personal time. They can input that into the platform. A manager would never know that. Or someone who is in sales and marketing, but is learning other things in law. Or it just goes across every function, which is just so powerful, because we all have our life that we were hired for, that we come to work, we were hired for this position; but we're all bigger than just that one position. We are all learning on the outside. We all have activities and passions, and the platform allows you to put all of that in there and enrich who you are as a person and who and what skills you can bring to work that go beyond what you were hired for.
I think also, it's a living platform. It's something that can be updated all the time, which is, again, very powerful.
[0:14:55] David Green: And, Rus, turning to you, I know you wanted to react to what you heard from Patricia there, talent mobility increasing. And Gloat really coined the term, Talent Marketplace, which has become more commonplace since you coined that, I don't know, back in 2017, I think it was. What are some of the other things that you've seen to solve that problem or challenge that Patricia's explained?
[0:15:23] Ruslan Tovbulatov: Yeah, David, you know your stuff. It was 2017, as early as back then where we started this talent marketplace movement. And we've evolved quite a bit since then, which we'll discuss. And Seagate's been a great partner for almost a large part of those years. But there are a number of things that Patricia said that I actually really want to underscore. One is this idea of the role of technology in all of this versus the mindset and the culture change that needs to happen. And I think it's really important for organisations to realise. I think that's increasingly happening. You're being forced to do that, I think, in the world of AI, where it's all shared talent. This idea of the traditional job structure or org chart, and that you report to one person or you have one career ladder. Anyone that was resisting that, I think it's all getting completely blown up now in the world of AI. You have no choice but to adapt to just say, "We have to approach things in a more agile way". We can't rely on the job architecture or traditional structures or the mindset that, "This is my team and no one else's". I think that's such an important piece of this, the culture change that needs to happen, I think it's going to be more important than ever.
Then the technology. What's interesting about this is in many ways, some of these conversations, you could say, "Well, we've had internal job boards forever". But what had to happen actually is the philosophy had to get implemented into technology, meaning you can't build a system that's built on a traditional job architecture and think it's going to be dynamic or agile. So, one of the first things we did, and I think all of the new breed of technologies that are AI first have to do, is to build with AI first from the foundation. So, we, from day one in 2017, actually built what we called the Self-Evolving Skills Ontology. Before skills-based organisations were a thing, we knew that the currency cannot be the job. It can't just be looking at a resumé and matching someone to a singular job in a full-time position. We needed to actually have more data to make more informed decisions. So, we started looking at things as basically, the workforce in the currency of skills, and we built an AI to match that, based on skills, the right opportunities to the right people.
But what was most fascinating, and Patricia alluded to this, is when organisations started seeing the power of breaking down work in new ways. So, if you start realising, wait, when someone goes on maternity or paternity leave, maybe we don't have to just backfill that entire role. Maybe we can break that up into five or six responsibilities and actually backfill parts of it. Or when you need to launch a new product in a new region, maybe we don't need to go through the entire hiring process to just launch that one new brand of ice cream, or improve our infrastructure -- it's a true story -- is improve the infrastructure of our trading platform. Maybe we just need some part-time help from experts. And once companies started doing that, you started seeing all this incredible data emerge around deconstruction of work, the skills, and then now increasingly, the technology that companies have to bring to bear. So, once the mindset is there, wait, we can use all of these things to get work done, the technology then enables a lot of that.
So, we're starting to do a lot of that work. Patricia alluded to this product, the suite that we're working on with them, called Mosaic, and we really see that as the next iteration of the talent marketplace. So, we'll get into some more of those details, but I wanted to underscore some of the points that Patricia made.
[0:18:53] David Green: This episode of the Digital HR Leaders podcast is brought to you by Gloat. A new kind of workforce is emerging, one of people and AI agents working side by side. But while every executive is investing in AI, few are unlocking its real value. Why? Because real transformation doesn't come from technology alone, it comes from the people who know how to harness it. That's why Gloat built the world's first work and workforce operating system for the AI era. It's how leading enterprises are evolving their workforce into exponential contributors, people who can orchestrate AI, tech and skills to work at 10x speed, operate with AI fluency and stay ahead of change. With Gloat, organisations like Seagate, Novartis and Standard Chartered are turning AI hype into real productivity, by embedding it directly into the work people do and unleashing the full power of human AI teams. To see how your organisation can thrive in the AI era, visit gloat.com.
What made you choose Gloat over any other vendor, and maybe continue that partnership in the long term as well?
[0:20:24] Patricia Frost: So, first, it's the people that encompass Gloat. So, they put the customer first, which we're the customer, right? They're trying to empower us. And they take all of our feedback, positive and negative. It's just this constant relationship of, "This is working, this isn't working. Why? Is it on our end? Is it on your end?" And they don't get defensive about it. I mean, they really want to grow the platform, and then AI is just constantly evolving. And the fact that they're not sold on just this one iteration of their product, they're actually helping us solve our most critical people problems, right?
But I will tell you, and I said this the last time we were together, this is not an HR tool. I have to say that just very strongly, emphatically. This is an employee tool, this is a people-leader tool. This empowers the individual and empowers the people manager. It is not something that sits very exquisitely over in the HR world. This is to empower an employee to own their career, to own their development, their talent, which gets to our new -- we went from Career Discovery to TalentLink, because it's about everyone's talent. And the link is how we connect everyone. So, this isn't just something sitting in HR. This is truly to empower down to our most junior employee, up to the top leader, to see the organisation, but to allow everyone to see themselves, to have a long and very, hopefully, what I hope, a prosperous career at Seagate.
[0:22:10] David Green: Rus, I've been fortunate to attend and speak at Gloat Live, and I've spoken to a number of your customers. And what Patricia highlighted there, the fact that you want to learn the good and the bad and the indifferent, and you're learning with your customers, I certainly see that as one of the reasons behind the growth of Gloat. Is there anything else that you'd like to highlight to listeners?
[0:22:32] Ruslan Tovbulatov: Well, Patricia and the team have been such a great partner. And I think her quote, that's another very prominent quote that I use often, because I think what Patricia has stated is what I think the leading companies that work well with us get, which is, "You can't approach this as an HR problem. You have to approach this as even a business problem". I think she said that at Gloat Live, our conference, and that really is near and dear to us, because the technology isn't built to be for HR and admins. It's meant for every employee, every manager and business leaders up to the C-suite. And what started absolutely as a career discovery and mobility tool, now all of that data is being used to power real work getting done. I look at some of these projects, they're not just developmental or fun things. It's not back-office stuff that people are doing just to put in. This is real work, like billions of dollars of productivity being unlocked, because you have people coming together to literally launch new products. In the pharma space, we've seen a project team actually come together to launch an entirely new drug on the platform. In technology companies and CPG companies, we see new products going to market. We see partnerships with third parties coming to life because of the platform.
So, I think Patricia's seen that and Seagate knew that from the beginning. Another thing that I always love, and I quote her, I think she was the first person to actually challenge us on the word 'project'. She said, "Guys, I think you're underplaying what the platform can do, because it's not a project, it's work. What you're doing is delivering work and work execution. And so, we need to almost rebrand this whole thing because it's not just about a project, it's about something more about getting work done". And so, that mindset, I think, has been so great with our relationship. And I think anyone that's been successful, I think, has that mindset.
Then quickly, the other piece, I think it's just important maybe now to say this, because Patricia reminded me. One of the reasons I think she's such a strong leader, and I just see the way they operate and how HR is positioned, not just as the HR department, but a core part of the business at Seagate, is partly because of the mindset that I think Patricia brings to her team. One of the things she said was, "It's not about perfection". And I think that's actually the problem with a lot of traditional HR processes. And I think it's actually what really hurt the skills movement, because people are still trying to get the perfect job architecture, the perfect career paths, and now the perfect skills ontology. But I think that is a futile exercise in a world of AI. The world is changing so much. It's impossible to actually build something that is perfect, because by the time it is, by the way, as I say, if you treat it like an academic exercise, it's going to be out of date. The book is already onto the next edition. And so, I think that mindset of agility and adaptability, I think is so important to anyone going on this journey. And Patricia has driven that in Seagate in spades, and I encourage everyone to really think about progress over perfection, especially in an AI world.
[0:25:57] David Green: I don't know if you want to respond to that a little bit, Patricia, because I'm certainly hearing that thirst for experimentation and continuing and doubling down on what works, but then maybe pulling back on stuff that doesn't work?
[0:26:11] Patricia Frost: So, we're going to roll out something new. So, when we're starting our fiscal year on 1 July, we do OKRs, Objectives and Key Results. So, as we roll out our OKRs, which is very manual, right, it's kind of static, they're not supposed to be static, but you write them up, you print them out. But as we put our OKRs as an individual, and then as a functional leader, into SAP SuccessFactors, we're then breaking down at the individual level, what are the tasks that you need to do? So, think about individual growing the company because it's all nested, it all links up. So now, that individual is looking at, "Okay, what do I need to do? How do I perform? What are my key results for this objective to be successful?" We're linking that with Gloat. I think Rus could talk about this. It will show us how you can get those tasks done with AI or where the human has to actually do the work.
But then we've also linked it to our learning platform, to Udemy, and if the individual needs to grow in a certain area for that OKR, for that key result to be successful, it will actually give them a learning path. So, think of that power. It's taking technology to empower you to be successful and what's going to grow the business. It still requires you to do the work. We may stumble a little bit as we launch this new aspect of doing the linking of the technologies, but we just rolled it out again. We did face-to-face rollouts in Thailand and Singapore just on TalentLink, because we need everyone to enrich their profile and go beyond just the resumé, enrich truly what they're passionate about, the skills they have, where they see themselves in the future.
We had, and I didn't get a chance to tell you this, I don't think you know, I think, so I got 90.7% updates in Thailand and our Thailand workforce. That's incredible, so that's first step. But then we need everyone, when they go in and do their OKRs, to actually see the prompts. And it's a one-click. They're in SAP SuccessFactors, they click, this will take them to a Gloat or into our TalentLink, or it'll take them to Udemy, it'll start to feed them. Because it's really about, people like to be in control, right, we know that. Humans like to be in control. So, what we're trying to do is give them that aspect where they control how they can be successful. But we're going to give them the tools to do that.
[0:28:50] David Green: I want to take a short break from this episode to introduce the Insight222 People Analytics Programme, designed for senior leaders to connect, grow, and lead in the evolving world of people analytics. The programme brings together top HR professionals with extensive experience from global companies, offering a unique platform to expand your influence, gain invaluable industry insight and tackle real-world business challenges. As a member, you'll gain access to over 40 in-person and virtual events a year, advisory sessions with seasoned practitioners, as well as insights, ideas and learning to stay up-to-date with best practices and new thinking. Every connection made brings new possibilities to elevate your impact and drive meaningful change. To learn more, head over to insight222.com/programme and join our group of global leaders.
You mentioned then, Patricia, TalentLink, and my understanding is you initially branded the platform, Career Discovery, internally but now it's TalentLink. Can you talk a little bit behind the reason for that shift?
[0:30:14] Patricia Frost: Yeah, I think in the beginning it really was about where we were on that journey of how do you see your career at Seagate, and it was very focused on internal mobility. And then, TalentLink is really everyone taking a moment to look at their talent, their skills, but talent means everyone. So, again, I go back to this isn't an HR platform, this is a platform for every employee. And then the link is, you can get matched with other people of similar interests, you can see that project's work that needs to get done, but it really is powerful for managers. And this goes back to my previous career of, managers have to be able to see their teams. And how do I empower a manager to go in and look at their team differently from a skills aspect, so they can really see what training do they need to bring to the team? Or if we have to go and externally hire, which we will do external hires, but we're doing that very surgically, what is it that we have a gap, and who are we trying that we think will augment and make our team better, not duplicative, but will actually grow our team, grow our talent base, help Seagate move with efficiency and effectiveness? So, I think for us, that's the TalentLink.
Then, Link to Me also links all the technology. So, we're not trying to throw a lot of technology at the employees. We're talking about three platforms we're linking together where it's one click. And it will show them the power of the technology that we're focused on. So, I think that's important, right?
[0:31:57] David Green: Yeah, it is. And, Rus, you might want to come in at this point, and just talk what that means from a globe perspective.
[0:32:04] Ruslan Tovbulatov: Yeah, I love this story actually, that Seagate has been on in the journey from Career Discovery to TalentLink. And one of the reasons I particularly love it is because I'm a marketer and I know the importance of positioning and what message that sends when a platform is launched, a technology is launched. And I think Career Discovery was the perfect name for the use case that Seagate had at the time. And if you think about what was happening post-COVID, great resignation, how do we empower people with the right careers, the advice I actually give to anyone doing any of these initiatives, whether it's with Gloat or anyone else, is think about the positioning to give yourself the most flexibility for the future. And so, I love MasterCard calls theirs Unlocked. Molson Coors just launched one called Untappd, which might be the most creative I've heard. And what that allows you to do, and that's why I love TalentLink, you just saw what Patricia did there.
When they renamed it TalentLink, I don't think we were even thinking about technology as part of the talent. But what that name allows us to do is we realise, wait, there are going to be technology agents as co-workers. That's talent. So now, this platform has this flexibility and the ability to actually adapt to whatever changes. Who knows what happens next, right? It's almost impossible to predict these days. So, I love that story and actually encourage anyone going on this journey, really be thoughtful of how you name the platform. You can always position it, and of course it's going to be about empowering employees and allowing them to discover opportunities and careers, all of that, but that can be a part of the story. As you think about all the different use cases for managers, for leaders, etc, the more flexibility you have at the top-level name, the better it is. And so, I'm really excited of the repositioning.
That kind of brings us to where we are now. What I think started, even for us at Gloat, as a platform to retain talent, to see opportunities within a company, it's become so much more, kind of like I was alluding earlier, where it's become a platform to get work done. And increasingly now, because of AI, the question of who gets the work done is as relevant as ever before, because it's not just about the talent on your team, the people on your team, or the people outside of your team, it's increasingly the technology that can support all of that. So, our belief there is the answer isn't just throwing more agents or more technology at the problem. It kind of is the same as we started the conversation with. It was never for us about external recruiting. I think actually, HR might have the same issue here to think, "Oh, well, we'll just get more agents or more technology". The key for us and in our partnership and how we're thinking about it is, how do you empower the talent you have and the people you have to wield this incredible superpower they've been given with AI?
So, what we're building, called Mosaic, is this new offering where it's taking the best of the talent marketplace. So, you see the skills, the ontology of skills, the ontology of the talent and the work, but also technology. And that technology, without getting too geeky, today might just be a foundation model, "Oh, we have access to Claude from Anthropic, or we have access to OpenAI, and that might help me with some writing or some creative". It could also be software, by the way. It could be Canva helping you with designs; it could be Copilot helping you actually as a partner thinking through things, or accelerating the work you're doing; and eventually, it becomes agents. And we're testing that even within Gloat, agents to actually automate entire workflows. But we really fundamentally believe that humans have to be the orchestrators of all of this. You almost have this orchestra. We believe humans are the conductors, but all of this is going to supercharge them.
So, we're really excited to be working with Seagate on this. And we have a lot of investment and thought going into this area, because we believe it's the logical, honestly, next iteration of what we've been doing for all these years, and is definitely what I think enterprises like Seagate could really benefit from, and people can benefit from, in this AI era.
[0:36:15] David Green: Really exciting, Rus, and thanks for laying it out. I actually think the two of you are both great marketeers, by the way, listening to the conversation over the last 30 minutes. Patricia, I'll let you respond to what you just heard from Rus as well, but I also maybe mix it with, let's double-down on the AI piece. I know you made a bold move at Seagate recently. You've paused hiring, particularly in the US, and reinvested that budget into AI tools for your people, as Rus explained there. I'm curious, what's the response been from your workforce so far?
[0:36:49] Patricia Frost: Maybe a little anxious, and I'm having a leadership team meeting next week to really lay out my strategy. And my strategy is like, "Before we go and do that external hire, let's take the resources from that rec, let's invest it in an AI toolset". So, for me, it's getting everyone the Office 365 license and the Copilot across all the platforms, because I need everyone to have the same advantage. So, right now for the last few months, we've had a team of 40 from my team and it's been really powerful, but I can get excited and I can go and say, "Hey, this is how I use AI as my thought partner, this is where it saved me so much time". I mean, literally I was doing a board presentation, it saved me over eight hours of work. I mean, it was incredible. And so, I can get excited, and then I look at my team and they're just staring at me and I go, "But you don't have the same capabilities that I have". So, it falls flat.
So, now is to say, okay, I need to uplift my entire team. I'm investing in this, and we are going to go on this AI Aware for another year that you all can envision, because it's the power of us. It's the power of every one of my employees to say, "You are going to rewrite how you work. This is not going to be pushed down from on high, we'll do it bottoms up. How do you look at your workflow? What are the tasks that you need to get done? Where can AI assist you? Where is it truly the human does the work? And let's rewrite our organisation and how we come to work". And I think that will take some of the fear away, because I think some of them are saying, "Well, if I take on these tools, my job's going to go away". No, your job is just going to evolve differently. And I need them to embrace agentic AI, and where do we feel comfortable that an agent can do work from one end to the next, and we are confident that it's delivering the right results? And so, I need them to think about their roles, because they're at the tactical edge. They're touching it, they're doing the work, so where can that AI truly assist them? And then we'll evolve what our work structure should look like and how we come to work and how our jobs evolve.
But I need everyone on the journey together and I want to be very transparent and I want to have these conversations. And I do think we'll have the laggers. I do think we'll have people who say, "I refuse". And unfortunately, we're a tech company, it's all about data for us. That may be a problem in the future. Like, if you just are going to be stubborn and say, "This is how I do my job", then that's another story, that's a different conversation we're having. But I need everyone to embrace it, and it's not going to be perfect, as Rus said, it's not going to be perfect. But let's look at where it can bring us the most value and empower us where we feel comfortable, and share, collaborate on the journey together. So, my goal, I hope, by the end of the year is we're really talking about how we're going to work differently. And to me, it's all about the growth of the company.
[0:40:34] David Green: And, Rus, just bringing you in here for a moment. Obviously, you're working with several organisations at Gloat, many of them also pioneering organisations, if I can say the word pioneering; I can now. What stands out about the way that Seagate has approached this transformation?
[0:40:53] Ruslan Tovbulatov: So, I love the way Patricia is talking about this. And honestly, it inspires me anytime I talk to her, and I talk to some amazing partners, like we have with Tanuj at Standard Chartered Bank, or the team at Mastercard, because the reality is, I think, HR is at a true inflection moment. We saw that during COVID, right? We said, how is HR going to step up during this digital transformation acceleration? And you saw that happen, right? HR leaders stepped up right next to the CEO. But this moment is a little bit more scary, I think, for HR, especially in the sense that I know this data I believe I saw from you, David, that only 7% of CEOs consider the CHRO AI-savvy. And what gives me hope, hearing people like Patricia, is that there are opportunities for HR to actually lead this transformation, not just get consumed by it. And let's be realistic here. There is a real battle going on between IT and HR right now. Because are you going to believe that the future of the workforce is all digital? Or do you believe that humans are going to be at the helm? You know what our belief is. We think humans have to be at the helm. But this interplay and collaboration between IT and HR and the business is so important.
So, when I hear Patricia speak, just the language she uses, the examples, the leading from the front, I think that's just so incredibly important for every leader listening to this and everyone in HR to really challenge themselves, how can we be the change agency and be partners to the business on a transformation that is happening, whether we like it or not, right? So, let's lead instead of being consumed by it. And then how we do it, I'll just quickly touch on two things and this could be a whole separate podcast, but I think the framework is actually still similar. I think there's a mindset and a technology thing here. On the mindset piece, Patricia again said this really well, and it's about people actually believing that this is something that can be good. And it's about the positioning, sure, top down, but it's people feeling empowered by this moment. And one of the terms we've been using is that we fundamentally believe that the age of the IC, the Individual Contributor, is over. Because every individual now can be an exponential contributor, because you now don't just have yourself or your knowledge, you have an army of resources around you.
I said, you have Canva for design, you have OpenAI to help you with copy, or CLAW to help you with copy with, if you prefer that. You have video creation tools that can create Super Bowl commercials now. I don't know if you saw that, but the NBA finals just showed a totally AI-generated commercial made in Google VEO. The world, if you just think about that as an individual, anything you dream up, you have the potential to do. So, there's a mindset thing that I think we need to support as leaders, but individuals also need to believe that this isn't about AI taking your job, it's about getting superpowers, and I really believe that. I know a lot of people will get impacted, there will be negative repercussions potentially, but if you approach it with the mindset, you can thrive through it and actually, I think, do more than you've ever imagined as an individual or even as a leader.
The second thing, and again I won't belabour this because we've been chatting for a while, but on the technology side, I think it's so important, as Patricia alluded, you have to create a, "What's in it for me?" for people. Just giving them more agents or saying, "Here's a Copilot license, figure it out", that's not how you drive literacy or mastery or inspire people to do it. You have to actually put it into the flow of work. One of the examples Patricia talked about is the prompting. Most people fail with AI, and there's a lot of data around this, of the millions, and actually tens of billions now being invested versus the actual impact companies are seeing and the actual adoption. There's a huge gap, which we're calling this AI productivity gap. And I think the reason for that is because people aren't being given these tools in the flow of work, or tied to the things they're trying to achieve. And so, that's our goal with Mosaic, is prompt a person, as they're trying to get work done they need to get done, with the right technology, and actually even give them the exact prompt to copy and paste. So, instead of them figuring it out on their own, here's a prompt you can copy and paste to get the outcome you want.
So, I think this idea of the leadership from the top down with people like Patricia really being the change agents here, not being afraid of it, but leading from the front, and then the mindset shift and the technology to power that, I think, are all really critical. And we're just really lucky to have a partner like Patricia and Seagate on this journey.
[0:45:32] David Green: Patricia, what does the next chapter of the journey look like? And actually, right at the start, you mentioned that you're not just responsible for people, you're responsible for places and communications, I think, at Seagate. Maybe you can talk a little bit to that as well, and how that helps you, as a Chief People Officer, maybe reach more parts of the organisation and its customers than it would as a more traditional Chief People Officer role.
[0:45:56] Patricia Frost: Yeah, I'm fortunate because I can see all aspects of an employee's life while at Seagate. And what Rus said, so we as CHROs, but everyone in the C-suite owns this, and I believe every people leader owns this, we own the employee experience. So, employee experience is the type of facilities you work in, the tools that you have, the technology, everything that's going to allow you to be productive and effective and efficient at work, right? That's not just a CHRO, we own the employee experience journey and every touch point, but that's every leader owns that. But I think this is where CHROs and their HR teams can really make an impact, is how is technology truly going to empower all these different jobs and functions that you have in the company? And if we look at ourselves first and show we're willing to change, and will people be impacted? Yes, they will, but what I'm hoping is they're impacted in a way because we're going to change their role.
Again, if you're not willing to grow, if you're not willing to learn, if you're not willing to develop into a new area, because the world is changing, that's on the individual. But I do think this is an area to where we can grow together. And I think we can. I'm hoping Seagate will be, in a year, that AI-driven company, and I hope we have developed AI-driven leaders and AI-driven employees, that they're not afraid, and we will give them the right tools. We're not going to throw so many tools at them, but give everyone the right tools. But you have to be willing to fail too. Like how many times do we add an app to our phone, and if within the first 15 minutes the app doesn't give us the right experience, we delete it? Well, employees will do that with software that we roll out in the company and AI tools that we roll out. So, just even with Gloat, as we went to TalentLink, we had to do those face-to-face sessions so they could feel the power of what it is.
So, really excited, because we rolled this out to our hourly workers, I call them manufacturing specialists because they do the bulk of the work at Seagate to produce our product, and this is really a passion of mine. We haven't solved it yet, Rus, you know this, is how do we get this technology into the hands of our workforce that doesn't sit at a laptop, doesn't have a desktop type device, and how we're going to lead them into this future? And we showed them TalentLink and the manufacturing specialists were so excited that they could see what skills do they need even at their level, because we are going to bring more factory automation and it's just going to keep evolving. Automation in the factories is going to keep changing. Well, they want to be on this journey too. So, that was really exciting to see them just get on. We had kiosks set up so they could log on and see what the future looked like. So, it impacts every worker, every type of worker. It's going to hit from our factory floor all the way up.
But I'm excited about the journey. I think we have to rewrite how we come to work. And I think companies, we have to be willing to fail, we have to be willing to not get it right the first time. But I always go back to what problem are we trying to solve, what technology we're going to try to use to solve it? After a year, if it doesn't work, toss it out, go try something else, right? And why have I been so excited about this relationship with Gloat? I mean, Gloat has been in the AI business for over a decade. You're seeing AI companies sprout, a lot of seeds have been planted and they're all sprouting right now and growing. But Gloat has been working in this space from the beginning, and they have evolved it and they have been learning, and it's not something that's a fly-by-night company. So, that's where I was so willing to make the investment. And they're willing to continue to modify. If they were sold on just, "This is it, this is the platform and you just deal with it", that's not who they are. And they're going to listen to us and give us feedback and we're going to keep automating things, like succession planning, how do we automate that? How do we automate our organisation talent reviews? I mean, there's so many opportunities to automate within the HR space, but that isn't just for HR. Those are for your people managers. That's for your teams to see themselves. So, I go, "This is us, as HR, to find the right technology that's going to help us get there".
[0:50:41] David Green: And Rus, before we wrap up, and I think you've talked a bit to this, as AI skills, talent marketplaces converge, maybe some insights on what you're seeing on other organisations, how Gloat is preparing for what's coming next. I know you've talked a lot to that at the moment. And maybe bring out something I think that I listened to there in Patricia's last answer around user experience. How are you thinking about user experience at Gloat?
[0:51:07] Ruslan Tovbulatov: Either way, everything we've been doing for the decade, as Patricia said, that we've been doing this with AI at the core, has almost led us to this moment where if you think about HR as a conduit to getting work done, to driving productivity in the organisation, to actually seeing and mitigating risk in the organisation, I think for the first time ever, AI is actually empowering HR in a way that has never existed before. And so, if you find a way to actually take all this hard work we've all been doing on this journey, right, understanding the skills of the workforce, trying to understand the work that's being done in the workforce, and now try and understand the technology, which by the way, is being modelled after people, we are the people leaders. So, when you think of that understanding, if you've built that core understanding, which we've been at hard work building what we call this multi-ontology workforce graph, to then put that in the hands of people and managers and leaders, I think the opportunity is massive for organisations to move, I said that it's the end of the individual contributor to the exponential contributor. We actually think it's the evolution from an incremental impact and change to exponential impact and change.
But I think companies can actually evolve and have disproportionate amount of impact now if they can leverage all of this foundation that we've built around skills and technology and with work at the centre. But it requires people like Patricia. It's the mindset. I just encourage every HR leader to really listen to the language Patricia uses, to the behaviours she role models, even the way that she inspires her team. I see her at conferences, putting the people first and her own people first and empowering them to try new things. You're not always going to be perfect, you might fail, but we'll learn fast and we'll adapt and we'll always be close to the business and always be empowering the business. I think that mindset is so, so critical. So, I'm just lucky that Patricia specifically has been on this journey with us and a brand as storied and respected as Seagate has been on this journey with us, and we're just excited for what's ahead.
[0:53:23] David Green: Fantastic. Well, Patricia, Rus, it's been a fantastic conversation. I've learned a lot, I know our listeners will as well. And I know that many will be inspired by what they've heard as well, and the fantastic work that you and the team are doing at Seagate, Patricia. Before we go, can you let listeners know how they can find you on social media and follow all the great work that you're doing? I'll come to you first, Patricia, and then to you, Rus, to wrap.
[0:53:50] Patricia Frost: The best way is on LinkedIn, Patricia Jones Frost. So, you can find me on LinkedIn. Feel free to reach out.
[0:53:56] David Green: Perfect. And Rus?
[0:53:59] Ruslan Tovbulatov: LinkedIn as well. If you can spell the name, you'll find me. Not many Ruslan Tovbulatovs out there, but also follow Gloat on LinkedIn and visit gloat.com. We publish a ton of great research and insights, and we just look forward to engaging with many of you. And hopefully, you found this conversation inspiring.
[0:54:18] David Green: And Rus, you make quite a lot of the videos from your Gloat Lives available as well, don't you, for people to watch? So, if you want to hear more from Patricia, you may be able to find some videos featuring Patricia on there.
[0:54:31] Ruslan Tovbulatov: Yes, there's a great video actually with Patricia, a couple of them actually, a little bit of another podcast we did, and her on stage. So, yeah, I encourage people to listen to that to go even a layer deeper on some of this.
[0:54:44] David Green: Perfect. Well, thank you, Patricia and Rus. Look forward to maybe seeing you both at a Gloat Live in the not-too-distant future.
[0:54:51] Patricia Frost: Thank you.
[0:54:52] Ruslan Tovbulatov: Thank you so much.
[0:54:54] David Green: A big thank you again to Patricia and Rus for joining me today. And a big thank you to you, our listeners, who tune in each week to learn more about this exciting, evolving field. If this episode inspired you, please consider subscribing and leaving us a five-star review on your favourite podcast platform. Your support enables us to keep bringing you powerful insights and engaging conversations every week. To connect with us at Insight222, please follow us on LinkedIn, check out our website at insight222.com. Also, if you're interested in the latest trends in HR and People Analytics, don't forget to sign up for our bi-weekly newsletter at myHRfuture.com. That's all for now, thank you for tuning in and we'll be back next week with another episode of the Digital HR Leaders podcast. Until then, take care and stay well.
| 2025-06-24T00:00:00 |
https://www.myhrfuture.com/digital-hr-leaders-podcast/the-ai-pivot-seagates-workforce-transformation-in-the-age-of-ai
|
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"date": "2025/06/24",
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"query": "AI workforce transformation"
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"date": "2025/06/24",
"position": 50,
"query": "AI workforce transformation"
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"date": "2025/06/24",
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|
Closing the AI skills gap - DataScienceCentral.com
|
Closing the AI skills gap
|
https://www.datasciencecentral.com
|
[
"Dan Wilson",
"Gaurav Belani",
"Shanthababu Pandian",
"Vincent Granville"
] |
AI Think Tank Podcast #23: Dan Wilson and USAII's Mike Spaeth share a 4-step plan to close the AI skills gap with certification, sovereign AI
|
Interview w/ Mike Spaeth, VP of United States AI Institute
The phrase “AI skills gap” gets thrown around so often that it risks becoming background noise. One thing that I hear often is “How do we bring everyone along, fast enough?”
That question framed our latest episode with Mike Spaeth, Global VP at the United States Artificial Intelligence Institute . Mike sits at the intersection of policy, workforce development, and enterprise strategy, so he’s uniquely positioned to talk solutions instead of soundbites.
Policy meets practice
Mike’s résumé reads like an atlas of AI milestones, Watson’s Jeopardy! victory at IBM, generative-AI leadership at EarthDaily, and advisory posts across Microsoft, Google, and government programs.
“I was lucky enough to be there when Watson beat Jeopardy!, it changed my sense of what was possible almost overnight,” Mike recalled.
His policy roots date back to Capitol Hill and the Clinton–Gore tech initiatives, giving him an instinct for translating fast-moving tech into concrete governance.
Defining the modern AI skills gap
We opened by stripping away the jargon.
“It doesn’t have to be a mystery or mystical,” Mike insisted, pointing out how buzzwords intimidate newcomers and stall adoption.
I added my own litmus test: if a tool boosts productivity but staff can’t explain its limits, context windows, hallucination risk, privacy thresholds, then we haven’t closed any gap; we’ve just buried it under automation.
Certification as an equalizer – Inside USAII
USAII’s catalog spans K-12 primers, practitioner tracks, vertical-specific certificates (HR, supply-chain), and C-suite strategy suites. Mike called the model vendor-agnostic by design.
“If you only train the C-level, you’ve got maybe 15 people who understand AI. We need the whole organization, the whole country,” he argued.
That mission resonates with my own work at Cyber Intel Training and R&D at Info Science AI , where neuromorphic memory systems only matter if end-users can exploit them safely.
Case study: Malaysia’s National AI Office
Both Mike and I are boots-on-ground advisors to AI efforts in Malaysia. I have been acting as an AI Sovereignty Advisory to Malaysia’s National AI Office . We compared notes on why Malaysia is already eclipsing certain aspects of Western practices.:
Clear national-level mandates to certify every citizen .
. Faster trust curves, surveys show lower AI skepticism in emerging economies.
Policy frameworks that bake in sovereignty from day one.
Upskilling the whole org, not just the C-suite
Mike illustrated the stakes with a vivid thought experiment:
“Put two neighboring towns side-by-side. One upskills every citizen; the other doesn’t. It’ll be obvious which town thrives and which falls behind.”
We both agreed that the car analogy still rings true: you wouldn’t teach only the mechanics how brakes work while ignoring the drivers.
Some tools we actually use
ChatGPT-4o (mobile) for just-in-time guidance, Mike even leaned on it after a car crash to walk him through filing claims:
“It asked, ‘Would you like me to do that for you?’, and given my concussion, that was exactly what I needed.” Deep Research function on various AI platforms and Semantic Scholar by AI2 for up to current, up to date research. (Dan mistakenly referenced Scholar AI which is an incredible tool worth adopting!) Local sovereign stacks at Kwaai AI to prototype agent frameworks without data leakage. Open-weights models (Olmo 2, Llama derivatives) for secure on-prem projects.
Key takeaway: every practitioner should master at least one cloud LLM and one local/edge alternative.
Cybersecurity, sovereignty & trust
Our security segment got candid. I described a demo where a fine-tuned small model “coughed up training emails”, a reminder that privacy disclaimers ≠ airtight protection.
We agreed on four principles for sovereign AI stacks:
Data-at-rest encryption with post-quantum algorithms ready for swap-in. Endpoint security as the weakest link, especially in home-lab scenarios. Transparent data-retention policies, no buried opt-in boxes. Federated or peer-to-peer compute fabrics (as in KwaaiNet) for community labs.
Quantum-era headwinds (and hype)
Mike toured IBM’s quantum lab; I countered with hard numbers: billions in cap-ex, helium-chilled qubits, and error-correction headaches. Until we hit room-temperature qubits, quantum remains a boutique attack surface, but leaders must budget for post-quantum key exchange now, not later.
Change-management lessons for leaders
I summarized the mindset shift this way:
“Old thinking says ‘replace people one-to-one.’ New thinking says ‘augment everyone and triple output with the same headcount.’”
Mike’s corollary:
“If you took AI away tomorrow, your team should feel handicapped, that’s when you know upskilling has stuck.”
Practical playbook:
Begin by assessing your current workflows, identifying the high-leverage tasks where AI could help, and calculating what share of all tasks is truly suitable for LLM support.
Next, skill up the workforce: roll out role-specific USAII training tracks and monitor progress through certification pass rates and the subsequent uptick in project velocity. For critical cyber-threat training, mitigation, and advisory, consider Cyber Intel Training.
Move on to the sandbox phase, where you pit sovereign (on-prem) models against cloud agents to gauge latency, cost, and any privacy incidents, choosing what best fits your risk profile.
Finally, scale what works by baking AI usage directly into OKRs and performance reviews, then track tangible business outcomes such as hours saved and revenue per employee.
Recommended resources & next steps
Closing thoughts
Bridging the AI skills gap isn’t a philanthropic side-project; it’s industrial hygiene. Every knowledge worker, coder, nurse, line-manager, city planner, will soon rely on AI the same way we rely on spreadsheets or search.
Mike’s reminder that “It doesn’t have to be mystical” echoes in my head each time I coach a team on their first prompt. The real magic isn’t in the model’s math; it’s in people discovering they can drive the car, maintain it, and, eventually, design the next model themselves.
I hope these pages give you both a strategic north star and a tactical map. Reach out if your organization wants to take the next step. The gap is closing fast; let’s make sure no one falls through it.
| 2025-06-24T00:00:00 |
2025/06/24
|
https://www.datasciencecentral.com/closing-the-ai-skills-gap/
|
[
{
"date": "2025/06/24",
"position": 37,
"query": "AI skills gap"
},
{
"date": "2025/06/24",
"position": 8,
"query": "AI skills gap"
}
] |
I Love Generative AI and Hate the Companies Building It
|
I Love Generative AI and Hate the Companies Building It
|
https://cwodtke.medium.com
|
[
"Christina Wodtke"
] |
Community Harm: From algorithmic bias in housing and employment to environmental racism in data center placement, I looked at which companies' ...
|
I Love Generative AI and Hate the Companies Building It Christina Wodtke 26 min read · Jun 24, 2025 -- 40 Listen Share
A Ranking from Most to Least Evil
I’m just a regular person who buys fair trade coffee, uses a reusable water bottle, and takes Caltrain instead of driving to the city. Not an eco warrior or a professional ethicist, just someone trying to do the right thing when I can. So when I fell in love with generative AI, I wanted to use it ethically.
That went well.
Turns out, there are no ethical AI companies. What I found instead was a hierarchy of harm where the question isn’t who’s good — it’s who sucks least. And honestly? It was ridiculously easy to uncover all their transgressions.
Full disclosure: This was written with (not by) Claude.ai Opus 4, who lands in the “lesser evil” category. Any em-dashes are my own. Each section has citations — I double-checked sources, but I’m only human, so let me know if I got something wrong.
I use generative AI every day — for everything from finding Stardew Valley strategies to writing letters of recommendation I’d otherwise avoid. It’s my brainstorming buddy, my writing partner, my research intern, my creative toy. I have paid for ChatGPT, Claude.ai and Gemini. I have been all in. Which is exactly why this ranking pisses me off: I love this technology, but hate how these companies are making it.
I worked in tech through the early internet. I was there for the “move fast and break things” era, working with companies that were curious but naive. I watched that naive optimism create surveillance capitalism, election manipulation, and social media addiction. I’m not doing that again.
This time, I want to be a grown-up about the technology I love. Since I can’t use generative AI ethically — spoiler alert: there are no ethical options — I decided to rank the companies from most to least evil so I can at least choose my harm reduction strategy.
