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Generative AI in HR for Workforce Transformation - Remunance
|
Generative AI in HR for Workforce Transformation
|
https://remunance.com
|
[
"Rajendra Vaidya"
] |
It covers hiring, onboarding, learning and development (L&D), and communication. It also compares AI-driven hiring with EOR services like ...
|
Organizations aim for operations that are smarter, leaner, and easier to scale. This shift is changing HR management in big ways. Generative AI isn’t just a theory anymore. It’s now essential for operations. This article covers how HR can use generative AI. We discuss its advanced use cases, strategic benefits, and ways to implement it.
Our goal is simple: to create a key resource for HR professionals. This will help them gain an edge in managing their workforce and talent strategy.
What Is Generative AI in HR?
Generative AI creates new content, insights, or solutions. It uses large machine learning models trained on vast datasets. In HR, it is used to automate document creation. It boosts employee engagement. It predicts workforce trends and tailors employee experiences.
Strategic Applications of Generative AI Across the HR Lifecycle
Recruitment and Talent Acquisition
We use generative AI to improve old recruitment methods. AI models generate job descriptions and run Boolean searches on their own.
Role-specific job postings with SEO-optimized keywords. Tailored screening questions based on required skills. Email communication templates for outreach, interview scheduling, and rejections.
A generative AI engine can quickly match candidate traits to job profiles. This cuts down hiring time and boosts talent quality.
Onboarding Automation
Generative AI improves onboarding. It creates support systems that adapt to users’ needs. These systems offer:
Virtual onboarding assistants that respond to FAQs. Personalized welcome kits based on department and role. Auto-generated compliance checklists and form-fill automation.
Impact: Organizations see a 25–40% drop in onboarding time. They also report a 15% boost in early-stage employee satisfaction.
Learning & Development
We use generative AI tools to create engaging learning experiences. These tools:
Analyze skill gaps and recommend custom L&D paths. Generate real-time feedback for learners. Change course content as the industry evolves.
Use Case: AI creates real-world decision scenarios in training. It helps you remember better and think critically.
Employee Experience and Communication
Internal communication powered by AI is personalized and consistent. Here’s how we enable that:
Auto-generation of announcements, newsletters, and surveys. Sentiment-aware messaging to improve tone and engagement. Customized messages based on demographics, preferences, and previous engagement patterns.
HR Data Analysis and Workforce Planning
With generative AI, we move from static reporting to predictive workforce analytics. The capabilities include:
Attrition forecasting based on historical data. Identification of high-potential employees using behavioral analytics. Salary benchmarking and performance distribution modeling.
This helps make choices based on data for promotions, restructuring, and hiring.
Policy Drafting and Compliance Management
Policies are no longer manually created in isolation. Our use of AI includes:
Drafting HR policies based on legal frameworks and best practices. Version control with dynamic updates. Automated creation of job contracts and non-disclosure agreements.
Performance Management
AI interprets performance reviews, gauges sentiment in feedback, and maps out growth trends.
Automated evaluation summaries. Personalized employee feedback suggestions. Bias-minimized performance reports.
Generative AI vs EOR – Understanding the Right Hiring Strategy for your Business
Not everything needs to be automated. Generative AI can draft job descriptions and screen profiles. However, it often misses the nuance needed for important hiring decisions.
AI can assist. But it can’t understand people the way people do. Building a team goes beyond resumes and job descriptions. It’s about finding the right fit for your company’s culture, goals, and future. Generative AI cannot negotiate local labor laws, solve compliance issues, or keep employees happy for the long term.
That’s exactly why Employer of Record (EOR) services like Remunance matter. We provide more than just algorithms. We offer expert-managed HR, legal compliance, payroll, and benefits administration in India. We help you scale fast while protecting your business from costly mistakes. With Remunance, you get real people managing real challenges, so you can hire globally with peace of mind.
| 2025-05-28T00:00:00 |
2025/05/28
|
https://remunance.com/blog/generative-ai-in-hr-for-workforce-transformation/
|
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AI healthcare booms as drug discovery and precision medicine take ...
|
AI healthcare booms as drug discovery and precision medicine take leaps forward
|
https://explodingtopics.com
|
[
"James Martin",
"Research Journalist"
] |
AI is playing an increasingly important role in drug discovery. It is helping to triage patients and personalize treatment plans.
|
AI is transforming the healthcare industry.
As the technology evolves, the number of use cases within the sector continues to grow. Artificial intelligence now has a presence at almost every stage of the healthcare cycle.
AI is playing an increasingly important role in drug discovery. It is helping to triage patients and personalize treatment plans. It even has a part to play in carrying out surgery.
In this article, I explore all of that. But I also look at the trust and accuracy barriers that still need to be overcome before AI in healthcare can be truly ubiquitous.
Efficient AI as a driver of healthcare profits
Just like in other industries, the future role of AI in healthcare is to simplify existing processes. A paper in the National Bureau of Economic Research estimates that wider adoption of AI in the US healthcare system could generate annual savings of $200 billion to $360 billion.
“Healthcare AI” searches are up 913% in the last 5 years.
Studies from the University of Oxford have found that no single healthcare occupation can be entirely automated — and that even in areas with high automation potential, automation desirability is often lower. Human contact remains a critical component of primary care.
Instead, AI is well-placed to significantly improve the efficiency of the jobs already being done by caregivers. Goldman Sachs estimates that 28% of work tasks performed by healthcare technicians and practitioners in the US could be automated.
And 92% of healthcare leaders believe automating repetitive tasks is crucial for addressing staff shortages.
As a result, the global healthcare automation market is projected to be worth $119.5 billion by 2033.
“Healthcare automation” searches are up 122% in the last 5 years.
Practitioners in critical care, internal medicine, neurology, and oncology spend an average of 18 hours a week on paperwork and administrative tasks. Using AI to automate some or all of that work would free up a significant amount of extra time to see more patients.
More than half of health leaders say their organizations have already implemented automation in clinical data entry, with a further 33% planning to do so within the next three years.
Among healthcare organizations that have already implemented generative AI in some capacity, more than half (54%) have already seen a meaningful return on investment.
And such is the rush to offer automation solutions to the industry, “healthcare AI” is now considered a hard keyword to rank for, requiring 268 high-authority referring domains and well-optimized content.
Build a winning strategy Get a complete view of your competitors to anticipate trends and lead your market Analyze
Microsoft’s healthcare automation play
Microsoft paid almost $20 billion in 2022 to acquire Nuance, an “ambient intelligence” platform for the healthcare sector. It has since been incorporated within Microsoft Cloud for Healthcare.
“Nuance AI” searches are up by 614% in the last 5 years.
In March, Microsoft released Dragon Copilot, an AI-powered voice dictation tool for healthcare professionals. It converts spoken summaries into specialty-specific notes, saving clinicians numerous hours.
Microsoft already has an extensive healthcare software suite. Its AI note-taking functionality therefore comes with the added advantage of integrating into a lot of medical organizations’ existing structures.
Last year, the majority of healthcare organizations said they considered Nuance when purchasing a clinical documentation solution.
And Microsoft is rolling out AI across its healthcare software, automating administrative tasks like patient scheduling.
Investment flows into healthcare AI
It isn’t just Microsoft betting big on healthcare AI.
Across all sectors, investors poured $56 billion into generative AI firms in 2023-24. In fact, AI startups claimed approximately 35% of all startup funding last year.
The healthcare sector has felt some of that benefit. Total venture investment in the industry grew by 17% in 2024, fueled by some big bets on healthcare AI.
In January 2025, Qventus raised a $105 million Series D round to develop “AI teammates” for medical personnel. Its technology seeks to reduce staff workloads through effective automation.
“Qventus” searches are up 90% in the last 5 years.
Through simplification and automation of scheduling, Qventus says it can utilize more than 50% of released operating room (OR) time blocks that may otherwise go unused. In total, it can unlock up to 9% more primetime OR capacity.
In March, Navina raised a $55 million Series C for its AI-enabled clinical intelligence platform aimed at primary care physicians. Goldman Sachs Alternatives led the round.
Innovaccer has also raised funds in 2025, completing a $275 million Series F. Its AI clears up patient data to harvest better insights, as well as saving clinicians “hours a day” by automating documentation.
In May, Rad AI brought its Series C round to $68 million. By automating the administration of follow-up care, its “Continuity” AI improves follow-up exam completion rates from 30% to over 75%.
AI unlocks precision medicine
While scheduling, note-taking and the less glamorous side of AI might have the most immediate impact on the bottom line for healthcare companies, there are also some exciting industry-specific applications of the technology that could ultimately change the landscape in more radical ways.
In particular, AI is already starting to unlock advances in precision medicine.
Searches for “precision medicine” are up 80% in the last 5 years.
Precision medicine involves treating patients based on their unique characteristics. While treatment plans have always been somewhat individualized, AI allows practitioners to be far more granular.
AI can process entire medical histories far more quickly and easily than a doctor or nurse. 97% of healthcare data currently goes unused, but digital transformation is beginning to harness this mine of information.
There’s the potential hurdle of what’s known as “healthcare interoperability”. This refers to the ability to access and share data between departments and organizations.
It’s a necessary step in using the full power of AI, but one which requires a certain amount of restructuring, as well as safeguards regarding patient privacy.
But in theory, AI can be used to quickly generate an extremely thorough patient profile. It can even draw from the “Internet of Medical Things” (IoMT), incorporating data from connected devices like smartwatches.
“IoMT” searches have risen by 91% in the last 5 years.
That data is only becoming more comprehensive as consumer tech companies embrace AI too. Apple is planning to add an AI coach to its Health app in 2026, clearly believing that it already collects enough health information to provide meaningful medical insights.
Apple’s AI can already help to detect falls, sense irregular heartbeats, and conduct sleep analysis, among other things.
Digital twins
Using all this data, AI can help to create a “digital twin” of a patient. This is a virtual recreation of the physical consumer.
Digital twins are highly useful for running simulations and calculating optimal treatment paths. For instance, they can help to ascertain ideal dosages and timing of medicines.
Healthcare digital twin” searches are still low, but are trending upward over the long term.
At Johns Hopkins, digital twins of patient hearts are being used to predict arrhythmias and adjust treatment accordingly. Simulated electrical waves are sent through the digital twin, allowing practitioners to see if they interact unusually with any scarring or damage — which can then be removed in real life.
These advances produce better medical outcomes. But they can also help to strengthen the trust between patients and healthcare providers.
The Deloitte 2025 US Healthcare Outlook study found that 43% of consumers are now using connected monitoring devices. If this data is taken on board and used to help devise a treatment plan, patients will feel as though they have been heard.
That’s a major challenge for the industry. In another study, 46% of patients reported “never or rarely” being asked for self-assessments of their conditions, which one participant described as “degrading and dehumanizing”.
AI transforms drug trials
Digital twins can be used in another medical context to radically change the process of drug trials. With AI helping to create a significant body of digital patient replicas, there’s a strong case for running simulations of new medicines on these virtual counterparts.
Most obviously, this removes the risks of adverse effects encountered in physical drug trials. But it also speeds up the process by orders of magnitude, with the timeline from initial discovery to full approval currently often 10 years or more.
One study placed the average drug approval pipeline at approximately 15 years.
Additionally, in classic trials, a drug could fail because the average patient response falls short of the trial’s target. By using digital twins, it is easier to isolate groups of patients where a drug is working particularly well, providing alternative routes to commercial and medical viability.
Drug companies are still testing on humans in the latter stages of development, and that’s unlikely to change any time soon. But Sanofi is using digital twins to effectively “skip” from a Phase 1 study to a Phase 2b study, with virtual patients used to establish optimal dosage.
AI drug discovery
Even before reaching the trial stage, AI has a massive role to play in drug development.
“AI drug discovery” searches are up 609% in the last 5 years.
AI can drastically enhance the drug discovery process. Trained on a vast array of relevant data, machine learning models can predict at a far earlier point which medicines are worth taking to the trial stage.
As well as acting as an early filter, ever-more advanced AI can also pose entirely novel drug suggestions.
Last year, 46 “AI-discovered” drugs reached phase 2 and 3 clinical trials. In total, at least 75 “AI-discovered molecules” have entered clinical trials.
Google DeepMind and Isomorphic Labs have collaborated on AlphaFold 3. Drawing on a vast protein data bank, the AI model can accurately predict how combinations of these substances will interact on a molecular level.
AlphaFold 3 correctly predicted the true structure of a cold virus spike protein interacting with antibodies and simple sugars.
Isomorphic Labs is itself a drug discovery startup. And they and Google have since partnered with other pharmaceutical companies to make the AlphaFold 3 model available in drug development.
Deals with Eli Lilly and Novartis could be worth up to $2.9 billion, depending on the achievement of future milestones.
Using their own AI models, Insilico Medicine has taken a treatment for idiopathic pulmonary fibrosis to clinical trials within 18 months. The process would usually be expected to take 4 years.
Patient-Facing AI
AI is clearly already having a real impact on healthcare behind the scenes. But will patient-facing artificial intelligence ever become the norm?
AI doctors
There is already a vast array of “AI doctors” online.
“AI doctor” searches are up 1125% in the last 5 years
In one study, ChatGPT-4 scored an average of 90% when trying to diagnose a condition from a case report. Doctors acting alone scored 74%, while doctors aided by AI scored 76%.
Remarkably, another recent study even found that patients rated AI far higher than human doctors in terms of the empathy of their responses. ChatGPT was rated “empathetic” or “very empathetic” 45% of the time, compared to just 4.6% for physicians.
Even so, it seems unlikely that AI will be used this way in a clinical, institutional setting any time soon.
But Akido is using AI to tackle the shortage of human doctors.
“Akido” searches are up by 38% in the last year.
The startup says that the US population requires 3 billion doctor visits per year, with only 825 million currently available. It calls the physician shortage the single biggest challenge facing healthcare systems worldwide.
In May 2025, it raised a $60 million Series B round to develop ScopeAI as a solution to this problem.
ScopeAI visits are overseen by trained Medical Assistants, not doctors. The AI generates a preliminary diagnosis and treatment plan.
Akido says that its AI-guided healthcare visits have delivered a 5x increase in face-to-face time with patients.
AI robotic surgery
When discussing front-line medical automation, robotic surgery is never too far from the conversation. AI is impacting the landscape here as well.
“AI robotic surgery” searches are trending upward.
The “traditional” concept of robotic surgery is better referred to as robot-assisted surgery, with trained human surgeons guiding robotic arms to complete operations with greater precision. But what if the robotic equipment came equipped with AI?
Believe it or not, that is a question being asked in medical circles. A Johns Hopkins and Stanford University study trained a robot on hours of videos of skilled surgeons, after which it was able to execute the same surgical procedures with equal skill levels.
A senior author on the paper described it as a “significant step forward toward a new frontier in medical robotics”.
Robots are already used in one form or another in 4 million surgeries per year. The human role may well trend gradually from control to oversight.
As with the idea of AI primary care physicians, however, AI robotic surgery would need to become both more trustworthy and more trusted before becoming genuinely commonplace.
The need for trust
We’ve seen how AI can actually be a driver of trust when used to pursue more personalized, patient-driven precision medicine. But at least for now, the US public does not trust AI to play a front-and-center role in a healthcare setting.
According to one Deloitte study, 30% of consumers do not trust information provided by generative AI. 80% would want to be informed if a doctor was using AI in the medical decision-making process.
And the Deloitte Healthcare Outlook report was clear about the crisis of trust facing the healthcare industry. It’s an even higher priority for industry leaders than consumer affordability challenges.
Before AI can be widely used in any kind of patient-facing setting, healthcare bodies therefore need to ensure they have very robust AI governance frameworks.
Searches for “AI governance framework” are up 8900% in the last 5 years.
An AI governance framework sets parameters for how AI will be developed and deployed within an organization. This is of vital importance in the medical profession, where there are questions of accountability to consider in the event of an AI misdiagnosis.
The World Health Organization has officially called for caution in the deployment of AI technology. It cites a list of concerns, including:
The potential for bias in training data
The risk of using private patient data to train LLMs
The danger of convincing but medically inaccurate AI responses
The need for accuracy
Clearly, the need for accuracy in a medical setting is paramount. And while AI has beaten doctors in certain studies, models like ChatGPT currently remain susceptible to “hallucinating” plausible-looking but inaccurate information.
“AI hallucination” searches are up 203% in the last 2 years.
Human doctors might make a misdiagnosis. But these hallucinations introduce an entirely new class of potential error into the diagnostic process.
A National Institutes of Health study found that even when an AI model made the right final choice, it would often incorrectly describe medical images and give flawed reasoning behind a diagnosis. When allowed to consult external resources, physicians also diagnosed more accurately than the AI, especially on questions ranked most difficult.
AI needs to be more reliably accurate before it can be used on the front line in this manner. And perhaps even more critically, consumer trust in the technology’s accuracy needs to be built before such use cases are viable.
“Low-grade” clinical decisions
There are some clinical decisions AI can already make in its current form. In particular, the technology is proving useful in decisions one step removed from diagnostics.
A study at the University of California found that ChatGPT successfully identified the more urgent case in 88% of triage scenarios. Physicians made the right call 86% of the time.
The study noted that more tests would be needed before AI could be deployed responsibly in this manner in an emergency department setting. But across the healthcare industry as a whole, there is a definite movement toward automation of task prioritization.
36% of healthcare leaders have already implemented automation for the prioritization of clinical workflows. 41% plan to do so in the next three years, making it the largest single area of planned healthcare automation.
AIDOC has rolled out AI triaging software in over 1000 medical centers, including 7 of the 10 top-ranked US hospitals. Its software analyzes 3 million patients every month.
AIDOC’s AI triaging is already in use worldwide.
Away from triage settings, AI is already being used extensively to help analyze medical scans.
Of the 950 AI-enabled medical devices approved by the FDA, over 700 relate to radiology.
“AI radiology” searches are up 536% in the last 5 years.
Spectral AI is among the organizations working to apply AI to medical imaging. It specializes in scanning wounds.
Its DeepView technology predicts how wounds will heal, using scan information not visible to the human eye. Doctors can then use that information to inform treatment plans.
“Spectral AI” searches have grown 6700% in the last 5 years.
Spectral has received more than $7 million in US government funding.
Healthcare AI cybersecurity concerns
As in all areas of AI, advances in the medical sector are happening quickly. But it’s imperative that the security keeps up with the technology, especially in an area like healthcare.
Hundreds of millions of medical records are held on file in data centers across the US. In an ideal world, AI would play an important role in sifting through them and surfacing the insights needed to provide the best possible care for each patient.