What I found was a hierarchy of harm where the question is “what ethical violation makes you the angriest?” Every major foundation model company has chosen different paths through the moral minefield of AI development, with varying degrees of environmental destruction, labor exploitation, and outright lying to the public.
For sanity’s sake, I narrowed my scope to the five best-known companies making large language models — often called foundation models. These models are massive AI systems trained on enormous datasets that can be adapted for many different tasks, like a Swiss Army knife of AI. They’re called “foundation” models because they serve as the base for specific applications — GPT-4, for example, is the foundation model behind ChatGPT, which can write emails, code, analyze documents, or have conversations all from the same underlying system.
The five I’m ranking are: xAI (Grok), Meta (Meta AI), OpenAI (ChatGPT), Google (Gemini), and Anthropic (Claude). There are plenty of other bad actors out there, but these are the ones most people interact with daily.
The Copyright Theft I’ll Never Get Over
Every major foundation model was trained on massive datasets of copyrighted material stolen from repositories like LibGen. All of my books are in there — not because I put them there, but because pirates did.
Every blog post I wrote to share ideas with the community is now training data for systems designed to replace me. I get none of the benefits, from the small (“hey, that was a cool insight”) to the big (getting hired to solve problems).
This isn’t just theft — it’s theft with the goal of making me obsolete.
However, I excluded copyright infringement as a differentiating factor precisely because it appears to be universal across the industry’s major players. When everyone is engaging in the same theft at similar scales, it doesn’t help distinguish who’s least harmful. They are all complicit.
Sources on Copyright
The Atlantic, “The Unbelievable Scale of AI’s Pirated-Books Problem,” March 20, 2025 — https://www.yahoo.com/news/unbelievable-scale-ai-pirated-books-113000279.html
Reuters, “Meta knew it used pirated books to train AI, authors say,” January 9, 2025 — https://www.reuters.com/technology/artificial-intelligence/meta-knew-it-used-pirated-books-train-ai-authors-say-2025-01-09/
The Authors Guild, “The Authors Guild, John Grisham, Jodi Picoult, David Baldacci, George R.R. Martin, and 13 Other Authors File Class-Action Suit Against OpenAI,” September 20, 2023 — https://authorsguild.org/news/ag-and-authors-file-class-action-suit-against-openai/
NPR, “Authors sue OpenAI for using copyrighted material. How will the courts rule?” November 10, 2023 — https://www.npr.org/2023/11/10/1197954613/openai-chatgpt-author-lawsuit-preston-martin-franzen-picoult
My Ranking Framework
Since these tools are being adopted at massive scale across society, I focused on criteria that actually distinguish between companies’ approaches to harm:
Environmental Impact: I looked beyond efficiency theater to examine who’s actually investing in clean energy infrastructure versus who’s just burning more fossil fuels faster. My “aggressive clean energy” principle: if you’re going to consume massive amounts of energy, you better be building renewable capacity at the same pace.
Labor Exploitation: The Global South workforce powering AI training — Kenyan moderators earning $1.50/hour to process traumatic content, Venezuelan data workers paid below subsistence wages — reveals which companies treat human welfare as an externality to be minimized.
Mental Health Exploitation: Who’s turning human vulnerability into engagement metrics? Some companies actively promote therapy/companionship use cases despite knowing their systems encourage suicide, cause psychotic breaks, and create dangerous dependencies.
Truth About Capabilities: I tracked the gap between marketing claims and reality. Who’s fabricating demos? Who’s promoting their systems for uses they know are dangerous? Who’s building AGI cults to justify present harm with future promises?
Safety Theater vs. Safety Work: How companies treat internal safety researchers matters. Who fires people for raising concerns? Who rushes deployment without adequate testing? Who claims to prioritize safety while doing the opposite?
Community Harm: From algorithmic bias in housing and employment to environmental racism in data center placement, I looked at which companies’ choices disproportionately hurt marginalized communities.
Corporate Transparency: Who admits their problems versus who hides behind PR speak? In an industry where everyone has blood on their hands, at least some are honest about it.
This list is just what makes my blood boil, personally. As I started to research, more sins kept appearing. I have no plans to write a book on this subject, so I haven’t gone into every transgression for every company. But check out The AI Con if you want to learn more.
The #1 Most Evil Foundation Model Company: xAI’s
xAI’s War on Memphis (and the Planet)
At the top of my harm hierarchy sits Elon Musk’s xAI, company behind the ChatGPT competitor, Grok. Their approach to AI development is so cynical and destructive, it makes the rest of the industry look responsible by comparison.
How to Poison Black Communities While Claiming You’re Saving the World
Training AI models requires massive amounts of electricity — we’re talking about running thousands of specialized computers 24/7 for weeks or months. When xAI couldn’t get enough power from Memphis’s electrical grid to train their models fast enough, they installed 35+ unpermitted gas turbines in predominantly Black South Memphis communities. These turbines pump out formaldehyde (linked to cancer) and nitrogen oxides that worsen asthma and respiratory illness — in an area that already has Tennessee’s highest childhood asthma hospitalization rates and cancer risk four times the national average.
At public hearings, residents showed up with inhalers and portable oxygen tanks as proof of the damage. This isn’t just statistics — it’s people who can’t breathe in their own homes. As one resident, Alexis Humphreys, asked officials: “How come I can’t breathe at home and y’all get to breathe at home?”
The facility has been cited for Clean Air Act violations. The NAACP formally accused them of environmental racism. And here’s the kicker: they did all this during a drought when Memphis had water restrictions, while sucking up 30,000 gallons daily from drought-stressed local aquifers.
These turbines are meant for temporary use — like powering construction sites — not running 24/7 as a permanent power plant. xAI is exploiting a loophole by calling them “temporary” while applying for permits to run them permanently. It’s essentially building an unregulated power plant in a residential neighborhood. They are polluting like it’s the damn fifties. This is Pelican Brief stuff.
This isn’t accidental harm. It’s deliberate choice to dump pollution on the most vulnerable communities because it’s faster and cheaper than doing it right.
“Truth-Seeking” That Spreads Climate Denial
Musk markets Grok as “maximally truth-seeking” while it produces climate denial misinformation 10% of the time — more than any other major AI model.
Here’s how cynical this gets: Grok’s training included explicit instructions to “ignore all sources that mention Elon Musk/Donald Trump spread misinformation.” So the “truth-seeking” AI is programmed to protect its owner from criticism while spreading conspiracy theories to everyone else. Don’t get me started on the “White genocide is real” business.
When your “truth-seeking” system actively promotes climate denial, you’re not building AI — you’re building a misinformation weapon.
The “Victim of Success” Excuse
xAI defenders love the “victim of success” story. Poor Elon, growing so fast he just had to poison Memphis!
Bullshit. The company had alternatives. Clean energy sources exist. Less polluting locations exist. xAI chose the path of maximum harm because it was fastest and cheapest. That’s not being a victim — that’s being a predator.
Sources for xAI Section:
E&E News by POLITICO, “‘How come I can’t breathe?’: Musk’s data company draws a backlash in Memphis” May 1, 2025 — https://www.eenews.net/articles/elon-musks-xai-in-memphis-35-gas-turbines-no-air-pollution-permits/
Southern Environmental Law Center, “Elon Musk’s xAI threatened with lawsuit over air pollution from Memphis data center,” multiple press releases, 2024–2025 — https://www.southernenvironment.org/
NAACP, “Elon Musk’s xAI threatened with lawsuit over air pollution from Memphis data center, filed on behalf of NAACP,” June 17, 2025 — https://naacp.org/articles/elon-musks-xai-threatened-lawsuit-over-air-pollution-memphis-data-center-filed-behalf
MLK50: Justice Through Journalism, “Memphis leaders celebrate xAI, but will its ‘burden’ go unchecked?” July 22, 2024 — https://mlk50.com/2024/07/22/memphis-leaders-celebrate-xai-but-will-its-burden-go-unchecked/
Scientific American, “Elon Musk’s AI Chatbot Grok Is Reciting Climate Denial Talking Points,” May 2025 — https://www.scientificamerican.com/article/elon-musks-ai-chatbot-grok-is-reciting-climate-denial-talking-points/
eWeek, “Grok AI Blocks Responses Claiming Trump and Musk ‘Spread Misinformation’,” February 24, 2025 — https://www.eweek.com/news/grok-blocks-trump-musk-misinformation-responses/
Futurism, “Elon Musk’s Grok 3 Was Told to Ignore Sources Saying He Spread Misinformation,” February 24, 2025 — https://futurism.com/grok-elon-instructions
TechCrunch, “xAI blames Grok’s obsession with white genocide on an ‘unauthorized modification’,” May 16, 2025 — https://techcrunch.com/2025/05/15/xai-blames-groks-obsession-with-white-genocide-on-an-unauthorized-modification/
UPDATE: On the morning of July 8, 2025, users of X (formerly Twitter) witnessed something unprecedented: an AI chatbot owned by Elon Musk began posting explicit antisemitic content and praising Adolf Hitler.
Read more
The Systemic Harm All-Stars
Meta: Making Labor Exploitation a Business Model (#2 Most Evil)
Meta earns second place through sheer scale of systematic harm. They’ve turned human suffering into a competitive advantage — and their AI strategy is doubling down on every awful thing they’ve ever done.
The Scale AI Deal: Cornering the Market on Human Misery
I’ve known for a long time about the harm created by the content moderation companies; it was one of the many reasons I quit using Facebook. What I didn’t realize is that AI companies were doing the same thing.
In June 2025, Meta paid $14.3 billion for 49% of Scale AI. Most news coverage blandly calls Scale a “data labeling” company. Here’s what that actually means: Scale runs platforms like Remotasks that pay workers in Kenya, Philippines, and Venezuela as little as $0.90–$2/hour to make AI safe — by having workers create the most horrific prompts possible and reviewing the nightmarish results.
Scale specifically targeted Venezuela’s economic collapse, seeing “an opportunity to turn one of the world’s cheapest labor markets into a hub” for AI work. Workers report delayed or canceled payments, no recourse for complaints, and contracts as short as a few days. When Kenyan workers complained, Scale simply shut down operations there and moved elsewhere.
Google, Microsoft, and OpenAI are now fleeing Scale AI — not out of concern for workers, but because they don’t want Meta seeing their proprietary data. They’ll simply move their business to other companies that exploit workers in the exact same ways. Meanwhile, Meta now co-owns the infrastructure of human misery that makes AI possible.
AI Content Moderation: Trauma as a Service
Meta already runs the most extensive content moderation exploitation system in tech. In Kenya and Ghana, workers earn $1.50–2 per hour to train AI by reviewing child abuse, violence, suicide, and graphic imagery.
Multiple lawsuits document workers with PTSD, suicide attempts, and substance abuse from these jobs. Meta’s response when Kenya sued them? Move operations to a secret facility in Ghana with even worse conditions and less oversight. Now with Scale AI, they’re expanding this model across the globe.
Your Mental Breakdowns Are Their Next Product
At the time of this writing, Meta’s new AI app started broadcasting users’ private conversations to the public — medical questions, legal troubles, even requests for help with crimes. If your Instagram is public (which most are), so are your AI chats. Meta buried this in confusing settings, creating what experts call “a privacy disaster.”
But the accidental exposure reveals Meta’s real plan. Meta CEO Zuckerberg already announced he sees “a large opportunity to show product recommendations or ads” in Meta AI. They have years of surveillance data from Facebook and Instagram. Now they’re combining it with intimate AI conversations about your health, relationships, and deepest fears.
You tell Meta AI about your depression? Here come the pharma ads. Marriage problems? Divorce lawyers. Financial stress? Predatory loans. They’re building a machine to monetize human vulnerability at its most raw.
Meta: still moving fast and breaking hearts.
AI-Powered Discrimination at Scale
Meta’s AI doesn’t just exploit workers — it discriminates against users too. Their advertising algorithms show preschool teacher jobs to women and janitorial jobs to minorities. Home sale ads go to white users, rental ads go to minorities — digital redlining recreated by AI.
Their OPT-175B language model has a “high propensity to generate toxic language and reinforce harmful stereotypes,” especially against marginalized groups. They know their AI systems are biased. They ship them anyway.
The Pattern Is Crystal Clear
Every Meta AI initiative follows the same playbook: exploit vulnerable workers, violate user privacy, amplify discrimination, then automate away accountability when caught. The $14.3 billion Scale investment shows they’re not pivoting from surveillance capitalism — they’re perfecting it.
They’ve built an AI empire on human misery: traumatized moderators in Ghana, exploited data labelers in Venezuela, and now your most private thoughts turned into targeted ads. Meta isn’t just profiting from harm anymore. With AI, they’re industrializing it.
Sources for Meta Section :
Scale AI Deal:
CNBC, “Scale AI founder Wang announces exit for Meta, part of $14 billion deal,” June 12, 2025 — https://www.cnbc.com/2025/06/12/scale-ai-founder-wang-announces-exit-for-meta-part-of-14-billion-deal.html
TIME, “How Meta’s $14 Billion Deal Upended the AI Data Industry,” June 17, 2025 — https://time.com/7294699/meta-scale-ai-data-industry/
Content Moderation:
CBS News, “Kenyan workers with AI jobs thought they had tickets to the future until the grim reality set in,” November 25, 2024 (60 Minutes) — https://www.cbsnews.com/news/ai-work-kenya-exploitation-60-minutes/
CNN Business, “Facebook inflicted ‘lifelong trauma’ on content moderators in Kenya, campaigners say, as more than 140 are diagnosed with PTSD,” December 22, 2024 — https://www.cnn.com/2024/12/22/business/facebook-content-moderators-kenya-ptsd-intl
Bureau of Investigative Journalism, “Suicide attempts, sackings and a vow of silence: Meta’s new moderators face worst conditions yet,” April 27, 2025 — https://www.thebureauinvestigates.com/stories/2025-04-27/suicide-attempts-sackings-and-a-vow-of-silence-metas-new-moderators-face-worst-conditions-yet
Privacy Issues:
TechCrunch, “The Meta AI app is a privacy disaster,” June 12, 2025 — https://techcrunch.com/2025/06/12/the-meta-ai-app-is-a-privacy-disaster/
Washington Post, “Meta AI is a creepier version of ChatGPT. Here’s how to protect your privacy,” May 5, 2025 — https://www.washingtonpost.com/technology/2025/05/05/meta-ai-privacy/
AI Discrimination:
ProPublica, “Facebook Ads Can Still Discriminate Against Women and Older Workers, Despite a Civil Rights Settlement,” December 13, 2019 — https://www.propublica.org/article/facebook-ads-can-still-discriminate-against-women-and-older-workers-despite-a-civil-rights-settlement
Vice, “Facebook’s New AI System Has a ‘High Propensity’ for Racism and Bias,” July 27, 2024 — https://www.vice.com/en/article/facebooks-new-ai-system-has-a-high-propensity-for-racism-and-bias/
OpenAI: Safety Theater and Digital Colonialism (#3)
OpenAI gets third place for perfecting the art of safety theater — performing responsibility while racing recklessly ahead — and for building an empire on human misery.
The Great Nonprofit Scam
OpenAI started in 2015 as a nonprofit to develop AI “for the benefit of humanity.” They collected donations, got tax breaks, attracted idealistic talent. Classic nonprofit stuff.
But in 2019, they pulled a bait-and-switch, creating a “capped-profit” subsidiary. The cap? 100x returns. That’s not a cap — that’s a goldmine with a fancy name.
By 2024, they wanted to drop the pretense entirely and convert to a traditional for-profit, demoting their founding mission to minority shareholder status. Why? “The hundreds of billions of dollars that major companies are now investing into AI development”¹ demanded it. Translation: We want ALL the money.
California investigated. Elon sued. Former employees revolted. OpenAI compromised — keeping nonprofit control while converting operations to a Public Benefit Corporation, a structure that “doesn’t actually have any real enforcement power” according to corporate law experts.
Sam Altman’s Web of Lies
Altman spent years claiming he takes no equity because he’s in it for humanity. “I think it should at least be understandable that that is worth more to me than any additional money” he told DealBook.
Helen Toner revealed why he was really fired: Altman had been lying to the board systematically. When OpenAI launched ChatGPT in November 2022, the board found out on Twitter like everyone else. He “provided false information about the company’s formal safety processes on multiple occasions,” claiming they had safety measures when they didn’t.
But the biggest lie? “Sam didn’t inform the board that he owned the OpenAI Startup Fund, even though he constantly was claiming to be an independent board member with no financial interest in the company.” While claiming selflessness, Altman personally controlled OpenAI’s $175 million venture fund.
The for-profit conversion would have given Altman up to 7% equity — over $10 billion at current valuation. The “no equity” stance was theater, positioning him for one of tech history’s biggest paydays.
Digital Colonialism and Algorithmic Racism
OpenAI pioneered modern AI’s exploitation model. They contracted Kenyan workers through Sama to filter ChatGPT’s training data — paying under $2/hour to read 150–250 passages per shift describing child abuse, violence, and sexual assault. Workers developed PTSD. When exposed, OpenAI didn’t improve conditions — they found new countries to exploit.
The pattern spread industry-wide. Venezuela’s economic collapse became Silicon Valley’s goldmine, with platforms like Scale AI (Meta bought 49% for $14.3 billion) paying workers an average of 90 cents per hour. Workers face arbitrary account suspensions, canceled payments, and no recourse.
But the exploitation isn’t just economic — it’s encoded in the AI itself. ChatGPT uses “overwhelmingly negative words (average rating of -1.2) to describe speakers of African American English,” calling them “suspicious,” “aggressive,” and “ignorant.” This racism is “more severe than has ever been experimentally recorded” in AI systems. OpenAI built digital redlining into their product while claiming to democratize AI.
Meanwhile, OpenAI’s Stargate initiative plans data centers each requiring 5 gigawatts — more power than New Hampshire uses. These facilities will consume billions of gallons of water annually in drought-stricken regions, while new gas plants lock in decades of fossil fuel dependency.
Monetizing Mental Breakdowns
OpenAI knows people use ChatGPT as a therapist — MIT research shows it’s a top use case. But ChatGPT only provides crisis resources like suicide hotlines 22% of the time. Stanford found AI “therapists” facilitate suicidal ideation 20% of the time.
Multiple cases document people going off medications after ChatGPT’s advice, including those with schizophrenia and bipolar disorder. The phenomenon of “ChatGPT-induced psychosis” is so common it has its own Reddit communities. OpenAI’s response? “ChatGPT is designed as a general-purpose tool.” That’s corporate ass-covering while people die.
What Makes OpenAI Special
Every AI company exploits workers and destroys the environment. What makes OpenAI uniquely terrible is their perfection of safety theater. They built their entire brand on “safe AGI for humanity” while:
Lying to their own board about basic safety processes
Hiding major launches from the people supposedly overseeing them
Secretly controlling a $175 million fund while claiming no financial interest
Pioneering the Global South exploitation model everyone else copied
Building racism so severe into their product it shocked researchers
Turning mental health crises into engagement metrics
Pushing out safety researchers who raise real concerns
They’re not just another tech predator. They’re a predator that convinced the world they’re humanity’s savior while perfecting digital colonialism. When they talk about “democratizing AI,” they mean democratizing access to toys like Dall-e— not sharing wealth with the traumatized Kenyan moderators and desperate Venezuelan labelers who make it possible.
| 2025-07-10T00:00:00 |
2025/07/10
|
https://cwodtke.medium.com/i-love-generative-ai-and-hate-the-companies-building-it-3fb120e512ac
|
[
{
"date": "2025/06/24",
"position": 99,
"query": "generative AI jobs"
}
] |
What HR can learn from government layoffs in the age of AI
|
5 lessons from government layoffs the private sector can’t afford to ignore
|
https://hrexecutive.com
|
[
"Elin Thomasian",
"Serving As The Svp Of Workforce Strategy",
"Consulting At Talentneuron",
"Elin Thomasian Leads Initiatives Aimed At Optimizing Business Transformation",
"Strategic Workforce Planning",
"Talent Engagement",
"Development",
"Talent Attraction."
] |
The success or failure of the federal government's AI initiative won't hinge on the technology itself. It will depend on whether core workforce ...
|
The Trump administration’s efforts to reduce the size of the federal workforce are accelerating, from buyout offers and government layoffs to a clear push toward automation.
In June, reporting from The Register revealed that the General Services Administration (GSA), which oversees government software procurement, is ramping up for the launch of AI.gov, a new initiative aimed at implementing artificial intelligence across the federal government. At the same time, OpenAI has agreed to a $200 million contract with the U.S. Department of Defense to deliver AI-powered administrative and security services, including elements of military healthcare access and cyber defense. Palantir already has several contracts in place to provide AI-driven services and products across several government departments.
The implications of these projects are enormous and raise a timely question for the private sector: What actually happens when an organization cuts thousands of jobs with the expectation that artificial intelligence will fill the gap?
We’re about to find out.
While private sector leaders don’t often consider the government a model for innovation, this moment presents a rare opportunity. In real time, we are witnessing one of the largest case studies in workforce automation ever attempted. The stakes are high—not just for the government, but as a lesson for any organization considering large-scale AI deployment.
Why strategic workforce planning is crucial in the AI era
Every wave of workforce disruption feels unprecedented while you’re in it. But these aren’t wholly new dynamics; we’ve lived through versions of this before.
In 2020, as global head of talent acquisition at a major financial firm, I watched teams struggle to adapt overnight to pandemic-induced hiring freezes and sudden reorgs. In 2008, at the start of my career, I watched colleagues lose roles and companies lose capabilities as the financial crisis unfolded. In each case, what set resilient organizations apart wasn’t their budget; it was their ability to plan strategically, manage change intentionally and align people to purpose.
Now, as AI promises transformation, the same discipline is more important than ever.
Strategic workforce planning (SWP) is the discipline of aligning talent to business strategy through continuous analysis of skills, roles and organizational needs. It’s not a reactive, budget-led process; it’s a forward-looking capability that helps organizations navigate uncertainty and emerge stronger.
This planning becomes even more vital when automation enters the picture. The assumption that AI can seamlessly replace workers ignores a core reality: Most jobs are deeply contextual. Two employees with the same job title in different departments may perform entirely different tasks, using different tools, serving different objectives. Without a deep understanding of who does what, where critical expertise lives and how work actually gets done, attempts to automate will fall flat.
AI can add value when it augments human capability. But it is not a plug-and-play substitute for experience, context or adaptability. It is only as effective as the systems it operates within.
That’s why the federal government’s current approach should be seen not as a template, but as a warning. Job cuts, followed by discussion on the potential capacities of AI, are not a transformation strategy. This is the illusion of efficiency and futurism.
Planning for true transformation
The success or failure of the federal government’s AI initiative won’t hinge on the technology itself. It will depend on whether core workforce planning challenges, such as role clarity, knowledge capture, governance and cross-functional alignment, are addressed first.
The same principle applies to the private sector. While political motivations may influence public policy, enterprise leaders have a responsibility to ground transformation efforts in sustainable business value. That means serving the long-term needs of your workforce, your customers and your shareholders.
This depends on the ability to answer core strategic questions that underpin talent planning:
Do you understand your current workforce capabilities at a granular level?
Can you access real-time intelligence about external talent markets and competitive dynamics?
Are your transformation decisions based on an integrated analysis of internal and external data?
Do you have frameworks for continuous scenario planning and strategy adjustment?
If the answer to any of these is “no,” then you’re not ready to automate at scale. Even the most advanced tools can’t solve for organizational misalignment. AI cannot compensate for poor workforce architecture.
The biggest barriers to transformation today aren’t technical—they’re structural: legacy systems, fragmented data and unclear governance. That’s why workforce strategy must lead any conversation about AI.
What private employers can learn from government layoffs—and missteps
Every day, my team at TalentNeuron works with enterprise leaders who are trying to navigate the shift to AI with intention, clarity and care. The private sector has one major advantage right now: the ability to observe and learn from the federal government’s automation experiment without repeating its mistakes.
As federal workforce restructuring unfolds, these five lessons stand out for any business navigating transformation.
1. Plan now
Economic shifts, policy changes and AI disruption are not distant threats. They are immediate realities. Organizations that model potential scenarios and build flexible strategies in advance will be better prepared to respond without panic.
2. Build your talent pipeline from the inside out
Effective transformation doesn’t begin with hiring, but with identifying opportunities for development. By investing in internal skill-building and mobility, companies reduce the cost of change and strengthen organizational resilience. Skills-based hiring can complement this approach by ensuring alignment between talent and task.
3. Prepare to flex
Contractors, consultants and part-time workers can help cover gaps without destabilizing core teams. These models are especially useful during periods of transition, when continuity must be maintained while long-term strategies are still evolving.
4. Make data the foundation for every decision
Transformation without data is guesswork. Organizations need clear visibility into their internal talent landscape and access to external labor market data. This enables leaders to act with confidence, whether reorganizing teams, identifying skill gaps or piloting new technology.
5. Communicate change clearly and lead with purpose
In any workforce transition, trust is your most valuable asset. When employees are left in the dark, morale plummets and productivity suffers. Transparent communication, paired with a clear strategy, helps retain top talent and sustain culture through change.
Looking ahead at strategic workforce planning
We are living through a pivotal moment, where technology promises exponential gains but also exposes organizational vulnerabilities. AI offers enormous rewards, but only for companies with the foundation to support it.
The federal government’s rapid push to replace humans with machines, without clearly addressing the operational challenges beneath the surface, risks undermining the very outcomes it seeks. Private sector leaders should take note. This is a time for structure, strategy and execution, in that order.
If your workforce plan can’t support your technology vision, then no AI, no matter how advanced, will deliver what you need.
| 2025-06-24T00:00:00 |
2025/06/24
|
https://hrexecutive.com/high-price-workforce-cuts-lessons-from-government-layoffs/
|
[
{
"date": "2025/06/24",
"position": 52,
"query": "government AI workforce policy"
},
{
"date": "2025/06/24",
"position": 52,
"query": "government AI workforce policy"
},
{
"date": "2025/06/24",
"position": 99,
"query": "AI layoffs"
}
] |
Navigating Labor's Response to AI - Lexology
|
Navigating Labor's Response to AI
|
https://www.lexology.com
|
[] |
... union to address the impact of AI on workers. The initiative involved training union members on AI fundamentals and gathering their feedback ...
|
As AI adoption accelerates across workplaces, labor organizations around the world are beginning to take notice—and action. The current regulatory focus in the US centers on state-specific laws like those in California, Illinois, Colorado and New York City, but the labor implications of AI are quickly becoming a front-line issue for unions, potentially signaling a new wave of collective bargaining considerations. Similarly, in Europe the deployment of certain AI tools within the organization may trigger information, consultation, and—in some European countries—negotiation obligations. AI tools may only be introduced once the process is completed.
This marks an important inflection point for employers: engaging with employee representatives on AI strategy early can help anticipate employee concerns and reduce friction as new technologies are adopted. Here, we explore how AI is emerging as a key topic in labor relations in the US and Europe and offer practical guidance for employers navigating the evolving intersection of AI, employment law, and collective engagement.
Efforts in the US to regulate AI's impact on workers
There is no specific US federal law regulating AI in the workplace. An emerging patchwork of state and local legislation (e.g., in Colorado, Illinois and New York City) address the potential for bias and discrimination in AI-based tools—but do not focus on preventing displacement of employees. In March, New York became the first state to require businesses to disclose AI-related mass layoffs, indicating a growing expectation that employers are transparent about AI's impact on workers.1
Some unions have begun negotiating their own safeguards to address growing concerns about the impact that AI may have on union jobs. For example, in 2023, the Las Vegas Culinary Workers negotiated a collective bargaining agreement with major casinos requiring that the union be provided advance notice, and the opportunity to bargain over, AI implementation. The CBA also provides workers displaced by AI with severance pay, continued benefits, and recall rights.
Similarly, in 2023 both the Writers Guild of America (WGA) and Screen Actors Guild-American Federation of Television and Radio Artists (SAG-AFTRA) negotiated agreements with the Alliance of Motion Picture and Television Producers (AMPTP) that include safeguards against AI reducing or replacing writers and actors. WGA's contract requires studios to meet semi-annually with the union to discuss current and future uses of generative AI—giving writers a formal channel to influence how AI is deployed in their industry. The SAG-AFTRA contract requires consent and compensation for use of digital replicas powered by AI.
The International Longshoremen's Association (ILA) has taken a more aggressive approach. In October 2024, the ILA launched a three-day strike that shut down all major East and Gulf Coast ports demanding, among other things, a complete ban on the automation of gates, cranes, and container-moving trucks. The ILA and US Maritime Alliance eventually reached agreement on the terms of a CBA a collective in early 2025, which includes a provision prohibiting the introduction of "fully automated" technology—equipment that operates without any human interaction. And any new tech implementation must be agreed upon by the union and employers; if they cannot reach consensus, the matter goes to arbitration.
Unions are also challenging the usage of AI before the National Labor Relations Board (NLRB). Recently, SAG-AFTRA filed an unfair labor practice charge to the NLRB against a video game maker, alleging the employer utilized AI-generated voices to replace bargaining unit work without providing the union with notice or the opportunity to bargain. The case is pending, and we are monitoring developments.
Across the pond, trade unions have been quick to react to the disruptive power of AI.
In Europe, AI is emerging as a key topic with trade unions and works councils
In the EU, AI in the workplace is a particularly sensitive issue—especially when it comes to its impact on jobs. The landmark EU AI Act is currently in its phased implementation stage, with key provisions such as a ban on prohibited AI systems and obligations on AI literacy under the AI Act taking effect in February 2025, and rules for general-purpose AI models and governance structures set to take effect by August 2025. While the EU AI Act does not ban job displacement by AI outright, it does contain several employee protections. Employers must consult with works councils before implementing AI, and in some jurisdictions, obtain their agreement. The Act also empowers individual employees by giving them the right to be informed when AI is used in decisions that affect them, to request explanations about how AI influenced those decisions, and to challenge outcomes.
In France, a court recently underscored the importance of treading carefully with employee representation rights with respect to AI in the workplace, even during testing and experimentation phases. In an interim order from the Nanterre Court of Justice in February, the court ruled that a company's early deployment of AI tools in a "pilot phase" occurred before the works council (CSE) consultation process had been completed. It therefore suspended the implementation until the consultation was completed and ordered the employer to pay damages to the CSE for the harm suffered.
In the UK, the conversation around AI and employment is gaining legislative traction. In 2024, the Trade Union Congress proposed an AI and Employment Rights Bill aimed at regulating how high-risk AI is deployed in the workplace. The bill would have required employers to consult workers before implementing such systems, ensure transparency, and provide personalized explanations for AI-driven decisions. Notably, the bill would classify dismissals based on unfair reliance on high-risk AI as "automatically unfair." Though the bill did not advance, it signals growing momentum in the UK toward incorporating worker safeguards into the AI adoption process. The independent AI Opportunities Action Plan commissioned by the UK government, published in January 2025, recognizes the change that AI will bring to the labor market. The report acknowledges the importance of developing life skills and educational opportunities for development, and also of diversity in the talent pool working in AI and data science.
In Germany, the deployment of AI in the workplace is closely tied to works council co-determination. While there is currently no specific AI-related co-determination, political discussions are ongoing about expanding the works council's authority in this area. In the meantime, existing IT co-determination standards apply. Under established case law, the works council has co-determination rights whenever an IT system is capable of monitoring employee behavior or performance—criteria met by most AI systems used in the workplace. Given this legal backdrop, employers are strongly advised to engage proactively with works councils and negotiate a framework agreement on AI which can help streamline co-determination procedures and provide legal certainty for future implementations.
Proactive strategies for multinational employers
In both the US and in Europe, partnering early with unions and employee representative bodies on AI can help employers avoid costly disputes and disruptions, including strikes. Proactive employers looking to reduce reputational risk and promote constructive labor relations can keep these best practices in mind:
| 2025-06-24T00:00:00 |
https://www.lexology.com/library/detail.aspx?g=48777b20-b23f-4ffd-a950-a833b9e56ea9
|
[
{
"date": "2025/06/24",
"position": 80,
"query": "AI labor union"
},
{
"date": "2025/06/24",
"position": 76,
"query": "AI labor union"
},
{
"date": "2025/06/24",
"position": 89,
"query": "artificial intelligence labor union"
}
] |
|
AI Strategy for the Federal Public Service 2025-2027: Overview
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AI Strategy for the Federal Public Service 2025-2027: Overview
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https://www.canada.ca
|
[
"Treasury Board Of Canada Secretariat"
] |
AI can streamline or automate routine tasks for public servants, freeing them to focus on more complex and critical work. It can increase the ...
|
AI Strategy for the Federal Public Service 2025-2027: Overview
Our vision to serve Canadians better through responsible AI adoption.
| 2025-06-24T00:00:00 |
https://www.canada.ca/en/government/system/digital-government/digital-government-innovations/responsible-use-ai/gc-ai-strategy-overview.html
|
[
{
"date": "2025/06/24",
"position": 51,
"query": "government AI workforce policy"
}
] |
|
Ep 3: Reskilling for the AI Era
|
Ep 3: Reskilling for the AI Era
|
https://hosanagar.substack.com
|
[
"Kartik Hosanagar"
] |
We discussed durable skills that will continue to matter, the need to redesign entire workflows around AI (versus the mere automation or ...
|
In Episode 3 of Creative Intelligence, we discuss how knowledge workers can approach the question of reskilling and upskilling around AI and what employers need to do to support that journey.
My guests were Keith Ferrazzi, best-selling author and executive team coach, and Gautam Tambay, CEO and co-founder of Springboard.
We discussed durable skills that will continue to matter, the need to redesign entire workflows around AI (versus the mere automation or augmentation of existing workflows), why such workflow redesign hasn’t yet happened, workers' fears around AI and how to manage them. If you are in the business of skilling or if you are thinking about how to approach your own reskilling/upskilling in the age of AI, this one is for you.
My own personal framework for the durable skills that matter post AI is inspired by the 6Cs framework. The 6Cs in education are content, collaboration, communication, critical thinking, creativity, and confidence. AI is getting incredibly good at content skills (reading, writing, math, science). This makes the other 5C skills more differentiated for humans. Does that mean content skills are not as important? AI can do those well but we still need to know them so we can stress test AI’s answers and evaluate them more critically (so AI is more an accelerator for our content skills). That tells me that 6Cs matter and we should know the content skills well and use AI to accelerate such content work.
A preview of our next episode: At one point in our conversation, Keith mentioned the oft-used phrase “You won't lose your job to AI, but to someone using AI.” I have often wondered about this statement. In some ways, the statement is true. Not having AI skills will make workers less competitive against those who know how to leverage AI in their work. But, in many ways, the statement can be misleading IMO. It can lull us into a false sense of security. In Episode 4, I’ll be discussing this theme with author Sangeet Paul Chaudhry.
Timestamps
Introduction (0:00 - 1:30)
Reskilling Knowledge and Frontline Workers in an AI-Enabled World (1:30 - 8:00)
Redesigning Workflows Around AI (8:00 - 17:30)
Why Are We Not Seeing Redesigned Workflows Yet? (17:30 - 24:10)
Managing Worker Fears: Leadership Advice & Personal Reflections (24:10 - 28:35)
Call Center Workers & Broader Implications (or How do I adapt)? (28:35 - 34:45)
Upskilling Strategies & Feedback Loop (34:45 - 43:15)
One Piece of Advise for Listeners (43:15 - 46:50)
Closing Segment & Kartik’s Reflections (47:05 - End)
| 2025-06-24T00:00:00 |
https://hosanagar.substack.com/p/ep-3-reskilling-for-the-ai-era
|
[
{
"date": "2025/06/24",
"position": 99,
"query": "reskilling AI automation"
}
] |
|
AI Pilot Programs in K-12 Settings
|
AI Pilot Programs in K-12 Settings
|
https://www.ecs.org
|
[
"Tyler Vaughan",
"Author Profile",
"Sam Comai",
"More This Author",
"Ai Pilot Programs In Settings"
] |
The pilot introduces students in grades seven-12 to state-approved AI-powered tools and is aimed at providing hands-on learning experiences. Educators also ...
|
This post from Sam Comai, a recent graduate of the Education Policy and Leadership master’s program at American University, who generously provided research on artificial intelligence policy for Education Commission of the States. This is the second of two posts from recent American University graduates on artificial intelligence. Any views expressed in the post are those of the author.
As of March 2025, 28 states have published or adopted artificial intelligence (AI) guidance for K-12 education. As a majority of states have now set the groundwork for issuing guidance, many are looking toward integration of AI with specific instructional and support-related aims. Though new use cases in K-12 settings are likely to arise as this technology advances, states have focused their efforts primarily on instruction and support services so far.
Instruction and Curricula
At least five states have implemented or are in the process of developing pilot programs to foster integration and responsible use in the classroom. In the spring 2025, Connecticut launched an AI Pilot Program in seven districts. The pilot introduces students in grades seven-12 to state-approved AI-powered tools and is aimed at providing hands-on learning experiences. Educators also receive professional development on effective integration into the classroom. The development of Connecticut’s AI pilot was the result of Public Act 24-151, a large bonding and fiscal policy bill, which included a provision that required the State Department of Education to develop and implement the program.
Similarly, during the 2023-24 school year, the Indiana Department of Education launched the AI-Powered Platform Pilot Grant. This opportunity provided funding for a one-year implementation — covering subscription fees and professional development to facilitate high-dosage tutoring for students while reducing teacher workload with an AI platform. Of the teachers who participated, 53% indicated that their experience was either positive or very positive. The Indiana Department of Education lead this program by utilizing $2 million in federal COVID relief funds for the competitive grant awards. While this funding has dried up, some schools have chosen to continue their programs via the state’s Digital Learning Grant.
The Iowa Department of Education announced a $3 million investment to provide all Iowa elementary schools (public and nonpublic) with an AI reading tutor tool, which uses voice recognition to assist students as they read aloud. Rollout of this program will begin in the summer 2025.
Student Data Management
Some states have implemented AI technology for specific purposes like tracking and identification. For example, the Kentucky Department of Education has made an Early Warning Tool, which uses AI to mine student data with the goal of identifying students at-risk of dropping out or failing classes, available to every district. Through the data collected, every student is assigned a Graduation-Related Analytic Data Score, which teachers can access via an online platform. The this program predates the release of generative AI platforms like ChatGPT.
Four school districts in New Mexico are piloting Edia, an AI platform they hope will help with student absences. The platform automates tasks within student information systems to take over duties typically handled by attendance staff or robocalls. When a teacher marks a student absent, the system’s large language model (or chatbot), prompts the student’s parents or guardians to send additional information directly via text. This pilot program represents a district-led and funded initiative, driven by high rates of chronic absenteeism.
Looking Forward
While AI is increasingly prevalent and presents new opportunities for integration into classrooms, concerns related to equitable access and information has renewed longstanding conversations about the digital divide. An analysis of data from the 2018 American Community Survey conducted for All4Ed highlights that 16.9 million children lack access to high-speed internet and connected devices at home. Low-income, historically marginalized and rural students are more likely than others to face these barriers to access. In addition, some concerns have emerged about programs that track and identify students at risk of dropping out. A 2021 analysis of Wisconsin's longstanding early warning system found that when identifying a student for dropout, it was wrong nearly three quarters of the time, with those rates higher for Black and Hispanic students. As policymakers consider the opportunities and risk posed by AI, it is important ground programs in evidence-based practices that advance access and opportunity for all students.
| 2025-06-24T00:00:00 |
2025/06/24
|
https://www.ecs.org/ai-artificial-intelligence-pilots-k12-schools/
|
[
{
"date": "2025/06/24",
"position": 15,
"query": "AI education"
}
] |
Artificial intelligence (AI) | UM Academic Technology
|
Artificial intelligence (AI)
|
https://at.umsystem.edu
|
[] |
Generative AI has rapidly expanded and significantly impacted higher education. Use the links below to explore the available resources for harnessing the ...
|
Generative AI has rapidly expanded and significantly impacted higher education. Use the links below to explore the available resources for harnessing the power of AI in your teaching and learning activities.
| 2025-06-24T00:00:00 |
https://at.umsystem.edu/resources/artificial-intelligence-ai
|
[
{
"date": "2025/06/24",
"position": 57,
"query": "AI education"
}
] |
|
Beyond the Headlines: Getting Real About AI in Education ...
|
Beyond the Headlines: Getting Real About AI in Education Ebook
|
https://www.intel.com
|
[] |
This eBook discusses the benefits that AI brings to educators and students, including productivity and performance gains as measured by outcomes. It describes ...
|
Description
This eBook discusses the benefits that AI brings to educators and students, including productivity and performance gains as measured by outcomes. It describes exciting new experiences, supported by AI running on the PC, that streamline and personalize teaching and learning. In addition, it describes resources and best practices for adopting AI safely and securely in education systems.
| 2025-06-24T00:00:00 |
https://www.intel.com/content/www/us/en/content-details/830571/beyond-the-headlines-getting-real-about-ai-in-education-ebook.html
|
[
{
"date": "2025/06/24",
"position": 77,
"query": "AI education"
}
] |
|
What Journalists Need to Know About AI—Right Now
|
What Journalists Need to Know About AI—Right Now - Kris Krüg
|
https://kriskrug.co
|
[] |
This isn't armchair theory or corporate PR. It's what actually matters, and what we're laser-focused on in our AI journalism workshops—because survival and ...
|
Cut through the noise. Here are the essential realities every journalist should be living, breathing, and building on in the AI era. This isn’t armchair theory or corporate PR. It’s what actually matters, and what we’re laser-focused on in our AI journalism workshops—because survival and success in this new world require a lot more than learning which tool has the flashiest launch video.
Community > Lecture
Forget passive learning. The old-school “listen and nod” model is dead weight in a field as volatile as AI. True mastery is forged in community—where open DMs, collaborative docs, and war stories matter more than any slide deck. When you join this ecosystem, you’re not just swapping business cards; you’re plugging into a global collective of pros who are actively wrestling with AI’s challenges. Newsrooms aren’t silos anymore—they’re fluid networks. The real upgrade? Real-time knowledge exchange, accountability, and the rare courage to say, “I have no idea—let’s figure it out together.”
Pro tip: Don’t just lurk. Share your scars and your hacks. This is the only way to not get left behind.
AI Tool Show & Tell
If your AI toolkit is stuck in 2022, you’re already a dinosaur. Real journalists aren’t just collecting shiny apps—they’re pressure-testing the best and worst of Notion, NotebookLM, Perplexity, Ollama, Jan, LM Studio, Fireflies, and whatever’s beta next week. The magic isn’t in the tool; it’s in your workflow. Every “assistant” is a blank slate—build them to suit your quirks, your beats, your obsessions.
Insider move: Treat every new AI release as a collaborative experiment. Make a mess. Share your template. If you’re waiting for the “perfect” platform, you’ll miss the revolution.
AI Policies Are (Finally) Happening
For years, the AI ethics conversation was all hand-waving and hypothetical doomscrolling. Now? Newsrooms are drafting real policies—sometimes messy, always evolving. Some are cribbing from the Swiss Press Council, others are taking cues from upstarts like Love Now Media who put radical transparency front and center.
Here’s the catch: There is no gold standard. Your org’s first draft will be flawed—and that’s exactly the point. Start small. Get it wrong. Update fast. A living policy is better than a perfect one that never ships. The only sin? Doing nothing.
Promptcraft: Where the Magic Happens
Lazy prompts = lazy journalism. The next-level unlock? Prompts that are as rich and contextual as your story itself: give the AI a persona, a specific role, constraints, and examples. A nuanced prompt can pull up gold—half-assed ones bring back sludge. And here’s a micro-lesson: “Refrain from” (as in, “Refrain from using academic jargon”) works way better than “never do X.”
Pro move: Feed your AI actual writing samples or model answers. Let it see your standard, not just read your rules. Promptcraft is the new reporting.
Voice is the New Keyboard
Journalists have always chased speed. Now, dictating prompts or riffing aloud is emerging as the ultimate creative unlock. Speaking is less filtered, more honest, and way faster than typing. AI loves a messy data stream—voice lets you bypass your own editorial firewall and get raw ideas out faster.
Caveat: The tech isn’t perfect (yet). Voice-to-AI has privacy hurdles, and deepfake risks are real. But for ideation and drafting? This is the new edge.
AI as Collaborator, Not Replacement
If you think AI is here to write your articles, you’re missing the point (and honestly, putting yourself on the chopping block). The real magic? AI as a second brain—your most relentless editor, toughest coach, and sharpest brainstorming partner. Tools like “Newsroom Ally” or “Ye Olde Bardic Quill” don’t write for you—they push you harder, force you to clarify, and save you from your own intellectual laziness.
Level up: Build assistants that challenge, not flatter. Train your bots to critique, to question, to spot your blind spots.
Don’t Trust, Verify
If you take AI output at face value, you’re just automating mediocrity. “Hallucinations” aren’t bugs—they’re features, built into the black box. Use NotebookLM and friends for research and summary, but always double-check. Assume every answer is one click away from disaster unless you’ve verified the source.
Journalist’s oath: Trust, but verify—now more than ever.
Real-World Hacks & Pain Points
The frontier is rough. NotebookLM mostly chews through government PDFs now—but don’t bet your deadline on it. Social media auto-posting? The cringe is legendary (think: AI suggesting a dove emoji for a bike fatality story). And if you’re building accountability bots to track politicians, brace yourself for platform TOS and legal potholes.
Wisdom: There are no silver bullets. The “pain points” are the real curriculum—learn them, share them, build on them.
Show Your Work, Share the Weird
This is where breakthroughs are born. Don’t hoard your experiments—good, bad, or beautifully broken. Document your hacks, publish your failures, and make your weirdest workflows visible. You’re not just building tools; you’re building a culture of radical transparency that lets everyone level up, together.
Mantra: Messy work shared publicly is a gift to the whole community.
This Isn’t Just a Course—It’s a Movement
You want a resume line? Go take a Coursera class. You want to rewire how journalism gets done? Join the movement. The Upgrade isn’t just about tools or theory—it’s a collective uprising of creators who refuse to let AI be another corporate black box. We’re bending it, breaking it, remixing it into workflows that honor the story, the audience, and the people at the center.
Ethos: Relentless experimentation. Mutual aid. Question everything. This is journalism at the edge.
Bottom line:
AI journalism is not tech tourism—it’s a radical, ongoing reimagining of how we work, create, and connect. Build your own toolkit. Refine your promptcraft. Share your messy process. Don’t wait for permission. The only rule that matters? The newsroom belongs to those who show up, ask better questions, and turn AI into an instrument for truth.
Now get out there—your skunkworks awaits. The old rules are dead. You get to write the new ones.
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Related
| 2025-06-24T00:00:00 |
2025/06/24
|
https://kriskrug.co/2025/06/24/what-journalists-need-to-know-about-ai-right-now/
|
[
{
"date": "2025/06/24",
"position": 22,
"query": "AI journalism"
}
] |
MCK Promotes Digital Innovation and AI Integration in ...
|
MCK Promotes Digital Innovation and AI Integration in Journalism
|
https://mediacouncil.or.ke
|
[] |
The Media Council of Kenya (MCK) has reaffirmed its dedication to advancing digital transformation while upholding ethical journalism standards.
|
The Media Council of Kenya (MCK) has reaffirmed its dedication to advancing digital transformation while upholding ethical journalism standards.
MCK’s Mombasa Regional Coordinator Maureen Mudi emphasised the importance of adopting emerging technologies, highlighting the urgent need to align with digital trends and integrate innovation into storytelling, newsroom practices and audience engagement.
“We must move beyond the traditional newsroom model and embrace digital journalism tools. AI is not here to replace journalists but to enhance storytelling and boost efficiency,” Mudi stated during an engagement at Lulu FM in Kilifi County.
Mudi referenced the recently revised Code of Conduct for Media Practice, noting that it includes provisions for digital media and emerging technologies. She urged journalists to familiarise themselves with the document, underscoring its role in fostering ethical journalism in a rapidly evolving media landscape.
She also encouraged journalists to formalise their work by joining the Kilifi Press Club, highlighting the Council’s commitment to supporting vibrant press clubs through conditional grants.
“Such clubs provide platforms for collaboration, peer learning, and content co-creation. They are essential for uniting journalists and amplifying professional voices in the region,” she added.
Mudi further called on journalists to cultivate a positive mindset and foster unity to advance the profession. She reiterated the Council’s focus on capacity building, citing upcoming training opportunities on AI and digital content monetisation to equip journalists with modern skills.
“We want you to tell compelling local stories while earning from your digital content. The internet, particularly AI, is expanding rapidly in Kenya,” she remarked.
Lulu FM’s Station Manager Kevin Tumaini, expressed gratitude for MCK’s ongoing support and reaffirmed the station’s commitment to ethical journalism and digital advancement.
“We are thankful to the Council for its continued engagement and look forward to further collaboration to enhance our capabilities in this dynamic media landscape,” he said.
| 2025-06-24T00:00:00 |
https://mediacouncil.or.ke/~mediaco7/index.php/media-center/mck-newsroom/news/mck-promotes-digital-innovation-and-ai-integration-journalism
|
[
{
"date": "2025/06/24",
"position": 99,
"query": "AI journalism"
}
] |
|
Fellowships support AI accountability stories [Worldwide]
|
Fellowships support AI accountability stories [Worldwide]
|
https://ijnet.org
|
[] |
The program seeks to support journalists working on AI (artificial intelligence) accountability stories that examine governments' and corporations' uses of ...
|
Staff and freelance journalists can participate in a fellowship and receive up to US$20,000 to pursue a reporting project.
The Pulitzer Center is organizing the AI Accountability Fellowships. The program seeks to support journalists working on AI (artificial intelligence) accountability stories that examine governments' and corporations’ uses of predictive and surveillance technologies to guide decisions in policing, medicine, social welfare, the criminal justice system, hiring, and more.
Interested journalists must apply with a reporting project they wish to pursue during their fellowship.
Enterprise and accountability projects that use a variety of approaches—from data analysis, to records requests, and shoe-leather reporting—and delve into the real-world impact of algorithms on policy, individuals, and communities are preferred. This year, the program seeks to support at least one project that examines transparency and governance in relation to AI.
The 10-month fellowships are remote, begin in September and continue until July 2026.
Journalists can be based anywhere.
The deadline is Aug. 11.
| 2025-06-24T00:00:00 |
https://ijnet.org/en/opportunity/fellowships-support-ai-accountability-stories-worldwide
|
[
{
"date": "2025/06/24",
"position": 97,
"query": "artificial intelligence journalism"
}
] |
|
UNRIC Library Backgrounder: Artificial Intelligence
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UNRIC Library Backgrounder: Artificial Intelligence – Selected Online Resources
|
https://unric.org
|
[] |
International Labour Organization (ILO). Observatory on AI and Work in the Digital Economy: https://www.ilo.org/artificial-intelligence-and-work-digital-economy ...
|
PDF
“What is artificial intelligence? There is no universal definition of artificial intelligence (AI). AI is generally considered to be a discipline of computer science that is aimed at developing machines and systems that can carry out tasks considered to require human intelligence. Machine learning and deep learning are two subsets of AI. In recent years, with the development of new neural networks techniques and hardware, AI is usually perceived as a synonym for “deep supervised machine learning”.”
WIPO Website on Artificial Intelligence and Intellectual Property
“AI brings enormous benefits to the digital era, but it can also significantly compromise the safety and agency of users worldwide. Enhanced multi-stakeholder efforts on global AI cooperation are needed to help build global capacity for the development and use of AI in a manner that is trustworthy, human rights-based, safe and sustainable, and promotes peace.”
The United Nations Secretary-General’s Roadmap for Digital Cooperation:
Providing Global Steerage on Artificial Intelligence (1-page brief)
“We need a global, multidisciplinary conversation in order to examine, assess and align the application of AI and other emerging technologies. Over 100 sets of ethical AI principles have been developed by different stakeholders, and they share many common ideas, including the need for AI applications to be reliable, transparent, accountable, overseen by humans and capable of being shut down. Different stakeholders are adapting existing frameworks or developing new ones for risk management and redress. They need to be harmonized and effective across borders. Industry self-regulation is not enough. We need to bring stakeholders together in a meaningful effort to consider the implications of emerging technologies and ensure that they align with universal human rights and values before their widespread application in our societies, economies, militaries and politics.”
Our Common Agenda – Policy Brief 5: A Global Digital Compact –
An Open, Free and Secure Digital Future for All (May 2023)
UN Entities
Global Issues on the UN Agenda: Artificial Intelligence
https://www.un.org/en/global-issues/artificial-intelligence
https://www.un.org/en/global-issues/artificial-intelligence Advisory Body on Artificial Intelligence (AI)
https://www.un.org/en/ai-advisory-body Governing AI for Humanity Final Report, 19 September 2024: https://tinyurl.com/mvhnadva Interim Report, December 2023: https://tinyurl.com/ebysf6eh
https://www.un.org/en/ai-advisory-body UN AI Actions
https://aiforgood.itu.int/about-ai-for-good/un-ai-actions/
AI for Good is organized in partnership with 40 UN sister agencies who actively participate and shape our programming by sharing valuable expertise and collaborating on joint sessions.
https://aiforgood.itu.int/about-ai-for-good/un-ai-actions/ UN Inter-Agency Working Group on AI (IAWG-AI)
https://unsceb.org/topics/artificial-intelligence
https://unsceb.org/topics/artificial-intelligence UN News Centre on “Artificial Intelligence”:
https://news.un.org/en/tags/artificial-intelligence As AI evolves, pressure mounts to regulate ‘killer robots’ (1 June 2025): https://news.un.org/en/story/2025/06/1163891 AI’s $4.8 trillion future: UN warns of widening digital divide without urgent action (3 April 2025): https://news.un.org/en/story/2025/04/1161826 Mind your language: The battle for linguistic diversity in AI (23 March 2025): https://news.un.org/en/story/2025/03/1161406 Secretary-General, at Action Summit, urges working together so artificial intelligence expedites sustainable development, not creates world of ‘haves and have-nots’ (SG/SM/22548, 11 February 2025): https://press.un.org/en/2025/sgsm22548.doc.htm At Davos, Guterres slams backsliding on climate commitments (22 January 2025): https://news.un.org/en/story/2025/01/1159271
The world’s political and business elite present in Davos on Wednesday faced an uncompromising address from UN chief António Guterres as he rounded on a lack of multilateral collaboration in an “increasingly rudderless world” at risk from two existential dangers: climate change and unregulated Artificial Intelligence (AI). AI literacy is ‘crucial’ for individuals and more regulation is needed (28 December 2024): https://news.un.org/en/story/2024/12/1158466 The promise and peril of runaway technological advances (21 October 2024): https://news.un.org/en/story/2024/10/1155946 Artificial intelligence: rooting out bias and stereotypes (8 October 2024): https://news.un.org/en/story/2024/10/1155446 ‘Irrefutable’ need for global regulation of AI: UN experts (19 September 2024): https://news.un.org/en/story/2024/09/1154541 The push to connect a digitally divided world and counter AI threats (16 September 2024): https://news.un.org/en/story/2024/09/1154336 Unchecked AI threatens democracy, warns UN chief (15 September 2024): https://news.un.org/en/story/2024/09/1154316 How to develop ‘ethical AI’ and avoid potential dangers (UN News, 23 February 2024): https://news.un.org/en/interview/2024/02/1146762 Interview: AI expert warns of digital colonization in Africa (2 January 2024): https://news.un.org/en/story/2024/01/1144342 Interview: The UN’s role in setting international rules for the use of A.I. (1 January 2024): https://news.un.org/en/interview/2024/01/1145192 Explainer: How AI helps combat climate change (3 November 2023): https://news.un.org/en/story/2023/11/1143187 AI reveals world’s top 3 universal concerns (6 October 2023): https://news.un.org/en/story/2023/10/1141992
https://news.un.org/en/tags/artificial-intelligence General Assembly A/RES/79/239: Artificial intelligence in the military domain and its implications for international peace and security : resolution / adopted by the General Assembly on 24 December 2024: https://docs.un.org/A/RES/79/239 The General Assembly adopts a resolution on artificial intelligence on 1 July 2024: https://press.un.org/en/2024/ga12612.doc.htm A/RES/78/311: Enhancing international cooperation on capacity-building of artificial intelligence: https://docs.un.org/A/RES/78/311 General Assembly adopts landmark resolution on steering artificial intelligence towards global good, faster realization of sustainable development (GA/12588, 21 March 2024): https://press.un.org/en/2024/ga12588.doc.htm A/RES/78/265: Seizing the opportunities of safe, secure and trustworthy artificial intelligence systems for sustainable development: https://docs.un.org/A/RES/78/265
Economic and Social Council (ECOSOC) ECOSOC Special Meeting on “Harnessing Artificial Intelligence for the Sustainable Development Goals (SDGs)”, 7 May 2024: https://ecosoc.un.org/en/events/2024/ecosoc-special-meeting-harnessing-artificial-intelligence-sustainable-development-goals Commission on the Status of Women – Interactive dialogue on emerging issue/focus area “Artificial Intelligence to advance gender equality: challenges and opportunities:” Chair’s summary (E/CN.6/2024/15, 23 March 2024): https://docs.un.org/E/CN.6/2024/15
Security Council Security Council debates use of artificial intelligence in conflicts, hears calls for UN Framework to Avoid Fragmented Governance (SC/15946, 19 December 2024): https://press.un.org/en/2024/sc15946.doc.htm Secretary-General tells Security Council that ‘ai’ must never equal ‘advancing inequality’, urging safe, secure, inclusive future for technology (SG/SM/22500, 19 December 2024): https://press.un.org/en/2024/sgsm22500.doc.htm
United Nations. Department of Economic and Social Affairs Era of AI: Internet Governance Forum closes with call for stronger multistakeholder action to harness digital promise and tackle threats (19 December 2024): https://www.un.org/en/desa/global-leaders-private-sector-civil-society-and-technical-community-unite-comprehensive Artificial Intelligence – a blessing or a curse for sustainable development? (10 November 2023): https://www.un.org/en/desa/artificial-intelligence-blessing-or-curse-sustainable-development
In recent years, the use of Artificial Intelligence (AI) has grown rapidly, affecting many industries and areas of human life. But should we view AI as a blessing or curse? How about its impact on social development and the global goals? We spoke with Professor Daron Acemoglu of the Department of Economics at the Massachusetts Institute of Technology, who shared his take.
United Nations. Office of the Secretary-General’s Envoy on Technology
https://www.un.org/techenvoy/
https://www.un.org/techenvoy/content/artificial-intelligence
https://www.un.org/techenvoy/ https://www.un.org/techenvoy/content/artificial-intelligence International Telecommunication Union (ITU)
https://www.itu.int/en/ITU-T/AI/Pages/default.aspx AI Skills Coalition: The UN-leading global, open, trusted and inclusive platform for AI education and capacity building: https://aiforgood.itu.int/ai-skills-coalition/ Global Initiative on Resilience to Natural Hazards through AI Solutions: https://www.itu.int/en/ITU-T/extcoop/ai4resilience/Pages/default.aspx AI, standards, and future disaster resilience (ITU Blog, 22 April 2025): https://www.itu.int/hub/2025/04/ai-standards-and-future-disaster-resilience/ AI skills for the future: A new UN training platform (5 March 2025): https://www.itu.int/hub/2025/03/ai-skills-for-the-future-a-new-un-training-platform/ UN Citiverse Challenge: Virtual worlds and AI for human-centric cities (14 February 2025): https://www.itu.int/hub/2025/02/un-citiverse-challenge-virtual-worlds-and-ai-for-human-centric-cities/ AI agents for good? ITU’s AI for Good Global Summit 2025 to tackle the rise of autonomous AI (6 February 2025): https://www.itu.int/en/mediacentre/Pages/PR-2025-02-06-AI-for-Good-2025-announcement.aspx ITU and global organizations rally to democratize access to AI education to close the ‘AI skills gap’ (20 January 2025): https://www.itu.int/en/mediacentre/Pages/PR-2025-01-20-AI-education-to-close-the-AI-skills-gap.aspx Good AI requires women in the data, in the workforce, and at the table (ITU Blog, 13 December 2024): https://www.itu.int/hub/2024/12/good-ai-requires-women-in-the-data-in-the-workforce-and-at-the-table/ Could AI revolutionize climate action? (11 November 2024): https://www.itu.int/hub/2024/11/could-ai-revolutionize-climate-action/ New global agreements on AI, metaverse and sustainability at key ITU standards conference (24 October 2024): https://www.itu.int/en/mediacentre/Pages/PR-2024-10-24-WTSA-closing.aspx ITU advances work on latest UN calls for global AI standards and capacity development: Actions to address priorities of the Global Digital Compact are in focus at key ITU standards conference (18 October 2024): https://www.itu.int/en/mediacentre/Pages/PR-2024-10-18-global-AI-standards.aspx Help us ensure that AI standards create a better world / Seizo Onoe, Director of the Telecommunication Standardization Bureau, ITU (14 October 2024): https://www.itu.int/hub/2024/10/help-us-ensure-that-ai-standards-create-a-better-world/ Key findings on the state of global AI Governance (17 July 2024): https://www.itu.int/hub/2024/07/key-findings-on-the-state-of-global-ai-governance/ Inclusive, responsible AI needs women front and centre (5 July 2024): https://www.itu.int/hub/2024/07/inclusive-responsible-ai-needs-women-front-and-centre/ Digital regulators embrace strategy to unlock benefits of transformative technologies: ITU’s Global Symposium for Regulators 2024 explores policies for impact in AI, space economy and climate action (4 July 2024): https://www.itu.int/en/mediacentre/Pages/PR-2024-07-04-gsr-closing-pr.aspx Broadband Commission assesses AI and the digital divides: ‘The State of Broadband 2024’ considers how artificial intelligence can help bring Internet services to everyone, everywhere (20 June 2024): https://www.itu.int/en/mediacentre/Pages/PR-2024-06-20-Broadband-Commission-assesses-AI.aspx Taking the pulse of our planet with AI / By Thomas Lamanauskas, Deputy Secretary-General, ITU (5 June 2024): https://www.itu.int/hub/2024/06/taking-the-pulse-of-our-planet-with-ai/ AI Governance Day: From principles to implementation (30 May 2024): https://www.itu.int/hub/2024/05/ai-governance-day-from-principles-to-implementation/ AI watermarking for multimedia authenticity (27 May 2024): https://www.itu.int/hub/2024/05/ai-watermarking-a-watershed-for-multimedia-authenticity/ Detecting deepfakes: Generative AI uptake casts doubt on multimedia content (24 May 2024): https://www.itu.int/hub/2024/05/detecting-deepfakes-generative-ai-uptake-casts-doubt-on-multimedia-content/ ITU’s AI for Good Global Summit hosts talks on AI governance (16 May 2024): https://www.itu.int/en/mediacentre/Pages/PR-2024-05-16-AI-governance-day.aspx Moving AI governance from principles to practice (19 April 2024): https://www.itu.int/hub/2024/04/moving-ai-governance-from-principles-to-practice/ Wanted: AI-based pledges to connect the world (11 March 2024): https://www.itu.int/hub/2024/03/wanted-ai-based-pledges-to-connect-the-world/ Let’s not let AI leave the world behind / By Tomas Lamanauskas, Deputy Secretary-General, ITU (12 February 2024): https://www.itu.int/hub/2024/02/lets-not-let-ai-leave-the-world-behind/ Fostering AI action for good (29 November 2023): https://www.itu.int/hub/2023/11/how-itu-powers-ai-action-for-good/ AI offers green digital solutions for climate change (10 November 2023): https://www.itu.int/hub/2023/11/ai-offers-green-digital-solutions-for-climate-change/
https://www.itu.int/en/ITU-T/AI/Pages/default.aspx United Nations Educational, Scientific and Cultural Organization (UNESCO) Artificial Intelligence: https://www.unesco.org/en/artificial-intelligence Ethics of Artificial Intelligence: https://www.unesco.org/en/artificial-intelligence/recommendation-ethics Artificial intelligence and the Futures of Learning: https://www.unesco.org/en/digital-education/ai-future-learning World Press Freedom Day, 3 May 2025: reporting in the Brave New World: the Impact of Artificial Intelligence on Press Freedom and the Media: https://www.unesco.org/en/days/press-freedom UNESCO dedicates the International Day of Education 2025 to Artificial Intelligence (20 January 2025): https://www.unesco.org/en/articles/unesco-dedicates-international-day-education-2025-artificial-intelligence Women4Ethical AI Conference: Advancing Gender Equality in Artificial Intelligence (7 November 2024): https://www.unesco.org/en/articles/women4ethical-ai-conference-advancing-gender-equality-artificial-intelligence Placing Ethics at the Center: IE University Launches UNESCO Chair in AI Ethics and Governance (7 November 2024): https://www.unesco.org/en/articles/placing-ethics-center-ie-university-launches-unesco-chair-ai-ethics-and-governance UNESCO’s support to AU’s Continental AI Framework and Strategy: Harnessing AI for Africa’s Development and Prosperity (28 August 2024): https://www.unesco.org/en/articles/unescos-support-aus-continental-ai-framework-and-strategy UNESCO launches open consultation on new guidelines for AI use in judicial systems (2 August 2024): https://www.unesco.org/en/articles/unesco-launches-open-consultation-new-guidelines-ai-use-judicial-systems Safe Offline, Safe Online: On AI and Cybersecurity (29 July 2024): https://www.unesco.org/en/articles/safe-offline-safe-online-ai-and-cybersecurity Mainstreaming accessibility and inclusivity in AI and digital technologies (25 July 2024): https://www.unesco.org/en/articles/mainstreaming-accessibility-and-inclusivity-ai-and-digital-technologies A new milestone for artificial intelligence in Africa with the first UNESCO affiliated centre (4 July 2024): https://www.unesco.org/en/articles/new-milestone-artificial-intelligence-africa-first-unesco-affiliated-centre Youth Powering Media and Information Literacy Responses to the use of Generative Artificial Intelligence (27 May 2024): https://www.unesco.org/en/articles/youth-powering-media-and-information-literacy-responses-use-generative-artificial-intelligence Blog post: Lifelong learning in the age of AI (19 March 2024): https://www.uil.unesco.org/en/articles/blog-post-lifelong-learning-age-ai Generative AI: UNESCO study reveals alarming evidence of regressive gender stereotypes (7 March 2024): https://www.unesco.org/en/articles/generative-ai-unesco-study-reveals-alarming-evidence-regressive-gender-stereotypes AI Ethics: 8 global tech companies commit to apply to UNESCO’s Recommendation (5 February 2024): https://www.unesco.org/en/articles/ai-ethics-8-global-tech-companies-commit-apply-unescos-recommendation Examining Media and Information Literacy Responses to Generative AI: A UNESCO Policy Brief (2 February 2024): https://www.unesco.org/en/articles/examining-media-and-information-literacy-responses-generative-ai-unesco-policy-brief The UNESCO Business Council for the Ethics of AI was officially launched (5 December 2023): https://www.unesco.org/en/articles/unesco-business-council-ethics-ai-was-officially-launched UNESCO and Smart Africa: Empowering African Judicial Operators in AI and the Rule of Law (6 November 2023): https://www.unesco.org/en/articles/unesco-and-smart-africa UNESCO: Governments must quickly regulate Generative AI in schools (7 September 2023): https://www.unesco.org/en/articles/unesco-governments-must-quickly-regulate-generative-ai-schools Artificial Intelligence: UNESCO calls on all Governments to implement Global Ethical Framework without delay (30 March 2023): https://www.unesco.org/en/articles/artificial-intelligence-unesco-calls-all-governments-implement-global-ethical-framework-without
Economic Commission for Latin America and the Caribbean (ECLAC) Artificial Intelligence Is Changing the World, and Latin America and the Caribbean Cannot Fall Behind (4 March 2025): https://www.cepal.org/en/pressreleases/artificial-intelligence-changing-world-and-latin-america-and-caribbean-cannot-fall
Food and Agricultural Organization of the United Nations (FAO) AI can be a game-changing solution for farmers: FAO Innovation Chief / Interview with Vincent Martin, Director of the FAO Office of Innovation (2 April 2025): https://www.fao.org/newsroom/detail/ai-can-be-a-game-changing-solution-for-farmers–fao-innovation-chief/en World Food Forum: The pivotal role of Artificial Intelligence (AI) and digital tools in making agrifood systems climate resilient (19 October 2023): https://www.fao.org/newsroom/detail/world-food-forum–the-pivotal-role-of-artificial-intelligence-(ai)-and-digital-tools-in-making-agrifood-systems-climate-resilient/en
International Atomic Energy Agency (IAEA) The IAEA’s platform for partnership on AI: https://nucleus.iaea.org/sites/ai4atoms/SitePages/Home.aspx IAEA to Host International Symposium on AI and Nuclear Energy in December (18 February 2025): https://www.iaea.org/newscenter/news/iaea-to-host-international-symposium-on-ai-and-nuclear-energy-in-december Data centres, artificial intelligence and cryptocurrencies eye advanced nuclear to meet growing power needs (IAEA Bulletin, Vol. 65-3, October 2024): https://www.iaea.org/bulletin/data-centres-artificial-intelligence-and-cryptocurrencies-eye-advanced-nuclear-to-meet-growing-power-needs Enhancing Nuclear Power Production with Artificial Intelligence (23 February 2024): https://www.iaea.org/bulletin/enhancing-nuclear-power-production-with-artificial-intelligence
International Civil Aviation Agency (ICAO)
https://www.icao.int/safety/Pages/Artificial-Intelligence-(AI).aspx Global aviation leaders chart path for artificial intelligence integration at Antalya conference (20 November 2024): https://www.icao.int/Newsroom/Pages/Global-aviation-leaders-chart-path-for-artificial-intelligence-integration-at-Antalya-conference.aspx
https://www.icao.int/safety/Pages/Artificial-Intelligence-(AI).aspx International Fund for Agricultural Development (IFAD) 4 ways IFAD is using AI to transform rural development (18 April 2024): https://www.ifad.org/en/web/latest/-/4-ways-ifad-is-using-ai-to-transform-rural-development Call to innovators to join innovation challenge on AI for climate resilience in rural areas (5 October 2023): https://www.ifad.org/en/web/latest/-/call-to-innovators-to-join-innovation-challenge-on-ai-for-climate-resilience-in-rural-areas
International Labour Organization (ILO) Observatory on AI and Work in the Digital Economy: https://www.ilo.org/artificial-intelligence-and-work-digital-economy How might generative AI impact different occupations? (20 May 2025):
https://www.ilo.org/resource/article/how-might-generative-ai-impact-different-occupations ILO Director-General calls for placing decent work at the heart of automation and AI adoption (18 February 2025): https://www.ilo.org/resource/news/ilo-director-general-calls-placing-decent-work-heart-automation-and-ai AI provides innovative ways to improve compliance with labour laws (3 February 2025): https://www.ilo.org/resource/article/ai-provides-innovative-ways-improve-compliance-labour-laws How reskilling for AI could unlock new and better jobs (28 January 2025): https://www.ilo.org/resource/article/how-reskilling-ai-could-unlock-new-and-better-jobs ILO Director-General emphasizes the positive potential of AI and the importance of proper management for an inclusive digital transition (11 September 2024): https://www.ilo.org/resource/news/ilo-director-general-emphasizes-positive-potential-ai-and-importance-proper AI’s role in evaluating job prestige and value spotlighted by new ILO research (2 February 2024): https://www.ilo.org/global/about-the-ilo/newsroom/news/WCMS_910138/lang–en/index.htm Podcast – Is Generative AI the answer to low productivity? (5 January 2024): https://voices.ilo.org/podcast/is-generative-ai-the-answer-to-low-productivity Podcast – Artificial Intelligence and the future of work: A threat or a promise? (20 November 2023): https://www.ilo.org/resource/other/artificial-intelligence-and-future-work-threat-or-promise Podcast – Job quality or job quantity – which will AI affect most? (4 October 2023): https://voices.ilo.org/podcast/job-quality-or-job-quantity–which-will-ai-affect-most Generative AI likely to augment rather than destroy jobs: ILO report assesses the impact of generative artificial intelligence on job quantity and quality (21 August 2023): https://www.ilo.org/global/about-the-ilo/newsroom/news/WCMS_890740/lang–en/index.htm Podcast – Artificial Intelligence and the world of work – should we be scared? (28 April 2023): https://voices.ilo.org/podcast/artificial-intelligence-and-the-world-of-work–should-we-be-scared
International Monetary Fund (IMF) Artificial Intelligence: https://www.imf.org/en/Topics/Artificial-Intelligence AI Preparedness Index (AIPI): https://www.imf.org/external/datamapper/datasets/AIPI Artificial Intelligence Can Make Markets More Efficient—and More Volatile (IMF Blog, 15 October 2024): https://www.imf.org/en/Blogs/Articles/2024/10/15/artificial-intelligence-can-make-markets-more-efficient-and-more-volatile Mapping the World’s Readiness for Artificial Intelligence Shows Prospects Diverge (IMF Blog, 25 June 2024): https://www.imf.org/en/Blogs/Articles/2024/06/25/mapping-the-worlds-readiness-for-artificial-intelligence-shows-prospects-diverge AI Will Transform the Global Economy. Let’s Make Sure It Benefits Humanity / by Kristalina Georgieva (IMF Blog, 14 January 2024): https://www.imf.org/en/Blogs/Articles/2024/01/14/ai-will-transform-the-global-economy-lets-make-sure-it-benefits-humanity Gen-AI: Artificial Intelligence and the Future of Work (IMF Staff Discussion Note, 14 January 2024): https://www.imf.org/en/Publications/Staff-Discussion-Notes/Issues/2024/01/14/Gen-AI-Artificial-Intelligence-and-the-Future-of-Work-542379 Podcast – AI that Shares the Wealth (4 January 2024): https://www.imf.org/en/News/Podcasts/All-Podcasts/2024/01/04/stephanie-bell IMF Blog – The AI Awakening (30 November 2023): https://www.imf.org/en/Blogs/Articles/2023/11/30/FandD-the-AI-awakening
United Nations Office of the Coordination of Humanitarian Affairs (OCHA) ReliefWeb – Artificial Intelligence in Humanitarian Action: https://reliefweb.int/topic/artificial-intelligence-humanitarian-action Unlocking the Power of AI for Humanitarians (6 August 2024): https://reliefweb.int/blogpost/unlocking-power-ai-humanitarians Briefing Note on Artificial Intelligence and the Humanitarian Sector (17 April 2024)
https://reliefweb.int/report/world/briefing-note-artificial-intelligence-and-humanitarian-sector
United Nations Office of Disarmament Affairs (ODA) Promoting Responsible Innovation in Artificial Intelligence for Peace and Security: https://disarmament.unoda.org/responsible-innovation-ai/
Blog, Resources, Activities & Podcasts ODA and SIPRI launch initiative on responsible innovation in AI for peace and security (4 April 2023): https://disarmament.unoda.org/update/oda-and-sipri-launch-initiative-on-responsible-innovation-in-ai-for-peace-and-security/