But that data is highly sensitive, and highly vulnerable. Last year, a hack on Change Healthcare exposed the data of 190 million patients.
Since 2009, protected health information of almost 850 million patients has been exposed through data breaches.
It’s therefore unsurprising that more than 50% of healthcare decision-makers cite security concerns as the biggest roadblock to scaling the implementation of AI.
“AI cybersecurity” searches are up 1950% in 5 years.
Moreover, 72% of healthcare organizations are concerned about the security threats posed by advancements in AI. In particular, connected smart devices are considered easy access points for hackers.
This is a hurdle that needs to be overcome before AI can have a truly transformative effect on the healthcare industry.
Healthcare leaders must invest in AI to drive growth
AI is here to stay, and its use cases will only increase as the technology becomes more sophisticated. In terms of immediate applications, there’s a vast amount of administrative automation still to be done, and the healthcare industry is no exception.
As for specifically medical applications of AI, there are areas where the healthcare industry can already make use of the technology, notably in precision medicine, drug discovery, triage, and medical imaging.
And perhaps most importantly of all, the healthcare industry must work to build trust with patients. The growing use of AI within the sector makes this even more vital, and even more challenging — but when used responsibly, the technology can help to reinforce trust rather than undermine it.
| 2024-12-24T00:00:00 |
2024/12/24
|
https://explodingtopics.com/blog/healthcare-ai
|
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The Intersection of Artificial Intelligence and Employment Law
|
The Intersection of Artificial Intelligence and Employment Law
|
https://ogletree.com
|
[] |
AI-driven workforce decisions are covered by a variety of employment laws, and employers are facing an increasing number of agency investigations and lawsuits.
|
Quick Hits
Using automated technology to make workforce decisions presents significant legal risks under existing anti-discrimination laws, such as Title VII, the ADEA, and the ADA, because bias in algorithms can lead to allegations of discrimination.
Algorithmic HR software is uniquely risky because, unlike human judgment, it amplifies the scale of potential harm. A single biased algorithm can impact thousands of candidates or employees, exponentially increasing the liability risk compared to biased individual human decisions.
Proactive, privileged software audits are critical for mitigating legal risks and monitoring the effectiveness of AI in making workforce decisions.
What Are Automated Technology Tools and How Does AI Relate?
In the employment context, algorithmic or automated HR tools refer to software systems that utilize predefined rules to run data through algorithms to assist with various human resources functions. These tools can range from simple rule-based formula systems to more advanced generative AI-powered technologies. Unlike traditional algorithms, which operate based on fixed, explicit instructions to process data and make decisions, generative AI systems differ in that they can learn from data, adapt over time, and make autonomous adjustments without being limited to predefined rules.
Employers use these tools in numerous ways to automate and enhance HR functions. A few examples:
Applicant Tracking Systems (ATS) often use algorithms to score applicants compared to the position description or rank resumes by comparing the skills of the applicants to one another.
Skills-based search engines rely on algorithms to match job seekers with open positions based on their qualifications, experience, and keywords in their resumes.
AI-powered interview platforms assess candidate responses in video interviews, evaluating facial expressions, tone, and language to predict things like skills, fit, or likelihood of success.
Automated performance evaluation systems can analyze employee data such as productivity metrics and feedback to provide ratings of individual performance.
AI systems can listen in on phone calls to score employee and customer interactions, a feature often used in the customer service and sales industries.
AI systems can analyze background check information as part of the hiring process.
Automated technology can be incorporated into compensation processes to predict salaries, assess market fairness, or evaluate pay equity.
Automated systems can be utilized by employers or candidates in the hiring process for scheduling, note-taking, or other logistics.
AI models can analyze historical hiring and employee data to predict which candidates are most likely to succeed in a role or which new hires may be at risk of early turnover.
AI Liability Risks Under Current Laws
AI-driven workforce decisions are covered by a variety of employment laws, and employers are facing an increasing number of agency investigations and lawsuits related to their use of AI in employment. Some of the key legal frameworks include:
Title VII: Title VII prohibits discrimination on the basis of race, color, religion, sex, or national origin in employment practices. Under Title VII, employers can be held liable for facially neutral practices that have a disproportionate, adverse impact on members of a protected class. This includes decisions made by AI systems. Even if an AI system is designed to be neutral, if it has a discriminatory effect on a protected class, an employer can be held liable under the disparate impact theory. While the current administration has directed federal agencies to deprioritize disparate impact theory, it is still a viable legal theory under federal, state, and local anti-discrimination laws. Where AI systems are providing an assessment that is utilized as one of many factors by human decision-makers, they can also contribute to disparate treatment discrimination risks.
The ADA: If AI systems screen out individuals with disabilities, they may violate the Americans with Disabilities Act (ADA). It is also critical that AI-based systems are accessible and that employers provide reasonable accommodations as appropriate to avoid discrimination against individuals with disabilities.
The ADEA: The Age Discrimination in Employment Act (ADEA) prohibits discrimination against applicants and employees ages forty or older.
The Equal Pay Act: AI tools that factor in compensation and salary data can be prone to replicating past pay disparities. Employers using AI must ensure that their systems are not creating or perpetuating sex-based pay inequities, or they risk violating the Equal Pay Act.
The EU AI Act:This comprehensive legislation is designed to ensure the safe and ethical use of artificial intelligence across the European Union. It treats employers’ use of AI in the workplace as potentially high-risk and imposes obligations for continued use, as well as potential penalties for violations.
State and Local Laws: There is no federal AI legislation yet, but a number of states and localities have passed or proposed AI legislation and regulations, covering topics like video interviews, facial recognition software, bias audits of automated employment decision-making tools (AEDTs), and robust notice and disclosure requirements. While the Trump administration has reversed Biden-era guidance on AI and is emphasizing the need for minimal barriers to foster AI innovation, states may step in to fill the regulatory gap. In addition, existing state and local anti-discrimination laws also create liability risk for employers.
Data Privacy Laws: AI also implicates a number of other types of laws, including international, state, and local laws governing data privacy, which creates another potential risk area for employers.
The Challenge of Algorithmic Transparency and Accountability
One of the most significant challenges with the use of AI in workforce decisions is the lack of transparency in how algorithms make decisions. Unlike human decision-makers who can explain their reasoning, generative AI systems operate as “black boxes,” making it difficult, if not impossible, for employers to understand—or defend—how decisions are reached.
This opacity creates significant legal risks. Without a clear understanding of how an algorithm reaches its conclusions, it may be difficult to defend against discrimination claims. If a company cannot provide a clear rationale for why an AI system made a particular decision, it could face regulatory action or legal liability.
Algorithmic systems generally apply the same formula against all candidates, creating relative consistency in the comparisons. For generative AI systems, there is greater complexity because the judgments and standards change over time as the system absorbs more information. As a result, the decision-making applied to one candidate or employee will vary from the decisions made at a different point in time.
Mitigating the Legal Risks: AI Audits, Workforce Analytics, and Bias Detection
While the potential legal risks are significant, there are proactive steps employers may want to take to mitigate exposure to algorithmic bias and discrimination claims. These steps include:
Ensuring that there is a robust policy governing AI use and related issues, like transparency, nondiscrimination, and data privacy
Doing due diligence to vet AI vendors, and not utilizing any AI tools without a thorough understanding of their intended purpose and impact
Training HR, talent acquisition, and managers on the appropriate use of AI tools
Continuing to have human oversight over ultimate workforce decisions so that AI is not the decisionmaker
Ensuring compliance with all applicant and employee notice and disclosure requirements, as well as bias audit requirements
Providing reasonable accommodations
Regularly monitoring AI tools through privileged workforce analytics to ensure there is no disparate impact against any protected groups
Creating an ongoing monitoring program to ensure human oversight of impact, privacy, legal risks, etc.
Implementing routine and ongoing audits under legal privilege is one of the most critical steps to ensuring AI is being used in a legally defensible way. These audits may include monitoring algorithms for disparate impacts on protected groups. If a hiring algorithm disproportionately screens out individuals in a protected group, employers may want to take steps to correct these biases before they lead to discrimination charges or lawsuits. Given the risks associated with volume, and to ensure corrective action as quickly as possible, companies may want to undertake these privileged audits on a routine (monthly, quarterly, etc.) basis.
The AI landscape is rapidly evolving, so employers may want to continue to track changing laws and regulations in order to implement policies and procedures to ensure the safe, compliant, and nondiscriminatory use of AI in their workplace, and to reduce risk by engaging in privileged, proactive analyses to evaluate AI tools for bias.
Ogletree Deakins’ Technology Practice Group and Workforce Analytics and Compliance Practice Group will continue to monitor developments and will provide updates on the Employment Law, Technology, and Workforce Analytics and Compliance blogs as additional information becomes available.
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| 2025-06-17T00:00:00 |
https://ogletree.com/insights-resources/blog-posts/the-intersection-of-artificial-intelligence-and-employment-law/
|
[
{
"date": "2025/06/17",
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},
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},
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},
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},
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},
{
"date": "2025/06/17",
"position": 1,
"query": "artificial intelligence employers"
},
{
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"position": 1,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/17",
"position": 12,
"query": "artificial intelligence labor union"
}
] |
|
Amazon boss says AI will replace jobs at tech giant - BBC
|
Amazon boss says AI will replace jobs at tech giant
|
https://www.bbc.com
|
[] |
Amazon boss Andy Jassy has told staff to embrace artificial intelligence (AI) and warned the technology will lead to a smaller corporate ...
|
Amazon boss says AI will replace jobs at tech giant
17 June 2025 Share Save Natalie Sherman Business reporter, BBC News Share Save
Getty Images
Amazon boss Andy Jassy has told staff to embrace artificial intelligence (AI) and warned the technology will lead to a smaller corporate workforce in the next few years. He shared the prediction in a memo to staff on Tuesday, which urged employees to "be curious about AI". The tech giant is the latest firm to set out its plans for using AI amid concerns the technology will lead to rapid job losses across the world. Mr Jassy said he expected AI to lead to "efficiency gains" that would allow the firm to reduce its corporate workforce.
"We will need fewer people doing some of the jobs that are being done today, and more people doing other types of jobs," he wrote. "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."
Companies, especially in the tech sector, have been investing heavily in AI in recent years, spurred on by technological advances that have made it easier than ever for chatbots to create code, images and text with limited instruction. But as the new tools gain traction, they have sparked warnings from some tech leaders of job losses, especially in entry-level office roles. Dario Amodei, chief executive of AI-firm Anthropic, told news website Axios last month that the technology could wipe out half of entry-level white collar jobs. Geoffrey Hinton, whose work on AI, including at Google, has earned him the moniker "Godfather of AI", echoed those warnings on a recent podcast. "This is a very different kind of technology," he said, pushing back against arguments that job losses from AI will be outweighed as the technology creates new kinds of positions, in a pattern seen with earlier technological leaps. "If it can do all mundane human intellectual labor, then what new jobs is it going to create? You'd have to be very skilled to have a job that it couldn't just do." Amazon directly employed more than 1.5 million people around the world at the end of last year. The majority of those staff are in the US, where it ranks as the country's second-largest employer after Walmart. While many staff the firm's e-commerce warehouses, about 350,000 people also serve the company in office roles.
Amazon using AI in 'every corner of company'
| 2025-06-17T00:00:00 |
https://www.bbc.com/news/articles/cn0q2v851k9o
|
[
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}
] |
|
Nvidia's Jensen Huang clashes with Anthropic CEO over AI Job loss ...
|
Nvidia’s Jensen Huang clashes with Anthropic CEO over AI Job loss predictions
|
https://dig.watch
|
[] |
At the same time, Amodei has consistently warned that the economic fallout could be severe, rejecting universal basic income as a long-term ...
|
17 Jun 2025
Nvidia’s Jensen Huang clashes with Anthropic CEO over AI Job loss predictions
A fresh dispute has erupted between Nvidia and Anthropic after CEO Dario Amodei warned that AI could eliminate 50% of entry-level white-collar jobs in the next five years, potentially causing a 20% unemployment spike.
Nvidia’s Jensen Huang dismissed the claim, saying at VivaTech in Paris that he ‘pretty much disagreed with almost everything’ Amodei says, accusing him of fearmongering and advocating for a monopoly on AI development.
Huang emphasized the importance of open, transparent development, stating, ‘If you want things to be done safely and responsibly, you do it in the open… Don’t do it in a dark room and tell me it’s safe.’
Anthropic pushed back, saying Amodei supports national AI transparency standards and never claimed only Anthropic can build safe AI.
The clash comes amid growing scrutiny of Anthropic, which faces a lawsuit from Reddit for allegedly scraping content without consent and controversy over a Claude 4 Opus test that simulated blackmail scenarios.
The companies have also clashed over AI export controls to China, with Anthropic urging tighter rules and Nvidia denying reports that its chips were smuggled using extreme methods like fake pregnancies or shipments with live lobsters.
Huang maintains an optimistic outlook, saying AI will create new jobs in fields like prompt engineering. At the same time, Amodei has consistently warned that the economic fallout could be severe, rejecting universal basic income as a long-term solution.
Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!
| 2025-06-17T00:00:00 |
2025/06/17
|
https://dig.watch/updates/nvidias-jensen-huang-clashes-with-anthropic-ceo-over-ai-job-loss-predictions
|
[
{
"date": "2025/06/17",
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"query": "universal basic income AI"
},
{
"date": "2025/06/17",
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}
] |
Employees were already freaked out about AI — Amazon just ...
|
Employees were already freaked out about AI — Amazon just proved them right
|
https://www.businessinsider.com
|
[
"Katherine Tangalakis-Lippert",
"Tim Paradis"
] |
Layoffs and hiring ... Of course, not all the jobs affected by advancements in AI will mean the workers filling them will be laid off.
|
Many workers are increasingly concerned about job security, and on Tuesday, Amazon's CEO, Andy Jassy, acknowledged they're right to worry.
Many workers are increasingly concerned about job security, and on Tuesday, Amazon's CEO, Andy Jassy, acknowledged they're right to worry. Peter Dazeley/Getty Images
Many workers are increasingly concerned about job security, and on Tuesday, Amazon's CEO, Andy Jassy, acknowledged they're right to worry. Peter Dazeley/Getty Images
This story is available exclusively to Business Insider subscribers. Become an Insider and start reading now.
The once-hypothetical cuts are coming, whether employees are ready or not.
On Tuesday, Amazon's CEO, Andy Jassy, confirmed the fears of many workers in the age of artificial intelligence: He said he expects the technology will lead to job cuts at the tech giant.
In his memo, which was posted online, Jassy did not announce immediate layoffs. He said that, in the next few years, "efficiency gains" from AI would translate to a smaller corporate workforce.
Marlo Lyons, a certified executive coach, told Business Insider that jobs will inevitably change — including outright disappearances. "So is your job at risk? Absolutely. If you don't get on board with AI, yes, absolutely, you're going to lose your job."
Amazon is now one of the largest companies to explicitly state that AI will impact its employees' jobs.
It's not all outright layoffs — at least not yet
BI previously reported that roles that include tasks that AI can perform are disappearing from job boards faster than positions that have fewer tasks that AI can accomplish.
Shopify's CEO said in April that, before hiring anyone new, employees must prove AI can't do the job better. Duolingo plans to phase out contractors and replace them with AI. And Salesforce's CEO, Marc Benioff, has said that the company might not hire engineers in 2025 because those already on the payroll are getting so much more done thanks to AI tools.
The industry you're in matters. Office workers appear to be particularly at risk. In late May, Anthropic's CEO, Dario Amodei, suggested AI could wipe out half of all entry-level white-collar jobs . Klarna's CEO, Sebastian Siemiatkowski, said earlier this month that he expects the impact of AI on white-collar jobs to be so significant that it will lead to a recession .
Christian Schneider, the CEO of New York-based startup fileAI, told BI that he's already seeing job losses in corners of the tech industry, and he expects AI to exacerbate the trend.
"I'm totally expecting a tightening," he said. "I think when we look into tech layoffs, it's so apparent that something is changing."
Related stories Business Insider tells the innovative stories you want to know Business Insider tells the innovative stories you want to know
Melissa Swift, the founder and CEO of work consultancy Anthrome Insight, told BI that productivity hasn't always increased to the same degree as tech advances. It often "ticks up slowly, like a kiddie roller coaster going up the first big hill."
Those who aren't keeping up risk being left behind. And refusing to acknowledge the risk doesn't make it go away, Lyons said.
"So if you're redesigning the workplace, and how things are getting done — whether it's a workflow or structures of teams, or the same thing with AI — you can hold on with white knuckles, but it's still going to happen around you," Lyons said.
Of course, not all the jobs affected by advancements in AI will mean the workers filling them will be laid off. Jassy acknowledged in his statement that Amazon will "need fewer people doing some of the jobs that are being done today, and more people doing other types of jobs."
Schneider said some jobs will change so that typical back-office, rote tasks will fall to AI and allow more workers to take on people-facing roles. Or, officegoers once responsible for pulling and preparing data might now move to the end of the process to, for example, check the quality of the results AI produces.
While some jobs will disappear and others will evolve, Schneider said, workers are often good at adapting.
"Honestly, I wouldn't want to underestimate people's drive," he said.
| 2025-06-17T00:00:00 |
https://www.businessinsider.com/amazon-announcement-proof-workers-rightly-worry-about-ai-layoffs-2025-6
|
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{
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}
] |
|
Amazon CEO: AI Will Lead to Layoffs, 'Change the Way Our Work Is ...
|
Amazon CEO Says AI Will Reduce Number of Corporate Jobs and ‘Change the Way Our Work Is Done’
|
https://variety.com
|
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Amazon CEO Andy Jassy told employees generative AI will change the way they work and will lead to a lower number of workers overall.
|
Amazon chief executive officer Andy Jassy outlined a near future where AI will “make our jobs even more exciting and fun than they are today” — but at the same time, he said, the technology will cut the overall number of jobs at the ecommerce giant.
In a memo Tuesday to Amazon employees, Jassy shared “Some thoughts on Generative AI.”
“As we roll out more Generative AI and agents, it should change the way our work is done,” the CEO said. “We will need fewer people doing some of the jobs that are being done today, and more people doing other types of jobs. 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.”
According to an Amazon spokesperson, Jassy’s reference to a reduction in workforce does not necessarily mean layoffs; for example, the company could offer voluntary early retirement packages.
Popular on Variety
As of the end of March, Amazon reported 1.56 million employees, up 3% from a year earlier. Jassy encouraged Amazon employees to “be curious about AI” and “educate yourself.”