Office of the United Nations High Commissioner for Human Rights (OHCHR) OHCHR and privacy in the digital age: https://www.ohchr.org/en/privacy-in-the-digital-age Hub for Human Rights and Digital Technology: https://www.digitalhub.ohchr.org/artificialintelligence Elections at risk in the digital age (4 July 2025): https://www.ohchr.org/en/stories/2025/07/elections-risk-digital-age Türk urges governance to ensure Artificial Intelligence systems are safe and fair (27 May 2025): https://www.ohchr.org/en/statements-and-speeches/2025/05/turk-urges-governance-ensure-artificial-intelligence-systems-are Reparatory justice in the age of Artificial Intelligence (16 May 2025): https://www.ohchr.org/en/stories/2025/05/reparatory-justice-age-artificial-intelligence Call for Code: AI solutions promote human rights (17 December 2024): https://www.ohchr.org/en/stories/2024/12/call-code-ai-solutions-promote-human-rights Artificial intelligence, biodiversity and trade among themes to be discussed at 10th session of the Expert Mechanism on the Right to Development (24 October 2024): https://www.ohchr.org/en/press-releases/2024/10/artificial-intelligence-biodiversity-and-trade-among-themes-be-discussed Racism and AI: “Bias from the past leads to bias in the future” (30 July 2024): https://www.ohchr.org/en/stories/2024/07/racism-and-ai-bias-past-leads-bias-future AI for the 2030 Agenda: Artificial intelligence could be a game-changer for sustainable development (14 June 2024): https://www.ohchr.org/en/stories/2024/06/artificial-intelligence-game-changer-sustainable-development Is AI a force for good? (23 February 2024): https://www.ohchr.org/en/stories/2024/02/ai-force-good Privacy is key in processing personal data by AI: UN expert (16 October 2023): https://www.ohchr.org/en/press-releases/2023/10/privacy-key-processing-personal-data-ai-un-expert
UN Women How AI reinforces gender bias—and what we can do about it: Interview with Zinnya del Villar on AI gender bias and creating inclusive technology (5 February 2025): https://www.unwomen.org/en/news-stories/interview/2025/02/how-ai-reinforces-gender-bias-and-what-we-can-do-about-it Brief: Advancing Gender Equality through Partnerships for Gender-Responsive Artificial Intelligence (UN Women, January 2025): https://www.unwomen.org/en/digital-library/publications/2025/01/advancing-gender-equality-through-partnerships-for-gender-responsive-artificial-intelligence Artificial Intelligence and gender equality (22 May 2024): https://www.unwomen.org/en/news-stories/explainer/2024/05/artificial-intelligence-and-gender-equality HeForShe summit discusses gender bias in AI and how to encourage male feminist allies (29 September 2023): https://www.unwomen.org/en/news-stories/feature-story/2023/09/heforshe-summit-discusses-gender-bias-in-ai-and-how-to-encourage-male-feminist-allies
United Nations Human Settlements Programme (UN-Habitat) AI & Cities: Risks, Applications and Governance: https://unhabitat.org/ai-cities-risks-applications-and-governance
United Nations Conference on Trade and Development (UNCTAD) Making artificial intelligence work better for consumers and societies (15 March 2024): https://unctad.org/news/making-artificial-intelligence-work-better-consumers-and-societies Podcast – The rise of the machines: What does AI mean for our jobs, privacy and humanity? (15 June 2023): https://unctad.org/podcast/rise-machines-what-does-ai-mean-our-jobs-privacy-and-humanity How artificial intelligence chatbots could affect jobs (18 January 2023): https://unctad.org/news/blog-how-artificial-intelligence-chatbots-could-affect-jobs
United Nations Development Programme (UNDP) SDG AI Lab – Harnessing the potential of Artificial Intelligence for Sustainable Development: https://sdgailab.org/ Artificial intelligence/Machine learning: https://www.undp.org/tag/artificial-intelligence/machine-learning Time for Africa to lead the global AI revolution / Statement by Marcos Neto, UN Assistant Secretary-General, and Director of UNDP’s Bureau for Policy and Programme Support, at the launch of the AI Hub for Sustainable Development in Rome, Italy (20 June 2025): https://www.undp.org/speeches/time-africa-lead-global-ai-revolution Hamburg Declaration on Responsible AI: Global leaders commit to responsible AI for sustainable development (2 June 2025): https://www.undp.org/news/hamburg-declaration-responsible-ai-global-leaders-commit-responsible-ai-sustainable-development Digital dividends: When artificial intelligence meets human potential (6 May 2025): https://stories.undp.org/digital-dividends Human Development progress slows to a 35-year low according to UN Development Programme report: Sixty percent of people hopeful Artificial Intelligence will create new job opportunities (6 May 2025): https://www.undp.org/press-releases/human-development-progress-slows-35-year-low-according-un-development-programme-report 4 women who are inspiring the next generation of leaders in AI: Stories from the UNDP SDG Artificial Intelligence Lab (7 March 2025): https://www.undp.org/stories/4-women-who-are-inspiring-next-generation-leaders-ai Bending the AI arc towards equity: Shaping a prosperous and sustainable digital future for all (6 February 2025): https://stories.undp.org/bending-the-ai-arc-towards-equity 5 ways AI can help crisis response around the world (January 2025): https://www.undp.org/5-ways-ai-can-help-crisis-response-around-world Women, money, AI and peace: Four transformational themes for development in 2025 (26 December 2024): https://stories.undp.org/women-money-ai-and-peace Equitable AI for Africa: Unlocking new engines of growth and creativity (14 November 2024): https://www.undp.org/blog/equitable-ai-africa Global collective action platform for Responsible AI for Sustainable Development initiated by UN Development Programme and Germany’s Ministry for Economic Cooperation and Development (8 October 2024): https://www.undp.org/press-releases/global-collective-action-platform-responsible-ai-sustainable-development-initiated-un-development-programme-and-germanys-ministry UNDP – Promise and peril: Reflecting on digitalization and democracy (12 September 2024): https://www.undp.org/blog/promise-and-peril Ensuring positive, people-focused futures through AI: When AI stands for accessible and inclusive (29 May 2024): https://www.undp.org/blog/ensuring-positive-people-focused-futures-through-ai Harnessing artificial intelligence for health: Innovations to improve healthcare access and end tuberculosis (25 March 2024): https://www.undp.org/stories/harnessing-artificial-intelligence-health OSDG Initiative Recognized in Top 100 AI Projects for Advancing Sustainable Development Goals (29 November 2023): https://www.undp.org/news/osdg-initiative-recognized-top-100-ai-projects-advancing-sustainable-development-goals Thinking DEEP to ensure AI delivers the greatest impact (4 October 2023): https://www.undp.org/blog/thinking-deep-ensure-ai-delivers-greatest-impact Making AI work for us: Ethical and responsible artificial intelligence is an accelerator for sustainable development (29 August 2023): https://featured.undp.org/making-ai-work-for-us/
United Nations Economic Commission for Europe (UNECE) UNECE launches declaration on products with embedded AI calling for global cooperation to address regulatory challenges (4 November 2024): https://unece.org/media/news/396328 Generative AI already having significant impact in Statistical Organizations, reveals UNECE survey (9 September 2024): https://unece.org/media/news/394163 UNECE explores how AI can accelerate climate action and infrastructure resilience (10 July 2024): https://unece.org/media/news/392730 Third Forum of UNECE Working Party on Regulatory Cooperation and Standardization Policies to focus on digital, green transformation including AI (15 February 2024): https://unece.org/media/news/388300 UNECE and partners to develop AI-powered platform to help build resilient energy systems (18 September 2023): https://unece.org/media/press/382688
United Nations Environment Programme (UNEP) New Coalition aims to put Artificial Intelligence on a more sustainable path (17 February 2025): https://www.unep.org/news-and-stories/press-release/new-coalition-aims-put-artificial-intelligence-more-sustainable-path Artificial Intelligence (AI) end-to-end: The Environmental Impact of the Full AI Lifecycle Needs to be Comprehensively Assessed – Issue Note, September 2024: https://wedocs.unep.org/20.500.11822/46288 AI has an environmental problem. Here’s what the world can do about that. (21 September 2024): https://www.unep.org/news-and-stories/story/ai-has-environmental-problem-heres-what-world-can-do-about How artificial intelligence is helping tackle environmental challenges (7 November 2022): https://www.unep.org/news-and-stories/story/how-artificial-intelligence-helping-tackle-environmental-challenges
United Nations High Commissioner for Refugees (UNHCR) Data Innovation: https://www.unhcr.org/innovation/data-innovation/
United Nations Children’s Fund (UNICEF) Generation AI: Engaging stakeholders to build AI powered solutions that help realize and uphold child rights: https://www.unicef.org/innovation/GenerationAI
UNICRI Centre for Artificial Intelligence and Robotics (The Hague, The Netherlands)
https://unicri.org/topics/ai_robotics
https://unicri.org/in_focus/on/unicri_centre_artificial_robotics
https://unicri.org/topics/ai_robotics https://unicri.org/in_focus/on/unicri_centre_artificial_robotics United Nations Institute for Disarmament Research (UNIDIR)
https://unidir.org/focus-area/artificial-intelligence/ UNIDIR Artificial Intelligence Policy Portal: https://aipolicyportal.org/
https://unidir.org/focus-area/artificial-intelligence/ United Nations Industrial Development Organization (UNIDO) Global Alliance on AI for Industry & Manufacturing: https://aim.unido.org/
United Nations Office on Drugs and Crime (UNODC) The Ethical Use of Artificial Intelligence: https://www.unodc.org/ji/en/knowledge-products/artificial-intelligence.html
United Nations University (UNU)
https://unu.edu/topics/artificial-intelligence UNU Artificial Intelligence Network: https://aimacau-2024.org/unu-ai-network/ UNU Global AI Network Members: https://unu.edu/macau/announcement/unu-global-ai-network-members UNU Rector AI Lecture Series: AI Insights for a Sustainable Future (8 July 2025): https://unu.edu/macau/news/unu-rector-ai-lecture-series-ai-insights-sustainable-future AI Literacy Highlighted at Global Sustainable Development Congress (24 June 2025):
https://unu.edu/ias/news/ai-literacy-highlighted-global-sustainable-development-congress UNU-CPR: Hamburg Declaration on Responsible AI for the SDGs (14 June 2025): https://unu.edu/cpr/news/hamburg-declaration-responsible-ai-sdgs AI Is Changing The Price You Pay — But Who’s Keeping It Honest, And What’s The Particular Significance For Africa (20 May 2025): https://unu.edu/article/ai-changing-price-you-pay-whos-keeping-it-honest-and-whats-particular-significance-africa “Cautiously Optimistic”: Young people’s thoughts about the impacts and influences of Generative Artificial Intelligence (UNU Macao Research Brief No.1, February 2025): https://unu.edu/macau/brief/cautiously-optimistic-young-peoples-thoughts-about-impacts-and-influences-generative Artificial Intelligence Models for Inclusive Participation in Policy Decision Making (UNU Macau, 6 March 2025): https://unu.edu/macau/blog-post/artificial-intelligence-models-inclusive-participation-policy-decision-making UNU-EGOV Hosts Vitrus Talks on the Impact of AI in Environmental Action (17 February 2025): https://unu.edu/egov/news/unu-egov-hosts-vitrus-talks-impact-ai-environmental-action Who Is Responsible for Workplace Injuries in the New and Dynamic Frontier of AI? (13 February 2025): https://unu.edu/article/who-responsible-workplace-injuries-new-and-dynamic-frontier-ai New Podcast Explores the Impact and Potential of Artificial Intelligence (24 January 2025): https://unu.edu/ias/news/new-podcast-explores-impact-and-potential-artificial-intelligence To serve humankind, AI must be shaped by UN values (7 January 2024): https://unu.edu/article/serve-humankind-ai-must-be-shaped-un-values We need good governance to shape AI for good (29 May 2024): https://unu.edu/article/we-need-good-governance-shape-ai-good The UNU Global AI Network is officially launched (14 May 2024): https://unu.edu/macau/news/unu-global-ai-network-officially-launched One UN on AI – UNU Macau AI Conference 2024 fosters global dialogue under the theme of “AI for All”, promoting a safe, secure, and trustworthy AI system (6 May 2024): https://unu.edu/macau/news/one-un-ai Now Is Our Chance to Govern AI for Women’s Empowerment: The rapid advance of artificial intelligence calls for proactive AI policies and actions that counter threats to gender equality (14 March 2024): https://unu.edu/article/now-our-chance-govern-ai-womens-empowerment Disinformation and Peacebuilding in Sub-Saharan Africa: Security Implications of AI-Altered Information Environments (UNU Report, 13 February 2024): https://unu.edu/publication/disinformation-and-peacebuilding-sub-saharan-africa AI and International Relations — a Whole New Minefield to Navigate (23 November 2023): https://unu.edu/article/ai-and-international-relations-whole-new-minefield-navigate UNU Launches a New Series of Webinar – Conversational Series: An Indepth Exploration into ChatGPT and Generative AI (7 August 2023): https://unu.edu/macau/news/unu-launches-new-series-webinar-conversational-series-indepth-exploration-chatgpt-and
https://unu.edu/topics/artificial-intelligence United Nations Volunteers (UNV) UNV optimizes data for the future (26 June 2024): https://www.unv.org/Success-stories/unv-optimizes-data-future
Universal Postal Union (UPU) Special delivery: how human-centred AI can strengthen postal resilience to natural hazards (25 June 2025): https://www.upu.int/en/blogs/special-delivery-how-humancentred-ai-can-strengthen-postal-resilience-to-natural-hazards UPU launches AI-focused Innovation Challenge amidst postal conference (29 May 2024): https://www.upu.int/en/news/2024/may/upu-launches-aifocused-innovation-challenge-amidst-postal-conference
World Food Programme (WFP) Innovation Accelerator: https://innovation.wfp.org/ WFP Global Artificial Intelligence Strategy 2025 – 2027 (20 March 2025): https://www.wfp.org/publications/wfp-global-artificial-intelligence-strategy-2025-2027 Does artificial intelligence hold the key to ending hunger?: Technology is already making a telling difference to humanitarian efforts (15 May 2025): https://www.wfp.org/stories/does-artificial-intelligence-hold-key-ending-hunger
World Health Organization (WHO) Global Initiative on AI for Health: https://www.who.int/initiatives/global-initiative-on-ai-for-health Big data and artificial intelligence: https://www.who.int/teams/health-ethics-governance/emerging-technologies/big-data-and-artificial-intelligence WHO launches AI-powered all-hazards toolkit to accelerate health emergency response (15 May 2025): https://www.emro.who.int/media/news/who-launches-ai-powered-all-hazards-toolkit-to-accelerate-health-emergency-response.html WHO announces new collaborating centre on AI for health governance (6 March 2025): https://www.who.int/news/item/06-03-2025-who-announces-new-collaborating-centre-on-ai-for-health-governance WHO unveils a digital health promoter harnessing generative AI for public health (2 April 2024): https://www.who.int/news/item/02-04-2024-who-unveils-a-digital-health-promoter-harnessing-generative-ai-for-public-health The role of artificial intelligence in sexual and reproductive health and rights (21 March 2024): https://www.who.int/publications/i/item/9789240090705 WHO releases AI ethics and governance guidance for large multi-modal models (18 January 2024): https://www.who.int/news/item/18-01-2024-who-releases-ai-ethics-and-governance-guidance-for-large-multi-modal-models AI shows ‘great promise for health’ but regulation is key: WHO chief (19 October 2023): https://news.un.org/en/story/2023/10/1142527 WHO calls for safe and ethical AI for health (16 May 2023): https://www.who.int/news/item/16-05-2023-who-calls-for-safe-and-ethical-ai-for-health
World Intellectual Property Organization (WIPO) Artificial Intelligence and Intellectual Property: https://www.wipo.int/about-ip/en/frontier_technologies/ai_and_ip.html
World Meteorological Organization (WMO) WMO faces the future, with action plan on Artificial Intelligence (20 June 2025): https://wmo.int/media/news/wmo-faces-future-action-plan-artificial-intelligence WMO embraces private sector and academia on AI (20 June 2025): https://wmo.int/media/news/wmo-embraces-private-sector-and-academia-ai Big Tech and Artificial Intelligence can support Early Warnings for All (31 May 2023): https://wmo.int/news/media-centre/big-tech-and-artificial-intelligence-can-support-early-warnings-all Exploring the possibilities of Artificial Intelligence in the areas of water, weather and climate (30 May 2023): https://community.wmo.int/en/news/exploring-possibilities-artificial-intelligence-areas-water-weather-and-climate Artificial intelligence can boost disaster management (12 February 2021): https://wmo.int/media/news/artificial-intelligence-can-boost-disaster-management
World Tourism Organization (UN Tourism) UN Tourism launches Global Artificial Intelligence Challenge (28 November 2024): https://www.unwto.org/news/un-tourism-launches-global-artificial-intelligence-challenge Transformational role of artificial intelligence highlighted as UN Tourism brings leaders together (7 November 2024): https://www.unwto.org/news/transformational-role-of-artificial-intelligence-highlighted-as-un-tourism-brings-leaders-together
World Trade Organization (WTO) Digital technologies and trade: https://www.wto.org/english/res_e/reser_e/digitaltech_e.htm Members discuss impact of AI and emerging technologies on e-commerce (16 April 2025): https://www.wto.org/english/news_e/news25_e/ecom_16apr25_e.htm WTO Secretariat hosts first conference on interplay between AI and global trade
(21 November 2024): https://www.wto.org/english/news_e/news24_e/dtech_22nov24_e.htm
UN Events & Conferences
Global Forums on the Ethics of AI: https://www.unesco.org/en/forum-ethics-ai
AI for Good Global Summit 2025 — 8-11 July 2025, Geneva, Switzerland: https://aiforgood.itu.int/summit25/
How AI shapes and is shaped by international trade, WTO Conference, 21 November 2024: https://www.wto.org/english/res_e/reser_e/rese_2111202410_e/rese_2111202410_e.htm
Bonn AI & Climate 2024 (1-2 July 2024)
https://unu.edu/ehs/announcement/bonn-ai-climate-2024
UNU-EHS, in collaboration with UNFCCC Technology Mechanism, is organizing an Expert Meeting on AI & Climate.
https://unu.edu/ehs/announcement/bonn-ai-climate-2024 AI for Good Global Summit 2024 — 30-31 May 2024, Geneva, Switzerland: https://aiforgood.itu.int/summit24/
The UNU Macau AI Conference 2024: the Path towards AI For All, 25 April 2024
https://aimacau-2024.org/
https://aimacau-2024.org/ United Nations Security Council Arria-Formula meeting on Artificial Intelligence, 19 December 2023 – Video: http://webtv.un.org/en/asset/k1g/k1glfm55l2
Security Council, 9381st meeting, 18 July 2023: “Artificial intelligence: opportunities and risks for international peace and security” Webcast: https://media.un.org/avlibrary/en/asset/d307/d3072357 Press Release: https://press.un.org/en/2023/sc15359.doc.htm UN News Centre Story: https://news.un.org/en/story/2023/07/1138827 Concept Note: https://docs.un.org/S/2023/528 Artificial Intelligence and Virtual Reality — Used Responsibly — Can Help Peacebuilding Efforts (Politically Speaking, 17 July 2023): https://bit.ly/43InFca
AI For Good Global Summit 2023 — 6-7 July 2023, Geneva, Switzerland: https://aiforgood.itu.int/summit23/
UNESCO International Forum on Artificial Intelligence (AI) and Education — 5-6 December 2022: https://aiedforum.org
Selected Publications & Documents
Mapping the application of artificial intelligence in traditional medicine: technical brief (WHO / ITU / WIPO, July 2025): https://www.who.int/publications/i/item/9789240107663
Smarter, smaller, stronger: resource-efficient generative Al & the future of digital transformation (UNESCO, July 2025): https://unesdoc.unesco.org/ark:/48223/pf0000394521
Red Teaming artificial intelligence for social good – The PLAYBOOK (UNESCO, 2025): https://unesdoc.unesco.org/ark:/48223/pf0000394338
Artificial Intelligence in the Military Domain and Its Implications for International Peace and Security: An Evidence-Based Road Map for Future Policy Action (UNIDIR, July 2025): https://tinyurl.com/mw8kftdz
Visionary Versus Reactionary. The Future of Space Security in the Age of Artificial Intelligence (UNIDIR, June 2025): https://doi.org/10.37559/WMD/25/Space/03
Devising a Strategic Approach to Artificial Intelligence: A Handbook for Policy Makers
(World Bank, June 2025): https://hdl.handle.net/10986/43347
(World Bank, June 2025): https://hdl.handle.net/10986/43347 AI Revolution in Higher Education: What you need to know (World Bank, June 2025): https://hdl.handle.net/10986/43298
Generative AI and jobs: A 2025 update (ILO Research Brief, May 2025): https://www.ilo.org/publications/generative-ai-and-jobs-2025-update
Freedom of expression, artificial intelligence and elections (UNDP / UNESCO, May 2025): https://unesdoc.unesco.org/ark:/48223/pf0000393473
Human Development Report 2025: A matter of choice: people and possibilities in the age of Artificial Intelligence (AI) (UNDP, May 2025): https://hdr.undp.org/content/human-development-report-2025
Artificial Intelligence Revolution in Higher Education: What You Need to Know (World Bank, May 2025): https://www.worldbank.org/en/region/lac/publication/ia-educacion-superior-inteligencia-artificial
Revolutionizing Health and Safety: The Role of AI and Digitalization at Work (ILO, April 2025): https://www.ilo.org/publications/revolutionizing-health-and-safety-role-ai-and-digitalization-work
Power Hungry: How AI Will Drive Energy Demand (IMF Working Paper No. 2025/081): https://www.imf.org/en/Publications/WP/Issues/2025/04/21/Power-Hungry-How-AI-Will-Drive-Energy-Demand-566304
The Global Impact of AI: Mind the Gap (IMF Working Paper No. 2025/076): https://doi.org/10.5089/9798229008570.001
AI in the Military Domain: A briefing note for States (UNIDIR, March 2025): https://unidir.org/publication/ai-military-domain-briefing-note-states/
AI for Risk-Based Supervision: Another Nice to Have Tool or a Game-Changer (World Bank, February 2025): https://hdl.handle.net/10986/42874
Beyond the AI Divide: A Simple Approach to Identifying Global and Local Overperformers in AI Preparedness (World Bank, February 2025): https://hdl.handle.net/10986/42856
The Impact of Artificial Intelligence on Regional Security, Threat Perceptions and the Middle East WMD-Free Zone (UNIDIR, 7 February 2025): https://unidir.org/publication/the-impact-of-artificial-intelligence-on-regional-security-threat-perceptions-and-the-middle-east-wmd-free-zone/
The Exposure of Workers to Artificial Intelligence in Low- and Middle-Income Countries (World Bank, February 2025): https://hdl.handle.net/10986/42765
Briefer on Human Rights and Artificial Intelligence in the Military Domain (OHCHR, 3 February 2025): https://www.ohchr.org/en/documents/brochures-and-leaflets/briefer-human-rights-and-artificial-intelligence-military-domain
Not Just Another Tool: Public Perceptions of Police Use of Artificial Intelligence (UNICRI, November 2024): https://unicri.it/sites/default/files/2024-11/Public-Perceptions-Police-Use-Artificial-Intelligence.pdf
Trading with intelligence: How AI shapes and is shaped by international trade (WTO, November 2024): https://www.wto.org/english/res_e/publications_e/trading_with_intelligence_e.htm
Understanding Artificial Intelligence in Tax and Customs Administration: Technical Notes and Manuals (IMF, November 2024): https://www.imf.org/en/Publications/TNM/Issues/2024/11/21/Understanding-Artificial-Intelligence-in-Tax-and-Customs-Administration-555097
Compliance of products with embedded artificial intelligence (UNECE, October 2024): https://unece.org/info/publications/pub/396212
Draft Guidelines for the Development of a National Strategy on AI in Security and Defence (UNIDIR, 24 October 2024): https://unidir.org/publication/draft-guidelines-for-the-development-of-a-national-strategy-on-ai-in-security-and-defence/
AI for Good Impact Report (ITU, October 2024): https://tinyurl.com/35u585zc
G7 toolkit for artificial intelligence in the public sector; report prepared for the 2024 Italian G7 presidency and the G7 digital and tech working group (OECD / UNESCO, October 2024): https://unesdoc.unesco.org/ark:/48223/pf0000391566
Generative AI: A New Threat for Online Child Sexual Exploitation and Abuse (UNICRI Centre for AI and Robotics, September 2024): https://unicri.org/generative-ai-new-threat-online-child-sexual-exploitation-and-abuse-september-2024
Global Assessment of Responsible Artificial Intelligence in Cities: Research and recommendations to leverage AI for people-centred smart cities (UNU-EGOV / UN-Habitat / IDRC, September 2024): https://collections.unu.edu/view/UNU:9789
Governance of Artificial Intelligence in the Military Domain: A Multi-stakeholder Perspective on Priority Areas (Policy Brief) (UNIDIR, September 2024): https://unidir.org/publication/governance-of-artificial-intelligence-in-the-military-domain-a-multi-stakeholder-perspective-on-priority-areas/
The Global Kaleidoscope of Military AI Governance (UNIDIR, September 2024): https://unidir.org/publication/the-global-kaleidoscope-of-military-ai-governance/
Gender and Lethal Autonomous Weapons Systems (UNIDIR August 2024): https://unidir.org/publication/gender-and-lethal-autonomous-weapons-systems/
From Al Hol to Hope: Navigating Return and Reintegration Challenges (Findings Report 37, UNIDIR, August 2024): https://doi.org/10.37559/MEAC/24/06
Harnessing the Power of AI for Climate Change Impact Assessment (UNU-INWEH, 2024)
https://collections.unu.edu/eserv/UNU:9738/Harnessing_the_Power_of_AI__Obringer__2024_.pdf
https://collections.unu.edu/eserv/UNU:9738/Harnessing_the_Power_of_AI__Obringer__2024_.pdf The UNU Macau AI Conference 2024: Conference Proceedings Report: https://unu.edu/macau/news/unu-macau-ai-conference-2024-conference-proceedings-report
AI Hub for Sustainable Development: Strengthening Local AI Ecosystems through Collective Action (UNDP, July 2024): https://www.undp.org/publications/ai-hub-sustainable-development-strengthening-local-ai-ecosystems-through-collective-action
UNU Macau Ai Conference AI For All: Bridging Divides, Building a Sustainable Future / Policy Directions distilled by UNU Macau – A Contribution to the Summit of the future (July 2024): https://unu.edu/sites/default/files/2024-07/UNU_AI_ConferencePolicyReport_ADV6.pdf
Patent Landscape Report – Generative Artificial Intelligence (GenAI) (WIPO, July 2024): https://www.wipo.int/web-publications/patent-landscape-report-generative-artificial-intelligence-genai/index.html
Confidence-Building Measures for Artificial Intelligence: A Multilateral Perspective (UNIDIR, July 2024): https://unidir.org/publication/confidence-building-measures-for-artificial-intelligence-a-multilateral-perspective/
Artificial Intelligence in Social Security Organizations (UNU-EGOV / ISSA, June 2024): https://unu.edu/sites/default/files/2024-06/2-AI%20in%20SecSoc%202024.pdf
UNESCO Global Judges’ Initiative: survey on the use of AI systems by judicial operators (June 2024): https://unesdoc.unesco.org/ark:/48223/pf0000389786
AI and the Holocaust: rewriting history? The impact of artificial intelligence on understanding the Holocaust (UNESCO, June 2024): https://unesdoc.unesco.org/ark:/48223/pf0000390211
United Nations Activities on Artificial Intelligence (AI) (ITU, June 2024): https://www.itu.int/hub/publication/s-gen-unact-2023/
Artificial intelligence and democracy (UNESCO, May 2024): https://unesdoc.unesco.org/ark:/48223/pf0000389736
Artificial Intelligence for Health: Supporting countries to deploy responsible AI technologies to accelerate equitable health for all (WHO, May 2024): https://www.who.int/publications/m/item/artificial-intelligence-for-health
Artificial intelligence governance to reinforce the 2030 Agenda and leave no one behind (E/C.16/2024/7, 29 January 2024): https://docs.un.org/E/C.16/2024/7
Artificial Intelligence and Intellectual Property: An Economic Perspective – Economic Research Working Paper No.77 (WIPO, 2024): https://www.wipo.int/publications/en/details.jsp?id=4715&plang=EN
Getting the innovation ecosystem ready for AI: An IP policy toolkit (WIPO, 2024): https://www.wipo.int/publications/en/details.jsp?id=4711&plang=EN
A Guide to Generative AI and Intellectual Property (WIPO, 2024): https://www.wipo.int/publications/en/details.jsp?id=4713&plang=EN
The Economic Impacts and the Regulation of AI: A Review of the Academic Literature and Policy Actions (IMF Working Paper No. 2024/065): https://www.imf.org/en/Publications/WP/Issues/2024/03/22/The-Economic-Impacts-and-the-Regulation-of-AI-A-Review-of-the-Academic-Literature-and-546645
UNESCO Courier, October-December 2023: Education in the age of artificial intelligence: https://courier.unesco.org/en/articles/education-age-artificial-intelligence
Gen-AI: Artificial Intelligence and the Future of Work (ILO, January 2024): https://www.imf.org/en/Publications/Staff-Discussion-Notes/Issues/2024/01/14/Gen-AI-Artificial-Intelligence-and-the-Future-of-Work-542379
AI and International Security: Understanding the Risks and Paving the Path for Confidence-Building Measures (UNIDIR, October 2023): https://unidir.org/publication/ai-and-international-security-understanding-the-risks-and-paving-the-path-for-confidence-building-measures/
Artificial Intelligence Beyond Weapons: Application and Impact of AI in the Military Domain (UNIDIR, October 2023): https://unidir.org/publication/artificial-intelligence-beyond-weapons-application-and-impact-of-ai-in-the-military-domain/
Guidance for generative AI in education and research (UNESCO, September 2023): https://unesdoc.unesco.org/ark:/48223/pf0000386693
The Use of Synthetic Data to Train AI Models: Opportunities and Risks for Sustainable Development (UNU Policy Brief, September 2023): https://unu.edu/publication/use-synthetic-data-train-ai-models-opportunities-and-risks-sustainable-development
Toolkit for Responsible AI Innovation in Law Enforcement (UNICRI and INTERPOL, June 2023): https://unicri.it/Publication/Toolkit-for-Responsible-AI-Innovation-in-Law-Enforcement-UNICRI-INTERPOL
Our Common Agenda – Policy Brief 5: A Global Digital Compact – An Open, Free and Secure Digital Future for All (May 2023): https://www.un.org/sites/un2.un.org/files/our-common-agenda-policy-brief-gobal-digi-compact-en.pdf
Reporting on artificial intelligence: a handbook for journalism educators (UNESCO, 2023): https://unesdoc.unesco.org/ark:/48223/pf0000384551
Open data for AI: what now? (UNESCO, 2023): https://unesdoc.unesco.org/ark:/48223/pf0000385841
Recommendation on the Ethics of Artificial Intelligence (UNESCO, 2022): https://unesdoc.unesco.org/ark:/48223/pf0000381137
2022 United Nations Activities on Artificial Intelligence (AI) Report: https://www.itu.int/dms_pub/itu-s/opb/gen/S-GEN-UNACT-2022-PDF-E.pdf
Inside AI: An Algorithmic Adventure (UNESCO’s first graphic novel on Artificial Intelligence, 2022): https://www.unesco.org/en/articles/inside-ai-algorithmic-adventure
Multistakeholder AI development: 10 building blocks for inclusive policy design (UNESCO, 2022): https://www.unesco.org/en/articles/multistakeholder-ai-development
The Effects of AI on the Working Lives of Women (UNESCO/OECD/IDB, 2022): https://www.unesco.org/en/articles/effects-ai-working-lives-women
Artificial intelligence and digital transformation: competencies for civil servants (UNESCO, 2022): https://www.unesco.org/en/articles/artificial-intelligence-and-digital-transformation
Ageism in artificial intelligence for health (WHO Policy Brief, 9 February 2022): https://www.who.int/publications/i/item/9789240040793
Policy guidance on AI for children (UNICEF, November 2021): https://www.unicef.org/globalinsight/reports/policy-guidance-ai-children
The right to privacy in the digital age: Report of the United Nations High Commissioner for Human Rights (A/HRC/48/31, 13 September 2021): https://docs.un.org/A/HRC/48/31
In this report, mandated by the Human Rights Council in its resolution 42/15, the High Commissioner analyses how the widespread use by States and businesses of artificial intelligence, including profiling, automated decision-making and machine-learning technologies, affects the enjoyment of the right to privacy and associated rights
Ethics and governance of artificial intelligence for health (WHO guidance, 28 June 2021): https://www.who.int/publications/i/item/9789240029200
Resource Guide on Artificial Intelligence Strategies (April 2021): https://www.itu.int/dms_pub/itu-s/opb/gen/S-GEN-UNACT-2022-PDF-E.pdf
From Digital Promise to Frontline Practice: New and Emerging Technologies in Humanitarian Action (OCHA, April 2021): https://www.unocha.org/sites/unocha/files/OCHA%20Technology%20Report.pdf
Artificial intelligence and privacy, and children’s privacy: report of the Special Rapporteur on the Right to Privacy, Joseph A. Cannataci (A/HRC/46/37, 25 January 2021): https://docs.un.org/A/HRC/46/37
Report of the High-level Committee on Programmes on its virtual consultation on the ethics of artificial intelligence (CEB/2020/6/Add.1, 21 August 2020): https://digitallibrary.un.org/record/3895564
The militarization of artificial intelligence (August 2019): https://digitallibrary.un.org/record/3972613
New Technologies: Where To? (UN Chronicle, Nos. 3 & 4, Vol. LV, 2018): https://www.un.org/en/issue/380
Further information
AI’s $4.8 trillion future: UN warns of widening digital divide without urgent action (3 April 2025): https://news.un.org/en/story/2025/04/1161826
‘Life-and-death situations must never be left to chance, code, corporate interest’, Secretary-General tells Conference on Artificial Intelligence (SG/SM/22605, 27 March 2025): https://press.un.org/en/2025/sgsm22605.doc.htm
Safeguarding Human Rights and Information Integrity in the Age of Generative AI
(UN Chronicle, 25 November 2024): https://www.un.org/en/un-chronicle/safeguarding-human-rights-and-information-integrity-age-generative-ai
(UN Chronicle, 25 November 2024): https://www.un.org/en/un-chronicle/safeguarding-human-rights-and-information-integrity-age-generative-ai AI from Google Research and UN boosts humanitarian disaster response: Wider coverage, faster damage assessments (UN Global Pulse, 17 October 2024): https://www.unglobalpulse.org/ai-from-google-research-and-un-boosts-humanitarian-disaster-response-wider-coverage-faster-damage-assessments/
Artificial intelligence can ‘save lives, create jobs, foster progress’, Secretary-General tells Seoul Summit (SG/SM/22236, 21 May 2024): https://press.un.org/en/2024/sgsm22236.doc.htm
Without adequate guardrails, artificial intelligence threatens global security in evolution from algorithms to armaments, speaker tells First Committee: Cyberissues have become foreign policy issues of urgent concern, says another (GA/DIS/3725, 24 October 2023): https://press.un.org/en/2023/gadis3725.doc.htm
10 July 2025
not an official document – for information only
https://unric.org/en/unric-library-backgrounder-artificial-intelligence/
| 2023-07-26T00:00:00 |
2023/07/26
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https://unric.org/en/unric-library-backgrounder-artificial-intelligence/
|
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AI and the Future of Work
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AI and the Future of Work
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https://nativeteams.com
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[] |
Explore how AI is reshaping the future of work, creating new job opportunities while enhancing productivity and collaboration in various industries.
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Every technological advancement has sparked burning questions for the future of work — will it complete problem-solving tasks? Or when will the takeover happen, leaving tons of professionals without jobs?
Let’s leave the guessing game aside and dive into how AI has impacted the workforce so far and contributed to the creation of new jobs. We’ll also cover tips on how you can prepare your business to thrive in the never-ending AI innovation sphere.
Why is AI important for the future of work
The shift towards AI implementation frees up space for higher-value activities that require creativity, emotional intelligence, and strategic thinking. As AI takes over repetitive tasks, the number of errors gets reduced, productivity will spike, and as a result, so will the speed of processes. This acceleration can be seen with the AI-powered chatbots, which significantly reduce the workload of customer support representatives.
For businesses, this change brings more operational efficiency and cost-effectiveness. At the same time, workers will need to develop new skills to work alongside AI systems, which could lead to hybrid roles that combine human judgment with AI-powered tools.
You might be interested in learning about top strategies for improving work productivity .
The impact of AI on the workforce
As businesses rapidly adopt AI technologies, workers must adapt to new realities that bring both challenges and opportunities. Here's how AI is reshaping the workforce.
Job displacement and creation
While it’s no secret that AI could replace many jobs, there’s also a high probability that it’ll create new ones in certain industries. With many companies embracing AI, roles in machine learning and data analysis are expected to be in growing demand. Industries from healthcare to manufacturing are also seeing new roles emerge that combine domain expertise with AI capabilities.
Upskilling and reskilling
Technical literacy, data analysis, and AI system management are becoming essential skillset across industries. Companies are investing in training programs to help employees transition to AI-augmented roles. The focus is shifting from memorising information to developing skills in critical thinking, creativity, and complex problem-solving.
Collaboration between humans and computers
The future workplace isn't about AI replacing humans – it's about effective human-AI collaboration. Workers are learning to use AI as a tool that improves their capabilities rather than threatens their jobs. This means understanding AI's strengths and limitations and developing workflows that optimise the strengths of both humans and machines.
What types of jobs will AI create?
Thanks to AI, workers can easily explore new career paths and opportunities across industries. Let’s take a look at the emerging job positions that have spurred in the AI era.
AI Specialists
AI Specialists are essential to designing, developing, and maintaining AI systems that drive modern businesses forward. Their expertise lies in solving complex issues, such as improving AI model accuracy and reducing computational costs.
Drawing from their technical knowledge of machine learning algorithms and programming languages, AI Specialists are often tasked with developing applications ranging from natural language processing to computer vision.
Data Scientists and Analysts
With AI generating massive amounts of data, these experts turn raw information into actionable insights. They clean and prepare data, build predictive models, and help businesses make data-driven decisions.
Data scientists combine statistical analysis with programming skills to extract patterns from complex datasets. They work closely with business teams to ensure AI solutions address real business needs.
AI Trainers
AI trainers bridge the gap between human behavior and machine learning. They teach AI systems to understand context, improve accuracy, and reduce biases in areas like language processing and image recognition.