“As we go through this transformation together, be curious about AI, educate yourself, attend workshops and take trainings, use and experiment with AI whenever you can, participate in your team’s brainstorms to figure out how to invent for our customers more quickly and expansively, and how to get more done with scrappier teams,” Jassy wrote.
Nine months ago, Jassy informed Amazon’s corporate staffers they were expected to report to the office five days per week, so the company will be “better set up to invent, collaborate, and be connected enough to each other and our culture to deliver the absolute best for customers and the business.”
Today, Amazon is investing “quite expansively” in generative AI, according to Jassy’s June 17 memo. The company has more than 1,000 generative AI services and applications in progress or built to date, “but at our scale, that’s a small fraction of what we will ultimately build,” the CEO said.
“There’s so much more to come with Generative AI. I’m energized by our progress, excited about our plans ahead, and looking forward to partnering with you all as we change what’s possible for our customers, partners, and how we work,” Jassy wrote.
Jassy took over the role of Amazon’s CEO in July 2021 from founder Jeff Bezos, who is now executive chairman. After joining the company in 1997, Jassy started the Amazon Web Services group and led it for nearly 20 years.
| 2025-06-17T00:00:00 |
2025/06/17
|
https://variety.com/2025/digital/news/amazon-ceo-ai-employee-layoffs-change-work-memo-1236434424/
|
[
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"query": "AI layoffs"
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{
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}
] |
Amazon CEO Andy Jassy admits AI will 'reduce' corporate workforce
|
Amazon CEO Andy Jassy admits AI will ‘reduce’ corporate workforce
|
https://nypost.com
|
[] |
Amodei said he expects significant job losses in the next one to five years, with US unemployment potentially spiking to 20%, up from its ...
|
Amazon CEO Andy Jassy ominously warned Tuesday that he expects the rise of generative artificial intelligence to “reduce” the company’s corporate workforce in the next few years.
The Amazon boss, who replaced Jeff Bezos as CEO in 2021, said generative AI is a “once in a lifetime” technology that “should change the way our work is done” as the company integrates it into its business operations.
As a result, Amazon 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 lengthy memo to employees that was also posted on the company’s website.
3 Amazon CEO Andy Jassy outlined his thoughts on AI in a memo to employees. REUTERS
“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 added.
Amazon had a corporate workforce of approximately 350,000 employees as December. Overall, the company had more than 1.5 million full-time and part-time employees at the end of last year, including at its warehouse and fulfillment centers.
Jassy said Amazon already has more than 1,000 generative AI services or applications in the works, which will “small fraction of what we will ultimately build.”
Amazon’s inventory management, customer service chatbot and product pages are likely to get an upgrade as a result of AI.
3 Amazon CEO Andy Jassy replaced Jeff Bezos in 2021. REUTERS
Employees should “be curious about AI” and participate in efforts to learn “how to get more done with scrappier teams,” he added.
The remarks come as more AI leaders call out the likelihood that advancements in AI will shake up the labor market.
Last month, Anthropic CEO Dario Amodei raised alarms when he warned that executives and politicians should stop “sugar-coating” the mass layoffs that could occur in fields like tech, finance and law and be honest with workers.
Amodei said he expects significant job losses in the next one to five years, with US unemployment potentially spiking to 20%, up from its current level of 4.2%.
3 A growing number of AI executives have warned that the technology will shake up the job market. jaykoppelman – stock.adobe.com
In a dire scenario, AI could wipe out half of all entry-level white collar jobs, he suggested.
Amazon isn’t the only company likely to experience a major workforce shakeup as a result of generative AI.
Meta’s Mark Zuckerberg recently said he expects AI to take on a bigger role within Meta’s workforce.
“Probably in 2025, we at Meta, as well as the other companies that are basically working on this, are going to have an AI that can effectively be a sort of mid-level engineer that you have at your company that can write code,” Zuckerberg said during an appearance on “The Joe Rogan Experience” podcast.
Elsewhere, Google CEO Sundar Pichai warned in April 2023 that he expected “knowledge workers,” such as writers, accountants, architects and software engineers, to be at risk.
| 2025-06-17T00:00:00 |
2025/06/17
|
https://nypost.com/2025/06/17/business/amazon-ceo-andy-jassy-admits-ai-will-reduce-corporate-workforce/
|
[
{
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"position": 95,
"query": "AI job losses"
},
{
"date": "2025/06/17",
"position": 96,
"query": "AI job losses"
}
] |
Amazon CEO says AI agents will soon reduce company's corporate ...
|
Amazon CEO says AI agents will soon reduce company's corporate workforce
|
https://www.cbsnews.com
|
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"Reporter",
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In the Tuesday memo, Jassy sketched out a future in which AI agents are used to conduct tedious tasks, freeing up human workers to take on more ...
|
Amazon's CEO envisions an "agentic future" in which AI robots, or agents, replace humans working in the company's offices.
In a memo to employees made public by Amazon on Tuesday, CEO Andy Jassy said he expects the company to reduce its corporate workforce in as soon as the next few years, as it leans more heavily on generative AI tools to help fulfill workplace duties.
"As we roll out more generative AI and agents, it should change the way our work is done," Jassy stated. "We will need fewer people doing some of the jobs that are being done today, and more people doing other types of jobs."
Jassy added that this move toward AI would eventually "reduce our total corporate workforce as we get efficiency gains from using AI extensively across the company." With approximately 1.5 million employees worldwide, the e-commerce giant is the second largest private employer in the United States.
Reached for comment, an Amazon spokesperson deferred to the original memo.
Amazon shares dipped slightly on Tuesday, down 0.4% as of 3:45 p.m. EST.
Amazon investing "quite expansively" in AI
Amazon is "investing quite expansively" in generative AI technology, according to Jassy, adding that "the progress we are making is evident."
"Many of these agents have yet to be built, but make no mistake, they're coming, and coming fast," the CEO stated in the memo.
Amazon ramped up its participation in the generative AI arms race with the release of the Amazon Echo smart speaker in 2014, its first product to include its virtual assistant Alexa. This February, the company announced it was unveiling Alexa+, a new version of the AI-powered voice assistant that's "more conversational, smarter, personalized."
AI features have since been incorporated across Amazon's e-commerce websites through tools like "Buy for Me" which allow customers to ask a shopping assistant to buy an item for them and "Recommended Size" which predicts your clothing size based on past purchases. Amazon's AI shopping assistant is used by tens of millions of customers, according to Jassy.
AI replaces creativity for some
In the Tuesday memo, Jassy sketched out a future in which AI agents are used to conduct tedious tasks, freeing up human workers to take on more creative roles.
"Agents will allow us to start almost everything from a more advanced starting point," Jassy said. "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."
However, this hard-pivot into AI has generated negative feedback from some white-collar employees at the company. Amazon software engineers interviewed recently by the New York Times describe an intensified work environment in which they are pushed to use AI to increase productivity and meet higher output goals, making their jobs "more routine, less thoughtful and, crucially, much faster paced."
All told, Amazon currently has 1,000 generative AI services and applications either in the works or already built, a "small fraction" of what the company ultimately plans to build, said Jassy.
Jassy's pledge to invest in AI comes after the company announced in May that it would cut 100 jobs in its devices and services unit, an Amazon spokesperson confirmed.
| 2025-06-17T00:00:00 |
https://www.cbsnews.com/news/amazon-ceo-generative-ai-corporate-workforce/
|
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Amazon expects to cut corporate jobs as it relies more on AI
|
Amazon expects to cut corporate jobs as it relies more on AI
|
https://www.nbcnews.com
|
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The CEO of the country's second-largest retailer and employer said Amazon is using generative AI "in virtually every corner of the company.
|
Amazon CEO Andy Jassy said Tuesday that the company expects artificial intelligence "will reduce our total corporate workforce as we get efficiency gains" over time.
"We will need fewer people doing some of the jobs that are being done today, and more people do other types of jobs," Jassy added in a memo to Amazon's workforce.
The CEO of the country's second-largest retailer and employer said Amazon is using generative AI "in virtually every corner of the company."
Amazon employs more than 1.5 million people worldwide, according its most recent annual report.
This year, Amazon plans to spend $100 billion to expand AI services and data centers that power them, up from $83 billion last year.
Jassy said he believes so-called "AI agents" will "change how we all work and live." While "many of these agents have yet to be built," he said, "they're coming, and fast."
He continued by saying that they will "change the scope and speed at which we can innovate for customers."
Amazon currently has more than a thousand AI services and applications running inside the company or in progress of being built.
Jassy's comments Tuesday will likely invoke fears that many corporate workers have had as artificial intelligence captures the eye of efficiency-minded executives across corporate America. A recent study from Bloomberg Intelligence said that AI could replace up to 200,000 banking jobs.
Amazon CEO Andy Jassy in New York on Feb. 26. Michael Nagle / Bloomberg via Getty Images
Artificial intelligence has also been shown to be effective at coding for software programs.
Cybersecurity firm Crowdstrike eliminted 5% of its workforce in May, saying that AI was driving "efficiencies across both the front and back office."
Shopify CEO Tobi Lutke said managers at the e-commerce company will be expected to prove why they "cannot get what they want done using AI" before asking for more headcount.
"Having AI alongside the journey and increasingly doing not just the consultation, but also doing the work for our merchants is a mind-blowing step function change here," Lutke added.
Language learning firm Duolingo also recently said that it would replace contract workers with artificial intelligence. "We'll gradually stop using contractors to do work that AI can handle," CEO Luis von Ahn wrote in a memo to Duolingo employees in May. "Headcount will only be given if a team cannot automate more of their work," von Ahn added.
The CEO of U.K. telecom giant BT said this week that plans to cut 40,000 jobs from the company's workforce over the next 10 years "did not reflect the full potential of AI."
| 2025-06-17T00:00:00 |
2025/06/17
|
https://www.nbcnews.com/business/business-news/amazon-expects-cut-corporate-jobs-due-to-ai-artificial-intelligence-rcna213552
|
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"position": 99,
"query": "generative AI jobs"
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{
"date": "2025/06/17",
"position": 99,
"query": "generative AI jobs"
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How States Are Responding to the Rise of AI in Education
|
How States Are Responding to the Rise of AI in Education
|
https://www.ecs.org
|
[
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"How States Are Responding To The Rise Of Ai In Education"
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This post offers an overview of how AI continues to shape state education policy and highlights trends that have evolved over the past several years.
|
This post from Jenny McCann, 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 first of two posts on artificial intelligence. Any views expressed in the post are those of the author.
When ChatGPT debuted in 2022, no states had policies related to generative artificial intelligence (genAI). Fast forward to April 2025, and at least 28 states have published guidance on AI in K-12 settings. This post offers an overview of how AI continues to shape state education policy and highlights trends that have evolved over the past several years.
As of April 1, 2025, only one AI-related education bill has been enacted this year: Mississippi’s S.B. 2426, which creates a state AI task force. However, legislative interest is clearly growing. At least 20 states have introduced AI-related education bills in 2025, including three that passed one chamber (Alabama H.B. 332, Hawaiʻi H.B. 546/S.B. 1622 and Maryland H.B. 1391/S.B. 0906). Our review shows a growing shift from early experimentation and exploratory research toward more structured discussions around guidance, oversight and use cases in schools.
Balancing Guardrails and Innovation
Policymakers are seeking ways to ensure safe and ethical AI use without slowing down innovation. States like California (A.B. 1064), Connecticut (S.B. 2) and Texas (H.B. 1709) recently introduced bills to create oversight boards and “regulatory sandboxes,” or flexible spaces where AI tools can be tested before being rolled out more broadly. So far in 2025, at least seven bills have called for some version of oversight, regulation or sandbox programs for AI in education.
This balance between innovation and accountability is echoed in recent recommendations from the Southern Regional Education Board’s Commission on AI in Education and state-level task force reports, including reports from Arkansas (2025) and Georgia (2024), which call for comprehensive risk-management policies, cross-sector collaboration and phased policy development across government agencies.
Focusing on Guidance and Task Force Reports
Legislation isn’t the only way states are addressing AI in schools. State leaders are increasingly turning to guidance documents and task forces to better understand needs and set direction. As task forces formed in previous years begin to release their findings, a clearer picture is emerging of shared priorities and challenges.
Task force reports from Arkansas (2025), Georgia (2024) and Illinois (2024) highlight similar priorities like creating curricular frameworks for AI literacy, investing in educator professional development, ensuring equitable access to these technologies within the state, protecting student data, and supporting districts and schools with implementation. Meanwhile, Maine (Executive Order, 2024) and Mississippi (S.B. 2426) recently launched education-specific AI task forces — signaling that more guidance is likely on the way. (Note: Maine’s Department of Education released its own AI guidance in February 2025).
Aligning Instruction and Developing the Workforce
State leaders are also exploring how AI can align career pathways with core instruction. Alabama H.B. 332 and Georgia H.B. 487/S.B. 249 would embed AI concepts into graduation requirements through computer science education. Tennessee has proposed requiring AI literacy instruction for students (S.B. 0514/H.B. 0531) and professional development for educators (H.B. 0545/S.B. 0677).
At the same time, several states are drawing lines around the role of AI in instruction. Bills introduced in Connecticut (H.B. 5877) and Texas (H.B. 2400/S.B. 382) aim to ban the use of AI to replace or deliver classroom instruction.
Each state is moving forward AI policies at their own pace. Still, some common themes are starting to take hold: putting guardrails in place, boosting AI literacy among students and educators, and exploring how AI can support both learning and workforce goals. As these policies take hold, ECS will keep tracking new legislation, guidance and implementation tools as well as support leaders in their implementation processes as needed.
| 2025-06-17T00:00:00 |
2025/06/17
|
https://www.ecs.org/artificial-intelligence-ai-education-task-forces/
|
[
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"date": "2025/06/17",
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Exploring the Future of Artificial Intelligence in Education
|
Future of Artificial Intelligence in Education
|
https://www.21kschool.com
|
[
"Kumar Shivam",
"Jul",
"Min Read",
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AI in education supports personalized learning, automates administrative tasks, and enhances teaching and learning through intelligent systems. It's used in ...
|
Education is not an exception to the widespread adoption of artificial intelligence (AI) in many fields.
Applying practical artificial intelligence to the education sector is fostering the development of a novel approach to knowledge transfer and knowledge acquisition strategy.
Ranging from lending a helping hand in paperwork to crafting highly individualised learning experiences in general, AI in education is a key to making it more effective, less costly, and more enjoyable.
In this blog, we will explore how AI is shaping the future of education, its current applications, and the challenges that come with it.
What Is AI?
Artificial intelligence refers to the process by which systems imitate human intelligence or, in other words, the branch of computer science that deals with the creation of intelligent machines.
They are capable of thinking, learning, and solving problems, doing things that would traditionally require human input.
Thus AI systems can read data, decide, and solve problems even on their own.
Regarding education, AI is applied to facilitating administrative duties, assigning individual learning approaches as well as developing new instruments that prove useful to teachers as well as learners.
How AI is Helping Educators?
AI is not only changing the process of student learning; it is also revamping the specifics of the process for tutors. Here’s how AI is assisting teachers:
1. Make Administrative Tasks Simpler
The application of artificial intelligence involves assignment grading, class scheduling, student attendance, and many more repetitive tasks.
This relieves the teachers from much of the responsibility of organising the activity as it allows them to spend more time with the students and in the development of their lessons.
2. Personalising Lesson Plans
With the help of AI educators prepare different lesson plans depending on the student’s performance.
AI can process data about a student’s learning style and provide recommendations for how to teach them but the techniques can be changed to better fit the learning process.
3. Streamlines Assessment
AI systems include programmable task and exercise solutions to use in grading issues such as multiple choice, essays, and homework assignments.
This saves teaching time, which would otherwise have been employed in evaluation, and also helps the educators to give feedback to the student faster thereby improving learning outcomes.
Read, 10 Homework Tips to Become an A+ Student and help them to learn and grow.
4. Curriculum Enhancement
Since one can ascertain what is advantageous to the students when employing specific strategies and resources, artificial intelligence enhances the implementation of the curriculum.
Based on student learning habits and success rates, it can suggest curriculum modifications.
5. Improves Efficiency
All learning institutions perform better with the help of AI.
Teachers paperwork is reduced as a result of the simplification of certain tasks including resource assignment lesson planning and delivery and student supervision.
How AI is Helping Students?
AI is not just for teachers in the classroom. Students benefit greatly from it as it improves their educational experience in ways that were previously unthinkable.
1. Improved Engagement
AI-powered resources like chatbots and virtual tutors make online education dynamic and interesting.
Students are encouraged to remain motivated and focused by these tools which offer instant feedback and create an active learning environment.
2. Individualised Pace
AI enables students to study at their own speed.
Because there is no set time, students can only advance as they fully understand each concept, which increases the flexibility of education.
3. Tailored Learning Experiences
AI can create distinct learning experience profiles using student performance data.
These learning paths focus on a potential challenge that a student may encounter and the material is repeatedly presented.
4. Enhanced Understanding
AI applies aspects like machine learning and provides the student with feedback and assistance at the right time when their conception of certain concepts is not very clear.
When it is used appropriately it can simplify complicated subjects by breaking them down into smaller, easily digestible parts that will enhance learning.
5. Easy Accessibility
Education is now more accessible with the help of AI-driven features like online tutors e-learning platforms and virtual classrooms.
The ease with which students with disabilities or those from remote locations can access educational materials lowers the barriers to high-quality education.
6. Enhanced Skill Development
Students can gain academic and soft skills as well when utilising AI tools.
By using games and scenarios there is a great opportunity to intensify critical thinking, creative thinking and decision making among students.
Numerous AI-driven tools are already making waves in the educational field. Below you can check the examples:
Virtual Tutors: Virtual tutors are intelligent systems that communicate with students naturally using specialized computer programs. They provide individualized instruction based on the learning preferences style and pace of each student. This helps make learning more fun and effective.
Virtual tutors are intelligent systems that communicate with students naturally using specialized computer programs. They provide individualized instruction based on the learning preferences style and pace of each student. This helps make learning more fun and effective. Grammarly: Another AI component is an application known as Grammarly which helps students edit their writing, it underlines possible grammatical errors, offers vocabulary improvements, and gives stylistic advice.
Another AI component is an application known as Grammarly which helps students edit their writing, it underlines possible grammatical errors, offers vocabulary improvements, and gives stylistic advice. Chatbots: Chatbots assist with the realisation of many usual student inquiries and always respond with results to assignments or tests, making the learning process much faster.
Read Teaching with ChatGPT: How They Are Using AI in Education to know the role of ChatGPT in education.
Duolingo: Duolingo Inc. is an American business that provides language certificates and creates learning applications. It has courses in subjects like music, maths, and 43 different languages, including popular ones like English, French, and Spanish, as well as less common ones like Welsh, Irish, and Navajo.
Duolingo Inc. is an American business that provides language certificates and creates learning applications. It has courses in subjects like music, maths, and 43 different languages, including popular ones like English, French, and Spanish, as well as less common ones like Welsh, Irish, and Navajo. Carnegie Learning: A K–12 learning service that uses AI to help students explore maths, literacy and ELA, world languages, and makes learning personal.
A K–12 learning service that uses AI to help students explore maths, literacy and ELA, world languages, and makes learning personal. Brainly: Brainly is an app that involves peer-to-peer learning through the assistance of artificial intelligence which provides fellow students solutions and explanations to different questions.
Future Trends of AI in Education
On the same note, the future of AI in education holds a greater perspective on transformative changes. AI has the potential to completely transform education by making it more adaptable, personalized and transparent.
Backed by IDC, In 2027 the potential market for AI-based educational technology could reach a value of over $150 billion. Here are some key future trends:
1. Immersive Learning with AR and VR
New directions for the presentation of learning materials are brought by such technologies as Augmented Reality (AR) and Virtual Reality (VR) .
These are important because by providing concrete experiences, these technologies bring otherwise abstract concepts into practice.
Regardless of whether students are virtually dissecting a frog or exploring space, it is more interactive thanks to augmented and virtual reality.
2. AI-Powered Adaptive Learning Systems
It will be feasible to adapt learning systems in the future to each learners preferred style and speed while simultaneously offering extra learning materials and suggestions for enhancement.
3. AI-Assisted Collaboration
Interactive learning will have a more significant use of AI to help connect the students so that they can collaborate.
Features of automated discussion forums and group study applications will ensure that students collaborate regardless of where they are located.
Also, give a glance on Exploring the Future of Artificial Intelligence in Education to know more about AI’s role in future education.
4. AI Adaptive Assessment
Now, assessments are not only limited to notebooks and papers; AI-based systems are also generating assessments for students.
AI tool uses case studies, practical questions, and sample studies to generate interactive assessments for students. In order to evaluate students’ abilities based on the initial context, the AI system poses challenging questions.
The assessment would be generated by AI based resources on the candidates’ response and primary context, and prompts given by instructors. AI-based assessment also helps in the evaluation of students performance and skills.
5. AI Voice Assessment
Voice assessment is an incredible way of enhancing communication skills. AI voice assessment helps in developing critical thinking skills and the evaluation of performance.
Through AI Voice assessment, students can clarify their reading skills, writing skills, speaking skills, and listening skills, furthermore.
AI voice assessment is a transformative procedure that provides a detailed evaluation of communication skills within a few minutes.
6. AI Document Verification
Document verification is the first step of any organization or educational institute, however, the verification process is only done manually.
Doing document verification takes time and productivity. However, with the help of an AI tool, it becomes possible to automate the verification process.
AI tools will help in doing multiple functions in a minute and hence save time and human effort. With the aid of artificial intelligence, it is able to extract or analyze data from any given document.
7. AI Admission Interview
AI admission interview is a new generation method for enrollment of children for higher education.
With the help of AI, candidates are frequently interviewed as part of the admissions process in higher education, especially in management programs and Science programs.
These AI interviews evaluate the candidate’s motivation for applying to a particular course, domain knowledge confidence levels and communication abilities.
Challenges and Ethical Considerations
While AI offers exciting possibilities, it also brings several challenges and ethical concerns:
1. Data Privacy Concerns
The massive amounts of data that AI collects raise questions about how to use store and protect data.
Protecting student information will be an important issue as AI’s presence in the learning process increases.
2. Biases in AI Algorithms
The biases of the data used to train AI algorithms or the biases of their designers may be reflected in the algorithms themselves.
Biased results may result from this which would compromise the equity and inclusivity of teaching resources.
3. Accessibility Issues
On the one hand artificial intelligence (AI) technologies make education more accessible and open to more students on the other hand economically disadvantaged students have less access to the right tools and technology.
In order to support equal access to education it is crucial to close the digital divide.
4. Cybersecurity Issue
AI-driven organizations have serious ethical concerns about cybersecurity since these systems frequently handle sensitive data, which makes them easy targets for cyberattacks.
These cybersecurity challenges include phishing, malware, ransomware, and unauthorized access. These cybersecurity challenges are one of the major reasons that hinder the smooth flow of work.
5. Lack of Transparency
AI-driven software lacks transparency, as sometimes it uses its own learning and responding system. This allows them to become automated.
Most of the artificial intelligence (AI) systems, especially those with complex chain networks and black boxes, make it challenging to comprehend how they make decisions.
This creates a hindrance in automated services and data-driven challenges.
6. Job Challenges
AI is very useful in every field of organization and education. However, there are some considerations related to job loss.
With the advancement of automated AI, every work will be done with the help of AI, which leads to unemployment and has the potential to replace human effort.
For eg, China is using robots in car factories instead of human laborers for car manufacturing. The same AI may change the human job.
Global Initiatives Promoting AI in Education
AI is recognized globally as a powerful tool in advancing education. Several initiatives are promoting its use:
1. UNESCO’s Efforts
Today, UNESCO is instrumental in advancing the use of AI for the achievement of targets set under SDG 4, which addresses digital learning for all.
It is capable of solving problems such as shortages of teachers and a scarcity of educational equipment.
2. Singapore’s Smart Nation Strategy
It’s important to note that Singapore is an innovation-leading country in terms of implementing purely AI-based solutions into the education processes.
Among these measures are the following: AI-graded feedback helps students including those with special needs work efficiently.
3. India’s AI-driven Educational Solutions
With the aid of AI India hopes to make high-quality education more accessible.
Students can create mental images that are well-founded in three dimensions by using applications that use artificial intelligence, which makes learning more convenient, interesting and participatory.
4. AI for All
AI for all is a government initiative, self self-learning AI program in India. This program is designed to raise public awareness and disseminate the use of Artificial Intelligence.
These initiative has 2 sections, and one can complete all the assessments with interactive quizzes and assignments. This is a proactive method for supporting AI and to spread awareness about the concept of AI.
5. China’s AI vision for 2030
China has focused a lot on implementing focus on AI vision. By 2030, AI will become the cornerstone of China’s economic expansion, transforming every field, such as smart infrastructure, manufacturing, healthcare, finance, transportation, and energy.
By 2030, China will also have full AI-driven classrooms for every school. Where AI will be used for the teaching and learning process, as well as assessments. Even by 2030, the main goal of China is to create smart factories powered by AI will boost industrial productivity
Conclusion
Everyone interested in the subject and in education in general has nothing to lose but a lot to gain in the context of the development of AI in the future.
Education is one sector where the advent of AI can revolutionize the way it is currently delivered to students.
However, as with any powerful technology, challenges and ethical concerns must be addressed to ensure that AI serves as a tool for inclusion and innovation in education.
With its advances in the future, the introduction of AI is doubtful that it will expand newer horizons, making an education environment much more liberal, progressive, student centred, and globally interconnected.
| 2023-05-03T00:00:00 |
2023/05/03
|
https://www.21kschool.com/us/blog/future-of-ai-in-education/
|
[
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"date": "2025/06/17",
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AI skills are top priority for Gen-Z hires, execs say
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Employers want to hire Gen Z workers who have knowledge of AI: ‘You were born into this shift’
|
https://nypost.com
|
[] |
Employers want to hire Gen Z workers who have knowledge of AI: 'You were born into this shift' ... The most valuable skill an employee can have in the digital age ...
|
The most valuable skill an employee can have in the digital age is… the ability to ask AI?
Titans of the tech industry have taken to social media and other public speaking engagements to reassure Gen-Z, the newest members of the workforce, that AI won’t be detrimental to job availability — in fact, it might be able to aid in their employment.
“AI is changing everything, faster than most institutions, companies or curriculums can keep pace with. But no, that doesn’t mean your education or potential is obsolete. It means we have to think differently about what growth and opportunity look like,” wrote LinkedIn co-founder Reid Hoffman in a recent post on the platform.
“You were born into this shift. You’re native to these tools in a way that older generations aren’t. Lean into it. Teach others.”
5 “You are Generation AI,” LinkedIn co-founder Reid Hoffman wrote online, addressing recent graduates. REUTERS
“You don’t have to become an engineer to use AI powerfully,” Hoffman advised. “Think about how to apply it creatively, how to solve real problems with it, how to collaborate with it. One of your first reactions to any challenge should be ‘How can I use AI to help me here?'”
5 According to a study by KPMG and the University of Melbourne, 4 in 5 students use AI regularly in their studies. Supatman – stock.adobe.com
Hoffman isn’t the only one at his level who is optimistic about AI’s influence on the workforce — other high-level tech execs offered similar thoughts about the future landscape of the job market.
5 On June 17, Amazon CEO Andy Jassy shared company-wide updates about the tech giant’s use of AI. REUTERS
Amazon CEO Andy Jassy shared that the implementation of generative AI will likely “reduce” the company’s corporate workforce.
AI “should change the way our work is done,” wrote Jassy in a memo distributed to employees and posted publicly.
“Those who embrace this change, become conversant in AI, help us build and improve our AI capabilities internally and deliver for customers, will be well-positioned to have high impact and help us reinvent the company,” he added.
5 AI is being implemented into numerous industries and products, ranging from websites to cars, as seen at this Tesla showcase. JEANNE ACCORSINI/SIPA/Shutterstock
Overall, the message coming from industry leaders is that being adaptive and willing to incorporate AI into current professional practices is the real key to being well-positioned for the future job market — but this idea is being obscured under encouraging niceties that are fed to Gen-Z.
“Whilst they may be at an advantage with their AI skills more so than previous generations, they will still need the practical, world-wise experience to flush out any AI inconsistencies and errors that older workers will possess,” Keith Arundale, a visiting fellow at the UK’s Henley Business School, told Newsweek.
“Comfort without mastery can backfire. Gen Z’s early exposure is an advantage, but it isn’t a golden ticket,” agreed Fabian Stephany, assistant professor for AI and Work at the University of Oxford, in an interview with Newsweek.
5 Anthropic is the AI company, co-founded by Dario Amodei, responsible for the popular large language model (LLM) AI chatbot, Claude. AP
Despite the positive packaging that this potential employment crisis tends to be wrapped up in, some top tech figures remain skeptical.
Automation and increased usage of AI by large companies is “going to happen in a small amount of time — as little as a couple of years or less,” Dario Amodei, CEO of AI company Anthropic, told Axios.
“We, as the producers of this technology, have a duty and an obligation to be honest about what is coming. I don’t think this is on people’s radar,” Amodei continued.
In reality, Gen-Z isn’t necessarily better equipped to handle the demands of modern-day jobs just because of a generational familiarity with AI. They still need soft skills and the social abilities to properly navigate dilemmas that professional environments often pose — employers and industry leaders just tend to leave that part out.
| 2025-06-17T00:00:00 |
2025/06/17
|
https://nypost.com/2025/06/17/lifestyle/ai-skills-are-top-priority-for-gen-z-hires-execs-say/
|
[
{
"date": "2025/06/17",
"position": 32,
"query": "AI employers"
}
] |
Artificial Intelligence - Business.gov.uk
|
Artificial Intelligence
|
https://www.business.gov.uk
|
[] |
The UK is the third largest AI market in the world, after the US and China. Valued at $92bn (£72.3bn) in 2024, the UK's AI sector is larger than any other ...
|
The UK is the third largest AI market in the world, after the US and China. Valued at $92bn (£72.3bn) in 2024, the UK's AI sector is larger than any other country in Europe.
The UK is the first country in Europe to produce 168 tech unicorns. The combined market value of UK tech companies is now $1 trillion, after the biggest year-on-year increase since 2013/14.
With over 3,700 AI companies, employing over 60,000 people and contributing £3.7 billion to our economy, the UK is already a world leader in AI.
| 2025-06-17T00:00:00 |
https://www.business.gov.uk/campaign/grow-your-tech-business-in-the--uk/artificial-intelligence/
|
[
{
"date": "2025/06/17",
"position": 64,
"query": "AI employers"
}
] |
|
AI and Safety
|
AI and Safety
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https://www.aseonline.org
|
[
"Author"
] |
... artificial intelligence is reshaping the way companies approach safety in the workplace. ... By integrating AI into safety programs, employers not only improve ...
|
Every June, the U.S. observes National Safety Month, a campaign led by the National Safety Council to focus on reducing leading causes of injury and death in the workplace, on the roads, and in our communities. It's a time to reaffirm our commitment to safety and express appreciation for the workers who make safety a daily priority.
This month also serves as a time for safety appreciation, recognizing employees who go above and beyond to ensure a safe environment. From safety officers and HR managers to line workers and first responders, these individuals deserve praise for their diligence and care. Hosting recognition events, giving out awards, or simply saying “thank you” can go a long way in building a culture that values safety.
As we focus on the importance of National Safety Month, it's also the perfect time to explore how artificial intelligence is reshaping the way companies approach safety in the workplace.
AI offers superior speed, accuracy, and reliability, making it a valuable tool for enhancing organizations’ safety programs in most industries. Businesses can leverage AI tools in various ways.
AI-driven analytics utilizes machine learning and data analysis techniques to process and interpret vast amounts of safety-related data from sensor networks, cameras, and incident reports. This helps identify patterns, predict potential risks, evaluate job hazards, and highlight areas for improvement.
AI enhances safety training by personalizing learning experiences and offering immersive simulations through virtual or augmented reality. These tools help employees better understand and retain safety protocols. AI can also automate routine safety tasks like compliance checks, inspection scheduling, and real-time reporting thereby freeing up time for safety teams to focus on strategic improvements.
AI-powered systems continuously monitor environments for changes, such as temperature fluctuations, toxic emissions, or physical obstacles that could pose safety risks. It alerts workers or triggers automated safety protocols in real time, prompting immediate action.
By integrating AI into safety programs, employers not only improve compliance and reduce risk but also foster a culture of care and accountability. It’s a smart investment in both people and performance.
National Safety Month is more than an observance. It reminds us that safety is a collective responsibility. By appreciating those who prioritize it and continually educating ourselves on best practices, we build not just safer workplaces, but stronger, more caring communities.
ASE Connect
For more safety resources visit https://www.aseonline.org/HR-Compliance/Compliance-Services/Health-Safety-Consulting.
| 2025-06-17T00:00:00 |
https://www.aseonline.org/News-Events/ASE-News/EverythingPeople-This-Week/ai-and-safety
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[
{
"date": "2025/06/17",
"position": 69,
"query": "AI employers"
}
] |
|
Google DeepMind
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Google DeepMind
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https://deepmind.google
|
[] |
Artificial intelligence could be one of humanity's most useful inventions. We research and build safe artificial intelligence systems.
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Imagen
Our best text-to-image model yet, engineered for creativity
| 2025-06-17T00:00:00 |
https://deepmind.google/
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[
{
"date": "2025/06/17",
"position": 71,
"query": "AI employers"
}
] |
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AI Is Poised to Revolutionize Work — Or Wreck It
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AI Is Poised to Revolutionize Work — Or Wreck It
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https://www.shrm.org
|
[
"Brian J. O'Connor"
] |
The stakes are clear: AI has the potential to transform HR by streamlining operations, improving decision making, and elevating the employee experience. But too ...
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Where AI Goes Wrong
Despite its promise, AI adoption in HR is already littered with missteps, many of them predictable. Automating dysfunction and ignoring ethics often go hand in hand. These failures usually stem from poor training data or flawed HR processes — problems that AI doesn’t fix, but rather magnifies. It’s the latest version of an old programmer’s lament: Garbage in, garbage out.
Built to Fail
The biggest early adopter AI disaster in the HR space blew up when Amazon used its own early version to screen job applications, only to find that the AI prioritized resumes from men and penalized any mention of “women,” as in “women’s chess club,” and downgraded graduates of two women’s colleges. In 2018, Reuters revealed that the system had been trained using earlier applications from the mostly male candidates in the tech industry. The project was promptly scrapped, with just a small portion salvaged for redevelopment.
Similarly, but much more recently, tutoring company iTutorGroup settled a $365,000 suit brought by the Equal Employment Opportunity Commission (EEOC) in 2023 after its AI recruiting software automatically rejected more than 200 candidates who were women ages 55 and older or men ages 60 and older. “Even when technology automates the discrimination, the employer is still responsible,” then-EEOC Chair Charlotte Burrows said.
Going beyond discrimination into outright illegality, a Microsoft-powered chatbot launched by New York City’s government in 2024 advised entrepreneurs and business owners they were legally allowed to take part of their workers’ tips, and that it was perfectly legal to fire workers who complained about sexual harassment. As of late 2024, according to CIO.com, “the chatbot remains online,” accompanied by a pop-up with the dire warning to verify any answers and avoid using them “as legal or professional advice.”
These AI risks remain a long-running issue that continues to flare up even after a decade of cautionary cases. More recently, a 2023 suit against software provider Workday charging that its AI technology discriminated against applicants on issues of age, race, and disabilities was expanded in May, going from one single plaintiff to a collective action with four additional plaintiffs.
AI Errors Aren’t Just External Risks
Another risk of disaster can result from a lack of ongoing monitoring of AI, especially generative AI solutions which, in addition to fines, lawsuits and reputational damage, can wreak ongoing havoc with an organization’s internal operations, said Pragya Gupta, chief product and technology officer at isolved HCM, a provider of HR, payroll, and benefits solutions. Gupta recalled how, after launching an applicant tracking solution, isolved added functionality to generate job descriptions for recruiting.
“One day, the AI decided to include salary information in the job description,” she said. “It was not part of our prompts. It just decided that one day it was a great idea.”
An isolved client had recently acquired a subsidiary where the employees were being paid much less than the salary ranges listed in the new AI-generated job descriptions, and it didn’t take long for the underpaid workers to notice.