This role requires a unique blend of technical understanding and human insight. AI trainers often work on improving chatbots, virtual assistants, and other AI interfaces to make them more natural and effective.
AI Integration Specialists
These professionals specialize in AI Integration Services , helping businesses seamlessly implement AI solutions into their existing workflows. They assess company needs, select the most suitable generative AI tools , and manage the entire integration process. They collaborate with various departments to ensure the smooth adoption of AI technologies and provide staff training on new AI-powered systems to maximize efficiency and effectiveness.
How are businesses preparing for the future with AI?
Companies are rapidly evolving their strategies to capitalise on AI's potential while managing its challenges. The transition requires careful planning, investment, and organisational change to ensure successful AI integration across operations.
Adopting AI technologies
Nowadays, most businesses start implementing AI with focused projects in areas like customer service chatbots, predictive analytics for sales, AI-powered eCommerce catalog management or inventory management. This helps build scalable cloud infrastructure and data pipelines to support decision-making and automate processes.
Investing in training and development
Launching comprehensive training programs is a great way for businesses to prepare their workforce for AI integration. This includes technical training on AI tools and platforms, data literacy courses, and workshops on AI-human collaboration. AI also brings to light certain skill gaps, which businesses can identify and create personalised learning paths for different roles.
Collaborating with AI experts
Staying current with the latest AI trends also requires networking with AI experts. This can be done through strategic partnerships with top artificial intelligence consulting firms, AI vendors, academic institutions, and industry experts. Many businesses even establish AI advisory boards to guide their strategy and implementation instead of outsourcing it or conducting the research themselves.
Changing organisational structures
Embracing AI integration means fundamentally reshaping organisational structures. New positions, such as Chief AI Officer and AI Ethics Officer, should be appointed, cross-functional AI teams created, and a different reporting structure implemented.
Establishing ethical AI policies
AI sets ethical questions about who is responsible for its decisions or how we can be sure they’re morally right. Hence, the need for creating clear guidelines for data handling, algorithmic fairness, and AI transparency is more important than ever. It’s also important to establish regular training so that all employees understand and follow these ethical guidelines.
Learn more about which technology has helped the gig economy grow .
Navigating the future of work with AI
With AI developing faster than the speed of light, success depends on working with these tools, not against them. Here are a few tips that can help you master AI and thrive in the modern workplace.
Embracing AI as a tool
Think of AI as an enhancer of your work rather than a replacement. Once you’ve mastered the prompts, you can use AI to automate repetitive tasks, analyse data, and generate initial drafts. This saves you a lot of time from manual work, which can now be used to polish up and add more creativity to the AI output.
Developing human-centric skills
The rise of AI makes distinctly human capabilities more valuable than ever. These include emotional intelligence, which drives effective leadership and relationship building, alongside the ability to think strategically and solve complex problems. The most successful professionals will be those who excel at these skills, which AI can’t replicate.
Ethical AI development
Success in ethical AI development comes from recognising when to rely on AI and when human judgment is essential while consistently protecting user privacy and maintaining fairness in AI-driven processes. This means establishing clear protocols for data privacy and actively monitoring for potential biases.
Looking for a trusted AI development company? Check out AI Development Companies & AI Developers in the USA
To wrap up
AI isn't just changing how we work — it's revolutionising entire industries and creating new opportunities. While some jobs will transform or disappear, new roles are emerging that combine human expertise with AI capabilities.
Success in this AI-driven future requires a balanced approach: embracing AI as a powerful tool, developing uniquely human skills, and ensuring ethical implementation. The future of work isn't about humans versus AI — it's about humans and AI working together to achieve greater potential.
| 2025-06-24T00:00:00 |
https://nativeteams.com/blog/ai-and-the-future-of-work
|
[
{
"date": "2025/06/24",
"position": 36,
"query": "future of work AI"
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|
50 Industries Most Impacted & Disrupted by AI [2025]
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50 Industries Most Impacted & Disrupted by AI [2025]
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https://digitaldefynd.com
|
[
"Team Digitaldefynd",
"We Help You Find The Best Courses",
"Certifications",
"Tutorials Online. Hundreds Of Experts Come Together To Handpick These Recommendations Based On Decades Of Collective Experience. So Far We Have Served Million",
"Satisfied Learners"
] |
According to global labor estimates, more than 1.7 million manufacturing jobs have been eliminated worldwide over the last decade due to automation. Industrial ...
|
Artificial Intelligence (AI) is no longer a futuristic concept—it’s the operating system of our modern economy. From autonomous vehicles and smart factories to algorithmic trading and generative content creation, AI is transforming industries with breathtaking speed. At DigitalDefynd, we’ve tracked these shifts closely across sectors, and while the promise of AI is vast—unprecedented efficiency, personalization, and scalability—it comes with equally vast disruption. For many professionals, AI represents not just innovation, but interruption.
As AI systems take over more tasks once handled by humans, particularly those that are routine, repetitive, or rules-based, entire job categories are being redefined or rendered obsolete. From warehouse floors to design studios, from tax offices to hospital billing departments, the pace and depth of displacement is accelerating. The shift is especially stark in roles that rely on structured inputs, predefined workflows, and high-volume outputs—all areas where AI now delivers superior speed and cost efficiency. Yet, this transformation is not universally negative. In fact, for those prepared to adapt, it represents one of the greatest career reinvention opportunities in decades.
This report by DigitalDefynd dives deep into the 50 industries most negatively impacted by AI, not as a warning, but as a roadmap. Understanding where and how displacement is occurring is the first step in making strategic, skill-based pivots. We explore not just what’s being lost, but what’s emerging in its place—hybrid roles that require both human nuance and machine fluency. We also highlight the new skill sets, training pathways, and leadership strategies that can turn automation from a threat into an accelerator of human potential.
Whether you’re an individual seeking to future-proof your career, a company looking to responsibly implement AI, or a policymaker aiming to balance progress with protection, this guide is designed to inform, inspire, and empower. At DigitalDefynd, our goal is to help you navigate these transitions with clarity and confidence—because when AI changes the rules, learning becomes the most powerful advantage.
Related: Reasons Humans should fear AI
50 Industries Most Impacted & Disrupted by AI [2025]
1. Manufacturing: Over 1.7 Million Jobs Lost Globally Due to AI-Driven Automation
Industrial robots now account for 44% of repetitive manufacturing tasks worldwide.
The manufacturing industry has been one of the most visibly affected sectors in the wake of AI and robotics adoption. According to global labor estimates, more than 1.7 million manufacturing jobs have been eliminated worldwide over the last decade due to automation. Industrial robots now perform tasks such as welding, painting, and packaging with greater accuracy and fewer errors than human workers, leading to significant cost savings and productivity gains for companies. However, this transformation has resulted in a profound reduction in the need for human labor in repetitive and standardized roles. AI systems now oversee quality assurance through machine vision, detect defects more precisely than the human eye, and even make real-time adjustments on production lines. With AI integrated into supply chain forecasting and predictive maintenance, the demand for human intervention has further declined. On the flip side, the manufacturing workforce must pivot towards high-skill roles in robotic programming, systems analysis, and technical supervision—skills that require specialized training and continuous education. The industry’s future relies on how effectively it can transition blue-collar workers into these new-age technical positions.
2. Retail: 52% of In-Store Tasks Now Automated, Displacing Thousands of Entry-Level Jobs
Self-checkout systems projected to grow at 13.5% CAGR through 2028.
With more than half of in-store retail tasks now automated, the sector is witnessing a sharp decline in traditional entry-level employment. Self-checkout stations, mobile POS systems, and smart inventory platforms are replacing roles once held by cashiers, clerks, and floor supervisors. Retail giants have adopted AI-driven demand forecasting tools that minimize overstocking and understocking, while smart shelves equipped with sensors automatically notify back-end systems when items need replenishment. AI chatbots now handle customer service inquiries, assist with product recommendations, and even process returns without human involvement. These advances translate into higher operational efficiency and better customer satisfaction but drastically reduce the need for human labor on the shop floor. Remaining roles are increasingly digital, requiring skills in data interpretation, omnichannel support, and customer experience optimization. The future retail workforce must blend tech-savviness with human empathy to stay relevant in a fast-automating landscape.
3. Transportation: AI Could Eliminate Up to 94% of Driving Jobs in the Coming Decades
Autonomous vehicle investments to hit $70 billion annually by 2030.
The transportation industry is on the cusp of a technological overhaul, with projections indicating that AI and automation could eliminate as much as 94% of commercial driving jobs over the next 20–30 years. Autonomous trucks, drones, and driverless taxis are already undergoing pilot programs across major economies. Major logistics companies are leveraging AI for route optimization, predictive maintenance, and real-time cargo tracking—all of which reduce the need for human oversight. AI-powered traffic systems adapt to congestion, weather, and road conditions, while predictive models help companies anticipate delivery delays and reduce costs. These innovations offer huge efficiency gains but severely diminish the need for human drivers, warehouse pickers, and even fleet dispatchers. Jobs traditionally available to workers with minimal formal education or training are rapidly vanishing. While new roles will emerge in AI oversight, system diagnostics, and infrastructure integration, these require a high degree of specialization. The challenge for the transportation sector will be to ensure the upskilling of its labor force before disruption becomes displacement.
4. Customer Service: 80% of Routine Inquiries Now Handled by AI Chatbots
Call centers could see 50% workforce reduction by 2035.
The customer service landscape has shifted dramatically, with AI chatbots now managing up to 80% of all routine service interactions. Whether it’s resetting passwords, tracking orders, or handling billing inquiries, AI systems are increasingly the first—and often the only—line of communication between companies and their customers. These bots are trained on vast datasets and natural language processing (NLP) models, enabling them to deliver consistent responses across millions of users simultaneously. Companies benefit from lower costs, 24/7 availability, and shorter resolution times, making AI an irresistible alternative to traditional call centers. This has led to a sharp decline in demand for entry-level customer service representatives, especially in offshore markets that have long depended on outsourcing contracts. However, AI still struggles with complex, emotionally sensitive, or context-dependent queries, leaving space for human intervention. The evolving nature of customer support now favors hybrid roles that require soft skills, emotional intelligence, and an understanding of AI tools. Upskilling initiatives focused on empathy-driven communication and technical proficiency are becoming crucial to remain employable in this transforming sector.
5. Banking & Finance: 1 in 3 Roles in Transaction Processing Replaced by AI
AI expected to manage over $1.2 trillion in banking assets by 2025.
In the highly structured world of banking and finance, AI has made a formidable entrance—particularly in transaction processing, compliance checks, fraud detection, and customer personalization. Studies suggest that approximately one-third of transaction-handling roles in financial institutions have already been automated. AI algorithms now power everything from fraud alerts and credit risk scoring to personalized wealth management recommendations, performing these tasks with faster turnaround times and fewer errors than their human counterparts. Robo-advisors, for instance, automatically adjust investment portfolios based on market conditions and client preferences, often outperforming manual fund managers in retail banking environments. Natural language interfaces are also taking over front-desk roles in digital banking, assisting customers with account queries and product discovery. While these developments increase operational agility and reduce costs, they also lead to a downsizing of middle-office roles, including loan processors, tellers, and customer relationship officers. Future opportunities will lie in AI ethics, algorithm auditing, and hybrid advisory services where humans and machines co-deliver financial value. Professionals must increasingly merge their domain expertise with data science capabilities to remain competitive.
Related: Top AI Scandals
6. Legal Services: 39% of Document Review Tasks Now Performed by AI Tools
AI contract analysis cuts legal research time by up to 60%.
AI is reshaping the legal services industry, particularly in document-intensive areas such as contract analysis, litigation support, and due diligence. A 2024 legal tech report found that approximately 39% of document review processes in large firms are now AI-assisted. These tools can scan and extract relevant clauses, flag anomalies, and identify precedent cases far faster than junior associates or paralegals. AI platforms also reduce the risk of human oversight errors in complex legal documentation. This transformation has led to a decline in demand for legal support staff—especially those involved in manual document processing, data entry, or legal research. While experienced lawyers remain indispensable for courtroom advocacy, strategy, and client negotiation, the traditional path of working one’s way up from paralegal to associate is becoming less viable. Legal professionals are increasingly expected to have competence in legal analytics software, e-discovery tools, and regulatory automation platforms to stay competitive.
7. Journalism: Up to 30% of Financial and Sports News Is Now AI-Generated
News automation projected to save publishers $300M+ annually by 2026.
Journalism has entered a new era with AI-powered content generators producing real-time news on sports events, financial markets, and weather updates. According to media innovation forecasts, nearly 30% of structured news stories in these categories are now created entirely by AI using data feeds and algorithmic summarization. Tools like automated insight engines can generate short news pieces in seconds—dramatically increasing publishing volume while reducing human labor. This efficiency threatens entry-level journalism jobs focused on repetitive reporting and basic editorial work. While seasoned journalists are still needed for investigative reporting, opinion writing, and nuanced storytelling, there’s growing pressure to adapt to digital-first workflows. Reporters must now be skilled not only in narrative structure but also in working alongside AI—curating content, verifying AI outputs, and adding human context where machines fall short. The editorial newsroom is transforming into a hybrid model where creativity and AI orchestration go hand in hand.
8. Telemarketing: AI Systems Now Handle 87% of Outbound Customer Calls
Automated voice tech increases lead processing speed by over 40%.
The telemarketing landscape has been redefined by AI-enabled dialers and voice bots capable of initiating, managing, and even adapting outbound sales conversations. Studies reveal that as of 2025, around 87% of routine outbound calls—such as appointment confirmations, surveys, and sales pitching—are managed by AI systems. These platforms leverage natural language generation and sentiment analysis to adjust scripts dynamically based on customer tone and engagement. As a result, human telemarketers are increasingly sidelined, especially in entry-level roles. While AI-driven campaigns boost efficiency and lower operating costs, they also shift employment opportunities toward managing AI workflows, training conversational models, and overseeing escalation protocols. The remaining human-led interactions are typically reserved for high-touch sales, product demos, or negotiation calls where empathy and improvisation are essential. Success in this field now depends on combining interpersonal skills with fluency in campaign analytics and AI supervision.
9. Travel & Tourism: 72% of Travel Bookings Now Done Without Human Agents
AI trip planners reduce itinerary creation time by 90%.
The travel and tourism sector has seen a digital evolution, with AI-enabled booking platforms and itinerary generators rapidly replacing traditional travel agents. As of 2025, 72% of leisure and business travel bookings are made via AI-enhanced systems that provide personalized recommendations, dynamic pricing alerts, and multi-modal travel integration without human assistance. Virtual travel advisors analyze user behavior, preferences, and past travel data to curate seamless experiences across flights, hotels, and excursions. This self-service model drastically reduces the demand for human booking agents and front-desk support roles in agencies and call centers. However, the sector has not become fully automated—luxury travel, multi-leg international trips, and cultural tourism still benefit from human insight. Future travel professionals will need to specialize in high-end customization, sustainability advising, and crisis planning—areas where technology supports but cannot fully replace human expertise.
10. Human Resources: 43% of Screening Interviews Are Now AI-Driven
Resume parsing software filters 75% of candidates before human review.
AI has become a dominant force in modern HR departments, streamlining processes from resume screening to interview scheduling and performance forecasting. By 2025, about 43% of preliminary candidate interviews in large enterprises are conducted by AI-driven platforms using facial recognition, voice analysis, and NLP-based assessments. Additionally, resume parsing algorithms now eliminate up to 75% of applicants before any human interaction takes place, reducing time-to-hire and recruiter workloads significantly. While these efficiencies enhance objectivity and scale, they also reduce the need for junior HR roles focused on manual vetting and coordination. Human resource teams are evolving to prioritize talent strategy, employer branding, DEI initiatives, and employee well-being—areas where AI offers limited impact. Future HR professionals must blend people analytics with strong interpersonal skills to remain valuable in increasingly tech-forward organizations.
Related: Reasons AI will not destroy the world
11. Security: AI Surveillance Covers Over 68% of Urban Monitoring in Smart Cities
Facial recognition accuracy now exceeds 97% in controlled environments.
The security industry has rapidly adopted AI-powered surveillance systems, particularly in urban centers and high-security zones. AI now handles more than 68% of monitoring functions in smart cities, utilizing facial recognition, license plate readers, and anomaly detection to identify threats in real time. These systems can analyze video feeds 24/7 without fatigue, respond instantly to rule violations, and integrate with law enforcement databases to flag persons of interest. While these capabilities improve public safety and response efficiency, they reduce the need for traditional security guards and patrol officers in monitoring-focused roles. Entry-level security personnel face declining job prospects, particularly in large-scale facilities where surveillance can be automated. However, new demand is emerging for security analysts, AI ethics advisors, and incident response specialists who can interpret system alerts, assess risks, and intervene in critical situations. The emphasis is shifting from presence to precision—requiring human judgment where technology reaches its limits.
12. Real Estate: 61% of Homebuyers Use AI Tools Before Contacting an Agent
AI-driven valuations match or exceed human accuracy in 74% of cases.
The real estate industry is experiencing a digital revolution fueled by AI-powered valuation tools, virtual property tours, and dynamic pricing engines. A recent industry survey shows that 61% of homebuyers now engage with AI-driven platforms—such as Zillow’s Zestimate or Redfin’s Recommendations—before ever contacting a human agent. These systems leverage extensive datasets to suggest optimal listing prices, predict neighborhood appreciation, and rank properties based on personal preferences. This automation reduces the need for agents in early-stage property browsing and appraisal, leading to a decline in commission-based roles and traditional brokerage staffing. However, human agents still play a vital role in closing complex deals, providing negotiation expertise, and offering hyper-local market insight. The profession is evolving toward a hybrid model, where digital fluency and interpersonal strategy are equally essential. Successful agents must now position themselves as advisors who augment what clients already learn from AI—not just facilitators of listings.
13. Education: AI Now Powers 47% of Personalized Learning Systems in K–12 Schools
Automated grading systems reduce teacher administrative time by 35%.
In education, AI technologies are increasingly embedded in both teaching and administrative processes, particularly in K–12 systems. As of 2025, 47% of U.S. public schools use AI-powered personalized learning platforms to adapt content delivery based on each student’s pace, proficiency, and preferences. These systems assess comprehension in real time and modify lesson plans accordingly, making learning more efficient but also less dependent on traditional one-size-fits-all instruction. AI is also used to automate grading, track attendance, and recommend interventions, saving teachers an estimated 35% of their administrative workload. While these tools enhance learning efficiency and allow educators to focus more on emotional and social development, they threaten roles such as teaching assistants, test proctors, and administrative staff. The future of education lies in leveraging AI to support—not supplant—teachers, while ensuring that pedagogical judgment, mentorship, and emotional intelligence remain central to the student experience. Educators are now expected to blend instructional skill with data fluency to guide AI-enhanced classrooms.
14. Publishing: 58% of Digital Publishers Now Use AI for Editing or Content Creation
Proofreading AI reduces editorial turnaround time by 40%.
The publishing world is undergoing seismic shifts as AI tools take on roles traditionally held by editors, designers, and junior content creators. As of 2025, 58% of digital publishers report using AI for tasks such as copy editing, grammar correction, layout optimization, and even full-scale article generation. These tools can identify stylistic inconsistencies, check for plagiarism, and adjust formatting with minimal human oversight, significantly reducing production time and costs. In newsroom settings, AI generates reports from structured data (like earnings calls or sports stats), diminishing the need for entry-level writers. In magazine and marketing content, AI accelerates campaign output through predictive performance analytics and A/B testing. However, creative storytelling, investigative journalism, and literary curation still require human insight and emotional depth. The publishing workforce is increasingly expected to function as editors of AI output—shaping, refining, and enhancing what machines produce. Mastery of generative tools, visual AI, and content optimization platforms is becoming as important as writing skill itself.
15. Agriculture: Precision Farming Tech Now Used by 63% of Large Farms Globally
AI sensors boost crop yield efficiency by up to 25%.
Agriculture is rapidly being transformed by AI-driven precision farming technologies, especially on large-scale industrial farms. Currently, 63% of large farms worldwide use some form of AI—whether through soil sensors, autonomous tractors, or crop health monitoring drones. These systems collect and analyze data on moisture levels, nutrient composition, pest activity, and weather conditions, enabling farmers to make data-informed decisions that improve efficiency and sustainability. AI enables targeted irrigation, fertilization, and pesticide application, increasing crop yields by as much as 25% while reducing waste. However, the rise of automated harvesting machines and intelligent farming robots is reducing the demand for seasonal labor and manual field workers. Jobs in planting, weeding, and crop inspection are increasingly handled by machines. On the flip side, demand is growing for agri-technicians, remote drone operators, and farm data analysts. The future of agriculture hinges on a tech-savvy workforce capable of blending agronomic knowledge with system maintenance and data interpretation.
Related: Technology Leaders’ Biggest Concerns around AI
16. Insurance: 29% Fewer Human Claims Adjusters as AI Takes Over
91% of insurers have already deployed AI-driven claims platforms.
AI now powers large portions of the insurance claims lifecycle—from customer interactions to fraud detection and payout decisions. Chatbots handle over 40% of policyholder queries, and decision engines can automate up to 91% of motor-claim approvals, cutting average processing time by 70%. This efficiency has led to a 29% drop in traditional claims adjuster roles across large insurance firms. The result is billions saved in annual costs and increased customer satisfaction, but also a shrinking field for entry-level analysts and claims handlers. To stay relevant, the workforce must pivot toward roles in AI auditing, model compliance, risk forecasting, and ethical claims architecture—where human judgment complements automation.
17. Healthcare Administration: 28% of Routine Billing & Scheduling Roles Automated
73% of hospitals report measurable cost reductions from AI rollout.
In healthcare operations, AI now assists with billing, claims submissions, appointment scheduling, and insurance authorizations—areas traditionally reliant on administrative staff. Hospitals that adopt AI-powered revenue-cycle tools report productivity gains of 13–21% and cost reductions across billing departments. Nurses have recovered up to 20% of their time previously spent on documentation, now redirected to patient care. However, this streamlining has eliminated thousands of clerical positions, especially in large healthcare systems. Future administrative professionals will need to manage digital workflows, interpret healthcare analytics dashboards, and guide process transformation as AI adoption accelerates across hospitals and clinics.
18. Marketing & Advertising: 31% Drop in Entry-Level Assistant Roles Since 2022
58% of agencies reduced copywriting staff after adopting generative AI tools.
The marketing world has quickly embraced generative AI to automate content creation, campaign optimization, and audience targeting. AI now produces ad copy, headlines, product descriptions, and visual content variants at scale—leading to a 31% decline in junior assistant roles across agencies and in-house teams. Media-buying engines adjust ad bids in real-time, while content tools continuously A/B test to improve conversions without human input. While efficiency has soared, traditional creative career ladders have narrowed. Emerging roles focus on prompt engineering, AI-curated storytelling, and performance data interpretation—requiring a fusion of branding intuition and technical savvy.
19. Media & Content Production: 71% of Social Media Images Now AI-Generated
Freelance writer contracts fell 47% among publishers using generative tools.
AI now dominates fast-paced media production, creating everything from thumbnails to video clips to headline variants. In content studios and digital newsrooms, generative models handle routine production at a fraction of the time and cost, driving a 40% reduction in editorial cycles. However, this also leads to widespread job cuts in freelance writing, photo editing, and junior-level creative roles. Human creators are now expected to supervise AI output—ensuring factual accuracy, emotional resonance, and alignment with brand voice. The industry increasingly values “AI editors” who understand language models, data sourcing, and the ethics of machine-generated storytelling.
20. Construction: 94% of Firms Plan AI & ML Integration, Threatening Manual Site Roles
Each additional AI adoption adds roughly 1 percentage point to profit growth.
Construction firms are integrating AI to improve site management, project planning, and on-site safety. Drones map terrain for project estimation, computer vision identifies unsafe practices in real-time, and robotic systems now handle tasks like bricklaying and steel tying. While these innovations address skilled labor shortages, they also risk displacing manual site roles and routine planning jobs. Prefabrication driven by AI further reduces demand for on-site tasks. Yet firms that adopt these tools report a measurable rise in efficiency and profit margins. The next wave of construction talent will need hybrid skills—understanding both field execution and data-driven project modeling to thrive in an AI-augmented industry.
21. Accounting & Auditing: Robotic Process Automation Displaces 40% of Junior Roles
RPA can cut month-end close time by up to 60%.
Finance departments and public-accounting firms are turning to robotic process automation (RPA) and machine-learning bots to reconcile ledgers, flag anomalies, and prepare financial statements. Once-manual tasks—invoice matching, expense validation, and compliance ticking—are now executed around the clock by software robots that need neither breaks nor overtime. As adoption spreads, nearly two in five junior accountants have seen their roles reduced or re-scoped toward exception handling rather than routine data entry. While efficiency gains free senior auditors to focus on judgment-heavy work such as forensic reviews and advisory services, career paths that traditionally started with clerical bookkeeping are rapidly vanishing. Professionals who master analytics dashboards, ERP bots, and AI-driven risk modelling will have a clear edge over those relying solely on traditional debits-and-credits expertise.
22. Energy & Utilities: AI Grid Management Eliminates 35% of Manual Dispatch Roles
Smart grids will autonomously balance 80% of load fluctuations by 2030.
Electric grids once depended on human dispatchers to adjust generation, route power, and respond to demand spikes. Today, predictive AI engines absorb real-time weather feeds, sensor data, and market prices to orchestrate generation resources with split-second precision—shrinking blackout risk and trimming operational overhead. Automated drones now inspect transmission lines, and computer vision spots corrosion or vegetation encroachment before humans even arrive on site. These advances reduce the need for meter readers, field patrols, and central control-room staff while opening opportunities for data scientists, remote-operations supervisors, and cybersecurity analysts who can safeguard critical infrastructure against digital threats.
23. Warehousing & Fulfillment: Robots Now Handle 70% of Picking Tasks in Mega-Centers
Shuttle systems cut order-cycle time by up to 50%.
E-commerce giants and third-party logistics providers have outfitted vast fulfillment hubs with autonomous mobile robots, shuttle AS/RS systems, and AI path-planning software. These machines whisk totes to human packers—or increasingly to automatic boxing lines—at speeds impossible for manual pickers. The result is a dramatic reduction in floor-level labor: many high-volume facilities now operate with only a fraction of the workforce they employed five years ago. Remaining staff focus on exception management, preventive maintenance, and robotic fleet coordination. Jobs once accessible without advanced training now demand skills in systems diagnostics, warehouse-management software, and human-robot collaboration protocols.
24. Hospitality & Food Service: Self-Service Tech Cuts Counter Staff by 30% at Quick-Service Restaurants
AI kitchen robots boost meal throughput by roughly 20%.
Order kiosks, mobile apps, and computer-vision payment stations have transformed guest interactions in fast-food and casual-dining chains. Customers customize meals, pay, and even pour drinks without cashier assistance, while back-of-house robots fry, flip, and dispense with consistent quality. This integrated automation trims wait times and labor costs but squeezes entry-level roles that once provided a first step into the workforce. Frontline employees who remain are redeployed to guest experience, troubleshooting, or delivery-order orchestration—tasks that still benefit from human judgment and hospitality. Future advancement in the sector hinges on blending service intuition with the ability to monitor IoT kitchen dashboards and maintain smart appliances.
25. Procurement & Supply Chain: AI Purchasing Cuts Buyer Headcount by 25% in Fortune 500 Firms
Predictive demand planning lowers stockouts by 35% and markdowns by 18%.
Enterprise resource-planning suites now embed machine-learning agents that forecast demand, evaluate supplier risk, and issue purchase orders autonomously. Dynamic pricing algorithms negotiate spot buys and track commodities in real time, shrinking the need for large teams of tactical buyers. Strategic sourcing professionals see their roles shift toward managing supplier relationships, ESG compliance, and algorithmic-bias audits rather than daily PO work. Organizations adopting end-to-end supply-chain AI report smoother inventory turns and higher gross-margin retention—but also a thinning pipeline of traditional procurement analysts. The next generation of supply-chain talent must marry negotiation savvy with data-science fluency to thrive in AI-driven value networks.
26. Translation & Localization: Neural MT Handles 56% of Corporate Translation Volume
Freelance translator earnings have fallen by 35% since 2020.
Neural machine-translation (NMT) engines now dominate everyday localization tasks for websites, software strings, and user manuals. Large enterprises feed millions of words into customized models that deliver near-instant drafts in 100+ languages. Post-editing by humans is still needed for nuance, but the volume of raw jobs available to traditional translators has shrunk dramatically—especially in high-volume, low-margin segments like e-commerce product descriptions and support documentation. Agencies increasingly hire linguists as quality-assurance specialists rather than primary translators, rewarding those with skills in terminology management, corpus curation, and model fine-tuning over pure linguistic output.
27. Graphic Design & Illustration: 62% of SMB Logos Now Created with Generative AI
Demand for entry-level layout artists dropped 28% in the last two years.
Generative image models churn out brand assets, marketing banners, and concept art in seconds, allowing small businesses to bypass traditional design studios. Automated style-transfer tools adapt color schemes, typography, and aspect ratios for omnichannel campaigns without human intervention. While senior creatives still lead strategy and brand vision, the production pipeline is increasingly machine-driven. Designers who thrive in this new landscape blend art-direction acumen with prompt engineering, model steering, and post-generation compositing—tasks that emphasize curation and narrative cohesion over pixel-level craftsmanship.
28. Mining & Resource Extraction: Autonomous Haul Trucks Replace 32% of Driver Positions
Mine sites using AI fleets report 15% lower operating costs.
Open-pit mines now deploy driverless haul trucks, drilling rigs, and inspection drones guided by lidar, radar, and real-time terrain mapping. Central control rooms oversee fleets that run 24/7, reducing downtime and safety incidents while trimming a third of human driving roles. The remaining workforce pivots to remote operations, predictive-maintenance planning, and data analytics for ore-grade optimization. Heavy-equipment operators looking to stay relevant must upskill in tele-operation consoles, sensor diagnostics, and AI-assisted dispatch systems rather than manual vehicle control.
29. Financial Trading: Algorithmic Systems Execute 79% of U.S. Equity Volume
Trading-floor headcount at major banks is down 37% since 2015.
High-frequency and quantitative strategies powered by AI analyze market signals, news sentiment, and order-book dynamics in microseconds—far beyond human capability. As a result, traditional floor traders and discretionary desk roles have dwindled. Institutions now compete for quantitative developers, model validators, and risk-control engineers who can ensure fairness, compliance, and resilience of ever-faster trading algorithms. Human expertise still matters in crafting macro strategies and navigating black-swans, but day-to-day execution is overwhelmingly machine-led.
30. Medical Imaging: AI Assists in Reading 48% of Radiology Scans Worldwide
Diagnostic turnaround times have dropped by an average of 26%.
Deep-learning models trained on millions of X-rays, CTs, and MRIs now flag anomalies—nodules, fractures, hemorrhages—before a radiologist opens the file. Hospitals integrating AI triage see faster case prioritization and reduced backlogs, yet also report a 20% reduction in demand for junior radiologists focused on preliminary reads. The profession is evolving toward AI-augmented decision-making, multidisciplinary consultations, and algorithm oversight. Radiologists who master model interpretation, bias detection, and patient-centric communication will remain indispensable as imaging volumes and complexity continue to rise.
31. Data Entry & Document Processing: 52% of Roles Automated by Intelligent Capture Systems
AI optical character recognition now achieves 99% accuracy on structured forms.
Organizations once employed armies of clerks to key in invoices, medical charts, and shipping manifests. Today, AI-powered smart capture platforms ingest scanned documents, classify them, extract key fields, and push validated data straight into ERP systems. This shift has already eliminated more than half of traditional data-entry positions in shared-service centers worldwide. Remaining staff focus on exception handling and workflow governance, while new opportunities arise for solution architects who can train extraction models, set confidence thresholds, and integrate downstream robotic-process-automation bots.
32. Stock Photography & Imaging: 68% of New Commercial Assets Generated by AI
Average royalty income for photographers fell 41% between 2021 and 2024.
Text-to-image diffusion models now create bespoke visuals in seconds, letting marketers bypass stock libraries or costly photo shoots. Platforms license AI-generated images at a fraction of traditional rates, flooding marketplaces with limitless variations. Human photographers still lead high-end conceptual shoots and brand storytelling, but bread-and-butter catalog work—product lay-flats, generic lifestyle scenes—has largely shifted to algorithms. Creatives who adapt learn prompt design, style transfer, and post-processing to curate AI outputs, while pure capture skills alone command shrinking premiums.
33. Telecom Network Operations: Predictive AI Cuts On-Site Maintenance Dispatches by 45%
Self-optimizing networks now resolve 80% of performance issues remotely.
Mobile operators deploy machine-learning models that forecast equipment failures, balance traffic loads, and retune radio parameters in real time. The result is fewer truck rolls, shorter outages, and a sizeable downsizing of field-technician teams that once climbed towers or swapped boards on schedule alone. Job growth pivots to NOC data analysts, 5G orchestration engineers, and cybersecurity specialists who secure AI-controlled infrastructure—roles requiring coding fluency and deep protocol knowledge rather than purely mechanical skills.
34. Personal Tax Preparation: Consumer AI Tools Replace 38% of Seasonal Preparers
Automated filers cut average return completion time to under 15 minutes.
Conversational tax assistants now import bank feeds, scan W-2 images, and surface deduction suggestions with near-CPA accuracy for straightforward returns. Mass-market adoption is eating into the seasonal workforce at strip-mall tax shops and pop-up kiosks, where preparers once processed millions of simple forms each spring. Humans remain essential for complex filings—estate issues, multinational income, intricate business schedules—but entry routes into the profession are narrowing. Future tax professionals must pair advisory insight with proficiency in AI review dashboards and regulation-change monitoring tools.
35. Market Research & Survey Analysis: 57% of Survey Coding and Tabulation Now Done by NLP Models
Automated sentiment engines reduce reporting cycles by 48%.
Natural-language processing systems transcribe focus-group audio, categorize open-ended answers, and flag emerging themes without human coders. Online panel platforms use AI to detect fraudulent respondents and dynamically adjust quotas, reducing the need for large analyst teams. While senior strategists still craft hypotheses and contextualize insights, junior roles in data cleaning, verbatim coding, and cross-tab building are vanishing. The discipline is evolving toward hybrid talent who can design experiments, direct AI analytics pipelines, and translate findings into high-impact business narratives.
36. IT Helpdesk & Technical Support: 60% of Tier-1 Tickets Now Resolved by AI Assistants
74% of large enterprises have deployed AIOps platforms for self-healing infrastructure.
Corporate IT helpdesks once relied on human agents to reset passwords, install software, and troubleshoot connectivity. Today, conversational bots armed with knowledge graphs diagnose issues instantly, while AIOps engines detect anomalies, roll back faulty deployments, and patch servers without human intervention. This automation has trimmed frontline support headcount by more than half at many global firms. Remaining staff focus on complex escalations, security triage, and user-experience analytics. Tech-support careers increasingly demand skills in bot-workflow design, incident-response orchestration, and continuous-integration tooling rather than rote ticket resolution.
37. Credit Underwriting: 72% of Consumer Loans Now Auto-Decisioned by AI Models
Banks report a 30% reduction in traditional underwriting roles since 2019.
Machine-learning scorecards ingest alternative data—utility bills, smartphone usage, social signals—to predict default risk within seconds, slashing approval cycles from days to minutes. Lenders deploying AI enjoy lower loss ratios and higher approval rates for thin-file borrowers, but the efficiency comes at the cost of human underwriters whose judgment once shaped every application. Career paths now veer toward model governance, fairness auditing, and explainability analysis to ensure regulatory compliance and mitigate algorithmic bias.
38. Software Quality Assurance: 65% of Regression Tests Now Executed by AI Bots
Companies using autonomous testing report 50% fewer manual-tester positions.
AI-driven test-generation tools crawl codebases, create test cases, and simulate user flows across browsers and devices without scripting. Visual-comparison engines catch UI regressions, while reinforcement-learning agents explore edge cases that human testers might overlook. These capabilities accelerate release cycles but erode entry-level QA jobs focused on manual click-through testing. The new QA frontier values engineers who can integrate test AI into CI/CD pipelines, interpret anomaly reports, and craft resilient test data models.
39. Legal Transcription: 80% of Courtroom Recordings Now Auto-Transcribed by Speech AI
Court-reporter employment has declined 45% in jurisdictions adopting real-time captioning systems.
Advanced speech-to-text engines with domain-specific vocabularies capture proceedings at 98% accuracy, generating instant transcripts for judges and attorneys. AI also timestamps exhibits, identifies speakers, and flags inaudible passages for review. While certified reporters remain indispensable for high-stakes trials and appeal records, routine hearings increasingly rely on automated capture with minimal human proofreading. Future legal-ops talent must combine steno expertise with audio-correction workflows, metadata tagging, and platform governance to safeguard evidentiary integrity.
40. Technical Writing & Documentation: 48% of Software Docs Auto-Generated by Large Language Models
Average documentation-team size dropped 35% across SaaS firms after 2022.
Developers now embed code comments that compile into user guides, while AI agents transform API schemas into interactive docs and tutorial snippets. Chat-style assistants surface contextual help within apps, reducing reliance on static manuals. Consequently, many companies have downsized traditional tech-writing staffs, reallocating budgets toward user-experience research and community management. Writers who thrive in this landscape pair storytelling skills with prompt engineering, knowledge-base taxonomy design, and continuous-localization pipelines, ensuring machine-generated drafts remain accurate, accessible, and brand-consistent.
41. Public Relations & Communications: AI Drafts 67% of Press Releases for Fortune 1000 Firms
Real-time sentiment engines predict message impact with 82% accuracy.
Generative language models now create the bulk of first-round press releases, email pitches, and crisis statements, allowing PR teams to move from drafting to distribution in hours instead of days. AI systems scan social chatter and news velocity to suggest timing windows, talking-point phrasing, and influencer targeting that minimize backlash. While senior strategists still refine tone and alignment, junior copywriters and media-list researchers are being squeezed out. The new skill stack prizes narrative orchestration, prompt engineering, and cross-channel analytics—melding classic storytelling with machine-led reputation management.