“The customer was saying, ‘Oh my God, we have a mini-revolt within our company right now.’ It created a major issue within the company,” Gupta said. “Regular audits that inspect and adapt the process must be part of deploying technology. Those are either automated checks that say, ‘Hey, make sure there’s no salary information before you publish’ or there are humans looking [at and] approving those job descriptions.”
| 2025-06-17T00:00:00 |
https://www.shrm.org/enterprise-solutions/insights/ai-is-poised-to-revolutionize-work-wreck
|
[
{
"date": "2025/06/17",
"position": 73,
"query": "AI employers"
},
{
"date": "2025/06/17",
"position": 86,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/17",
"position": 100,
"query": "future of work AI"
},
{
"date": "2025/06/17",
"position": 8,
"query": "workplace AI adoption"
}
] |
|
AI in Hiring: Legal Shifts & Employer Guidance
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AI in Hiring: Legal Shifts & Employer Guidance
|
https://natlawreview.com
|
[] |
This article contains an overview of the shifting federal landscape on AI at work, the state level response, and offers recommendations for employers to ...
|
As we previously reported here and here, employers must navigate a rapidly evolving legal landscape as artificial intelligence (AI) continues to transform the modern workplace. From federal rollbacks to aggressive state-level regulation, the use of AI in employment decisions—particularly in hiring, performance management, and surveillance—has become a focal point for lawmakers, regulators, and litigators alike. This article contains an overview of the shifting federal landscape on AI at work, the state level response, and offers recommendations for employers to mitigate risk.
Trump Administration Rolls Back Federal AI Oversight
The federal approach to AI in employment has undergone a dramatic shift in 2025. On his first day in office, President Trump rescinded Executive Order 14110, which directed federal agencies to address AI-related risks such as bias, privacy violations, and safety concerns. This was followed by the removal of key guidance documents from the U.S. Equal Employment Opportunity Commission (EEOC), including technical assistance on Title VII compliance and the Americans with Disabilities Act (ADA) as they relate to AI tools. The Department of Labor has also signaled that its prior guidance on AI best practices may no longer reflect current policy, leaving employers with less clarity at the federal level than ever.
Despite these reversals, employers remain liable under existing anti-discrimination laws for the outcomes of AI-driven employment decisions—even when those tools are developed by third-party vendors.
States, Especially California, Fill the Federal Void With AI Regulation
In the absence of clear federal guidance, states have begun regulating AI in the workplace. California, in particular, has emerged as a bellwether.
Earlier this year, California introduced several bills aimed at curbing the unchecked use of AI in employment decisions:
SB 7 – “No Robo Bosses Act” : This bill would require employers to provide 30 days’ notice before using any automated decision system (ADS) and mandates human oversight in employment decisions. It also bans AI tools that infer protected characteristics or retaliate against workers.
: This bill would require employers to provide 30 days’ notice before using any automated decision system (ADS) and mandates human oversight in employment decisions. It also bans AI tools that infer protected characteristics or retaliate against workers. AB 1018 – Automated Decisions Safety Act : This legislation would impose broad compliance obligations on both employers and AI vendors, including bias audits, data retention policies, and impact assessments.
: This legislation would impose broad compliance obligations on both employers and AI vendors, including bias audits, data retention policies, and impact assessments. AB 1221 and AB 1331: These bills target AI-driven workplace surveillance, requiring transparency and limiting monitoring during off-duty hours or in private space.
Other states are following suit. For example, Illinois, Colorado, and New York City already have laws regulating AI in hiring, and over 25 states have introduced similar legislation in 2025.
Practical Implications for Employers
With limited federal guidance and state laws multiplying, inaction is risky and, indeed, reckless. Employers should therefore take proactive steps to mitigate legal exposure:
Audit AI Tools Regularly: Conduct bias audits and impact assessments to ensure compliance with anti-discrimination laws. Review Vendor Agreements: Ensure contracts with AI vendors include provisions for transparency, data handling, and liability. Train HR and Leadership: Equip decision-makers with the knowledge to use AI responsibly and in compliance with applicable laws. Implement Human Oversight: Avoid fully automated employment decisions. Ensure a human reviews and approves critical outcomes. Stay Informed: Monitor legislative developments in all jurisdictions where your business operates.
Looking Ahead: Balancing Innovation With Worker Protection
The use of AI in the workplace is not going away. In fact, it is accelerating. But with innovation comes responsibility. Employers should systematically document data collection from workplace technologies, update privacy-related polices, and ensure human oversight is integrated into any employment decisions that rely on algorithmic input.
| 2025-06-17T00:00:00 |
https://natlawreview.com/article/where-are-we-now-use-ai-workplace
|
[
{
"date": "2025/06/17",
"position": 89,
"query": "AI employers"
},
{
"date": "2025/06/17",
"position": 76,
"query": "artificial intelligence employment"
}
] |
|
Journalism: AI and Writing - Including ChatGPT
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Research Guides at Madison College (Madison Area Technical College)
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https://libguides.madisoncollege.edu
|
[
"Matthew Coan"
] |
Journalism: AI and Writing - Including ChatGPT. Links to key resources on the topic of journalism and publishing. Welcome - Journalism Research GuideToggle ...
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Journalism: AI and Writing - Including ChatGPT
Links to key resources on the topic of journalism and publishing.
| 2025-06-17T00:00:00 |
https://libguides.madisoncollege.edu/journalism/chatgpt
|
[
{
"date": "2025/06/17",
"position": 26,
"query": "AI journalism"
}
] |
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From Data to Story: Using AI for Reporting
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From Data to Story: Using AI for Reporting
|
https://www.journalism.cuny.edu
|
[
"Newmark J-School"
] |
... artificial intelligence (AI) to enhance data visualization ... in engaged journalism from the Newmark Graduate School of Journalism at CUNY in 2016.
|
Instructor: Joe Amditis, Associate Director of Operations, Center for Cooperative Media at Montclair State University
This training focuses on the essential skills needed to transform raw data into compelling stories, particularly in the context of election coverage, and how to leverage artificial intelligence (AI) to enhance data visualization.
Designed for journalists, analysts, and commentators, this 90-minute session will provide practical tools and techniques to boost reporting accuracy and clarity. Through hands-on exercises and expert guidance, participants will learn how to:
Find and clean data
Visualize the story
Create effective graphics and visualizations
Apply data effectively in election reporting
Utilize AI tools for increased efficiency and accuracy in data analysis
Register for the data reporting training
The training has been developed by CCM and is funded by the New York City Mayor’s Office of Media and Entertainment. If you have any questions, contact [email protected].
Instructor
Joe Amditis is the associate director of operations at the Center for Cooperative Media at Montclair State University and an adjunct professor in the School of Communication and Media. He is the former producer and host of the WTF Just Happened Today podcast. Joe is a veteran of the NJ Army National Guard. He was deployed to Iraq in 2008, and was activated to help with Hurricane Irene relief efforts in 2011. He earned a B.A. in political science and criminal justice from Rutgers in 2013 and an M.A. in engaged journalism from the Newmark Graduate School of Journalism at CUNY in 2016. Joe has also coordinated several collaborative reporting projects, including Democracy Day, a nationwide reporting collaborative involving 300+ newsrooms across the United States. He is the author of several guides and educational resources for small and local newsrooms, including guides on generative AI.
| 2025-06-17T00:00:00 |
https://www.journalism.cuny.edu/events/from-data-to-story-using-ai-for-reporting/
|
[
{
"date": "2025/06/17",
"position": 36,
"query": "AI journalism"
}
] |
|
Navigating AI Ethics in Journalism
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Navigating AI Ethics in Journalism
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https://www.numberanalytics.com
|
[
"Sarah Lee"
] |
Delving into the complexities of AI in journalism, this guide examines the ethical considerations and best practices for responsible innovation.
|
Exploring the Impact of Emerging Tech on Journalistic Integrity
Navigating AI Ethics in Journalism
Delving into the complexities of AI in journalism, this guide examines the ethical considerations and best practices for responsible innovation.
Introduction to AI in Journalism
The integration of Artificial Intelligence (AI) in journalism has been a transformative force, revolutionizing the way news is gathered, processed, and disseminated. From automated content generation to advanced data analysis, AI applications are increasingly becoming integral to newsrooms worldwide.
Overview of AI Applications in Newsrooms
AI is being utilized in various aspects of journalism, including:
Automated news writing: AI algorithms can generate news articles, especially for data-driven stories such as financial reports and sports news.
Data analysis: AI can process large datasets to uncover insights and patterns that may not be immediately apparent to human journalists.
Personalized news delivery: AI-driven systems can tailor news feeds to individual preferences, enhancing user experience.
Fact-checking: AI can assist in verifying the accuracy of information, helping to combat misinformation.
Historical Context of Technological Innovation in Journalism
Journalism has always been at the forefront of adopting new technologies to improve reporting and dissemination. From the advent of the telegraph to the use of social media, technological innovations have continually reshaped the media landscape. The current integration of AI is merely the latest chapter in this ongoing narrative.
The Evolving Role of Journalists in an AI-Driven Media Landscape
As AI assumes certain tasks, the role of journalists is evolving. Journalists are now expected to work alongside AI systems, leveraging their capabilities while also ensuring that the ethical standards of journalism are maintained. This collaboration requires journalists to develop new skills, including understanding AI's potential and limitations.
Ethical Considerations
The integration of AI in journalism raises several ethical considerations that must be addressed to ensure responsible innovation.
Bias and Fairness in AI-Driven Reporting
One of the primary concerns is the potential for bias in AI-driven reporting. AI systems learn from data, and if this data is biased, the output will reflect these biases. Ensuring fairness in AI-driven reporting is crucial and involves:
Data curation : Ensuring that the data used to train AI systems is diverse and representative.
: Ensuring that the data used to train AI systems is diverse and representative. Algorithmic auditing: Regularly testing AI systems for bias and taking corrective measures when necessary.
Transparency and Accountability in Automated Journalism
Transparency is vital in maintaining trust in AI-driven journalism. News organizations should be clear about when and how AI is used in the reporting process. Moreover, there must be mechanisms in place to hold AI systems accountable for their outputs, ensuring that they adhere to journalistic standards.
The Impact of AI on Journalistic Integrity and Credibility
The use of AI can impact journalistic integrity and credibility, particularly if not managed transparently. It is essential to maintain high standards of accuracy, fairness, and transparency to preserve the trust of the audience.
Best Practices for Responsible AI Use
To navigate the ethical complexities of AI in journalism, news organizations should adopt best practices that promote responsible AI use.
Strategies for Mitigating Bias in AI Systems
Mitigating bias involves a multi-faceted approach:
Diverse and representative data sets: Ensuring that the data used to train AI systems is diverse and free from bias. Regular auditing and testing: Continuously monitoring AI outputs for signs of bias and taking corrective action. Human oversight: Having human journalists review and edit AI-generated content to catch and correct any biased reporting.
Implementing Transparency and Explainability in AI-Driven Reporting
Transparency can be achieved through:
Clear disclosure : Clearly indicating when AI has been used in the reporting or generation of content.
: Clearly indicating when AI has been used in the reporting or generation of content. Explainable AI (XAI): Using techniques that provide insights into how AI systems arrive at their conclusions, making them more understandable to humans.
Ensuring Accountability in Automated Decision-Making Processes
Accountability mechanisms include:
Human review processes : Ensuring that AI-generated content is reviewed by humans before publication.
: Ensuring that AI-generated content is reviewed by humans before publication. Corrective feedback loops : Implementing processes to correct AI outputs that are found to be inaccurate or biased.
: Implementing processes to correct AI outputs that are found to be inaccurate or biased. Oversight bodies: Establishing or utilizing existing bodies to oversee the use of AI in journalism and address any ethical violations.
The following flowchart illustrates the process of ensuring accountability in AI-driven journalism:
flowchart LR A["AI Content Generation"] --> B["Human Review"] B --> C{"Accurate and Fair?"} C -->|"Yes"| D["Publish"] C -->|"No"| E["Corrective Action"] E --> B
Future Directions
The future of AI in journalism holds much promise, with potential advancements that could further enhance journalistic practices.
The Potential for AI to Enhance Journalistic Practices
AI can significantly enhance journalism by:
Automating routine tasks : Freeing journalists to focus on more complex and investigative reporting.
: Freeing journalists to focus on more complex and investigative reporting. Analyzing large datasets : Uncovering insights that might be missed by human journalists.
: Uncovering insights that might be missed by human journalists. Improving news personalization: Enhancing user experience through tailored news feeds.
Emerging Trends and Technologies in AI Journalism
Emerging trends include:
Advanced natural language processing (NLP) : Enabling more sophisticated automated content generation and analysis.
: Enabling more sophisticated automated content generation and analysis. Integration with other technologies: Such as the Internet of Things (IoT) and augmented reality (AR), to create more immersive and interactive news experiences.
Preparing for the Future: Skills and Competencies for Journalists in an AI-Driven World
To thrive in an AI-driven media landscape, journalists will need to develop new skills, including:
Understanding AI and its applications : Having a basic understanding of how AI works and its potential applications in journalism.
: Having a basic understanding of how AI works and its potential applications in journalism. Data analysis and interpretation : Being able to work with data and interpret the insights provided by AI systems.
: Being able to work with data and interpret the insights provided by AI systems. Critical thinking and ethical awareness: Maintaining a critical perspective on AI outputs and being aware of the ethical implications of AI use in journalism.
The following table summarizes the key skills and competencies required for journalists in an AI-driven world:
Skill/Competency Description Understanding AI and its applications Basic knowledge of AI principles and their application in journalism. Data analysis and interpretation Ability to analyze data and interpret insights generated by AI systems. Critical thinking and ethical awareness Maintaining a critical perspective on AI outputs and awareness of ethical implications. Collaboration with AI systems Ability to work effectively alongside AI, leveraging its capabilities while ensuring oversight.
Conclusion
The integration of AI in journalism presents both opportunities and challenges. By understanding the ethical considerations and adopting best practices for responsible AI use, news organizations can harness the potential of AI to enhance journalistic practices while maintaining the integrity and credibility of their reporting.
References
FAQ
What are the main ethical considerations when using AI in journalism?
The main ethical considerations include ensuring bias and fairness in AI-driven reporting, maintaining transparency and accountability in automated journalism, and preserving journalistic integrity and credibility.
How can bias in AI systems be mitigated?
Bias can be mitigated through the use of diverse and representative data sets, regular auditing and testing of AI outputs, and human oversight of AI-generated content.
Why is transparency important in AI-driven journalism?
Transparency is crucial for maintaining trust in AI-driven journalism. It involves clearly disclosing when AI is used in the reporting or generation of content and making AI decision-making processes understandable.
What skills do journalists need to develop to work effectively with AI?
Journalists need to understand AI and its applications, be able to analyze and interpret data, maintain critical thinking and ethical awareness, and collaborate effectively with AI systems.
How can AI enhance journalistic practices?
AI can automate routine tasks, analyze large datasets to uncover new insights, and improve news personalization, thereby enhancing the quality and reach of journalistic work.
| 2025-06-17T00:00:00 |
https://www.numberanalytics.com/blog/ai-ethics-journalism-guide
|
[
{
"date": "2025/06/17",
"position": 40,
"query": "AI journalism"
},
{
"date": "2025/06/17",
"position": 36,
"query": "artificial intelligence journalism"
}
] |
|
How audiences think about news personalisation in the AI ...
|
How audiences think about news personalisation in the AI era
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https://reutersinstitute.politics.ox.ac.uk
|
[] |
Of the media leaders surveyed for the Reuters Institute's latest Journalism, Media and Technology Trends and Predictions report, 80% said AI would be very or ...
|
As newsrooms continue to experiment with AI technologies, many are setting their sights on tools to help tackle declining news engagement and growing news avoidance, especially among younger audiences, while also cultivating loyalty among those who already rely on them. While personalisation is not new to the news industry, where many have implemented recommendation systems and tailored newsletters for some time (e.g. Kunert and Thurman 2019), recent developments in AI have drastically changed the kinds of personalisation that are potentially feasible at scale.1
In addition to enabling further personalisation in the selection of news, generative AI now makes it technically possible to personalise news formats according to the needs and preferences of individual users, while also enabling entirely new possibilities, such as generative AI chatbots that can answer news-related questions. To the extent that these tools work reliably in practice, they may enable organisations to deliver news in ways that are more accessible, convenient, and relevant to individual users. However, achieving this will partly depend on how audiences feel about using personalised news in the first place, in addition to how open they are to the use of AI for this purpose, in a context where many remain sceptical about these technologies.
I begin this chapter by exploring audience attitudes towards the personalisation of content selection across different kinds of websites and apps, showing how comfort with algorithmic recommendation in news compares to other domains. Then I move onto AI-driven personalisation, first showcasing examples of how newsrooms are already experimenting with these technologies, before examining public interest in different types of AI-driven news personalisation.
A podcast episode on the findings
Spotify | Apple | Transcript
Comfort with personalised selection across domains
Automated personalisation has become an increasingly common feature of digital life, yet the nature, utility, and implications of relying on personalised content differ considerably depending on the kinds of content being personalised. To contextualise audience comfort with the personalisation of news selection, we first asked survey respondents in 27 markets about their comfort using websites or apps with automated selection across different kinds of websites and apps.
We find that close to half of respondents are comfortable with news personalisation, but comfort is low compared to other domains. Respondents are most comfortable with automated selection when it comes to weather, where people tend to be more interested in places they are or will be. Majorities are also comfortable with the automated selection of music and online television, which many are accustomed to on platforms such as Netflix and Spotify, and where people tend to see benefits of recommendations based on genres they like and may appreciate being freed from the burden of having to choose. Comfort is lower for news, where important stories of the day can be about almost any topic. Comfort is lowest on social media and video feeds (e.g. YouTube, TikTok), where some may have had negative experiences or encountered more public debate on the matter. However, younger people – who are heavier users of platforms like TikTok, where algorithmic recommendation is integral to the user experience – tend to be much more comfortable with automated selection on social media (54% among under-35s vs 38% among those 35+). Across all domains, comfort tends to be lower in much of Europe (e.g. Western and Northern Europe) compared to other parts of the world (e.g. Latin America, Asia, Africa).
This begs the question of what beliefs drive people’s attitudes towards personalised news selection. An analysis of open comments from a subset of countries shows that respondents who are comfortable with personalised news selection see four key benefits. First, many feel personalisation ensures they receive news that is more relevant to their lives, for example, ‘highlighting information about my city, my province’ (F, 34, Argentina). Relatedly, some emphasise the greater efficiency of personalised news selection, which helps bypass topics that are uninteresting or which they intentionally avoid: ‘It always knows … the relevant information I need, instead of wasting time viewing everything’ (M, 24, US). A smaller number of respondents express greater trust in news selection performed by algorithms, which they view as ‘less biased than human editors, as they are programmed to make selections based on data rather than personal opinions or preferences’ (M, 26, US). Lastly, some believe algorithmic selection delivers more varied topics and viewpoints, serving ‘articles that I wouldn't have seen myself that are relevant’ (F, 47, UK). Across all four themes, participants think these technologies work well and, as a result, benefit them.