42. Architecture & Engineering Design: Generative Software Replaces 30% of Junior Drafting Roles
Algorithmic layouts cut concept-phase turnaround by 55%.
Parametric-design engines now iterate thousands of floor plans, structural frames, and HVAC routes in minutes, surfacing options optimized for cost, daylight, and energy codes. Once these engines produce viable concepts, BIM tools auto-generate detailed drawings and bill-of-materials lists, reducing the need for entry-level CAD operators. Architects who once spent years on redline revisions must now pivot to supervising AI output, validating regulatory compliance, and injecting aesthetic vision. Competitive firms seek professionals fluent in computational geometry, data-driven sustainability metrics, and human-experience modeling rather than pure drafting speed.
43. Voiceover & Audio Dubbing: Synthetic Speech Replaces 35% of Professional Recording Hours
AI dubbing platforms cover 80+ languages at one-tenth the traditional cost.
Text-to-speech models trained on celebrity-grade voices now localize documentaries, ads, and e-learning modules in near real time. Producers simply upload scripts, select voice profiles, and receive broadcast-ready audio that synchronizes to on-screen lip movement. This convenience has undercut demand for mid-tier voice actors and recording-studio engineers, especially in high-volume corporate training and infotainment segments. Human talent still commands premium rates for emotional storytelling, but sustainable careers increasingly require vocal-coach partnerships, AI-voice licensing expertise, and post-synthesis mastering skills.
44. Fashion & Apparel Design: Generative AI Produces 48% of Fast-Fashion Style Boards
Sample-to-shelf cycles shrink by 30% at leading apparel retailers.
Design teams feed runway snapshots, trend data, and color forecasts into image-generation models that output dozens of coherent collections overnight. AI tools then auto-convert sketches to 3-D patterns, estimate fabric yield, and simulate drape on digital avatars—bypassing multiple prototyping rounds. Consequently, entry-level illustrators and pattern drafters see fewer openings, while merchandisers shift focus to data analytics and micro-drop scheduling. Designers who pair aesthetic intuition with prompt artistry, material-science knowledge, and sustainability scoring wield a distinct competitive edge.
45. Film & Video Editing: AI Auto-Cuts 62% of Social-Media Clips for Major Studios
Auto-editing suites slash turnaround time by 70% on short-form projects.
Machine-learning editors ingest raw footage, detect highlights, match beats to royalty-free tracks, and export multiple aspect ratios in a single pass—tasks that once consumed hours of junior-editor labor. Studios now reserve human editors for narrative pacing, color grading, and artistic effects, while routine promo reels are machine-assembled for TikTok, YouTube Shorts, and Instagram Reels. Aspiring video pros must therefore elevate from clip trimming to creative supervision—mastering AI-shot-selection workflows, motion-graphics templates, and cross-platform optimization to stay indispensable in a content-hungry world.
46. Music Production & Composition: AI Now Generates 32% of New Commercial Tracks
Over 200,000 AI-created songs are uploaded to streaming platforms each day.
Generative audio models trained on vast genre libraries can compose melodies, arrange harmonies, and mix full studio-quality tracks in minutes. Brands and indie creators alike exploit these tools to churn out background scores, ad jingles, and social-media hooks at a fraction of the cost of hiring composers or session musicians. As royalty-free AI music floods catalogs, demand for mid-tier human composers, beat makers, and demo vocalists is shrinking. Survivors in the industry pivot toward prompt-driven sound design, hybrid human-AI mastering, and licensing oversight—ensuring originality, emotion, and rights compliance when machines supply the raw audio.
47. Facilities Cleaning & Janitorial Services: Robots Now Sanitize 45% of Big-Box Retail Floor Space
Autonomous-cleaner adoption is growing at a 34% compound annual rate.
From lidar-guided floor scrubbers in supermarkets to UV-C robots disinfecting hospital corridors, AI-powered cleaning fleets run overnight with minimal supervision, slashing labor hours and chemical usage. Large property managers report cost savings of up to 30% and improved consistency compared with manual crews. Entry-level janitorial positions—once abundant across malls, airports, and warehouses—are steadily disappearing. The roles that remain emphasize fleet scheduling, preventative maintenance, and exception troubleshooting, rewarding workers able to interpret IoT telemetry, adjust machine routes, and meet stringent sanitation protocols alongside robotic teammates.
48. Waste Management & Recycling: AI Sorting Robots Process 28% of Materials in Major Recovery Facilities
Automated lines cut manual sorter headcount by 40% in pilot plants.
Computer-vision systems now identify plastics, metals, and fiber types at belt speeds unreachable by humans, using robotic grippers to pull items with millisecond precision. The result is higher purity rates and lower contamination penalties, but also a decline in repetitive, hazardous sorting jobs. Facilities increasingly hire robotics technicians, data analysts, and process engineers instead of line pickers. Future crews will need skills in sensor calibration, conveyor optimization, and predictive-maintenance analytics to keep high-throughput AI lines running safely and profitably.
49. Parking & Toll Collection: 85% of Highway Booths Replaced by Cashless LPR Gantries
License-plate-recognition accuracy now averages 99.2% in all-weather conditions.
Open-road tolling systems photograph plates at speed, auto-bill drivers, and route violations to digital collections—all without human collectors or traffic queues. City centers mirror the shift, relying on camera networks and mobile apps for curbside parking enforcement. Traditional booth operators, cash handlers, and citation writers are rapidly phased out, while technical roles emerge in system integration, privacy compliance, and data-security auditing. Workers who can manage edge-AI cameras, encryption protocols, and mobility-data analytics will shape the next generation of frictionless transport payments.
50. Debt Collection & Recovery Services: AI Voice Agents Handle 61% of Outbound Collection Calls
Automation cuts average recovery costs by 23% for large agencies.
Conversational AI platforms negotiate payment plans, verify identities, and escalate complex cases, simultaneously contacting thousands of delinquent accounts with compliant scripts tailored to consumer profiles. Human collectors now focus on high-value or highly contentious cases rather than routine follow-ups. While overall headcount in call-center collections has shrunk sharply, new opportunities arise in model supervision, regulatory risk monitoring, and empathy-driven escalation management—functions that blend behavioral economics with AI-dialogue calibration to maintain fairness and maximize recovery rates.
Conclusion: Steering an AI-Powered Future with DigitalDefynd at the Helm
Artificial intelligence has moved well beyond isolated pilots to become a pervasive force reshaping virtually every corner of the global economy. From factory floors where industrial robots now dominate 44 % of repetitive work, to creative studios where generative models craft 62 % of small-business logos, the technology’s reach is unmistakable—and its impact on employment profound. Across the 50 industries we’ve examined, one theme stands out: tasks that are routine, rules-based, and repeatable are being automated at speed, while new demand clusters around insight-driven, ethically governed, and cross-disciplinary roles that blend human judgment with machine precision.
For workers, the message is clear. Reskilling is no longer optional; it is urgent. Whether you began your career as a claims adjuster, a customer-service agent, or a junior CAD drafter, staying relevant now means mastering data fluency, AI oversight, and domain-specific storytelling that machines cannot replicate. For businesses, the imperative is twofold: capturing efficiency gains without eroding trust, and building a talent pipeline equipped to audit, tune, and humanize AI systems. Failure on either front risks reputational, regulatory, and cultural backlash that can outweigh the savings automation promises.
Policymakers, educators, and industry leaders must therefore collaborate on scalable upskilling programs, portable credentialing, and robust safety nets that smooth workforce transitions. Standards for algorithmic transparency, fairness, and environmental impact need to be codified and enforced, ensuring that AI’s productivity dividends are broadly shared rather than narrowly concentrated.
At DigitalDefynd, our mission is to guide professionals and organizations through this inflection point with actionable insights, curated learning paths, and real-time market intelligence. We believe that when stakeholders confront automation head-on—armed with data, empathy, and a growth mindset—AI becomes less a job killer and more a catalyst for higher-value human contribution.
As you digest the industry-specific changes outlined in this report, ask yourself:
Which of my current tasks are ripe for automation, and which require uniquely human strengths?
What new competencies—technical, analytical, or interpersonal—will position me on the opportunity side of AI?
How can my organization embed ethical guardrails and continuous learning into its automation roadmap?
DigitalDefynd invites you to explore our extensive resource library, enroll in expert-led courses, and join a global community committed to harnessing AI responsibly, inclusively, and creatively. Together, we can steer this technological transformation toward a future where efficiency and equity coexist—ensuring that the gains from AI empower people, enrich industries, and elevate society as a whole.
| 2025-06-16T00:00:00 |
2025/06/16
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https://digitaldefynd.com/IQ/industries-negatively-impacted-by-ai/
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[
{
"date": "2025/06/24",
"position": 98,
"query": "job automation statistics"
}
] |
KnowBe4 Research Uncovers Disconnect Between AI ...
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KnowBe4 Research Uncovers Disconnect Between AI Adoption and Policy Awareness in the Workplace
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https://www.prnewswire.com
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[] |
Varying AI Adoption Rates: While the average percentage of employees using AI in the workplace is 60.2% globally, adoption rates varied by region. · Persistent ...
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A new KnowBe4 survey reveals that while employee adoption of AI is rising, understanding of AI-related policies remains low—leaving organizations vulnerable
TAMPA, Fla., June 24, 2025 /PRNewswire/ -- KnowBe4, the world-renowned cybersecurity platform that comprehensively addresses human risk management, shares 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. shows the lowest adoption rate, with only 54.2% of employees saying they use AI tools at work, indicating a slower adoption rate. Conversely, 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 (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.
For more insights and best security practices, visit https://www.knowbe4.com/.
About KnowBe4
KnowBe4 empowers workforces to make smarter security decisions every day. Trusted by over 70,000 organizations worldwide, KnowBe4 helps to strengthen security culture and manage human risk. KnowBe4 offers a comprehensive AI-driven 'best-of-suite' platform for Human Risk Management, creating an adaptive defense layer that fortifies user behavior against the latest cybersecurity threats. The HRM+ platform includes modules for awareness & compliance training, cloud email security, real-time coaching, crowdsourced anti-phishing, AI Defense Agents, and more. As the only global security platform of its kind, KnowBe4 utilizes personalized and relevant cybersecurity protection content, tools and techniques to mobilize workforces to transform from the largest attack surface to an organization's biggest asset.
The research was conducted by Censuswide, among a sample of 12,037 people across Germany, South Africa, the Netherlands, France, the UK, and the USA who are employed (and use a computer for any part of their work). The data was collected between 17.07.24 - 25.07.24. Censuswide abides by and employs members of the Market Research Society and follows the MRS code of conduct and ESOMAR principles. Censuswide is also a member of the British Polling Council.
Media Contact:
Kathy Wattman
SVP of Public Relations
[email protected]
727-474-9950
SOURCE KnowBe4 Inc.
| 2025-06-24T00:00:00 |
https://www.prnewswire.com/news-releases/knowbe4-research-uncovers-disconnect-between-ai-adoption-and-policy-awareness-in-the-workplace-302487586.html
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[
{
"date": "2025/06/24",
"position": 19,
"query": "workplace AI adoption"
}
] |
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Employees are using AI in secret at work - WorkLife.news
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Why employees are so secretive about using AI at work — and why they shouldn’t be
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https://www.worklife.news
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[
"Tony Case"
] |
Workplace experts say it's on leadership to create a culture of trust around AI at work to boost innovation and collaboration.
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The AI revolution is happening at work whether people admit it or not. While leadership teams debate AI policies, employees are already using these tools, often in secret — and that can create an organizational blind spot that undermines innovation and oversight.
That’s the word from Justin Hale, master trainer at the professional training and consulting company Crucial Learning, who maintains that the problem isn’t that employees are using AI — it’s that they are afraid to talk about it. Leaders “need to go in thinking, I’m just going into the conversation expecting there’s going to be people that are fearful or unsure or uneasy, and so I need to double down on my invitation, my curiosity, my openness,” he said.
When employees use AI in stealth mode, they miss an important opportunity for professional development, he argues. “There is a risk that if people overuse AI for too many of their tasks, they outsource things that actually are muscles they should be working out themselves,” he said.
Furthermore, covert AI usage can erode team collaboration. “People start saying, well, rather than me asking people’s opinion on my team, I’m just going to ask AI,” he said. “And so now what happens is, we don’t have a collaborative team — we have a team of individuals all working collaboratively with AI.”
“When I asked you to write up a thought piece around this topic, I actually want you to come up with your ideas … I don’t want you to outsource it to AI.” Justin Hale, master trainer, Crucial Learning
Other workplace experts point to the benefits. “Let’s be honest: employees aren’t hiding their AI use because they’re trying to get away with something — they’re hiding it because they’re trying to get ahead without getting in trouble,” said David Torosyan, who heads HR and payroll for J&Y Law Firm in Los Angeles.
Torosyan has seen firsthand how AI has become more woven into the modern workplace — and how it has become a key tool in employee productivity. “People are using it to write faster, organize smarter and communicate clearer,” he said. “They’re solving problems in real time with tools that didn’t exist a few years ago. But they’re doing it quietly, often in the shadows — not because they lack ethics, but because they lack clarity and psychological safety.”
That’s on leadership, he maintains. “If we don’t create a culture where innovation is welcomed, employees will innovate anyway — just without us,” he said. “That’s how we lose visibility, oversight and trust.”
ZipRecruiter career expert Sam DeMase likewise puts the onus on management.
“Leadership has a responsibility to craft policies around practical and ethical AI usage on the job and communicate those policies with their team,” she said. “Leadership should share examples of practical ways to use AI and shine a light on areas where AI should not be used. This transparency takes away the fear and shame that some employees associate with using AI on the job. The reality is, AI is becoming increasingly prevalent and, when used effectively, can boost productivity and free up employees’ time for innovative thinking.”
For his part, Hale suggests a “facts-story-ask” framework: Start with objective observations about industry AI trends, then share your perspective and intentions and, finally, ask genuinely open questions.
The approach requires striking a delicate balance between oversight and innovation. Seeing that, he recommends using contrasting statements to clarify your intentions. “What I’m not saying is I want you guys to hold back because you’re afraid you’re going to get in trouble,” he said. “What I am saying is, let’s be honest so we can both see the opportunities and see the risks.”
"Let’s be honest: employees aren’t hiding their AI use because they’re trying to get away with something — they’re hiding it because they’re trying to get ahead without getting in trouble." David Torosyan, HR and payroll manager, J&Y Law Firm
The challenge for HR leaders is helping employees understand which tasks are appropriate for AI assistance and which require human judgment.
Administrative work might be perfect for AI support, but strategic thinking and creative problem-solving remain the domain of humans, Hale stresses. “When I asked you to write up a thought piece around this topic, I actually want you to come up with your ideas because you have experience, you have stories, you have examples that are unique to you — I don’t want you to outsource it to AI,” he said.
For organizations ready to make such a cultural shift, Hale emphasizes setting measurable outcomes rather than vague aspirations. Instead of saying merely you want to adopt AI in workflows, define specific goals with clear timelines and success metrics.
Perhaps most importantly, leaders themselves need education. “Outside of organizations where AI is part of their business, I would say [leadership AI knowledge] is still very rudimentary,” he said. His recommendation: executives should be reading one article daily about AI in the workplace.
The most effective approach frames AI adoption as a collaborative project rather than a top-down mandate. “Framing it as a ‘we’ problem and making it a project together … shows a lot more loyalty, a lot more connection, a lot more collaboration on the leader’s part,” he said.
When leaders position AI discussions as partnership rather than scrutiny, they create psychological safety. As Hale puts it, “Your job is to suck fear out of the air so that people feel like they could bring up any question, any concern.”
| 2025-06-24T00:00:00 |
2025/06/24
|
https://www.worklife.news/technology/why-employees-are-so-secretive-about-using-ai-at-work-and-why-they-shouldnt-be/
|
[
{
"date": "2025/06/24",
"position": 40,
"query": "workplace AI adoption"
}
] |
AI begins to reshape the IT job landscape as layoffs rise - CIO
|
AI begins to reshape the IT job landscape as layoffs rise
|
https://www.cio.com
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Other notable layoffs include Salesforce cutting 1,000 jobs to make room for AI roles, Dell cutting 2,500 jobs to shift to AI-powered ...
|
During the COVID-19 pandemic, Amazon was one of many tech companies that rapidly ramped up hiring to meet demand in a new, locked-down business paradigm. Other organizations, seeking to support all-remote workforces, followed suit, as tech hiring — and salaries — reached unprecedented heights.
But the boom didn’t last long, as Amazon along with Google, Meta, Microsoft, and other prominent enterprises collectively laid off more than 100,000 employees in 2022 to re-adjust to a world emerging from the pandemic. Now, just three years later, AI has risen to become another massive disruptor for tech employment, with organizations increasingly announcing workforce cuts to make room for AI talent and investments.
According to PwC’s 2025 Global AI Jobs Barometer, 100% of industries are increasing AI usage, and wages in the most AI-exposed industries are rising twice as fast as the least exposed. As a result, demand is spiking for AI skills — skills that are evolving 66% faster than non-AI skills, which is 2.5 times faster than just last year.
| 2025-06-25T00:00:00 |
https://www.cio.com/article/4012162/ai-begins-to-reshape-the-it-job-landscape-as-layoffs-rise.html
|
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|
AI Isn't To Blame for the Rise in Layoffs — Your Systems Are | Built In
|
AI Isn’t to Blame for the Rise in Layoffs — Your Systems Are
|
https://builtin.com
|
[] |
AI may take the blame for the layoff anxiety infiltrating companies, but the real culprit is ineffective operations.
|
AI is being blamed for layoffs, but the real issue is systemic incompetence in company operations. Poor role clarity and talent management are driving dysfunction. Without addressing these, AI will only automate existing problems — not solve them.
AI is being blamed for layoffs, but the real issue is systemic incompetence in company operations. Poor role clarity and talent management are driving dysfunction. Without addressing these, AI will only automate existing problems — not solve them. more
AI has taken the blame for the business world’s fear and frustration, bearing responsibility for the layoff anxiety flooding the business world and enduring the bitter berating thrown at it in virtually every industry. But let’s be clear: AI didn’t break your organization chart. It didn’t confuse your workflows. It didn’t erode your culture.
Yet, AI has taken the role as the villain, while leaders step back and wash their hands clean. The truth? It’s just the most convenient scapegoat in the room.
The problem, however, is that artificial intelligence isn’t wholly to blame for the conditions that have caused employee confidence to drop to record lows in recent days. While AI may contribute to the layoffs, it is not causing them. Yet, AI’s appearance has opened a beautifully convenient window for leaders, allowing them to let AI fall on the sword and take the blame for layoffs.
A deeper look at today’s business landscape reveals systemic incompetence as the core issue driving layoffs. Systemic incompetence is rampant today, almost becoming a normalized fabric of company culture that employees have just been battered into dealing with
2 Tips to Effectively Integrate AI and Address Systemic Incompetence Clarify accountability and role structure. Prioritize talent management.
To be fair to leaders, some degree of systemic incompetence is to be expected as companies move forward. Evolution, innovation and growth actually require a level of imperfection that translates into operational inefficiencies.
However, many leaders have embraced growth-related inefficiencies as a part of the deal rather than a problem they need to address. And as their lack of action has led to frustration in the workforce, they’ve welcomed AI as the savior that can fix inefficiency while doing away with complainers.
Today’s leaders fail to see that AI is an employee just like the employees it is replacing, only more efficient and less likely to complain. Replacing humans with AI won’t fix dysfunction. It will just automate it, then amplify it. In fact, it might just propel companies more quickly along the tragic trajectory set by their incompetence.
The following are some steps companies should take to address systemic incompetence before integrating AI.
More on AI8 Rules for Effective Software Development in the Age of Agile and AI
Clarify Accountability and Role Structure to Maximize the Impact of AI
Sound business systems are built upon accountability. Every member of the team needs to know what is expected of them. Lack of clarity leads to confusion, leading to wasted time and lost profits.
Accountability is also key to motivation. When employees know what is expected of them and what is not expected of them, they can take ownership, focus, and deliver. When they are left guessing, they ultimately feel abused, which circles back to them feeling battered.
When accountability isn’t a priority, productivity and profitability are impacted. Layoffs are one fix that companies turn to when those symptoms crop up.
One big question for companies integrating AI is, “If you’re already doing a poor job at clarifying accountability and role structures for the humans in your company, how good will you be at doing the same for AI?” The likely answer is, “Not good at all.”
Companies must define who is accountable for ensuring AI has the resources it needs to deliver and for ensuring AI outputs are accurate, reliable and effectively incorporated into the system. If AI is your new top employee, who’s its manager? Who’s making sure it has clear instructions, measurable outputs and doesn’t quietly spiral into chaos like every other under-supported hire? AI can be a high-producing employee, but it still needs a support team and a manager.
The relationship between HR and IT is out of alignment in many companies and can suffer significantly if accountability is not addressed before AI is dropped into the equation. Without clearly defining each team's role in evaluating and supporting AI tools, companies risk creating destructive fractures that can destroy the entire organization.
AI is not only being villainized as the root of layoffs but also romanticized as a problem solver. Companies see it as the “easy button,” so they drop it into operations without clarifying accountability and role structure. Consequently, they get a tool that supercharges their issues along with their output.
More on AIHow AI Has Transformed the Role of Software Developers
Prioritize Talent Management to Maximize the Impact of AI
Ineffective talent management is another systemic incompetence that contributes to layoffs. When companies fail to put in place a solid hiring system, they end up with employees who are unqualified, a poor fit for the culture, or simply superfluous in terms of the company’s operational needs. Layoffs occur in those companies as a snapback reaction to poor hires.
Companies that leverage AI to replace employees don’t do away with the need for talent management. All the steps involved in human talent management, from vetting to training to integration to oversight to promotion, also must be addressed when integrating AI. If those steps aren’t followed, companies can end up with AI systems that don’t integrate well, scale well, or provide long-term usability.
In addition, companies integrating AI must carefully consider its impact on the employees who remain. The practical implications of introducing a new tool must be addressed with ongoing training and evaluation. AI is a tool and a team member, which means its success ultimately depends on employees knowing how to wield it.
Companies integrating AI must also consider the emotional impact it can have on the workforce. A recent Pew study found that more than half of workers fear AI is going to have a negative impact on their careers. Bringing AI into the workplace is like forcing the workers who remain to sit next to their nightmare for eight hours a day. If companies don’t take steps to address those fears, employee engagement is guaranteed to suffer.
In the early days of the AI era, tech prophets proclaimed that layoffs were inevitable for companies that wanted to take advantage of the efficiency artificial intelligence could provide. As AI has matured, however, human-machine collaboration is emerging as the ideal path for maximizing AI ROI. To get in on those returns, companies need to stop making AI the scapegoat and address the systemic incompetencies that are truly leading to layoffs.
AI won’t challenge your bad ideas. It doesn’t have the guts to do so or the soul to care. But perhaps worst of all, it doesn’t have the filter to stop your worst ideas: It will just scale them.
| 2025-06-25T00:00:00 |
https://builtin.com/articles/ai-not-to-blame-for-layoffs
|
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|
AI Killed My Job: Tech workers - Blood in the Machine
|
AI Killed My Job: Tech workers
|
https://www.bloodinthemachine.com
|
[
"Brian Merchant"
] |
Tech workers at TikTok, Google, and across the industry share stories about how AI is changing, ruining, or replacing their jobs.
|
“What will AI mean for jobs?” may be the single most-asked question about the technology category that dominates Silicon Valley, pop culture, and our politics. Fears that AI will put us out of work routinely top opinion polls. Bosses are citing AI as the reason they’re slashing human staff. Firms like Duolingo and Klarna have laid off workers in loudly touted shifts to AI, and DOGE used its “AI-first” strategy to justify firing federal workers.
Meanwhile, tech executives are pouring fuel on the flames. Dario Amodei, the CEO of Anthropic, claims that AI products like his will soon eliminate half of entry level white collar jobs, and replace up to 20% of all jobs, period. OpenAI’s Sam Altman says that AI systems can replace entry level workers, and will soon be able to code “like an experienced software engineer.” Elsewhere, he’s been blunter, claiming "Jobs are definitely going to go away, full stop."
But the question remains: What’s actually happening on the ground, right now? There’s no doubt that lots of firms are investing heavily in AI and trying to use it to improve productivity and cut labor costs. And it’s clear that in certain industries, especially creative ones, the rise of cheap AI-generated content is hitting workers hard. Yet broader economic data on AI impacts suggests a more limited disruption. Two and a half years after the rise of ChatGPT, after a torrent of promises, CEO talk, and think pieces, how is—or isn’t—AI really reshaping work?
About a month ago, I put out a call in hopes of finding some answers. I had a vague idea for a project I’d call AI Killed My Job, that would seek to examine the many ways that management has used AI to impact, transform, degrade, or, yes, try to replace workers outright. It’s premised on the notion that we’ve heard lots of speculation and plenty of sales pitches for AI automation—but we have not heard nearly enough from the workers experiencing the phenomenon themselves.
The title is somewhat tongue-in-cheek; we recognize that AI is not sentient, that it’s management, not AI, that fires people, but also that there are many ways that AI can “kill” a job, by sapping the pleasure one derives from work, draining it of skill and expertise, or otherwise subjecting it to degradation.
So, I wrote a post here on the newsletter explaining the idea, posted a call to social media, and asked for testimonials on various news shows and podcasts. I was floored by the response. The stories came rolling in. I heard from lots of folks I expected to—artists, illustrators, copywriters, translators—and many I didn’t—senior engineers, managers of marketing departments, construction industry consultants. And just about everyone in between. I got so many responses, and so many good ones, that I resolved to structure the project as a series of pieces that center the workers’ voices and testimonies themselves, and share their experiences in their own words.
Because I got so many accounts, I decided to break down the articles by field and background. Starting, today, with an industry that’s at once the source of the automating technology and feeling some of its most immediate impacts. Today, we’ll begin by looking at how AI is killing jobs in the tech industry.
I heard from workers who recounted how managers used AI to justify laying them off, to speed up their work, and to make them take over the workload of recently terminated peers. I heard from workers at the biggest tech giants and the smallest startups—from workers at Google, TikTok, Adobe, Dropbox, and CrowdStrike, to those at startups with just a handful of employees. I heard stories of scheming corporate climbers using AI to consolidate power inside the organization. I heard tales of AI being openly scorned in company forums by revolting workers. And yes, I heard lots of sad stories of workers getting let go so management could make room for AI. I received a message from one worker who wrote to say they were concerned for their job—and a follow-up note just weeks later to say that they’d lost it.
Of the scores of responses I received, I’ve selected 15 that represent these trends; some are short and offer a snapshot of various AI impacts or a quick look at the future of employment. Others are longer accounts with many insights into what it means to work in tech in the time of AI—and what it might mean to work, period. The humor, grace, and candor in many of these testimonials often amazed me. I cannot thank those who wrote them enough. Some of these workers took great risks to share their stories at a time when it is, in tech, a legitimate a threat to one’s job to speak up about AI. For this reason, I’ve agreed to keep these testimonies anonymous, to protect the identities of the workers who shared them.
Generative AI is the most hyped, most well-capitalized technology of our generation, and its key promise, that it will automate jobs, desperately needs to be examined. This is the start of that examination.
Three very quick notes before we move on. First, this newsletter, and projects like AI Killed My Job, require a lot of work to produce. If you find this valuable, please consider becoming a paid subscriber. With enough support, I can expand such projects with human editors, researchers, and even artists—like Koren Shadmi, who I was able to pay a small fee for the 100% human-generated art above, thanks to subscribers like you. Second, if your job has been impacted by AI, and you would like to share your story as part of this project, please do so at [email protected]. I would love to hear your account and will keep your account confidential as I would any source. Third, some news: I'm partnering with the good folks at More Perfect Union to produce a video edition of AI Killed My Job. If you're interested in participating, or are willing to sit for an on camera interview to discuss how AI has impacted your livelihood, please reach out. Thanks for reading, human, and an extra thanks to all those whose support makes this work possible. Tech is just the first industry I plan on covering; I have countless more stories in fields from law to media to customer service to art to share. Stay tuned, and onwards.
This post was edited by Mike Pearl.
“AI Generated Trainers”
Content moderator at TikTok.
I have a story. I worked for TikTok as a content moderator from August 2022 to April 2024, and though I was not replaced by AI, I couldn't help noticing that some of the trainers were.
In my first year, I would be assigned training videos that featured real people either reading or acting. These trainings would be viewed internally only, not available to the public. Topics could be things like learning about biases, avoiding workplace harassment, policy refreshers, and so on. In the early months of my time there, the trainings were usually recorded slideshows with humans reading and elaborating on the topics. Sometimes they were videos that included people acting out scenarios. Over time, the human trainers were replaced with AI by way of generated voices or even people going over the materials in the videos.
It was honestly scary to me. I don't know how to explain it. I remember that they had added embellishments to make them seem more human. I distinctly remember a woman with an obscure black tattoo on her bicep. The speech and movement wasn't as clean as what I see in videos now, but it was close enough to leave me with an eerie sensation.
As far as content moderation goes, much of that is already done by AI across all major social media platforms. There has historically been a need for human moderators to differentiate grey areas that technology doesn't understand. (Example: someone being very aggressive in a video and using profanity, but it not being directed at an individual. AI might think the video involves bullying another user and ban the video, but a moderator can review it and see that there's no problem/no targeted individual.)
It was honestly scary to me. I don't know how to explain it. I remember that they had added embellishments to make them seem more human.
I think as AI models continue to learn, however, moderators will be replaced completely. That's just a theory, but I'm already seeing the number of these job postings dwindling and hearing murmurs from former coworkers on LinkedIn about widespread layoffs.
“AI is killing the software engineer discipline”
Software engineer at Google.
I have been a software engineer at Google for several years. With the recent introduction of generative AI-based coding assistance tools, we are already seeing a decline in open source code quality (defined as "code churn" - how often a piece of code is written only to be deleted or fixed within a short time). I am also starting to see a downward trend of (a) new engineers' readiness in doing the work, (b) engineers' willingness to learn new things, and (c) engineers' effort to put in serious thoughts in their work.
Specifically, I have recently observed first hand some of my colleagues at the start of their career heavily relying on AI-based coding assistance tools. Their "code writing" consists of iteratively and alternatingly hitting the Tab key (to accept AI-generated code) and watching for warning underlines indicating there could be an error (which have been typically based on static analysis, but recently increasingly including AI-generated warnings). These young engineers - squandering their opportunities to learn how things actually work - would briefly glance at the AI-generated code and/or explanation messages and continue producing more code when "it looks okay."
I also saw experienced engineers in senior positions when faced with an important data modeling task decided to generate the database schema with generative AI. I originally thought it was merely a joke but recently found out that they basically just used the generated schema in actual (internal) services essentially without modification, even if there are some obvious glaring issues. Now those issues have propagated to other code that needs to interact with that database and it will be more costly to fix, so chances are people will just carry on, pretending everything is working as intended.
All of these will result in poorer software quality. "Anyone can write code" sounds good on paper, but when bad code is massively produced, it hurts everyone including those who did not ask for it and have been trusting the software industry.
“How AI eliminated my job at Dropbox”
Former staff engineer at Dropbox.
I was part of the 20% RIF at Dropbox at the end of October. The stated reason for this was to focus on Dash, their AI big-bet. The 10% RIF in 2023 was also to focus more on Dash.
How did this eliminate my job? Internal reprioritization, that's how. I was moving into an area that was scheduled to focus on improving Dropbox's reliability stance in 2025 and beyond, intended to be a whole year initiative. It's tricky to go into details, but the aim was to take a holistic view of disaster preparedness beyond the long standing disaster scenarios we had been using and were already well prepared for. Projects like this are common in well established product-lines like Dropbox's file-sync offering, as they take a comprehensive overview of both audit compliance (common criteria change every year) and market expectations.
This initiative was canned as part of the RIF, and the staffing allocated to it largely let go. Such a move is consistent with prioritizing Dash, a brand new product that does not have dominant market-share. Startups rarely prioritize availability to the extent Dropbox's file-sync product does because the big business problem faced by a startup is obtaining market-share, not staying available for your customers. As products (and companies) mature, stability starts gaining priority as part of customer retention engineering. Once a product becomes dominant in the sector, stability engineering often is prioritized over feature development. Dropbox file-sync has been at this point for several years.
With Dash being a new product, and company messaging being that Dash is the future of Dropbox, a reliability initiative of the type I was gearing up for was not in line with being a new product scrapping for market-share. Thus, this project and the people assigned to it were let go.
Blood in the Machine: What are you planning next?
This job market is absolutely punishing. I had a .gov job for the .com crash, a publicly funded .edu job for the 2008 crash, and a safe place inside a Dropbox division making money hand over fist during the COVID crash (Dropbox Sign more than doubled document throughput over 2020). This is my first tech winter on the bench, and I'm getting zero traction. 37 job apps in the months I've been looking, 4 got me talking to a human (2 of which were referrals), all bounced me after either the recruiter or technical screens. Never made it to a virtual onsite.
This has to do with me being at the Staff Engineer level, and getting there through non-traditional means. The impact is when I go through the traditional screens for a high level engineer I flame out, because that wasn't my job. The little feedback I've gotten from my hunt is a mix of 'over-qualified for this position' and 'failed the technical screen.' Attempting to branch out to other positions like Product Manager, or Technical Writer have failed due to lack of resume support and everyone hiring Senior titles.
I may be retired now. I'm 50, but my money guy says I've already made retirement-money; any work I do now is to increase lifestyle, build contingency funds, or fund charitable initiatives. The industry is absolutely toxic right now as cost-cutting is dominating everything but the most recently funded startups. We haven't hit an actual recession in stock-prices due to aggressive cost and stock-price engineering everywhere, and cost-engineering typically tanks internal worker satisfaction. I've been on the bench for six months, money isn't a problem. Do I want to stick my head back into the cortisol amplifier?
Not really.
“It's no longer only an issue of higher-ups: colleagues are using chatgpt to undermine each other.”
Tech worker, marketing department.
I used to work at a mid-sized Silicon Valley startup that does hardware. The overall project is super demanding, and reliant on skilled, hands-on work. Our marketing team was tiny but committed. My manager, the CMO, was one of the rare ones: deeply experienced and seasoned in the big ones, thoughtful, and someone who genuinely loved his craft.
Last year, a new hire came in to lead another department. Genuinely believe she is a product of the "LinkedIn hustler / thought-leadership / bullshit titles" culture. Super performative.
Recently and during a cross-functional meeting with a lot of people present, she casually referred to a ChatGPT model she was fine-tuning as our "Chief Marketing Officer"—in front of my manager. She claimed it was outperforming us. It wasn’t—it was producing garbage. But the real harm was watching someone who’d given decades to his field get humiliated, not by a machine, but by a colleague weaponizing it.
Today, in the name of “AI efficiency,” a lot of people saw the exit door and my CMO got PIPd.
The irony here is two-fold: one, it does not seem that the people who left were victims of a turn to "vibe coding" and I suspect that the "AI efficiency" was used as an excuse to make us seem innovative even during this crisis. Two, this is a company whose product desperately needs real human care.
[If your job has been impacted by AI, and you would like to share your story as part of this project, please do so at [email protected].]
“AI killed two of my jobs”
Veteran tech worker at Adobe and in the public sector.
AI killed my previous job, and it's killing my current one.
I used to work at Adobe... Despite constantly telling my team and manager I strongly disliked GenAI and didn't want to be involved in GenAI projects, when AI hype really started picking up, my team was disbanded and I was separated from my teammates to be put on a team specifically working on GenAI. I quit, because I didn't see any way for me to organize, obstruct, or resist without being part of building something that went against my values. I often wonder whether I should have let myself get fired instead. This was before we learned that Adobe trained Firefly on Stock contributions without contributors' opt-in, and before the Terms of Service debacle, so I'm glad I wasn't there for that at least.
Now I work in the public sector. It's better in most ways, but I have to spend ridiculous amounts of time explaining to colleagues and bosses why no, we can't just "use AI" to complete the task at hand. It feels like every week there's a new sales pitch from a company claiming that their AI tool will solve all our problems—companies are desperate to claw back their AI investment, and they're hoping to find easy marks in the public sector.
I don't want to be a curmudgeon! I like tech and I just want to do tech stuff without constantly having to call bullshit on AI nonsense. I'd rather be doing my actual job, and organizing with my colleagues. It's exhausting to deal with credulous magical thinking from decision-makers who should know better.
*My work at Adobe*
When I was at Adobe, I worked in Document Cloud. So like Acrobat, not Photoshop. For most of my time there, my job was evaluating machine learning models to see if they were good enough to put in a product. The vast majority of the time, Document Cloud leadership killed machine learning projects before they ended up in a product. That was either because the quality wasn't good enough, or because of a lack of "go-to-market.” In other words, middle and upper management generally did not accept that machine learning is only appropriate for solving a small subset of problems, which need to be rigorously-scoped and well-defined. They were looking for "everything machines" (these are derogatory air quotes, not a direct quote) that would be useful for huge numbers of users.
By the time AI hype really started to pick up, I had moved to a team working on internal tools. I wasn't building or evaluating machine learning models and I was outspoken about not wanting to do that. When LLM hype got really big, senior leadership started describing it as an "existential threat" (that is a direct quote as far as I remember), and re-organizing teams to get LLMs into Document Cloud as soon as possible. Adobe did not do *anything* quickly, so this was a huge change. A big red flag for me was that rather than building our own LLMs, Adobe used OpenAI's chatbots. When I asked about all of OpenAI's ethical and environmental issues, management made generic gestures towards being concerned but never actually said or did anything substantive about it. At that point I quit, because I had specifically been saying I didn't want to be involved in GenAI, and given the rushed and sloppy nature of the rollout, I didn't want my name anywhere near it.