The reasons underpinning discomfort with personalised selection vary more, with some opposing these technologies rooted in a belief they do a poor job, while others are uncomfortable precisely because they think they are effective but may have negative outcomes, and others yet express concerns that go beyond the quality of the recommendations. For instance, some feel these technologies are bad at predicting their interests, delivering content that is ‘useless or false’ (F, 57, Argentina), or as one participant put it, ‘because the algorithm is always wrong about me’ (F, 61, US). However, others worry that, in adhering to their personal interests, algorithmic selection may lead them to miss out on important issues, preferring instead ‘a general overview rather than only specific pre-selected areas of knowledge’ (F, 76, UK). Likewise, some believe personalised selection leads to more biased (or worse yet, manipulated) information, which some associate with echo chambers and polarisation: ‘I worry that the algorithmic filtering might block out important stories and may also be intentionally manipulated’ (M, 34, Argentina). Beyond news content itself, many express concerns about the ‘invasion of privacy’ (M, 60, UK) by surveillance technologies – ’Big brother is watching’ (M, 52, US) – or simply oppose personalised selection grounded in a desire to make up their own minds about news and what to consume: ‘I don’t like news to be imposed on or chosen for me’ (M, 56, Argentina).
Reasons people are comfortable vs uncomfortable with personalised news selection
Some of these concerns may be assuaged through communication and/or design, clarifying for users what personalisation consists of and any measures taken to minimise potential risks (e.g. approaches in which big stories of the day will remain prominent regardless of individual preferences). However, the broader question of how enthusiastically to lean into audience preferences remains important to the extent that it risks undermining editorial values and public interest, a concern that is especially salient for public service media (e.g. Sehl and Eder 2023).
Growing interest in AI personalisation in the news industry
While personalised news selection has been around for some time, it is increasingly AI powered. Of the media leaders surveyed for the Reuters Institute’s latest Journalism, Media and Technology Trends and Predictions report, 80% said AI would be very or somewhat important in 2025 for news distribution and recommendation, such as personalised homepages and alerts (Newman and Cherubini 2025). Media leaders are increasingly setting their sights on more ambitious AI personalisation initiatives that account not only for news selection but also the formats in which content is offered. As Deborah Turness, chief executive of BBC News, said in her announcement to staff about the creation of a new department that will use AI to deepen personalisation: ‘We must become ruthlessly focused on understanding our audience needs, on delivering the kind of journalism and content they want, in the places they want it, designed and produced in the shape that they enjoy it.’2
Publishers are already experimenting with AI to personalise news formats. The BBC has been trialling OpenAI’s speech-to-text tool Whisper to add subtitles and transcripts to some items published on BBC Sounds. Others, such as India Today and the Miami Herald, have been testing the opposite – AI technologies that allow users to turn text articles into audio, using an AI-generated voice. Swedish newspaper Aftonbladet has introduced ‘quick versions’ of news stories produced with AI on top of extended versions of articles. And Argentina’s Clarín newspaper now offers users both a text-to-audio option and UalterAI, a tool offering a range of supplementary analyses ranging from key bullet points and highlighted quotes, to key figures, a glossary, and a list of Frequently Asked Questions.
Examples of AI used to adapt news formats and delivery
Other publishers are introducing entirely new products. The Independent (UK) has launched a new digital news service called Bulletin – advertised as ‘News for Seriously Busy People’ – which uses Google AI tools to create article summaries overseen by journalists.3 Others such as the Washington Post (US)4 and the Financial Times5 (UK) have launched generative AI tools that can answer user questions based on their own corpus of articles. Rather than modifying news story formats, these tools provide an advanced search function that can understand complex queries.
Audience interest in AI-driven news personalisation
When we ask audiences about their interest in different options for adapting news to their individual needs with AI, we find relatively low interest across the board – below 30% for any single option, which may be shaped by low familiarity with these kinds of tools. We see a greater appetite for alternatives that make news consumption more efficient and relevant: article summaries and translations of news articles are at the top of the list, followed by customised news homepages and recommendations or alerts. Meanwhile, interest is lowest in modality conversion options such as text-to-audio. This contrasts with the high interest reported among industry leaders for AI format conversion options, where text-to-audio tops the list of AI initiatives planned for 2025, perhaps because it is seen as relatively easy, cheap, and uncontroversial to implement (Newman and Cherubini 2025).
Relative interest in different types of AI personalisation also varies somewhat across markets. While article summarisation – one of the more widely rolled out generative AI features – tends to be of high interest everywhere, translation more often tops the list in linguistically unique European countries with relatively small populations, such as Finland and Hungary, perhaps signalling an appetite to be able to access news content from outside their countries. Likewise, interest in the ability to adapt news text to different reading levels often ranks higher in countries with lower literacy rates or reading proficiency relative to countries with higher literacy or reading proficiency levels. In India, Kenya, Nigeria, and the Philippines, the option to adapt news to different reading levels ranks in the top three, and in India is the most popular option. This compares to countries like Finland, Norway, and Japan where adapting the language in news articles for different reading levels ranks in the bottom three.
More broadly, respondents tend to express more enthusiasm in countries where comfort with the use of AI in journalism is higher, such as India and Thailand, whereas we see much lower interest in countries with low AI comfort, such as the UK. Likewise, younger groups, who tend to be more comfortable with AI in general, show greater interest in the use of AI for personalising formats, such as adapting articles to different reading levels, as well as chatbots. This suggests that news organisations may want to focus these kinds of AI innovation on younger audiences. Likewise, respondents who are less keen on reading news show greater interest in options to convert text to audio or text to video.
There is also the question of how effective such tools are likely to be among people disengaged from news. Our data show that interest in AI personalisation is considerably lower among those least interested in news and those who avoid news more frequently. That said, small pockets of news avoiders may be more amenable to certain types of personalisation. For example, those who avoid news because they find it hard to understand express higher interest across the board relative to news avoiders in general, with the largest gap when it comes to the use of AI to adapt news for different reading levels.
Conclusion
Audiences are broadly sceptical about news personalisation in ways they aren’t about other areas of digital life. Our research finds greater interest in the use of AI to personalise news formats, particularly those that make news easier or quicker to consume, followed by personalised news selection, where some already worry about algorithmic recommendation, including fears about missing out on important stories. Reported interest does not necessarily mean people will use options, just as lack of interest doesn’t necessarily mean they won’t (and it is possible some respondents don’t understand what each would entail or look like in practice). However, there is a risk of overestimating public enthusiasm around AI-driven personalisation or prioritising tools audiences are less interested in. It is also possible, given relatively low appetite for any single option, that offering a palette of options for audiences to choose from may be necessary in order to add value for a critical mass of users.
We find evidence that interest in AI personalisation is shaped both by comfort with the use of AI in journalism and the potential these technologies show in satisfying audience needs or preferences. In light of this, the rollout of AI personalisation may play out differently from one country to the next, with greater openness and enthusiasm in markets such as Thailand, India, and much of Africa, where attitudes towards the use of AI in news are more favourable, compared to Northern and Western Europe, where audiences are considerably more sceptical about AI. Likewise, news organisations will need to evaluate possible strategies and potential trade-offs of serving these options to audiences who have more of an appetite for them (e.g. younger people) without being off-putting for more hesitant users.
Given that AI can power such different kinds of personalisation, communicating clearly what these technologies consist of may help offer reassurance in light of some of the concerns identified in our open responses, especially regarding personalised selection. It is also worth keeping in mind the desire for self-determination expressed by many respondents in the open responses. While the uptake of customisation tends to be limited, offering audiences options to exercise some control over personalisation might help placate concerns, especially in the early stages of AI adoption.
Footnotes
1 Some in industry circles differentiate personalisation (understood as the automated selection of news content based on user data) from customisation (referring to when users can choose or configure their own news experiences). In this chapter, we use personalisation more broadly to describe different scenarios that enable the tailoring of news to the needs and preferences of users, regardless of whether it is automated or selected by users.
2 https://www.theguardian.com/media/2025/mar/06/bbc-news-ai-artificial-intelligence-department-personalised-content
3 https://www.independentadvertising.com/the-independent-launches-bulletin-a-new-brand-delivering-essential-news-briefings-for-seriously-busy-people/
4 https://www.washingtonpost.com/ask-the-post-ai/
5 https://www.ft.com/content/fc5d4642-af71-4ac6-8311-1920726f8baa
| 2025-06-17T00:00:00 |
https://reutersinstitute.politics.ox.ac.uk/digital-news-report/2025/how-audiences-think-about-news-personalisation-ai-era
|
[
{
"date": "2025/06/17",
"position": 44,
"query": "AI journalism"
},
{
"date": "2025/06/17",
"position": 37,
"query": "artificial intelligence journalism"
}
] |
|
Seeing is Believing? Journalism at a Crossroads in the Age of ...
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Seeing is Believing? Journalism at a Crossroads in the Age of Synthetic Imagery
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https://cfom.org.uk
|
[] |
Astrid Vandendaele, Assistant Professor of Journalism and New Media, discusses AI generated images and how journalists are adapting to using them in newsrooms.
|
One of our most striking findings was the absence of clear editorial policies, even though the need for them is real. As an image editor told us: “I think it’s very important that media outlets have a charter or at least a flow chart to decide in which cases automatically generated pictures are allowed. This is a discussion that each newsroom should have.” In many cases, decisions about whether and how to use Gen-AI visuals are made on a case-by-case basis, often guided by intuition rather than codified standards.
This ad-hoc approach is risky. Without shared norms, journalism becomes vulnerable, inconsistent, at risk of reputational damage, and manipulation. Some practitioners told us they worry that formal rules would stifle creativity or compromise press freedom. One of them warned: “What do you want to regulate? Are you going to tell the media what they must comply with? I believe the law should not interfere with what journalists do. Our task is to monitor the legislative power, not the other way around.”
But the greater danger lies in opacity. As AI advances, silence is complicity. In other words: by not acting, journalism may end up enabling the erosion of its own credibility.
We propose a middle ground: flexible, evolving guidelines co-created with newsroom staff, legal experts, and ethicists. These should cover sourcing, labelling, verification, and limits—especially for hard news. AI should assist journalism, not impersonate it.
| 2025-06-17T00:00:00 |
2025/06/17
|
https://cfom.org.uk/2025/06/17/seeing-is-believing-journalism-at-a-crossroads-in-the-age-of-synthetic-imagery/
|
[
{
"date": "2025/06/17",
"position": 85,
"query": "AI journalism"
}
] |
Amazon CEO Tells Staffers to Expect AI-Related Layoffs
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Amazon CEO Tells Staffers to Expect AI-Related Layoffs: ‘It Should Change the Way Our Work Is Done’
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https://www.thewrap.com
|
[
"Raquel 'Rocky' Harris",
"Raquel",
"Rocky",
"Harris Is An Audience Writer For Thewrap. She Previously Served As A Senior Multiplatform Reporter For Forbes. Some Of Raquel S Producing Credits Include Former Daytime Talk Show",
"The Real",
"The Nationally-Syndicated Talk Show",
"Dr. Phil.",
"In Addition",
"Her Print",
"On-Camera Work Has Been Featured On Several Platforms"
] |
Amazon CEO Andy Jassy informed staffers that they should anticipate potential layoffs across the company as they expedite the implementation of artificial ...
|
Amazon CEO Andy Jassy informed staffers that they should anticipate potential layoffs across the company as they expedite the implementation of artificial intelligence in an effort to boost and/or improve the customer experience.
“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 wrote in a message to employees on Tuesday. “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.”
The potential layoffs could impact many across Amazon’s workforce, which consists of about 1,556,000 full-time and part-time staffers globally. Jassy mentioned that Amazon now has over 1,000 Generative AI services and applications in progress, adding that the amount is just a small fraction of what the company would ideally like to build.
While noting that Amazon has already shifted into an AI-leaning model, highlighting its rollout of Alexa+ and the use of its AI shopping assistant, Jassy further encouraged workers to become “curious about AI.”
“Educate yourself, attend workshops and take trainings, use and experiment with AI whenever you can, participate in your team’s brainstorms to figure out how to invent for our customers more quickly and expansively, and how to get more done with scrappier teams,” Jassy, who started at Amazon in 1997 as an Assistant Product Manager, wrote.
For now, he shared that Amazon has only scratched the surface in its heavy pivot to AI-powered tools and resources, but added that he believes the technology will “change how we all work and live.”
“Agents let you tell them what you want (often in natural language), and do things like scour the web (and various data sources) and summarize results, engage in deep research, write code, find anomalies, highlight interesting insights, translate language and code into other variants, and automate a lot of tasks that consume our time,” his message continued. “There will be billions of these agents, across every company and in every imaginable field. There will also be agents that routinely do things for you outside of work, from shopping to travel to daily chores and tasks. Many of these agents have yet to be built, but make no mistake, they’re coming, and coming fast.”
Lastly, the executive shared that he’s excited about the future of AI at the company and that he hopes his staff will take part in its journey.
“There’s so much more to come with Generative AI,” Jassy concluded. “I’m energized by our progress, excited about our plans ahead and looking forward to partnering with you all as we change what’s possible for our customers, partners and how we work.”
| 2025-06-17T00:00:00 |
2025/06/17
|
https://www.thewrap.com/amazon-ceo-warns-staff-ai-layoffs/
|
[
{
"date": "2025/06/17",
"position": 4,
"query": "AI layoffs"
}
] |
Amazon announces 'workforce reduction' due to AI
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Seattle-based Amazon announces 'workforce reduction' due to AI
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https://www.fox13seattle.com
|
[
"Ramsey Pfeffinger"
] |
Amazon representatives have announced plans to reduce their workforce amid an increased commitment to implementing AI services across the company.
|
The Brief Amazon is continuing to invest heavily in integrating Generative AI across its services. The company plans to develop AI agents to automate tasks and customer interactions, reshaping workforce dynamics by reducing certain roles.
Amazon representatives have announced plans to reduce their workforce amid an increased commitment to implementing AI services across the company.
The adoption of AI is expected to change the workforce dynamics, potentially reducing the corporate workforce while creating new job opportunities focused on strategic and innovative tasks, said the Amazon CEO Andy Jassy in a Tuesday press release.
However, the CEO said that even though the shift in operations will create some new jobs, the company expects an overall decline in the number of employees.
What they're saying:
"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."
Dig deeper:
The move comes just over a year after the company closed its Tukwila warehouse, impacting 172 workers, and two years after a series of 2023 layoffs and return-to-work orders.
Amazon is reportedly investing extensively in Generative AI to "make customers lives better and easier." across their services such as Alexa+, AI shopping assistants, and advertising tools.
What's next:
Jassy says the company will leverage AI to improve internal operations, such as inventory placement, demand forecasting, and customer service, aiming to enhance efficiency and reduce costs. This will reduce the need for a physical workforce in some departments, according to Amazon.
Corporate employees in Seattle were ordered back to the South Lake Union offices at the start of 2025, leading to increased traffic frustrations among locals.
The Source: Information in this story came from Amazon.
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| 2025-06-17T00:00:00 |
https://www.fox13seattle.com/news/seattle-amazon-layoffs-ai
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[
{
"date": "2025/06/17",
"position": 15,
"query": "AI layoffs"
}
] |
|
New York Becomes First State to Require Disclosure of AI ...
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New York Becomes First State to Require Disclosure of AI-Driven Layoffs
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https://www.aaaa.org
|
[] |
New York has quietly become the first state to require employers to disclose when artificial intelligence contributes to layoffs.
|
New York has quietly become the first state to require employers to disclose when artificial intelligence contributes to layoffs. As of March 2025, amendments to the state’s Worker Adjustment and Retraining Notification (WARN) Act require companies to indicate whether job reductions were influenced by “automation or technological advances,” including AI.
The update does not change when or how employers must issue WARN notices but adds a new transparency requirement. Covered employers—those with 50 or more employees planning mass layoffs, closures, or significant hour reductions—must now check a box on their WARN filing if AI played a role in the decision. The New York Department of Labor has also requested a short explanation when the AI box is selected, though formal guidance remains limited.
| 2025-06-17T00:00:00 |
https://www.aaaa.org/blog/new-york-becomes-first-state-to-require-disclosure-of-ai-driven-layoffs/
|
[
{
"date": "2025/06/17",
"position": 29,
"query": "AI layoffs"
}
] |
|
Amazon chief says AI will mean fewer 'corporate' jobs
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Amazon chief says AI will mean fewer ‘corporate’ jobs
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https://www.ft.com
|
[] |
Technology company bosses have been reluctant to publicly espouse the view that AI will lead to job cuts, preferring to emphasise the increases in efficiency ...
|
Try unlimited access Only $1 for 4 weeks
Then $75 per month. Complete digital access to quality FT journalism on any device. Cancel anytime during your trial.
| 2025-06-17T00:00:00 |
https://www.ft.com/content/9e66ba5b-5403-4e82-b26b-8d72aadf95d4
|
[
{
"date": "2025/06/17",
"position": 57,
"query": "AI layoffs"
}
] |
|
Amazon plans to cut corporate jobs as it turns more to AI
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Amazon plans to cut corporate jobs as it turns more to AI
|
https://www.the-independent.com
|
[] |
People familiar with the matter told The Wall Street Journal that Amazon doesn't expect to have mass layoffs soon. Amazon laid off more than 18,000 ...
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Your support helps us to tell the story Read more Support Now From reproductive rights to climate change to Big Tech, The Independent is on the ground when the story is developing. Whether it's investigating the financials of Elon Musk's pro-Trump PAC or producing our latest documentary, 'The A Word', which shines a light on the American women fighting for reproductive rights, we know how important it is to parse out the facts from the messaging. At such a critical moment in US history, we need reporters on the ground. Your donation allows us to keep sending journalists to speak to both sides of the story. The Independent is trusted by Americans across the entire political spectrum. And unlike many other quality news outlets, we choose not to lock Americans out of our reporting and analysis with paywalls. We believe quality journalism should be available to everyone, paid for by those who can afford it. Your support makes all the difference. Read more
Amazon CEO Andy Jassy shared his thoughts on generative artificial intelligence Tuesday and said it could lead to a reduction in its corporate workforce over the next few years.
“Today, in virtually every corner of the company, we’re using generative AI to make customers lives better and easier,” Jassy said in a memo shared first with Amazon employees and then the public.
Generative AI is used to create new content.
The executive said Amazon is “investing quite expansively” in generative AI and listed several projects such as Alexa+ that will be able to provide “intelligent answers to virtually any question.”
Amazon CEO Andy Jassy shared his thoughts on generative artificial intelligence Tuesday and said it could lead to a reduction in its corporate workforce over the next few years ( Ian Maule/AFP via Getty Images )
Amazon is also using generative AI in its internal operations, Jassy said, adding, “In our fulfillment network, we’re using AI to improve inventory placement, demand forecasting, and the efficiency of our robots—all of which have improved cost to serve and delivery speed.”
He said the company has more than 1,000 generative AI services and applications either in progress or already built.
But all this innovative work will come at a cost to workers amid fears AI will replace human jobs.
“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 wrote in the memo.
He continued: “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.”
It’s unclear how many workers are expected to be replaced by AI and when. When The Independent reached out to Amazon for comment, it did not give any specific numbers.
People familiar with the matter told The Wall Street Journal that Amazon doesn’t expect to have mass layoffs soon.
Amazon laid off more than 18,000 employees in 2022 and 2023, the Journal previously reported. Those cuts were focused on its devices business, recruiting and retail operations, according to the publication.
The company employed more than 1.5 million full-time and part-time workers as of last December.
| 2025-06-17T00:00:00 |
2025/06/17
|
https://www.the-independent.com/news/world/americas/amazon-layoffs-ai-job-cuts-b2771887.html
|
[
{
"date": "2025/06/17",
"position": 94,
"query": "AI layoffs"
}
] |
Things People Share With ChatGPT That Unknowingly ...
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5 Things People Regularly Share With ChatGPT That Unknowingly Jeopardizes Their Job & Safety, According To An Expert
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https://www.yourtango.com
|
[] |
Studies and analyses have found that 38% of regular users have admitted to sharing sensitive work data with AI tools without their employer's permission, ...
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We're all relying more and more on AI tools like ChatGPT to help us get things done, even if we don't necessarily realize it (Siri and Alexa, anyone?). But while they're a wonder at helping us streamline tasks, a security expert says we're not thinking critically enough about what exactly we're sharing with these tools, and especially about what they might be able to do with our information down the road.
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5 things people regularly share with ChatGPT that put their jobs and safety at risk:
We tend to think of using tools like Claude or ChatGPT as a sort of digital assistant as fairly innocuous (aside from the fact that chatbots are literally sending people down conspiratorial rabbit holes and even into full-blown psychosis, that is). But, experts at digital security firm Indusface say that we're being far too presumptuous about the privacy of what we're entering into those chat prompts.
And the statistics on the matter bear this out. Studies and analyses have found that 38% of regular users have admitted to sharing sensitive work data with AI tools without their employer's permission, including things like customer information and sensitive legal or financial data.
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Not only are AI tools not, you know, humans you can ask to keep a secret, but they're also hackable. And accordingly, data breaches of this kind of information reportedly increased by 60.4% just between February and April of 2023, which coincides with a period of exponential user growth of ChatGPT following its November 30, 2022, launch.
Hanging in the balance are not just sensitive details from our jobs, but our own personal details that are often included in the data along with them. Many find it hard to care about their data privacy anymore, since it's basically non-existent, but these breaches also present a risk of being fired from your job if you're found to be at fault for causing these data breaches.
Here are 5 things to avoid sharing with AI tools at work to avoid these situations, according to Indusface.
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1. Work files, such as reports and presentations
These are, of course, riddled with sensitive data about both your company and you yourself. Studies have found that as much as 80% of Fortune 500 employees use tools like ChatGPT to help with things like emails, reports, and presentations. All of which are frequently riddled with sensitive data and often elements that are strictly confidential.
So, security experts recommend removing anything sensitive before inputting these kinds of files into tools like ChatGPT, as large language models, or LLMs, hold onto everything they receive indefinitely and might share your information with other users if prompted.
2. Passwords and access credentials
We've all had it drilled into our heads for decades now that you should never, ever share your password to anything with anyone. But people regularly share them with LLMs while using them to help with tasks, and AI features are embedded in many password management tools.
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"It’s important to remember that [LLMs] are not designed with confidentiality in Mind," Indusface cautioned. "Rather, the purpose is to learn from what users input, the questions they ask, and the information they provide." Proceed with caution.
3. Personal details like your full name and address
Jopwell | Pexels
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Security experts say that while sharing this kind of info is second nature if you're using AI tools as a sort of assistant, doing so throws the doors open to making yourself a victim of fraud. This includes photos of you, including those with other people, by the way.
Indusface said that if it's a piece of information that fraudsters could use to either impersonate you or create deepfakes of you or your associates, it needs to stay off of ChatGPT. These situations could ruin not just your finances but your reputation. And in the latter case, it could also impact your employer's reputation, which Indusface says puts both your employer and you personally in danger of legal action.
4. Financial information
While LLMs like ChatGPT can be very useful in breaking down complex financial topics or even doing financial analysis, security experts say they should never be used for decision-making. This is because, apart from security concerns, LLMs are designed primarily for word-processing, so their numerical literacy can be lacking.
Use them for financial analysis and you're likely to get inaccurate responses, leading to potentially catastrophic mistakes that could cost you your job.
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5. Company code or other intellectual property.
Tech companies are notorious for having incredibly exploitative intellectual property rights written right into their terms of service. Every word of that novel or love note you're writing in that online word-processing platform is open season for being used to train AI LLMs on, for example.
And in a business environment, this means that whatever sensitive company secrets or IP is within the information you're sharing with AI tools is ripe for the picking, too. Using ChatGPT to help with coding is an increasingly popular use, for example, but Indusface said this means that code is in danger of being "stored, processed, or even used to train future AI models, potentially exposing trade secrets to external entities." Once again, this could potentially cost you your job.
The bottom line is that while these tools feel like tech miracles, they need to be used with abundant precautions, because their creators' entire business models are literally dependent on you not taking any.
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John Sundholm is a writer, editor, and video personality with 20 years of experience in media and entertainment. He covers culture, mental health, and human interest topics.
| 2025-06-17T00:00:00 |
2025/06/17
|
https://www.yourtango.com/self/things-people-share-chatgpt-jeopardizes-jobs-safety
|
[
{
"date": "2025/06/17",
"position": 33,
"query": "ChatGPT employment impact"
}
] |
ChatGPT Security Risks in 2025: A Guide to Risks Your ...
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ChatGPT Security Risks in 2025: A Guide to Risks Your Team Might Be Missing
|
https://concentric.ai
|
[
"Mark Stone",
"Karthik Krishnan",
"Lane Sullivan"
] |
... ChatGPT by well-meaning employees just trying to get their work done. And ... What steps do you take to assess impact? Simulate the scenario now, and ...
|
In a dramatically short period, AI has gone from creeping into the enterprise to storming down the boardroom doors with full force. From Microsoft Copilot to Google Gemini to OpenAI’s ChatGPT, generative AI tools have embedded themselves into day-to-day workflows faster than security teams can down their first morning coffee.
We’ve spoken about the risks associated with Copilot and Gemini, but ChatGPT deserves its own spotlight. That’s because it’s the most widely used and the least governed by many organizations.
In this guide, we’ll explore why ChatGPT poses a real threat to enterprise data security if left unchecked.
Why ChatGPT Is Still a Risk Even Without Native Access to Your Files
Unlike Copilot, ChatGPT doesn’t have built-in access to your corporate emails, documents, or Teams chats. Which certainly sounds safer, until you realize how often sensitive data is pasted directly into ChatGPT by well-meaning employees just trying to get their work done.
And therein lies the problem, as they say. ChatGPT’s security risk isn’t really about what it can access, it’s more about what users share, how data is processed, and what guardrails (if any) are in place to stop mistakes from becoming incidents.
Let’s break it down.
Six Security Risks That Make ChatGPT a Threat in 2025
1. Employees don’t think twice about pasting sensitive data
People copy and paste internal data into ChatGPT every day, including customer emails, product roadmaps, and even contract language. That data is then processed and can be retained and used to train future models. Despite OpenAI’s opt-out options, usage habits haven’t changed, and enterprises rarely have visibility into how AI tools are being used at the edge.
2. Attackers weaponize ChatGPT for malware and phishing
Are you a hacker who needs polymorphic malware or a convincing phishing campaign? ChatGPT has got what you need. But wait, there’s more! While OpenAI has added filters to prevent abuse, threat actors continue to jailbreak the system. In one example, they’re disguising prompts as academic questions or penetration tests to generate harmful code or social engineering scripts.
3. Better phishing campaigns to trick employees
What used to be an easy-to-spot email scam now looks like a professional message from your CFO. ChatGPT allows attackers to localize, personalize, and perfect their outreach, especially in spear-phishing and business email compromise attacks.
4. How to be a cybercriminal 101
Every AI prompt is a free lesson. Aspiring hackers use ChatGPT to study exploits, write Python scripts for scanning vulnerabilities, and test basic obfuscation techniques. It makes cyberattacks easier, and cybercriminals stronger.
5. More vulnerable API integrations, more attack surface problems
When companies integrate ChatGPT into internal workflows via APIs, they open a new vector for attacks. Many of these APIs are new, rushed to market, and inconsistently secured, giving adversaries a path into core business systems.
6. No guardrails on how output is used
ChatGPT might generate insecure code or inaccurate analysis, and because it sounds confident, users are more likely to trust it. There’s no sandbox, no enforcement, no review process unless you build one yourself. That turns every output into a potential liability.
How Is ChatGPT Different Than Copilot?
While both tools use OpenAI’s models, their enterprise usage and risk posture are wildly different:
Feature Microsoft Copilot ChatGPT Integration Embedded in Microsoft 365 apps Standalone or via API Security Governed by Microsoft’s compliance framework Requires custom safeguards Data Access Directly accesses company files No native access—but users share data manually Custom Controls Built-in enterprise IT management Must be built from scratch
The takeaway here is that Copilot is governed, but ChatGPT is a wild card unless you lock it down.
Five Ways to Remediate ChatGPT Security Risks
ChatGPT wasn’t exactly built for enterprise use. It doesn’t follow your security policies, respect your compliance boundaries, or ask permission before processing sensitive data. But that doesn’t mean your only option is to block it entirely.
Security teams that win in 2025 aren’t the ones playing whack-a-mole with AI tools and avoiding AI governance; they’re the ones who set up invisible protections that let employees move fast without accidentally blowing holes in their security posture.
Here’s how to rein in the chaos and stay in control, even when ChatGPT isn’t.
1. Control access and integrations
Restrict access to ChatGPT through SSO and enforce a zero-trust model across endpoints. If you’ve deployed ChatGPT via API, use API gateways with OAuth 2.0 and apply encryption in transit to protect data.
2. Monitor AI use and flag sensitive data
Don’t assume employees will know what’s okay to share. Use data security tools to monitor AI-generated and user-submitted content for sensitive data. Bonus points if the tools can do it without relying on rules, regex, or manual classifiers.
3. Deploy smart DLP that understands context
Traditional DLP breaks when data doesn’t match the patterns it expects. Look for tools that label data based on meaning, not format—so even if someone pastes a contract summary or source code into ChatGPT, it gets flagged before it leaves the perimeter.
4. Educate employees, frequently and engagingly
Your AI policy shouldn’t live in a shared document that no one ever reads. Train users on what’s safe to share, how ChatGPT works, and the risks of hallucinations or code reuse. Reinforce with real-world examples and internal phishing simulations.
5. Plan for the worst
Don’t have an AI incident response plan? Time to get on that. If sensitive data is shared with ChatGPT, what’s your remediation process? Who gets notified? What steps do you take to assess impact? Simulate the scenario now, and don’t wait until it happens.
Let Concentric AI Do the Heavy Lifting
ChatGPT isn’t going anywhere (although it does go down from time to time). And banning it outright doesn’t work, because users will find a workaround.
What you need is visibility, control, and the right automation to keep sensitive data from leaking in the first place.
With Concentric AI, organizations get a GenAI taming tool that:
Discovers and classifies sensitive data, even in shared docs, Slack threads, and API payloads
Applies sensitivity labels automatically—no end-user action required
Monitors usage patterns and flags risky behaviors in real time
Detects AI-generated content containing sensitive info before it leaves your environment
No agents. No rules. No maintenance overhead. Just smart, autonomous data protection that thinks the way your users do—and stops the risks they don’t see coming.
Book a demo and see how Concentric AI keeps your generative AI adoption secure, scalable, and under control.
| 2025-06-17T00:00:00 |
https://concentric.ai/chatgpt-security-risks-in-2025-a-guide-to-risks-your-team-might-be-missing/
|
[
{
"date": "2025/06/17",
"position": 56,
"query": "ChatGPT employment impact"
}
] |
|
Jobs Replaced by AI: Top Professions at Risk
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Jobs Replaced by AI: Top Professions at Risk
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https://www.davydovconsulting.com
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[] |
Professions Most Likely to Disappear Due to AI · Taxi Drivers · Accountants · Photoshop Designers · Video Editors · Factory and Plant Workers · Couriers · Fast ...
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Artificial Intelligence (AI) is ushering in a new era across industries, transforming not just how businesses operate but also the nature of work itself. No longer confined to research labs or science fiction, AI now powers real-world tools and services used by millions every day. This accelerating progress is making some traditional roles obsolete while reshaping the landscape of employment. As companies strive to increase efficiency and reduce costs, many positions that once seemed indispensable are at risk of disappearing. This article examines the top professions most likely to vanish in the next five years due to AI, explores those facing partial replacement, and considers which roles are likely to endure despite technological upheaval.
Professions Most Likely to Disappear Due to AI
Automation is rapidly advancing in accuracy, speed, and cost-effectiveness.
Tasks that are repetitive or rules-based are especially vulnerable to AI disruption.
Entire job sectors are already seeing layoffs and shrinking hiring pools as a result.
Businesses are eager to adopt AI to remain competitive and maximise profits.
The following professions are at the top of the list for likely extinction within five years.
Taxi Drivers
Self-Driving Cars Are Already Here
Self-driving cars are no longer a futuristic fantasy—they are already on the roads in cities like San Francisco, Phoenix, and Shenzhen. Major technology companies and car manufacturers have invested billions into the research and deployment of autonomous vehicles. One of the leading examples is Waymo, a subsidiary of Alphabet Inc., which operates a fully driverless taxi service in Los Angeles and San Francisco. Users can book rides through an app, and the vehicles drive without any human intervention. Early pilot programmes like Waymo's are demonstrating that AI-driven taxis can safely and efficiently transport passengers without human drivers. This trend is only accelerating as legislation and public acceptance catch up with the technology. The era of traditional taxi drivers is under immediate threat as more cities embrace driverless fleets.
Efficiency vs. Human Interaction
Autonomous taxis bring unmatched efficiency by operating around the clock without breaks, fatigue, or distraction. While some passengers appreciate the banter or guidance of a human driver, many now value the predictability, reliability, and lower costs that AI-powered vehicles provide. Companies are keen to deploy fleets that never need holidays, call in sick, or demand overtime. Although there may always be a niche for personalised chauffeur services, the mainstream taxi profession is set to dwindle as automation proves its worth. In the end, efficiency and cost savings are likely to trump the human touch for most customers and operators.
Accountants
AI and Automated Bookkeeping
The rise of cloud-based accounting platforms powered by AI has dramatically reduced the need for manual data entry and routine bookkeeping. These systems can automatically categorise expenses, reconcile accounts, generate financial reports, and ensure compliance—all without direct human input. Artificial intelligence can also analyse large volumes of data to identify trends, anomalies, and opportunities for optimisation with remarkable speed and accuracy. As a result, small and medium-sized businesses are shifting away from traditional accountants in favour of these high-powered tools. With continued improvement in AI, the profession of the general accountant is rapidly becoming redundant.
Cost-Effective and Error-Free Systems
Businesses are increasingly drawn to AI bookkeeping solutions because they promise lower costs and fewer mistakes. Manual accounting is not only slower but also more prone to human error and fraud. AI-driven platforms provide real-time insights and automated alerts, empowering business owners to make smarter decisions. This level of oversight and accuracy was previously impossible without a team of experts. As trust in AI accounting grows, companies are moving away from hiring full-time accountants for routine tasks, hastening the profession’s decline.
Photoshop Designers
Generative AI Replacing Human Creativity?
In the past, creating original digital art or manipulating photos required years of experience with complex tools like Photoshop. Today, generative AI models such as DALL-E, Midjourney, and Stable Diffusion can produce breathtaking visuals from simple text prompts in seconds. These platforms are continually learning and evolving, offering ever-greater levels of realism, style, and creative diversity. What once demanded technical mastery and an artist’s eye can now be accomplished by anyone with access to the right AI tool. The very idea of what it means to be a “designer” is being redefined as machines learn to mimic and even surpass human creativity.
The Speed and Scale of AI-Generated Art
AI enables the rapid creation of marketing campaigns, web graphics, and even original artworks at a scale and speed that humans simply cannot match. Entire agencies and content teams are now leveraging these technologies to generate high volumes of visuals on demand. This has major implications for freelance designers and agencies whose business models relied on time-consuming, bespoke work. As AI-generated art becomes mainstream, the demand for traditional Photoshop designers is expected to plummet, with only the most innovative creatives likely to survive. The landscape of digital design will soon be almost unrecognisable compared to just a few years ago.
Retouching vs Art
The traditional work of Photoshop designers often blends technical retouching with artistic creativity, but AI is rapidly encroaching on both fronts. Automated tools can now perform advanced retouching tasks—such as blemish removal, colour correction, background replacement, and even facial feature adjustments—with remarkable speed and precision. One prominent example is FaceApp, a popular AI-driven app that allows users to apply highly realistic transformations to facial images, such as aging, changing hairstyles, or adding smiles. What previously required skilled manual editing can now be done instantly by a mobile app, showcasing how AI is putting powerful tools directly into the hands of everyday users. While human designers once prided themselves on their ability to enhance photographs subtly and tastefully, AI systems can now achieve similar or even better results in a fraction of the time. When it comes to purely artistic manipulation, AI is capable of generating original images, styles, and effects that challenge the boundaries of digital art itself. The distinction between technical retouching and creative artistry is becoming blurred, as AI demonstrates proficiency in both, threatening to make the specialised skills of human Photoshop designers less essential in the evolving digital landscape.