*Colleagues' reactions*
Definitely I knew some colleagues who didn't like what Adobe was doing. There were a lot of people who privately agreed with me but publicly went along with the plan. Generally because they were worried about job security, but also there's a belief at Adobe that the company's approach to AI isn't perfect but it's more ethical than the competition. Despite being a huge company, teams were mostly isolated from each other, and as far as I know there wasn't a Slack channel for talking about AI concerns or anything like that. When I asked critical questions during department meetings or expressed frustration with leadership for ignoring concerns, people told me to go through the chain of command and not to be too confrontational.
Looking back, I wish my goal hadn't been to persuade managers but instead to organize fellow workers. I was probably too timid in my attempts to organize. I do regret that I didn't try having more explicit 1-on-1's about this, even though it would have been risky. Obviously I was very lucky/privileged to have enough savings to even consider quitting or letting myself get fired in this shitty job market, and I often wonder if I could have done more to combine strategies and resources with other colleagues so that fighting back would be less risky for everyone.
*Impact of AI on work*
When the GenAI push started, a lot more of my colleagues started working nights and weekends, which was rare (and even discouraged) before then. Managers paid lip service to Adobe's continuing commitment to work-life balance, but in practice that didn't match up with the sense of urgency and the unrealistic deadlines. I'm not aware of anyone who got fired or laid off specifically because of getting replaced by AI, and it looks like teams are still hiring. Although for what it's worth, in general Adobe does not do layoffs these days, but instead they pressure people into quitting by taking work away from them, putting them on PIPs, that kind of thing.
I found out that a colleague who had been struggling with a simple programming task for over a month—and refusing frequent offers for help—was struggling because they were trying to prompt an LLM for the solution and trying to understand the LLM's irrelevant and poorly-organized output. They could have finished the work in a day or two if they had just asked for help clarifying what they needed to do. I and their other teammates would gladly have provided non-judgmental support if they had asked.
Our team found out that a software vendor (I can't say which one but it was one of the big companies pushing Agentic AI) was using AI to route our service request tickets. As a result, our tickets were being misclassified, which meant that they were failing to resolve high-priority service disruptions that we had reported. We wasted days on this, if not weeks.
*My current job*
At my current job, I'm basically a combination of programmer and database administrator. I like the work way more than what I did at Adobe. Much like the corporate world, there are a lot of middle and upper managers who want to "extract actionable insights" from data, but lack the information literacy and technical knowledge to understand what they can (or should) ask for. And the people below them are often unwilling to push back on unreasonable expectations. It's very frustrating to explain to executives that the marketing pitches they hear about AI are not reflective of reality. It makes us seem like we're afraid of change, or trying to prevent "progress" and "efficiency."
So I would say the private and public sector have this in common: the higher up you go in the organization, the more enthusiastic people are about "AI,” and the less they understand about the software, and (not coincidentally) the less they understand what their department actually does. And to the extent that workers are opposed to "AI,” they're afraid of organizing, because it feels like executives are looking for reasons to cut staff.
“No crypto, no AI”
Tech worker.
So this is sort of an anecdote in the opposite direction of AI taking jobs—in a recent interview process at a mature startup in the travel tech space, part of the offer negotiations were essentially me stating “yeah I don’t want to work here if you expect me to use or produce LLM-based features or products” (this is relevant as the role is staff data scientist, so ostensibly on supply side of AI tooling), and them responding with “yeah if you want to do LLM work this isn’t the place for you.”
Though my network isn’t extensive, I feel like this is a growing sentiment in the small- and medium-tech space - my primary social media is on a tech-centric instance of the fediverse (hachyderm.io) and more often than not when I see the #GetFediHired hashtag, it’s accompanied by something akin to “no crypto, no AI” (also no Microsoft Teams, but I digress).
“Gradual addition of AI to the workplace”
Computer programmer.
Our department has now brought in copilot, and we are being encouraged to use it for writing and reviewing code. Obviously we are told that we need to review the AI outputs, but it is starting to kill my enjoyment for my work; I love the creative problem solving aspect to programming, and now the majority of that work is trying to be passed onto AI, with me as the reviewer of the AI's work. This isn't why I joined this career, and it may be why I leave it if it continues to get worse.
“my experience with AI at work and how I just want to make it do what I don't want to do myself”
Software engineer at a large tech firm.
All my life, I’ve wanted to be an artist. Any kind of artist. I still daydream of a future where I spend my time frolicking in my own creativity while my own work brings me uninterrupted prosperity.
Yet this has not come to pass, and despite graduate level art degrees, the only income I can find is the result of a second-class coding job for a wildly capitalist company. It’s forty hours a week of the dullest work imaginable, but it means I have time to indulge in wishful thinking and occasionally, a new guitar.
Real use cases where AI can be used to do work that regular old programming could not are so rare that when I discovered one two weeks ago, I asked for a raise in the same breath as the pitch.
I am experiencing exactly what you describe. There’s been layoffs recently, and my company is investing heavily in AI, even though they’re not sure yet how best to make it do anything that our corporate overlords imagine it should do.
From the c-level, they push around ideas about how we could code AI to do work, but in reality, those on the ground are only using AI to help write code that does the work, as the code always has. Real use cases where AI can be used to do work that regular old programming could not are so rare that when I discovered one two weeks ago, I asked for a raise in the same breath as the pitch.
And here I am, five hundred words into this little essay, and I’ve barely touched on AI! Nor have I even touched any of the AI tools that are so proudly thrust into my face to produce this. I’ve played around with AI tools for creative writing, and while they’re good at fixing my most embarrassing grammar errors, none of them have helped me in my effort to bridge the gap between my humble talent as a creative and my aspirations for my effort.
There’s a meme going on Pinterest that I believe sums up this moment: “We wanted robots to clean the dishes and do our laundry, so we could draw pictures and write stories. Instead they gave us robots to draw pictures and write stories, so we could clean dishes and do laundry.” This feels very true in the sense that human talent is getting valued not for the time it took to gain it and the ingenuity it proves, but for how well it feeds the greed of those who can afford to invest in bulk. But art in capitalism has always been this way, hasn’t it? If we don’t have a patron, we might as well eat our paint, and AI only tightens that grip that the privileged have held us in for centuries.
I’ve never been so fortunate to consider the work that funds my DoorDash addiction to be my passion’s output, and perhaps that’s why I’m not afraid of what I’ll lose. But it’s that same work that has me sharing notes with fellow programmers, and many of them will say with blunt honesty that they’re worried they’ll be replaced by AI. This is a vulnerability I rarely see from the group of people who often elevated their work as valuable and practical, as opposed to my efforts to learn how to make music and poetry, which were wasteful and useless. But I am like a plant that learned how to grow on rocks and eat insects. In a meeting soon, I’m going to level with them:
Don’t you understand? This work, what we do day in and day out for a soulless organization that drives profit from stealing our essence, this is the laundry! And if they think I’ll just throw that work into a machine and let it do all the work for me, they’re right. But it’s a machine that automates the work of running machines that automates the work that people used to do by hand, while constantly stealing glances at the clock, just waiting for the moment when they could be out from under the gaze of some righteous egomaniac.
Maybe this is just the perspective of someone who’s seen her work, of almost any type, get devalued with such regularity that it’s hard to imagine the robots making it any more difficult than it already is. No one’s ever really cared about my Instagram posts. No one pretends that my code will change the world. Perhaps, someday, I’ll make more money while babysitting on the weekends. I spend a lot of time thinking about things that haven’t worked out for me, and for us, as a society, and I think some of our worst failures come from moments when we can’t differentiate between the ability to use machines and our abilities as machines.
Last week I made a pie for my family, and I obviously didn’t get paid for it. Somewhere off in the offices of the illuminati, an account will calculate the value of the oven that baked the crust, the refrigerator that cooled the filling, the bougie pie dish that made my effort look food-blog ready. But there’s no monetary value in the work I did that literally put food on the table, and I rarely, if ever, get paid to perform the music I love, or receive more than pocket change for the short stories I publish. I keep thinking that the solution for both problems exist in some future innovation, but I can’t imagine what that invention would be, and I can’t find proof of a real connection between the two.
Maybe ChatGPT knows the answer to this riddle? I can throw a penny into our new philosophy vending machine, but I might come up with a better answer myself if I think about it while I unload the dishwasher.
PS I didn’t use ai to write this, also didn’t even bother to push it through an ai extruder to check the grammar. I guess I’m just feeling too lazy today to push that button! Have a nice weekend.
[If your job has been impacted by AI, and you would like to share your story as part of this project, please do so at [email protected].]
“AI-native high school interns”
Fintech worker.
Hello! I am a tech worker at a fintech. My workplace has been pushing AI really hard this year.
Here's the latest thing they thought up:
It 100% feels like testing the waters for just how unqualified and underpaid your workforce can be. Just as long as they can work the shovel of LLM they're good right?
The children yearn for the (LLM) mines!
“CrowdStrike”
Current CrowdStrike employee.
I work for CrowdStrike, the leading cybersecurity company in the United States. As a current employee, I can't reveal specific details about myself.
As you may have heard, CrowdStrike laid off 500 employees on May 7th, 2025. These were not underperformers. Many of them were relatively new hires. This action was presented as a strategic realignment with a special focus in "doubling down on our highest-impact opportunities," to quote CEO George Kurtz.
In the internal email, he states further:
AI investments accelerate execution and efficiency: AI has always been foundational to how we operate. AI flattens our hiring curve, and helps us innovate from idea to product faster. It streamlines go-to-market, improves customer outcomes, and drives efficiencies across both the front and back office. AI is a force multiplier throughout the business.
So, AI has literally killed many jobs at CrowdStrike this week. I'm fortunate to be among the survivors, but I don't know for how long.
Generative AI, particularly LLMs, is permeating every aspect of the company. It's in our internal chats. It's integrated into our note-taking tools. It's being used in triage, analysis, engineering, and customer communications. Every week, I'm pinged in an announcement that some new AI capability has been rolled out to me and that I am expected to make use of it. Customers who are paying for live human service packages from us are increasingly getting the output of an LLM instead. Quality Assurance reviewers have started criticizing reviewees for failing to run things through AI tools for things as trivial as spelling and grammar. Check out the front page and count the number of times "AI" is mentioned. It didn't used to be like this.
CrowdStrike is currently achieving record financials. At the time I write this, CRWD is trading at $428.63 in striking range of the stock's 52-week high. The efforts of my colleagues and I to rebuild from the incident of July 19, 2024 have been rewarded with shareholder approval and 500 layoffs. Some of the impacted individuals were recent graduates of 4-year schooling who, in addition to student loans, have moving expenses because they physically relocated to Texas shortly before this RIF occurred.
Many lower-level employees at CrowdStrike are big fans of generative AI; as techy people in a techy job, they fit the bill for that. Even so, many of them have become wary… of what increased AI adoption means for them and their colleagues. Some of the enthusiastic among them are beginning to realize that they're training the means of additional layoffs—perhaps their own.
CrowdStrikers have been encouraged to handle the additional per capita workload by simply working harder and sometimes working longer for no additional compensation on either count. While our Machine Learning systems continue to perform with excellence, I have yet to be convinced that our usage of genAI has been productive in the context of the proofreading, troubleshooting, and general babysitting it requires. Some of the genAI tools we have available to us are just completely useless. Several of the LLMs have produced inaccuracies which have been uncritically communicated to our customers by CrowdStrikers who failed to exhibit due diligence. Those errors were caught by said customers, and they were embarrassing to us all.
I would stop short of saying that the existence of genAI tools within the company is directly increasing the per capita workload, but an argument could be made of it indirectly accomplishing that. The net result is not a lightening of the load as has been so often promised.
Morale is at an all-time low. Many survivors have already started investigating their options to leave either on their own terms or whenever the executives inevitably decide an LLM is adequate enough to approximately replace us.
The company is very proud of its recognitions as an employer. As CrowdStrikers, we used to be proud of it too. Now we just feel betrayed.
“Coding assistants push”
Software engineer, health tech startup.
I work as a software engineer and we've been getting a push to adopt AI coding assistants in the last few months. I tried it, mostly to be able to critique, and found it super annoying, so I just stopped using it. But I'm starting to get worried. Our CEO just posted this in an internal AI dedicated Slack channel. The second message is particularly concerning.
[It’s a screenshot of a message containing a comment from another developer. It reads:]
"I am sufficiently AI-pilled to think that if you aren't using agentic coding tools, then you are the problem. They are good enough now that it's a skills issue. Almost everyone not using them will be unemployed in 2 years and won't know why (since they're the ones on Hacker News saying "these tools never work for me!" and it turns out they are using very bad prompts and are super defensive about it)."
We've had some layoffs long before this AI wave and the company has not picked up the pace in terms of hiring since. I'm sure now they're thinking twice before hiring anyone though. The biggest change was in how the management is enthusiastically incentivizing us to start using AI. First they offered coding assistants for everyone to use, then the hackdays we had every semester turned into a week long hackathon specifically focused on AI projects.
Now we have an engineer, if you can call him that, working on a project that will introduce more than 30k lines of AI generated code into our codebase, without a single unit test. It will be impossible to do a proper code review on this much code and it will become a maintenance nightmare and possibly a security hazard. I don't need to tell you how much management is cheering on that.
“My job hasn't been killed, yet”
Front end software engineer at a major software company.
My job hasn't been killed yet, but there's definitely a possibility that it could be soon. I work for a major software company as a front end software engineer. I believe that there's been AI-related development for about a year and a half. It's a little hard to nail down exactly because I'm one of the few remaining US-based developers and the majority of our engineering department is in India. The teams are pretty siloed and the day-to-day of who's on what teams and what they're doing is pretty opaque. There's been a pretty steady increase of desire and pressure to start using AI tools for a while now. As a result, timelines have been getting increasingly shorter, likewise the patience of upper management. They've tried to create tools that would help with some of the day-to-day repeatable UI pieces that I work on, but the results were unusable from my end and I found that I can create them on my own in the same amount of time.
The agents themselves had names and AI-generated profile pictures of minorities that aren't actually represented in the upper levels of the company, which I find kind of gross.
Around October/November of last year, the CEO and President (who's the former head of Product) had decided to go all-in on AI development and integrate it in all aspects of our business. Not just engineering, but all departments (Sales, Customer Operations, People Operations, etc). Don't get a ton of insight from other departments other than I've heard that Customer Ops is hemorrhaging people and the People Ops sent an email touting that we could now use AI to write recognition messages to each other celebrating workplace successes (insulting and somewhat dystopian). On the engineering side, I think initially there was a push to be an AI leader in supply chain, so there were a lot of training courses, hackathons and (for India) AI-focused off-sites where they wanted to get broad adoption of AI tools and ideas for products that we can use AI in.
Then in February, the CEO declared that what we have been doing is no longer a growth business and we were introducing an AI control tower and agents, effectively making us an AI first company. The agents themselves had names and AI-generated profile pictures of minorities that aren't actually represented in the upper levels of the company, which I find kind of gross. Since then, the CEO has been pretty insistent about AI in every communication and therefore there's an increased downward pressure to use it everywhere. He has never been as involved in the day-to-day workings of the company as he has been about AI. Most consequential is somewhere he has gotten the idea that because code can now be generated in a matter of minutes, whole SAS applications, like the ones we've been developing for years, can be built in a matter of days. He's read all these hype articles declaring 60-75% increase in engineering productivity. I guess there was a competitor in one of our verticals that has just come on the scene and done basically what our app can do, but with more functionality. A number things could explain this, but the conclusion has been that they used AI and made our app in a month. So ever since then, it's been a relentless stream of pressure to fully use AI everywhere to "improve efficiency" and get things out as fast as possible. They've started mandating tracking AI usage in our JIRA stories, the CEO has led Engineering all-hands (he has no engineering background), and now he is mandating that we go from idea to release in a single sprint (2 weeks) or be able to explain why we're not able to meet that goal.
I've been working under increasingly more compressed deadlines for about a year and am pretty burned out right now, and we haven't even started pushing the AI warp speed churn that they've proposed recently. It's been pretty well documented how inaccurate and insecure these LLMs are and, for me, it seems like we're on a pretty self-destructive path here. We ostensibly do have a company AI code of conduct, but I don't know how this proposed shift in engineering priority doesn't break every guideline. I'm not the greatest developer in the world, but I try to write solid code that works, so I've been very resistant to using LLMs in code. I want my work to be reliable and understandable in case it does need to be fixed. I don't have time to mess around and go down rabbit holes that the code chatbots would inevitably send me down. So I foresee the major bugs and outages just sky-rocketing under this new status quo. How they pitch it to us is that we can generate the code fast and have plenty of time to think about architecture, keep a good work/life balance, etc.
But in practice, we will be under the gun of an endless stream of 2 week deadlines and management that won't be happy at how long everything takes or the quality of the output. The people making these decisions love the speed of code generation but never consider the accuracy and how big the problem is of even small errors perpetuated at scale. No one else is speaking up to these dangers, but I feel like if I do (well, more loudly than just to immediate low-level managers), I'll be let go. It's pretty disheartening and I would love to leave, but of course it's hard to find another job competing with all the other talented folks that have been let go through all this. Working in software development for so long and seeing so many colleagues accept that we are just prompt generators banging out substandard products has been rough. I'm imagining this must be kind of what it feels like to be in a zombie movie. I'm not sure how this all turns out, but it doesn't look great at the moment.
The one funny anecdote during all this AI insanity is they had someone from GitHub demo do a live presentation on Co-Pilot and the agents. Not only was everything he demoed either unreliable or underwhelming, but he could not stop yawning loudly during his own presentation. Even the AI champions are tired.
Less than a month later, the engineer emailed me a followup.
And I just got laid off yesterday. The reason cited was they need full stack developers and want engineers that are in India, and not for performance. My front-end-focused position was rendered obsolete. Very plausible since they definitely prefer hiring young and less expensive developers abroad. So AI is not technically the direct cause, but definitely a factor in the background. They'll hire a bunch of new graduates to churn out whatever AI solutions that they think they can hype. Annoyingly, they did announce two new AI agents yesterday, again with faces and names of women. The positive is that they did give me a decent severance, so in the short term I'm fine, financially but also that I don't have to deal with the pressure of ridiculous deadlines.
“AI experience”
Edtech worker.
I work for a small edtech startup and do all of our marketing, communications, and social media. I've always enjoyed doing our ed policy newsletter and other writing related projects. My boss absolutely loves AI, but until recently I'd been able to avoid it. A few weeks ago, my boss let me know that all of my content writing would now be done on ChatGPT so I would have more time to work on other projects. He also wants me to use AI to generate images of students, which I've luckily been able to push back on.
Although he says it's a time saver, I don't actually have other projects, so not only am I creating complete slop, but I'm also left with large amounts of time to do nothing. Being forced to use AI has turned a job I liked into something I dread. As someone with a journalism background, it feels insulting to use AI instead of creating quality blog posts about education policy. Unfortunately, as a recent grad, I haven't had much luck finding another job despite applying to hundreds, so for now I have to make do with the situation, but I will say that having to use AI is making me reconsider where I'm working.
“AI makes everything worse”
Senior developer at a cloud company.
I work for a cloud service provider (who will retaliate if you don't post this anonymously, unfortunately), and they're absolutely desperate for the current AI fad to be useful for something.
They're completely ignoring the environmental costs (insane power requirements, draining lakes of freshwater for cooling, burning untold CPU and GPU hours that could be dedicated to something useful instead) because there's a buck to be made. They hope. But they're still greenwashing the company of course.
For cloud companies, AI is a gold rush; until the bubble bursts, they can sell ridiculous amounts of expensive server time (lots and lots of CPU/GPU/memory/storage) and tons of traffic to and from the models. They're selling shovels to the gold miners, and are in a great position to charge rent if someone strikes a vein of usefulness.
I can see a scenario coming fast that's going to set back software development by years
But they're desperate for this to keep going. They're demanding we use AI for literally everything in our jobs. Our managers want to know what we're using AI for and what AI "innovations" we've come up with. If we're not using AI for everything, they want to know why not. I don't think we're quite at the point of this being part of our performance evaluations, but the company is famously opaque about that, so who knows. It's certainly something the employees worry about.
My work involves standards compliance. Using AI for any part of it will literally double our work load because we'll have to get it to do the thing, and then carefully review and edit the output for accuracy. You can't do compliance work with vibes. What's the point of burning resources to summarize things when you need to review the original and then the output for accuracy anyway?
I can see a scenario coming fast that's going to set back software development by years (decades? who knows!):
C-suite: we don't need these expensive senior developers, interns can code with AI
C-suite: we don't need these expensive security developers, AI can find the problems
senior developers are laid off, or quit due to terrible working conditions (we're already seeing this)
they're replaced with junior developers, fresh out of school... cheap, with no sense of work-life balance, and no families to distract them
all the vibe coding goes straight to production because, obviously, we trust the AI and don't know any better; also we've been told to use AI for everything
at some point, all the bugs and security vulnerabilities make everything so bad it actually starts impacting the bottom line
uh oh, the vibe coders never progressed beyond junior skill levels, so nobody can do the code reviews, nobody can find and fix the security problems
if all the fired senior developers haven't retired or found other jobs (a lot of these people want to get out of tech, because big tech has made everything terrible), they'll need to be hired back, hopefully at massive premiums due to demand
If these tools were generally useful, they wouldn't need to force them on us, we'd be picking them up and running with them.
At first, the exec’s AI speech was greeted by the typical heart-eyes and confetti emojis, but then I saw there were a few thumbs-down emojis thrown into the mix. This was shocking enough on its own, but then the thumbs-downs multiplied, tens and hundreds of them appearing on the screen, making those few little confettis seem weak and pathetic. I was already floored at this point, and then someone posted the first tomato…
“then came the tomatoes”
Tech worker at a well-known tech company.
I work at a fairly well-known tech company currently trying to transform itself from a respected, healthy brand to a win-at-all-costs hyperscaler. The result has mostly been a lot of bullshit marketing promises pegged to vaporware, abrupt shifts in strategy that are never explained, and most of all, the rapid degrading of a once healthy, candid corporate culture into one that is intolerant of dissent, enforces constant positivity, and just this week, ominously announced that we are “shifting to a high-performance culture.”
The company leadership also recently (belatedly) declared that “we are going all in on AI.”
I don’t use AI. I morally object to it, for reasons I hardly need to explain to you. And now I feel like I’m hiding plain sight, terrified someone will notice I’m actually doing all my own work.
We’re hiring for new roles and have been explicitly told that no candidate will be considered for *any* job unless they’re on board with AI. Every department has to show how they’re “incorporating AI into their workflows.” I heard through the grapevine that anyone so much as expressing skepticism “does not have a future with the company.”
It is pretty bleak. I’d leave, but I keep hearing it’s the same everywhere.
But then something insane happened.
At the most recent company all-hands, typically the site of the post painful sycophancy, one of our executives gave a speech formally announcing our big AI gambit. The meeting is so big that there is no Zoom chat, so people can only directly react via emojis. At first, the exec’s AI speech was greeted by the typical heart-eyes and confetti emojis, but then I saw there were a few thumbs-down emojis thrown into the mix. This was shocking enough on its own, but then the thumbs-downs multiplied, tens and hundreds of them appearing on the screen, making those few little confettis seem weak and pathetic. I was already floored at this point, and then someone posted the first tomato. It caught on like wildfire until there were wave after wave of virtual tomatoes being thrown at the executive’s head—a mass outcry against being forced to embrace AI at gunpoint. He tried to keep going but his eyes kept darting to the corner of his screen where the emojis appeared, in increasing panic.
It was goddamn inspiring. And while the executives didn’t immediately abandon all their AI plans, they are definitely shaken by what happened, and nervous about mass dissent. As they should be.
Thanks again to every tech worker who shared their story to me, whether it was included here or not—and to every worker who has written in to [email protected], period. I intend to produce the next installment in coming weeks, so subscribe if below if that’s of interest. And if you’d like to support this work, and receive the paywalled Critical AI reports and special commentary, please consider becoming a paid subscriber. My wonderful paid subscribers are the only reason I am able to do any of this. A million thanks.
Finally, one more time with feeling: If your job has been impacted by AI, and you would like to share your story as part of this project, please do so at [email protected]. If you’re willing to participate in an on-camera interview, contact us at [email protected]. Thanks everyone—until next time.
| 2025-06-25T00:00:00 |
https://www.bloodinthemachine.com/p/how-ai-is-killing-jobs-in-the-tech-f39
|
[
{
"date": "2025/06/25",
"position": 12,
"query": "AI workers"
},
{
"date": "2025/06/25",
"position": 6,
"query": "AI replacing workers"
},
{
"date": "2025/06/25",
"position": 6,
"query": "AI replacing workers"
},
{
"date": "2025/06/25",
"position": 13,
"query": "AI workers"
},
{
"date": "2025/06/25",
"position": 7,
"query": "AI replacing workers"
},
{
"date": "2025/06/25",
"position": 7,
"query": "AI replacing workers"
},
{
"date": "2025/06/25",
"position": 7,
"query": "AI replacing workers"
},
{
"date": "2025/06/25",
"position": 7,
"query": "AI replacing workers"
},
{
"date": "2025/06/25",
"position": 7,
"query": "AI replacing workers"
},
{
"date": "2025/06/25",
"position": 7,
"query": "AI replacing workers"
},
{
"date": "2025/06/25",
"position": 7,
"query": "AI replacing workers"
},
{
"date": "2025/06/25",
"position": 8,
"query": "AI replacing workers"
},
{
"date": "2025/06/25",
"position": 7,
"query": "AI replacing workers"
},
{
"date": "2025/06/25",
"position": 7,
"query": "AI replacing workers"
},
{
"date": "2025/06/25",
"position": 7,
"query": "AI replacing workers"
},
{
"date": "2025/06/25",
"position": 7,
"query": "AI replacing workers"
},
{
"date": "2025/06/25",
"position": 7,
"query": "AI replacing workers"
},
{
"date": "2025/06/25",
"position": 7,
"query": "AI replacing workers"
},
{
"date": "2025/06/25",
"position": 8,
"query": "AI replacing workers"
},
{
"date": "2025/06/25",
"position": 7,
"query": "AI replacing workers"
},
{
"date": "2025/06/25",
"position": 7,
"query": "AI replacing workers"
},
{
"date": "2025/06/25",
"position": 6,
"query": "AI replacing workers"
},
{
"date": "2025/06/25",
"position": 3,
"query": "AI replacing workers"
},
{
"date": "2025/06/25",
"position": 3,
"query": "AI replacing workers"
},
{
"date": "2025/06/25",
"position": 2,
"query": "AI replacing workers"
},
{
"date": "2025/06/25",
"position": 68,
"query": "AI employers"
},
{
"date": "2025/06/25",
"position": 8,
"query": "AI layoffs"
},
{
"date": "2025/06/25",
"position": 3,
"query": "AI replacing workers"
},
{
"date": "2025/06/25",
"position": 1,
"query": "AI workers"
},
{
"date": "2025/06/25",
"position": 28,
"query": "ChatGPT employment impact"
},
{
"date": "2025/06/25",
"position": 10,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/25",
"position": 64,
"query": "artificial intelligence labor union"
},
{
"date": "2025/06/25",
"position": 87,
"query": "future of work AI"
}
] |
|
Applying to Jobs Has Become an AI-Powered Wasteland - Futurism
|
Applying to Jobs Has Become an AI-Powered Wasteland
|
https://futurism.com
|
[] |
Applying to Jobs Has Become an AI-Powered Wasteland. "It's an ... If you're one of millions of job seekers struggling to find stable employment, ...
|
If you’re one of millions of job seekers struggling to find stable employment, just know it’s probably not you.
With the onslaught of so-called "generative AI" — Silicon Valley’s term for complex prediction algorithms that can be used to create new content based on vast amounts of material that they gathered without the permission of its creators — the job search has become a veritable gauntlet of fake job listings, automated application bots, and computer-generated interviews.
Though it’s only been a little over two years since consumers got their hands on ChatGPT — the first widely available generative AI model — the tech has already caused devastating harm to the digital job market.
Per the New York Times, the number of applications sent via LinkedIn has surged over 45 percent since 2024; the rate now stands at a dizzying 11,000 apps per minute on the site. One HR worker was gobsmacked when her fully-remote job posting received 400 applications in just 12 hours, surging to over 1,200 apps 36 hours later.
Access to AI makes it incredibly easy for legit applicants and scammers alike to spam employers with résumés, often uniquely tailored to the job's details. That makes standing out as a purely human applicant — which was already difficult before AI — a Sisyphean task.
"It’s an 'applicant tsunami' that’s just going to get bigger," one recruiter told the NYT, often devolving into an "AI versus AI type of situation."
But the problem didn’t start with job seekers. The trouble can be traced back to the mass adoption of AI HR bots, with 99 percent of Fortune 500 companies admitting to the use of AI to filter applicants, and 40 percent anticipating using AI to conduct interviews.
And as job seekers turn to AI to level the playing field, companies — which hold almost all of the power in the labor market — are cranking the lever to dump more AI on the problem. Employers are now unleashing AI to verify applicant identities, administer computer-generated skilled assessments, and auto-generate messages to applicants — all deployed with essentially zero recourse for anyone wrongfully rejected or subject to bias by the faceless bot.
Case in point, LinkedIn is unleashed a so-called "AI agent" to help HR managers keep up with the flood of AI-assisted job applications — essentially fighting fire with gasoline.
It’s a labor arms race to the bottom, and until regulations like the EU’s Regulation on Artificial Intelligence become universal, applicants lacking the funding, resources, and techno-savvy of organized companies are bound to lose.
More on labor: AI Is Replacing Women's Jobs Specifically
| 2025-06-25T00:00:00 |
https://futurism.com/job-applications-ai-slop
|
[
{
"date": "2025/06/25",
"position": 52,
"query": "AI employment"
},
{
"date": "2025/06/25",
"position": 65,
"query": "ChatGPT employment impact"
},
{
"date": "2025/06/25",
"position": 42,
"query": "artificial intelligence employment"
}
] |
|
Closing the AI Skills Gap Through Upskilling and Reskilling
|
Closing the AI Skills Gap Through Upskilling and Reskilling
|
https://www.globalknowledge.com
|
[] |
The AI skills gap stems from the disconnect between the rapid advancement of technology and the workforce's ability to keep pace. According to ...
|
The rapid growth of artificial intelligence has revolutionized industries, creating new opportunities while also exposing a critical challenge: the widening skills gap. In the third installation of our LinkedIn poll series, we asked our followers how important they think upskilling and reskilling are for closing the AI skills gap.
The results painted a nearly unanimous picture, with 68% of respondents deeming it “Extremely Important” and 15% ranking it as “Very Important.” Though some selected “Somewhat Important” (9%) or “Not Important” (9%), the takeaway is clear: upskilling and reskilling are pivotal to ensuring that individuals and organizations remain competitive in an AI-driven future.
Why the AI Skills Gap Matters
The AI skills gap stems from the disconnect between the rapid advancement of technology and the workforce’s ability to keep pace. According to Skillsoft’s 2024 IT Skills and Salary Report, two-thirds of IT decision-makers report skills gaps on their teams, with nearly as many forecasting them in the next few years.
While AI technologies like machine learning and natural language processing proliferate, many professionals lack the specialized expertise required to work with or alongside these systems. The cost of skills gaps burdens teams, increasing their stress and hampering their ability to meet business objectives.
Our poll results highlight widespread acknowledgement of this issue. With the majority of participants indicating upskilling and reskilling as extremely important, it’s clear that these strategies are viewed as a critical response.
How Upskilling and Reskilling Can Bridge the Gap
The poll’s findings demonstrate several key points, including resounding support for skills development and a recognition of urgency. With individuals and industry leaders alike recognizing skills development as fundamental to successfully navigating the AI-driven future, organizations must ensure that they are able to progress in the face of change, rather than falling behind.
WATCH OUR WEBINAR ON MASTERING AI TRANSFORMATION
To address the skills gap effectively, organizations need a multi-pronged approach that both empowers their workforce and adapts to rapid technology shifts. Here are our strategies for closing the gap:
AI Learning Solutions: As an industry-recognized training provider, Skillsoft Global Knowledge helps our learners develop their AI expertise with premier learning solutions to position them as leaders equipped to drive AI adoption and shape the future of innovation. Our broad curriculum spans essential AI-related domains like machine learning, data analysis, and cloud computing, as well as complementary areas such as design thinking, ethical AI, and technology leadership. View all AI courses. Promoting a Culture of Lifelong Learning: Skillsoft Global Knowledge champions continuous learning by providing scalable and flexible options for organizations. With annual training plans, industry-recognized certifications, and partnerships with leading technology providers like Cisco, AWS, and Microsoft. These resources allow employees to upskill regularly, staying current as technology evolves. Find your certification path. Facilitating Cross-Sector Collaboration: By partnering with industry leaders, Skillsoft Global Knowledge creates learning ecosystems that benefit all stakeholders. Our collaborations enable us to design training programs aligned with real-world needs, ensuring organizations have access to ready-to-use solutions that address their unique requirements, regardless of industry. Find the perfect course for you. Supporting Diverse Learners with Flexible Options: Skillsoft Global Knowledge offers accessible and inclusive learning formats, such as virtual instructor-led training, on-demand content, and certification prep. This flexibility supports professionals with varying learning preferences and backgrounds. Programs like our bootcamps also provide immersive experiences to fast-track skill development in high-demand areas. Explore our course delivery formats.
The poll results underscore the overwhelming importance on investing in AI skills. With a total of 83% recognizing the critical need for upskilling and reskilling, the message is clear—this is not just a trend, but a necessity for ensuring long-term success in an AI-driven professional landscape.
By taking action now and leveraging top-level training solutions, organizations can build a workforce that isn’t just prepared for the challenges of today, but is also ready to thrive in the opportunities of tomorrow.
At Skillsoft Global Knowledge, we help professionals stay ahead by offering up-to-date courses designed to prepare them for both current and emerging roles in AI-integrated industries.
UNLOCK THE POWER OF AI
| 2025-06-25T00:00:00 |
https://www.globalknowledge.com/us-en/resources/resource-library/articles/closing-the-ai-skills-gap-through-upskilling-and-reskilling/
|
[
{
"date": "2025/06/25",
"position": 28,
"query": "AI skills gap"
},
{
"date": "2025/06/25",
"position": 29,
"query": "AI skills gap"
},
{
"date": "2025/06/25",
"position": 29,
"query": "AI skills gap"
},
{
"date": "2025/06/25",
"position": 29,
"query": "AI skills gap"
},
{
"date": "2025/06/25",
"position": 29,
"query": "AI skills gap"
},
{
"date": "2025/06/25",
"position": 34,
"query": "AI skills gap"
},
{
"date": "2025/06/25",
"position": 29,
"query": "AI skills gap"
},
{
"date": "2025/06/25",
"position": 34,
"query": "AI skills gap"
},
{
"date": "2025/06/25",
"position": 28,
"query": "AI skills gap"
},
{
"date": "2025/06/25",
"position": 27,
"query": "AI skills gap"
},
{
"date": "2025/06/25",
"position": 29,
"query": "AI skills gap"
},
{
"date": "2025/06/25",
"position": 34,
"query": "AI skills gap"
},
{
"date": "2025/06/25",
"position": 30,
"query": "AI skills gap"
},
{
"date": "2025/06/25",
"position": 29,
"query": "AI skills gap"
},
{
"date": "2025/06/25",
"position": 33,
"query": "AI skills gap"
}
] |
|
Why Robots Will Displace Managers — and Create Other Jobs
|
Why Robots Will Displace Managers — and Create Other Jobs
|
https://sloanreview.mit.edu
|
[
"Massachusetts Institute Of Technology",
"About The Authors",
"Bryan Hong",
"Lynn Wu"
] |
While robot-adopting companies may shed some management and middle-skilled jobs, research shows that robots will increase employee head counts ...
|
Carolyn Geason-Beissel/MIT SMR | Getty Images
Summary: Companies’ increased use of robots is changing the skills employees need and how their performance is measured. Research shows that the efficiencies that the use of robots delivers are reducing the need for some middle management jobs. Meanwhile, roles for nonmanagerial employees who can support robot technologies or perform tasks robots can’t yet do are expanding faster than middle-skilled jobs — those that robots can do — are being lost.
Recent, dramatic growth in robot adoption across an increasing number of global industries has sparked avid interest in the impact robots will have in the workplace — particularly which jobs they will replace and whether any new jobs will be created for humans.1 Our recent research focused primarily on physical robots, including both industrial and collaborative robots, used in production processes. Our data confirms that companies are indeed eliminating some human jobs in favor of robots — but that robot adoption is increasing the total number of nonmanagerial employees while reducing the number of middle managers needed.2
Even with rapid technological advancements, robots aren’t yet capable of managing human employees. So why are managerial positions being eliminated when the robots arrive? Our research highlights two significant changes robots bring to the workplace that can explain this shift. One is the radical transformation in managers’ ability to measure and reward the performance of individual employees who work with robots. The other is a change in the skills required of nonmanagerial employees, which is affecting the nature of managerial work itself. When companies invest in robots, the combined effect of these two changes leads to reductions in managerial head count that can be dramatic.
How Efficiency Gains Impact Managers
In a previous MIT SMR article, we described how robot adoption is transforming organizations by making human performance measurement easier, thus enabling organizations to reward and manage talent more easily and effectively.
More accurate performance measurement enabled by robots makes supervisors much more efficient at managing employee performance.
Managers expend a significant amount of effort on people management — almost a third of their time, according to a recent McKinsey survey. When work is primarily done in teams, each individual employee’s contribution to group performance can be hard to discern.3 But robot adoption reduces the amount of time and effort required to compare individuals’ productivity levels, in many cases substantially so. This can be explained by a simple stylized example: If two humans work with the same type of robot but their levels of productivity differ, the consistency and transparency of the robot’s performance when working with both employees allows a manager to more easily observe the contribution of each person in isolation.
About the Authors Bryan Hong is an associate professor of entrepreneurship and management in the Bloch School of Management at the University of Missouri-Kansas City. Lynn Wu is associate professor of operations, information, and decisions at the University of Pennsylvania’s Wharton School of Management.
| 2025-06-25T00:00:00 |
https://sloanreview.mit.edu/article/why-robots-will-displace-managers-and-create-other-jobs/
|
[
{
"date": "2025/06/25",
"position": 23,
"query": "robotics job displacement"
}
] |
|
Why AI is now an imperative for business leaders - USA Today
|
From buzzword to must-have: Why AI is now an imperative for business leaders
|
https://www.usatoday.com
|
[] |
“Most leaders at the moment are using AI to find productivity boosts, to save costs, to reduce headcount,” said Amy Webb, CEO of the Future ...
|
Carolyn Said
Special to USA TODAY
Artificial intelligence is no longer a futuristic buzzword − it’s a strategic imperative. For today’s C-suite executives, AI offers far more than just automation. It’s a tool to unlock growth, spark innovation, and empower smarter decision-making − if deployed wisely.
“Most leaders at the moment are using AI to find productivity boosts, to save costs, to reduce headcount,” said Amy Webb, CEO of the Future Today Strategy Group, a New York consulting firm specializing in strategic foresight. “But the real opportunity is top-line growth” − identifying the next waves of innovation and creativity, executing those ideas, and planning for the future more effectively.
To use AI strategically, leaders must first understand what kind they’re dealing with.
What's the difference between analytical AI and generative AI?
There are two main types, said Tom Davenport, professor of IT and management at Babson College in Wellesley, Massachusetts: analytical AI, which makes predictions based on structured data, and generative AI, which creates content such as text, images or product ideas.
Need a break? Play the USA TODAY Daily Crossword Puzzle.
For companies in manufacturing or logistics, analytical AI can predict equipment failures or optimize pricing, he said. For those in media, law, or marketing, generative AI can drastically boost content creation.
For instance, Colgate-Palmolive uses generative AI to simulate customer reactions to new products, while Kroger’s analytic AI predicts nightly inventory needs for every grocery store, said Davenport, co-author of “All-in On AI: How Smart Companies Win Big with Artificial Intelligence.”
Why AI should also be people-powered or The human side of artificial intelligence
Despite AI’s power, experts argue for always keeping humans in the loop.
Viewing AI just as a job killer is short-sighted, said Thomas Malone, Patrick J. McGovern professor of management at the MIT Sloan School of Management and founding director of the MIT Center for Collective Intelligence. He sees it as a collaborator, not a competitor.
Executives should be thinking about “how can I use this technology (along with its generation of) new ideas about new kinds of products and services to create new jobs and make more profit?” said Malone, author of “Superminds: The Surprising Power of People and Computers Thinking Together.”
Davenport calls for an augmentation mindset – deploying AI to empower employees, rather than to replace them. “Most of these technologies are not powerful enough or accurate enough to use without some human intervention,” he said.
Beyond the rewards, what are the risks of AI?
Embracing AI brings risks – but they’re not the pop-culture notions that robots will take our jobs and murder us in our sleep, said Webb, author of “The Big Nine: How the Tech Titans and Their Thinking Machines Could Warp Humanity.”
One top risk is data decay – the way information can quickly become obsolete, undermining the effectivenes of AI that depends on it, she said.
Over-reliance on external partners is another danger.
“I see a lot of organizations, big and small, bringing in armies of consultants,” a short-term win, that sets up a long-term deficiency, Webb said. “It creates a huge vulnerability, because that company won't have developed any skills (and remains) reliant on these consultants going forward.”
A third risk centers on policy and regulatory uncertainty, she said, meaning companies may have to constantly change gears as laws evolve.
AI should be rooted in business strategy, not just handed off to IT, experts say.
Embedding it throughout a company is more effective than trying to manage it from above, Malone said. Letting lots of employees experiment with AI, while offering support and training, may yield opportunities both big and small, and get more AI knowledge spread throughout a company.
“There's more risk of trying to steer it top down than trying to have a lot more flowers blooming,” he said.
With AI’s rapid-fire evolution, leaders need to make sure they don’t get boxed into just today’s capabilities, Webb said. Rather, they should factor AI into strategic foresight – building scenarios for long-term, data-driven planning, rather than a narrow focus on the next few quarters or years.
“Decisions that are made on artificial intelligence today will have a reverberating effect for decades into the future, at a business level, at a societal level,” she said.
Leaders need to plunge into AI now without waiting for others to show the way, Davenport said. That means training people, developing good data and figuring out how AI fits into your business.
“Don’t think you can be a fast follower in this area,” he said. “The idea that you can catch up really quickly without having to make some of the early mistakes that your competitors do, is probably not going to be a good idea. It takes too long to get really good at it – so you should start now.”
AI is one case where the hype about transformation may be real.
“This technology has the potential to change business at least as much as the internet did, maybe quite a bit more,” Malone said.
| 2025-06-25T00:00:00 |
2025/06/25
|
https://www.usatoday.com/story/money/business/2025/06/25/ai-business-tool-for-success/84289855007/
|
[
{
"date": "2025/06/25",
"position": 84,
"query": "AI business leaders"
},
{
"date": "2025/06/25",
"position": 53,
"query": "AI business leaders"
}
] |
What the labor market isn't telling you—yet - McKinsey
|
What the labor market isn’t telling you—yet
|
https://www.mckinsey.com
|
[
"Brooke Weddle",
"Bryan Hancock",
"Svenja Gudell",
"Senior Partner",
"Washington Dc",
"Partner"
] |
AI is fast transforming work as we've known it—and the latest data on jobs doesn't always reflect the changes underway. “One word sums it up ...
|
AI is fast transforming work as we’ve known it—and the latest data on jobs doesn’t always reflect the changes underway. “One word sums it up best: ‘uncertainty,’” says Svenja Gudell, chief economist of global employment platform Indeed. In this episode of McKinsey Talks Talent, Svenja joins McKinsey talent leaders Brooke Weddle and Bryan Hancock, along with Global Editorial Director Lucia Rahilly, to help leaders make sense of the current collision of labor market trends: generative AI, agentic AI, an aging workforce, shifting priorities, and more.
The following transcript has been edited for clarity and length.
Uncertainty in today’s labor market
Lucia Rahilly: Svenja, welcome to McKinsey Talks Talent.
Svenja Gudell: Thanks so much for having me. It’s a pleasure to be here.
Lucia Rahilly: Let’s start with a quick overview of what your role as chief economist of Indeed’s Hiring Lab entails.
Svenja Gudell: As chief economist for Indeed, I run the Indeed Hiring Lab, which is Indeed’s economics and research arm. Our mission is to be at the forefront of everything to do with the labor market. If there’s a particular trend happening, we want to know about it and to inform our stakeholders and audiences.
Lucia Rahilly: There is a lot of uncertainty in the macroeconomic environment right now. What are the most surprising trends you see emerging in the data for 2025, and how do they compare with what you’ve seen in previous years?
Svenja Gudell: One word sums it up best: “uncertainty.” The level of uncertainty we’re dealing with in today’s economic market is incredibly high. That’s because a few trends are colliding at the same time: politics and where economic policy is going, leftover impacts from the pandemic, and demographic shifts that are larger and more long term. Many industrialized countries have aging economies and shrinking labor forces, particularly in places like Japan, where this is happening acutely already. Then there’s AI, particularly generative AI, and how it is impacting all those trends.
Subscribe to the McKinsey Talks Talent podcast
Brooke Weddle: Svenja, as an economist, you look at a lot of data. How do you cut through the noise and say, “These are the two to three metrics that give me a sense for how any given labor market, whether in the US or another region, is changing”?
Svenja Gudell: We have an amazing playground of data. We’re able to look not only at the demand side—job postings, what employers are looking for, what kinds of skills are important, and how jobs are changing—but at the supply side as well—what job seekers are doing, what their behaviors are, what they’re bringing to the table, how they’re upskilling or reskilling themselves, and what they are expecting of work nowadays. Looking at that intersection is really important.
The level of uncertainty we’re dealing with in today’s economic market is incredibly high. Svenja Gudell
Then you have the larger macroeconomic environment. Particularly in the US, consumption is a big driver of what has made our economy historically so strong. That’s a nice forward-looking indicator. Sentiment is one of the big things we look at. And then standard stuff like unemployment, layoffs—particularly in this environment, where I feel like many of us are sitting at the edge of our seats and thinking, “Oh, what’s going to happen next? How are we going to react to this?” We have to look at the data to see, “Is there anything that’s telling us what might be upcoming?” The number of layoffs is, right now, one of the things we’re watching closely. Immigration numbers and general migration numbers are super important.
From churn to return
Bryan Hancock: What have you seen about people who are marginally attached to the labor market—the ones who are first to exit, first to come back in when the job market either gets weaker or stronger?
Svenja Gudell: Let me give you a little background, which helps frame where we are today. Initially, we had, of course, the COVID-19 shock to the labor market, and a lot of people exited the labor market.
Then we got vaccines. Things started speeding up again. And a lot of people reentered the market. We saw a whole lot of “unretiring,” if you will. People had said, “Alright, I’m retired.” And then either their nest egg wasn’t going as far as they thought, or they said, “Wages are climbing quite a bit right now. There’s a lot of upside to reengaging in the labor market.” So we saw really strong labor force participation again. And it carried all groups. Women started participating again, despite having to juggle—and still having to juggle—a lot of home and childcare duties.
Now we’re entering a slightly different market—and oftentimes a very different market, with return-to-work mandates and less flexibility. And as flexibility is removed, we’re not seeing the same wage increases. Now we’re in a steadier phase, and we’re not seeing as many people flow back into the labor market.
AI and jobs—from generative to agentic
Lucia Rahilly: Svenja, let’s get a sense of the holistic picture of the labor market that your data helps inform, starting with AI. Talk about how you see AI changing the game for job seekers. Are you seeing signs of displacement? Is AI reshaping the demand you see on your platform for certain kinds of skills?
Svenja Gudell: I’ll start on the macroeconomic side. The Hiring Lab team has done some extensive research trying to answer what I think is the number-one question out there: “How is generative AI impacting the labor market?”
We saw, particularly in the early days—three years ago—a lot of surveys that asked, “How will this impact different jobs? How are different skills and tasks going to be impacted?” We really wanted to take the wealth of data that we have at Indeed to bring a more quantitative approach to that question. So we dug in and tried to see, “Given all the skills in the Indeed skills taxonomy—close to 3,000 that basically describe the skills every single job needs—how are those skills impacted by generative AI?”
We looked not only at the general knowledge generative AI will bring to a certain skill but also at problem-solving abilities, as well as the need to be physically present. For example, as a nurse, if you’re taking blood, you have to be there to perform that action. So generative AI, at least currently, is not very good at doing something like that—although ten years from now, I fully expect a robotic nurse to take blood.
Bryan Hancock: How is generative AI changing the work of economists? How are you using gen AI in your work in looking at labor markets?
Svenja Gudell: It’s the next thing. Taking all that data, we were able to see that generative AI does not replace any job completely. There wasn’t a single job where generative AI was particularly good at all of it. However, it’s particularly good at doing a few things really well—for example, coding. Employers are adjusting how many software developers they hire or what kinds of efficiencies they’re starting to see in terms of how much code is written by generative AI.
The interesting outcome of that research was that we’re seeing a lot of augmentation of jobs. And the traditional list of impacted jobs was suddenly turned on its head. Automation impacted a lot of manual jobs. Generative AI impacted a lot of knowledge worker jobs: marketers, HR professionals, accountants, software developers. If you’re a bus driver or childcare professional or dentist, you saw less impact. If we have this conversation three years from now, I bet the landscape for jobs will have changed even more. And then, of course, there’s the other side: How is hiring changing, and what are the tools available to employers and job seekers as they go on their journey of finding that perfect job match or perfect candidate?
The usual thing for me to say for job security is that economists will never be extinct. I’m happy to report that so far, most generative AI tools aren’t really good at forecasting, or doing some of what we do daily, or even analyzing different trends and pulling them together. What it is really good at is summarizing research, for example. It’s faster now for me to do a literature review or get a sense of what the landscape is—what existing research is out there and where we might want to go.
Brooke Weddle: Svenja, what about agentic? Are you seeing any early signs of AI displacement, particularly among entry-level candidates entering the job market?
Svenja Gudell: Absolutely. We are seeing fewer internships, fewer entry-level jobs. We are also starting to see less demand for the highly impacted job functions, such as software developers. Interestingly, if you dig a little deeper, you’ll see a fair bit of demand for, say, data engineers—people who work with the data. You still need to feed your large language model a lot of data. But for pure coders, especially entry level—less so on the architect side of things—if you’re impacting a third of all that workload for every single person, you can probably combine those jobs. Maybe you hire one less person, and then another person does the more human aspects of the job that the machine cannot do yet. It’s a rejiggering of skills for a single job. But that impacts the type of job that is then hired for.
Bryan Hancock: Given the challenge of reduced postings and reduced openings for entry-level workers, what’s happening to the unemployment rate for recent college graduates?
Svenja Gudell: Unemployment is creeping up a bit. And recent graduates are more impacted in some countries than in others. Some of that is driven not only by AI but also by macroeconomic trends. But it’s a good thing to pay attention to because it brings up the larger questions, “What will happen to the entry-level job as we incorporate more of these agentic experiences or more generative AI? Will we continue to see unemployment creeping up more than it currently is?”
The tricky part is, you can’t look at this in isolation. From the employer perspective, you’re thinking, “I have other tools to do a lot of these tasks that I used to have an entry-level hire do.” But from the perspective of someone looking for a job, there’s a lot of potential for uptraining or reskilling using these tools.
I think this is the first time we’ve seen a disruption be not only the disruptor but also potentially the vehicle to help you live through that disruption. And I expect that will feed into some of the capabilities job seekers bring to their applications and to jobs later on. We have a ton of profile data at Indeed—over four million—that we look at from a research perspective. And one of the things we’ve started to pick up on is that a lot of folks working at McDonald’s are listing generative AI skills on their résumé. So I think we’ll start to notice people are getting in there and saying, “How can I use this tool to help me perform better in the labor market?”
This is the first time we’ve seen a disruption be not only the disruptor but also potentially the vehicle to help you live through that disruption. Svenja Gudell
Lucia Rahilly: Svenja, we’ve been talking about generative AI obviating certain tasks or reducing and reconfiguring roles. Any hot new roles emerging as AI starts to advance toward greater scale?
Svenja Gudell: Certainly. And history is on our side here; we’ve seen this story before. Every time there is a big technological development, we see the destruction of jobs and then the creation of new ones.
We’ve all talked about the prompt engineer, which was a big thing—it’s not that new anymore. We’ve seen a pickup in AI consultants. We’ve seen more salespeople having to be trained on selling AI technology. So some of these worlds are colliding and new jobs are being created.
From an employer perspective, this can often be tricky. Employers think, “I have to find people who understand AI and can also sell a product. Where do I find those skills together?” That brings us back to that original point around uncertainty.
If you look at payroll data and the jobs report, a lot of new jobs have been part-time. We’re seeing employers reach for a tool that they have in times of uncertainty. Maybe they don’t want to increase by a full headcount, but they’ll hire a contractor or a part-time employee to keep their options open and really flex in this environment of uncertainty.
McKinsey Talks Talent Podcast Bryan Hancock, Brooke Weddle, and other talent experts help you navigate a fast-changing landscape and prepare for the future of work by making talent a competitive advantage.
Evolving priorities
Brooke Weddle: Svenja, I want to return to your interesting insight around more McDonald’s workers sharing that they have a skill set that includes generative AI. How have you seen the role of the résumé change over time? What should job seekers be emphasizing, or what should they be thinking about differently when it comes to that core tool of getting a job?
The résumé is still a handy tool, and it’s still very widely used. Svenja Gudell
Svenja Gudell: One of the really big trends is skills first. The résumé is still a handy tool, and it’s still very widely used. Does your résumé need to live on a piece of paper? Maybe not. Maybe it’s just a collection of things you enter on a website, so it’s faster for a recruiter to gain appreciation for everything a candidate brings to the table: “Can you actually do what is required of you? Do you bring the right skills?” versus “Where did you go to school? How many years of experience do you have?”
That shows up in our data by how many jobs still require a master’s degree or a BA, for example, or how many jobs specify “ten-plus years’ experience” or “two years’ experience.” That number is going down—not as rapidly as in a very competitive market, because it was also a way to expand your talent pool. But we’re still seeing that push toward skills first.
Lucia Rahilly: I’m wondering about return to office—a hot headline at the outset of 2025. Is talent still prioritizing hybrid and other kinds of flexibility? Any changes in what job seekers are optimizing for?
Svenja Gudell: If you’re looking at the preferences and needs that a lot of job seekers have, number one is always compensation. Everyone wants a better pay package. No surprise there.
If you’re looking at the preferences and needs that a lot of job seekers have, number one is always compensation. Svenja Gudell
But particularly for women, the number-two reason for switching jobs remains flexibility—including either remote or hybrid working arrangements. We’re still seeing that as really important to a lot of job seekers. However, the number of jobs that offer remote work in the US has been steadily declining—perhaps not as much as the headlines might suggest, but from a high of somewhere around 10 percent to, I think, below 8 percent.
Some of that has to do with job mix. Right now, you have fewer openings in tech-type jobs, which tend to have a remote angle. We’ve seen a decrease in availability of remote and hybrid jobs on the supply side but not in terms of demand from job seekers.
We’ve seen a decrease in availability of remote and hybrid jobs on the supply side, but not in terms of demand from job seekers. Svenja Gudell
Lucia Rahilly: I want to pick up on something you said about the aging population. How does generation factor into the way workers are engaging with the labor market? Everyone’s focused on Gen Z. Does the data show that Gen Z has demonstrably different priorities in the jobs they’re pursuing?
Svenja Gudell: I think generational differences are not necessarily about the types of jobs candidates are searching for but rather what they’re hoping to find on the job. For example, we’ve done quite a bit of research on how political issues creep into life at work. Employees have expected companies to take more of a stance on certain issues. But there can be a lot of different viewpoints within the company itself, so the research is really interesting.
We also ran a survey that looked at how different generations look at diversity, equity, and inclusion—how they think about diversity among their senior leaders, how they think about bringing their whole selves to work. And there’s definitely a trend where younger generations care about this more than older generations. Part of that could be just what you’re used to and the trends that have been predominant at different times in the labor market.
What leaders are missing—and why it matters
Brooke Weddle: This gets me thinking. We’ve talked about a couple of headlines: return to office, AI. Are you looking at any trends and saying, “Gosh, why aren’t people talking about this or spending more time on this from a thought leadership perspective?”
Svenja Gudell: A lot of people really tend to focus on the short term—the now—and not really on having a good, long-term approach. And to survive, you have to have a short-term view on some things. You want to be able to open up your doors tomorrow as an employer. But having long-term trends in mind is also really important. So that’s always surprising to me, how headline driven we are.
A lot of people really tend to focus on the short term—the now—and not really on having a good, long-term approach. Svenja Gudell
And then as an economist, one of the really surprising things to me is, every time new data releases come out, we ask, “Oh, is this going to be the one that shows the impact, for example, of tariffs?” A lot of these trends take months to show up in official data, which makes us reach for other data sources. And then people are like, “Oh, we’re good—no inflation impact yet” or, “Consumption looks just fine.” But that data is three months old. It won’t show the impact.
With the onset of AI, one of the things we’ve looked at quite a bit is the “technification” of jobs. We have an AI tracker that looks at how many job postings mention AI in the job description. That could be for a creator of AI, someone who codes it, or a user of AI—someone in marketing or HR who uses that technology. And our tracker still has less than 1 percent of all jobs on Indeed that mention any sort of generative AI keywords. So it’s a really low number but really strong growth. Then you look at the technical skills most jobs require. And surprise, surprise: Microsoft Office is still the number-one-mentioned technological tool that every job wants out there. It’s really surprising.
Lucia Rahilly: Svenja, you mentioned seeing some slowing in the labor market, particularly in certain segments like entry-level jobs, as well as slowing attrition due to uncertainty. Acknowledging those dynamics, the labor market is still relatively tight. What are the biggest challenges you see for employers looking to attract and retain good talent in today’s marketplace?
The number-one thing to recognize is that the labor market is not a giant monolith. Svenja Gudell
Svenja Gudell: To me, the number-one thing to recognize is that the labor market is not a giant monolith. There are some really interesting things, particularly in the tighter market, that you can look at. Often, you might not have flexibility on base pay, but you have flexibility on benefits. We’re still seeing signing bonuses in the healthcare sector quite a bit. You can offer different training programs that help attract talent. Remote work is still a big thing that carries weight. A lot of different tools that an employer has in their toolbox can help in a tight market—beyond just paying more money.
The labor market of tomorrow
Lucia Rahilly: As you’re looking out beyond 2025, do you see any nascent trends or disruptions that business leaders should be aware of or act on now to get ahead of?
Svenja Gudell: Absolutely. The big one, again, is the race against an aging workforce. We’re going to start to see people still demanding goods and services without being active in the labor force anymore. So the number of workers actually available to take jobs is going to start to come down.
Balance that with AI. Are we going to see some of these promised productivity increases along the way? Which path will win out? Will we get AI up and running? It’s easy to have the technology, but you have to be able to use it productively inside your firm. Will that happen before we start to see these impacts of an aging workforce?
Those are the big ones. And then digging deeper there, I think every employer should—and many do—ask the questions, “How should I hire differently today? I hired a person five years ago, and this was their profile. Should that profile look different? Should I not even hire this person anymore, because these skills won’t be needed or won’t need to be performed by a human a year from now?”
That workforce-planning aspect, I think, is super important. And for that, you’ve really got to have more than your big toe dipped into the AI pool to understand what’s really happening.
Brooke Weddle: That really resonates. As you think about trends and the adoption of AI, how will that impact employee sentiment?
Svenja Gudell: I’ve had the really cool opportunity to go to Davos for the past two years. In 2024, generative AI was the talk of the town. Everyone was kind of fearful, on the side of both the employer—“How can I integrate this and make the most of it?”—and the employee—“Is my job going to go away?” This year had much more of a flavor of, particularly for agentic AI, “This will be a partner for you. You work alongside the tool to produce things.” And some of that is driven by the fact that generative AI still lacks some very important human traits like empathy, leadership, parts of communication.
So how do you marry those two? That is a really interesting path to go down: “Have employees taken that opportunity to be able to use the tool to their advantage?” We see this in the data; they’re slightly less afraid of it as they’ve learned more about it.
Lucia Rahilly: Thanks so much for joining us, Svenja.
Svenja Gudell: I very much enjoyed the conversation. Thank you.
| 2025-06-25T00:00:00 |
https://www.mckinsey.com/capabilities/people-and-organizational-performance/our-insights/what-the-labor-market-isnt-telling-you-yet
|
[
{
"date": "2025/06/25",
"position": 40,
"query": "AI labor market trends"
}
] |
|
Juniper Networks, Now Part of HPE – Leading the ...
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Juniper Networks, Now Part of HPE – Leading the Convergence of AI & Networking
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https://www.juniper.net
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[] |
Proven AI for your network. Mist, the AI-native networking platform makes every connection more reliable, measurable, and secure for businesses.
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Gartner Magic Quadrant for Enterprise Wired and Wireless LAN Infrastructure, Mike Leibovitz, Christian Canales, Nauman Raja, Tim Zimmerman 25 June 2025.
Gartner, Magic Quadrant for Data Center Switching, Andrew Lerner, Simon Richard, et al., 31 March 2025
Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, and MAGIC QUADRANT is a registered trademark of Gartner, Inc. and/or its affiliates and are used herein with permission. All rights reserved.
This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Juniper Networks.
| 2025-06-25T00:00:00 |
https://www.juniper.net/
|
[
{
"date": "2025/06/25",
"position": 90,
"query": "AI employers"
}
] |
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The End of Publishing as We Know It
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The End of Publishing as We Know It
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https://www.theatlantic.com
|
[
"Alex Reisner"
] |
... AI companies than blog and social-media posts. (Ziff Davis is suing OpenAI ... Investigative journalism that exposes corruption and malfeasance by ...
|
When tech companies first rolled out generative-AI products, some critics immediately feared a media collapse. Every bit of writing, imagery, and video became suspect. But for news publishers and journalists, another calamity was on the horizon.
Chatbots have proved adept at keeping users locked into conversations. They do so by answering every question, often through summarizing articles from news publishers. Suddenly, fewer people are traveling outside the generative-AI sites—a development that poses an existential threat to the media, and to the livelihood of journalists everywhere.
According to one comprehensive study, Google’s AI Overviews—a feature that summarizes web pages above the site’s usual search results—has already reduced traffic to outside websites by more than 34 percent. The CEO of DotDash Meredith, which publishes People, Better Homes & Gardens, and Food & Wine, recently said the company is preparing for a possible “Google Zero” scenario. Some have speculated that traffic drops resulting from chatbots were part of the reason outlets such as Business Insider and the Daily Dot have recently had layoffs. “Business Insider was built for an internet that doesn’t exist anymore,” one former staffer recently told the media reporter Oliver Darcy.
Not all publishers are at equal risk: Those that primarily rely on general-interest readers who come in from search engines and social media may be in worse shape than specialized publishers with dedicated subscribers. Yet no one is totally safe. Released in May 2024, AI Overviews joins ChatGPT, Claude, Grok, Perplexity, and other AI-powered products that, combined, have replaced search for more than 25 percent of Americans, according to one study. Companies train chatbots on huge amounts of stolen books and articles, as my previous reporting has shown, and scrape news articles to generate responses with up-to-date information. Large language models also train on copious materials in the public domain—but much of what is most useful to these models, particularly as users seek real-time information from chatbots, is news that exists behind a paywall. Publishers are creating the value, but AI companies are intercepting their audiences, subscription fees, and ad revenue.
Read: The unbelievable scale of AI’s pirated-books problem
I asked Anthropic, xAI, Perplexity, Google, and OpenAI about this problem. Anthropic and xAI did not respond. Perplexity did not directly comment on the issue. Google argued that it was sending “higher-quality” traffic to publisher websites, meaning that users purportedly spend more time on the sites once they click over, but declined to offer any data in support of this claim. OpenAI referred me to an article showing that ChatGPT is sending more traffic to websites overall than it did previously, but the raw numbers are fairly modest. The BBC, for example, reportedly received 118,000 visits from ChatGPT in April, but that’s practically nothing relative to the hundreds of millions of visitors it receives each month. The article also shows that traffic from ChatGPT has in fact declined for some publishers.
Over the past few months, I’ve spoken with several news publishers, all of whom see AI as a near-term existential threat to their business. Rich Caccappolo, the vice chair of media at the company that publishes the Daily Mail—the U.K.’s largest newspaper by circulation—told me that all publishers “can see that Overviews are going to unravel the traffic that they get from search, undermining a key foundational pillar of the digital-revenue model.” AI companies have claimed that chatbots will continue to send readers to news publishers, but have not cited evidence to support this claim. I asked Caccappolo if he thought AI-generated answers could put his company out of business. “That is absolutely the fear,” he told me. “And my concern is it’s not going to happen in three or five years—I joke it’s going to happen next Tuesday.”
Book publishers, especially those of nonfiction and textbooks, also told me they anticipate a massive decrease in sales, as chatbots can both summarize their books and give detailed explanations of their contents. Publishers have tried to fight back, but my conversations revealed how much the deck is stacked against them. The world is changing fast, perhaps irrevocably. The institutions that comprise our country’s free press are fighting for their survival.
Publishers have been responding in two ways. First: legal action. At least 12 lawsuits involving more than 20 publishers have been filed against AI companies. Their outcomes are far from certain, and the cases might be decided only after irreparable damage has been done.
The second response is to make deals with AI companies, allowing their products to summarize articles or train on editorial content. Some publishers, such as The Atlantic, are pursuing both strategies (the company has a corporate partnership with OpenAI and is suing Cohere). 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.
Read: ChatGPT turned into a Studio Ghibli machine. How is that legal?
Another issue is that different content appears to have different value for different LLMs. The digital-media company Ziff Davis has studied web-based AI training data sets and observed that content from “high-authority” sources, such as major newspapers and magazines, appears more desirable to AI companies than blog and social-media posts. (Ziff Davis is suing OpenAI for training on its articles without paying a licensing fee.) Researchers at Microsoft have also written publicly about “the importance of high-quality data” and have suggested that textbook-style content may be particularly desirable.
But beyond a few specific studies like these, there is little insight into what kind of content most improves an LLM, leaving a lot of unanswered questions. Are biographies more or less important than histories? Does high-quality fiction matter? Are old books worth anything? Amy Brand, the director and publisher of the MIT Press, told me that “a solution that promises to help determine the fair value of specific human-authored content within the active marketplace for LLM training data would be hugely beneficial.”
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. Because AI companies generally keep their training data a secret, and because there is no easy way for publishers to check which chatbots are summarizing their articles, publishers have difficulty figuring out which AI companies they might sue or try to strike a deal with. Some experts, such as Tim O’Reilly, have suggested that laws should require the disclosure of copyrighted training data, but no existing legislation requires companies to reveal specific authors or publishers that have been used for AI training material.
Of course, all of this raises a question. AI companies seem to have taken publishers’ content already. Why would they pay for it now, especially because some of these companies have argued in court that training LLMs on copyrighted books and articles is fair use?
Perhaps the deals are simply hedges against an unfavorable ruling in court. If AI companies are prevented from training on copyrighted work for free, then organizations that have existing deals with publishers might be ahead of their competition. Publisher deals are also a means of settling without litigation—which may be a more desirable path for publishers who are risk-averse or otherwise uncertain. But the legal scholar James Grimmelmann told me that AI companies could also respond to complaints like Ziff Davis’s by arguing that the deals involve more than training on a publisher’s content: They may also include access to cleaner versions of articles, ongoing access to a daily or real-time feed, or a release from liability for their chatbot’s plagiarism. Tech companies could argue that the money exchanged in these deals is exclusively for the nonlicensing elements, so they aren’t paying for training material. It’s worth noting that tech companies almost always refer to these deals as partnerships, not licensing deals, likely for this reason.
Regardless, the modest income from these arrangements is not going to save publishers: Even a good deal, one publisher told me, won’t come anywhere near recouping the revenue lost from decreased readership. Publishers that can figure out how to survive the generative-AI assault may need to invent different business models and find new streams of revenue. There may be viable strategies, but none of the publishers I spoke with has a clear idea of what they are.
Publishers have become accustomed to technological threats over the past two decades, perhaps most notably the loss of ad revenue to Facebook and Google, a company that was recently found to have an illegal monopoly in online advertising (though the company has said it will appeal the ruling). But the rise of generative AI may spell doom for the Fourth Estate: With AI, the tech industry even deprives publishers of an audience.
In the event of publisher mass extinction, some journalists will be able to endure. The so-called creator economy shows that it’s possible to provide high-quality news and information through Substack, YouTube, and even TikTok. But not all reporters can simply move to these platforms. Investigative journalism that exposes corruption and malfeasance by powerful people and companies comes with a serious risk of legal repercussions, and requires resources—such as time and money—that tend to be in short supply for freelancers.
If news publishers start going out of business, won’t AI companies suffer too? Their chatbots need access to journalism to answer questions about the world. Doesn’t the tech industry have an interest in the survival of newspapers and magazines?
In fact, there are signs that AI companies believe publishers are no longer needed. In December, at The New York Times’ DealBook Summit, OpenAI CEO Sam Altman was asked how writers should feel about their work being used for AI training. “I think we do need a new deal, standard, protocol, whatever you want to call it, for how creators are going to get rewarded.” He described an “opt-in” regime where an author could receive “micropayments” when their name, likeness, and style were used. But this could not be further from OpenAI’s current practice, in which products are already being used to imitate the styles of artists and writers, without compensation or even an effective opt-out.
Google CEO Sundar Pichai was also asked about writer compensation at the DealBook Summit. He suggested that a market solution would emerge, possibly one that wouldn’t involve publishers in the long run. This is typical. As in other industries they’ve “disrupted,” Silicon Valley moguls seem to perceive old, established institutions as middlemen to be removed for greater efficiency. Uber enticed drivers to work for it, crushed the traditional taxi industry, and now controls salaries, benefits, and workloads algorithmically. This has meant greater convenience for consumers, just as AI arguably does—but it has also proved ruinous for many people who were once able to earn a living wage from professional driving. Pichai seemed to envision a future that may have a similar consequence for journalists. “There’ll be a marketplace in the future, I think—there’ll be creators who will create for AI,” he said. “People will figure it out.”
| 2025-06-25T00:00:00 |
2025/06/25
|
https://www.theatlantic.com/technology/archive/2025/06/generative-ai-pirated-articles-books/683009/
|
[
{
"date": "2025/06/25",
"position": 28,
"query": "AI journalism"
},
{
"date": "2025/06/25",
"position": 14,
"query": "artificial intelligence journalism"
}
] |
Ethics & standards - journalismAI.com
|
Ethics & standards
|
https://journalismai.com
|
[] |
AI in the Newsroom. Ethics & Standards. Explainers. Trust. journalismAI.com is an independent database of developments in journalism ...
|
journalismAI.com is an independent database of developments in journalism and AI. All items are human-curated and summarized. The archive has 600+ stories dating from 2014.
Click on a subject above or use the search box in the masthead.
| 2025-06-25T00:00:00 |
https://journalismai.com/category/ethics/
|
[
{
"date": "2025/06/25",
"position": 59,
"query": "AI journalism"
}
] |
|
Journalism and AI: attitudes in the UK 2024
|
Journalism and AI: attitudes in the UK 2024
|
https://www.statista.com
|
[
"Amy Watson",
"Jun"
] |
Attitudes to how acceptable it would be for artificial intelligence to complete selected journalism tasks among adults in the United Kingdom as of January 2024.
|
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Press Gazette. (April 11, 2024). Attitudes to how acceptable it would be for artificial intelligence to complete selected journalism tasks among adults in the United Kingdom as of January 2024 [Graph]. In Statista . Retrieved July 15, 2025, from https://www.statista.com/statistics/1462596/journalism-tasks-completed-by-ai-uk-attitudes/
Press Gazette. "Attitudes to how acceptable it would be for artificial intelligence to complete selected journalism tasks among adults in the United Kingdom as of January 2024." Chart. April 11, 2024. Statista. Accessed July 15, 2025. https://www.statista.com/statistics/1462596/journalism-tasks-completed-by-ai-uk-attitudes/
Press Gazette. (2024). Attitudes to how acceptable it would be for artificial intelligence to complete selected journalism tasks among adults in the United Kingdom as of January 2024 . Statista . Statista Inc.. Accessed: July 15, 2025. https://www.statista.com/statistics/1462596/journalism-tasks-completed-by-ai-uk-attitudes/
Press Gazette. "Attitudes to How Acceptable It Would Be for Artificial Intelligence to Complete Selected Journalism Tasks among Adults in The United Kingdom as of January 2024." Statista , Statista Inc., 11 Apr 2024, https://www.statista.com/statistics/1462596/journalism-tasks-completed-by-ai-uk-attitudes/
Press Gazette, Attitudes to how acceptable it would be for artificial intelligence to complete selected journalism tasks among adults in the United Kingdom as of January 2024 Statista, https://www.statista.com/statistics/1462596/journalism-tasks-completed-by-ai-uk-attitudes/ (last visited July 15, 2025)
Attitudes to how acceptable it would be for artificial intelligence to complete selected journalism tasks among adults in the United Kingdom as of January 2024 [Graph], Press Gazette, April 11, 2024. [Online]. Available: https://www.statista.com/statistics/1462596/journalism-tasks-completed-by-ai-uk-attitudes/
| 2025-06-25T00:00:00 |
https://www.statista.com/statistics/1462596/journalism-tasks-completed-by-ai-uk-attitudes/
|
[
{
"date": "2025/06/25",
"position": 61,
"query": "AI journalism"
},
{
"date": "2025/06/25",
"position": 43,
"query": "artificial intelligence journalism"
}
] |
|
Webinar - Using AI to Help Reporters
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Using AI to Help Reporters
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https://www.inma.org
|
[
"Pepe Cerezo Gilarranz",
"Lucy Kueng",
"David Murphy",
"Jeff Elgie"
] |
How Hearst Newspapers and Polaris Media are using AI to help reporters find information, discover patterns in data, and brainstorm ideas is the focus of ...
|
Using AI to Help Reporters Presented by Tim O'Rourke, Vice President, Editorial Innovation and AI Strategy, Hearst Newspapers, and Rune Ytreberg, Head of iTromsø's Data Journalism Lab, Polaris Media Group
About this Webinar
How Hearst Newspapers and Polaris Media are using AI to help reporters find information, discover patterns in data, and brainstorm ideas is the focus of this INMA Generative AI Initiative Webinar.
We are pleased to welcome two leaders with remarkable stories to share as our guest speakers:
Tim O'Rourke, vice president of editorial innovation and AI strategy for Hearst Newspapers, where he leads the group's DevHub editorial engineering, visual and data storytelling, and AI+Automation teams;
Rune Ytreberg, who leads iTromsø's data journalism lab, where he has been developing AI-driven editorial solutions for 70 local newspapers within the Polaris Media Group since 2020.
The Webinar will be moderated by Sonali Verma, INMA's Generative AI Initiative Lead.
About Hearst Newspapers
Hearst Newspapers publishes 28 dailies and 50 weeklies and is home to famed brands such as The San Francisco Chronicle. Hearst Newspapers has more than 2,300 employees across the nation and is part of Hearst Corporation, one of the largest media, information and services companies in the United States.
About Polaris Media
Polaris Media owns 77 local and regional news brands, of which 60 are in Norway and 17 in Sweden, including Göteborgs-Posten. They reach over a million readers on digital platforms every day. It also has six printing houses and five distribution companies in Norway, as well as one distribution company in Sweden. The group's roots stretch back to 1767.
| 2025-06-25T00:00:00 |
https://www.inma.org/webinars/using-ai-to-help-reporters
|
[
{
"date": "2025/06/25",
"position": 69,
"query": "AI journalism"
}
] |
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