Video Editors
AI Tools Making Post-Production Faster
The video editing industry is experiencing a revolution as AI-driven platforms can now automatically select the best scenes, sync audio, and apply transitions or effects—all at lightning speed. Tools like Descript and Runway ML offer powerful “one-click” editing features, enabling even amateurs to produce professional-quality content. By analysing video content frame by frame, AI can cut hours of tedious manual work, freeing up time and reducing production costs for both individuals and studios. These systems are also capable of adjusting video styles, remastering footage, and even generating entirely new scenes. As AI continues to progress, traditional video editing roles are being phased out in favour of streamlined, automated solutions.
Templates, Effects, and Instant Output
In addition to speed, AI video editors provide access to an ever-growing library of templates, effects, and enhancements that can be instantly applied to any project. This enables content creators to maintain a consistent aesthetic across videos while dramatically reducing the learning curve and effort required. Businesses no longer need to hire specialised editors for basic or repetitive post-production tasks. While some high-level creative direction will always be valuable, most day-to-day editing can now be accomplished faster and more cheaply by machines. The job market for video editors will likely shrink, with demand shifting to those who can oversee and creatively direct AI-driven workflows.
Factory and Plant Workers
Robotics in Manufacturing
Factories have long embraced automation, but the advent of smart robotics and AI is taking this transformation to unprecedented levels. Today’s robots are capable of assembling, inspecting, packaging, and even quality-checking products with minimal human oversight. Machine learning enables these systems to adapt to new tasks, learn from errors, and work collaboratively with other machines in real time. This flexibility is making it possible to automate jobs that were previously considered too complex for robotics. As a result, factory and plant workers who perform repetitive or hazardous tasks are among the most vulnerable to displacement by AI-powered automation.
Machines Don’t Sleep, Humans Do
Robotic systems can operate continuously, day and night, without the need for rest or breaks. This 24/7 productivity provides manufacturers with significant cost savings and efficiency gains, allowing them to meet growing consumer demands. Unlike human workers, machines don’t suffer from fatigue, illness, or lapses in concentration, leading to higher consistency and fewer errors. Companies can also avoid many of the logistical and regulatory challenges associated with managing a large human workforce. The combined advantages of reliability, speed, and cost-effectiveness mean that human factory jobs are rapidly disappearing as robotics technology advances.
Couriers
Drone Deliveries and Autonomous Vehicles
The global logistics industry is at the cusp of a major shift with the introduction of AI-driven drone and autonomous vehicle deliveries. Major players like Amazon, UPS, and DHL are already piloting these technologies, demonstrating their ability to deliver packages swiftly and efficiently. Drones can bypass traffic, deliver goods to hard-to-reach locations, and operate beyond traditional business hours. AI-powered delivery vehicles can plan optimal routes, navigate complex environments, and adapt to changes in real time, reducing the need for human drivers. The rollout of these solutions is set to revolutionise last-mile delivery and make the traditional courier role increasingly obsolete.
The Logistics of the Future
Future logistics will rely on a complex web of interconnected AI systems coordinating vehicles, drones, and robots. These automated couriers can handle a much larger volume of deliveries than any human workforce, operating at lower costs and with fewer errors. As adoption spreads, businesses will transition away from hiring couriers for routine deliveries and focus instead on developing and managing their AI-powered fleets. Although some human oversight may be needed for exceptional cases or technical support, the majority of courier jobs will vanish as technology takes over. The world of logistics is poised for a dramatic transformation driven by automation.
Fast Food Workers
Robot Chefs and Automated Kitchens
Fast food chains are increasingly adopting robotic chefs and automated kitchen systems capable of preparing meals with speed and consistency. AI-powered robots can grill, fry, assemble, and package orders while tracking inventory and ensuring quality control. These systems are designed to minimise waste, improve hygiene, and meet growing demand during busy periods without hiring additional staff. Early trials by leading brands have shown that robots can handle peak workloads and maintain high standards, reducing reliance on human workers. As costs come down and technology improves, automated kitchens are expected to become the industry norm, threatening the future of fast food jobs.
Consistency Over Creativity
Fast food success depends on delivering the same product to every customer, every time. Robots excel at following precise instructions, guaranteeing consistency and efficiency that’s difficult for humans to match. While some culinary creativity remains in menu development or limited-time offers, day-to-day food preparation is increasingly mechanised. Businesses benefit from reduced labour costs, fewer workplace accidents, and more predictable output. In this environment, the human touch is less important, and the role of fast food workers will continue to shrink as automation takes over.
Janitors and Cleaners
Smart Cleaning Robots
Smart cleaning robots are becoming a common sight in offices, airports, hospitals, and shopping centres around the world. These machines are equipped with advanced sensors, cameras, and AI algorithms that enable them to navigate complex spaces, identify dirty areas, and perform targeted cleaning tasks. Capable of vacuuming, scrubbing, mopping, and even disinfecting surfaces, they operate autonomously and with impressive efficiency. Cleaning robots can be scheduled to work outside business hours, ensuring spaces are consistently hygienic without disturbing occupants. As businesses and institutions prioritise hygiene and cost control, the demand for human janitors and cleaners is falling fast.
Hygiene and Efficiency Combined
AI-powered cleaning solutions offer superior performance, adaptability, and record-keeping compared to traditional methods. By collecting and analysing data on usage patterns and cleanliness, these robots can continuously improve and provide detailed reports to facilities managers. Human cleaners are still required for certain specialised tasks or emergencies, but their roles are shrinking as robots take over routine maintenance. The trend is particularly pronounced in large, high-traffic facilities where efficiency and reliability are critical. In the coming years, janitorial work will increasingly be the domain of smart machines, leaving fewer opportunities for human workers.
Lawyers
Automated Legal Analysis and Case Preparation
The legal profession is increasingly susceptible to automation as AI tools become capable of processing vast quantities of legal information faster and more accurately than humans. Modern AI systems can analyse statutes, case law, and legal precedents within seconds, drafting documents and identifying relevant arguments that would take lawyers days or weeks to complete manually. Many routine legal tasks, such as contract review, compliance checks, and even some negotiations, are now being handled by specialised AI software. As these systems continue to evolve, their reliability and efficiency are making them a cost-effective alternative to hiring legal professionals for many standard services. This trend suggests that the majority of day-to-day legal work will soon be managed by intelligent machines, greatly reducing the need for human lawyers.
AI Outperforming Human Judgement in Routine Cases
AI is also beginning to outperform lawyers in certain aspects of legal judgement, particularly in straightforward or data-driven cases. Algorithms can assess risk, predict litigation outcomes, and recommend settlement options based on statistical modelling and historical trends. In areas like traffic disputes, small claims, and document-heavy litigation, AI’s objectivity and processing power often surpass the performance of even experienced attorneys. While complex litigation and high-stakes cases may still require some degree of human involvement, the bulk of legal work is increasingly shifting toward automated platforms. As a result, the legal profession is undergoing a profound transformation, with artificial intelligence set to replace many traditional lawyer roles within the next decade.
Professions Facing Partial AI Replacement
Some jobs are not expected to disappear completely but will be transformed.
AI will automate many routine or administrative aspects, changing how these roles are performed.
Workers will need to develop new skills to stay relevant and employed.
Demand for human input will persist in areas requiring judgement, empathy, or special expertise.
The following professions are examples where AI is making significant inroads but not fully replacing humans.
Bank Workers
Online Banking, But Still Human Support
Online and mobile banking have revolutionised the way customers interact with financial institutions, reducing the need for physical branches and in-person services. AI-powered chatbots and virtual assistants now handle everything from account opening to loan applications, providing 24/7 support. However, not all customer queries or problems can be resolved through automation, especially when it comes to complex financial products or fraud resolution. Human bank workers remain essential for handling nuanced situations and providing reassurance during stressful times. While the workforce is shrinking, there will still be a place for humans where trust and expertise are required.
A Hybrid Approach
Many banks are adopting a hybrid model that blends digital automation with traditional customer service. AI manages routine tasks and queries, freeing up human staff to focus on higher-value or more complex cases. This allows banks to reduce costs without sacrificing service quality or customer satisfaction. Employees who can adapt to working alongside AI systems and develop expertise in financial advice, compliance, or relationship management will continue to be valued. The profession is changing, not disappearing, with the greatest opportunities for those who embrace the new technology.
Customer Service Representatives
When Empathy Is Everything
Customer service is more than just answering questions or solving technical problems—it’s about making customers feel heard, respected, and valued. AI chatbots can provide quick answers for simple queries, but they often fall short when emotions are running high or problems are unusual. Human representatives excel at empathising with customers, defusing tense situations, and finding creative solutions that AI cannot anticipate. In sectors where loyalty and reputation depend on customer experience, businesses cannot afford to leave everything to machines. The ability to listen, understand, and respond with genuine care ensures that the role of customer service representative will continue.
Chatbots Can’t Handle Everything
While businesses are eager to automate as much as possible, they quickly discover that chatbots and virtual agents have limitations. Complex, ambiguous, or sensitive issues frequently require a human touch, particularly when the stakes are high. Customer expectations are rising, and companies that neglect the human element risk losing trust and business. The most successful organisations use AI to handle routine matters while empowering their human teams to resolve more challenging cases. This partnership ensures that customer service remains both efficient and deeply human.
Cashiers
Self-Checkout Systems
Self-checkout systems powered by AI and advanced sensors are now commonplace in supermarkets, department stores, and even small shops. These systems allow customers to scan and pay for their purchases with minimal human intervention, streamlining the checkout process and reducing labour costs. Retailers are also experimenting with fully automated “just walk out” stores where every item is tracked and charged automatically. As more customers become comfortable with these technologies, businesses will further reduce cashier staff. The trend is clear: fewer cashiers will be needed, and their roles will increasingly involve customer support or troubleshooting technology.
But What About the Elderly?
Not all customers are comfortable using self-checkout machines, especially older adults or those unfamiliar with digital payment methods. Many stores are maintaining some staffed checkouts to assist customers with special needs, handle cash payments, or resolve technical issues. Human cashiers also play an important role in providing personal service, answering questions, and preventing theft. However, even these functions are being gradually automated or supplemented by AI-driven security and support systems. The cashier profession is shrinking, but it is unlikely to disappear entirely in the near future.
Certain Medical Specialists
Diagnostics Over Empathy
Some medical specialities—particularly those focused almost exclusively on diagnostics, such as radiology and pathology—are increasingly seeing the rise of AI-powered systems. Advanced algorithms can now analyse medical images and test results with remarkable speed and accuracy, often outperforming humans in detecting subtle patterns or early signs of disease. For routine screenings and clearly defined cases, AI can process massive amounts of data in a fraction of the time, leading to faster diagnoses and potentially better outcomes. In these areas, the task is highly structured and data-driven, leaving little room for the interpersonal skills or empathy that are so vital elsewhere in medicine. As a result, the reliance on human specialists may decrease significantly as automated diagnostics continue to improve.
Routine Cases Don’t Need a Human Touch
For many straightforward medical cases—such as identifying common infections on X-rays or flagging abnormal blood results—AI systems have proven to be highly reliable and cost-effective. These tools can provide instant feedback to both patients and primary care providers, streamlining workflows and reducing bottlenecks in healthcare delivery. As a result, patients may receive diagnoses and treatment recommendations faster and with fewer errors. However, while AI can handle the bulk of routine cases, human expertise will still be required for ambiguous findings, rare diseases, or when results require integration with complex patient histories. The trend suggests that, over time, human medical specialists will focus more on the most complex and nuanced cases, while AI takes over much of the repetitive, routine diagnostic work.
Professions That Will Likely Stay Human
Some roles require skills, judgement, and emotional intelligence that AI cannot replicate.
Human interaction is essential for building relationships, trust, and rapport.
Careers that depend on empathy, creativity, or advocacy are more “AI-proof.”
Workers in these fields must still adapt and evolve, but are less likely to be replaced.
The following professions are expected to endure despite advances in automation.
Occupations that require supervision because they deal with human safety with people.
Receptionists
First Impressions Matter
Receptionists are often the first point of contact for visitors and clients, setting the tone for an organisation’s reputation and relationships. Their responsibilities extend beyond greeting people—they manage schedules, field enquiries, and address unexpected issues on the fly. The ability to read body language, respond empathetically, and build rapport are qualities that even the most advanced AI systems cannot replicate. In many sectors, especially those that value personal connection and hospitality, the human receptionist remains irreplaceable. While technology can assist with some tasks, the subtlety of first impressions is still best left to people.
Emotion Can’t Be Programmed
Automated kiosks and digital check-ins are becoming more common, but most businesses continue to rely on human receptionists for their emotional intelligence and adaptability. Humans can pick up on subtle cues, provide reassurance, and handle sensitive or confidential matters with discretion. These skills are vital in high-stress environments like healthcare, law, and corporate offices, where a personal touch can make all the difference. While AI can supplement receptionist roles with scheduling or information provision, it cannot replace the human warmth and intuition that make this job special. The receptionist’s role is likely to endure, albeit in a more technology-augmented form.
Teachers and Educators
More Than Just Information Delivery
The impact of teachers extends far beyond simply imparting facts or grading assignments. Effective educators inspire curiosity, foster critical thinking, and adapt their approach to suit the individual learning styles and needs of their students. While AI and online platforms can deliver lectures and automate assessments, they lack the flexibility and insight required to spark genuine intellectual growth. Teachers bring context to lessons, share personal experiences, and cultivate a classroom culture where students feel motivated and supported. Education is as much about nurturing potential as it is about delivering content, and this human element cannot be replicated by machines.
Emotional Support and Mentorship
For many students, teachers are mentors, role models, and sources of emotional support throughout their academic journeys. They notice when a student is struggling, offer encouragement during setbacks, and celebrate achievements both big and small. Educators help students develop resilience, confidence, and social skills—abilities that extend well beyond academic success. In challenging times, the presence of a caring teacher can be a stabilising force, offering guidance and a sense of belonging that AI cannot provide. The relationships forged between teachers and students are fundamental to personal development and lifelong learning, making the human role in education irreplaceable.
Scientists (Human Researchers)
Why Human Curiosity Can’t Be Coded
The role of scientists and human researchers is fundamentally shaped by curiosity, a drive to ask new questions, and a willingness to challenge assumptions—qualities that are difficult, if not impossible, to program into AI. While machines can process vast datasets and simulate experiments at incredible speed, they still rely on human input to define research questions, frame hypotheses, and interpret unexpected results. Human researchers possess the flexibility to shift focus, spot anomalies, and pursue unconventional ideas that may initially seem illogical to a machine. It is often in these moments of inspired curiosity that breakthrough discoveries occur. AI is a powerful tool, but it cannot replace the spontaneous, questioning spirit that propels science forward.
Creativity and Intuition in Research
Great science is as much an art as it is a methodical process, drawing heavily on creativity, intuition, and even a sense of wonder. Human researchers are able to synthesise knowledge from disparate fields, invent new methodologies, and imagine possibilities beyond the boundaries of current understanding. They recognise patterns, propose bold theories, and adapt to surprises in ways that go far beyond programmed logic. Many scientific advancements arise not from predictable procedures, but from serendipity, inspired leaps, and intuitive insights—all products of the human mind. As AI becomes more integrated into research, it will serve as an invaluable assistant, but the leadership and creative spark will always come from people.
Why Human Communication Still Matters
Some aspects of work can never be fully captured by algorithms or automation.
Building relationships, trust, and loyalty depends on genuine human interaction.
Emotional intelligence remains a uniquely human strength.
Even the most sophisticated AI lacks intuition, creativity, and cultural understanding.
Human communication is the foundation of personal and professional success.
The Irreplaceable Human Touch
Trust and rapport are built over time through consistent, caring, and authentic interactions.
Moments of kindness, understanding, or support create lasting impressions and drive loyalty.
AI can simulate dialogue but cannot provide the same comfort, reassurance, or sense of connection as a real person.
As automation spreads, organisations that prioritise human relationships will have a competitive advantage.
The future of work will always have a place for those who bring empathy and authenticity.
Genuine connection comes from shared experiences, understanding, and empathy—qualities that machines simply cannot replicate. Whether it’s a comforting word during a crisis or a reassuring smile at a first meeting, these moments have a profound impact. In business and in life, trust is built not just on efficiency or accuracy, but on care and authenticity. AI can simulate conversation, but it cannot replace the feeling of being truly understood and valued. As technology becomes ever more present, the human touch will only become more important.
Emotional Intelligence vs. Artificial Intelligence
Emotional intelligence includes self-awareness, empathy, and social skills—areas where AI still falls far short.
Machines can mimic tone or language but lack true understanding of human feelings and motivations.
People are uniquely equipped to handle ambiguity, conflict, and rapid change, using intuition and creativity.
These qualities are vital in leadership, negotiation, and customer-facing roles.
AI will improve, but emotional intelligence will remain a distinctively human strength.
Emotional intelligence encompasses skills like empathy, self-awareness, and social awareness—none of which AI can truly possess. While machines may learn to mimic human emotions or tone, they do so without genuine understanding or context. People bring creativity, intuition, and adaptability to every interaction, allowing them to navigate ambiguity and respond to the unexpected. These abilities are crucial in leadership, negotiation, and customer relations, where outcomes depend on more than logic or data. AI will continue to advance, but emotional intelligence will remain the defining feature of human communication.
AI Can’t Replace Trust
Trust develops through reliability, transparency, and emotional connection—qualities machines cannot replicate.
Customers and clients seek advice, support, and understanding from people they know and respect.
While AI can deliver information and consistency, it cannot build long-term loyalty or partnership on its own.
Businesses that nurture trust and human connection will stand out in an automated world.
The human element will always matter, no matter how advanced technology becomes.
Trust develops over time through consistent behaviour, transparency, and emotional connection. While AI can provide instant answers and reliable service, it cannot build the kind of trust that forms the basis of long-term relationships. People seek reassurance, advice, and understanding from those they know and respect—qualities that technology cannot supply. As workplaces become more automated, organisations that prioritise trust and human connection will stand out. The future belongs to those who recognise the irreplaceable value of real human relationships.
Preparing for the Future
The future of work will require adaptability, curiosity, and a willingness to change.
Upskilling and reskilling are essential for staying relevant in an AI-driven world.
AI-proof careers focus on uniquely human abilities like creativity and problem-solving.
Workers must embrace technology and learn to work alongside intelligent machines.
Proactive planning is the best way to ensure long-term career success.
Upskilling and Reskilling
Workers should pursue continuous education, learning both technical and soft skills that are valued in the modern workplace.
Courses, certifications, and hands-on experience help people pivot to new industries or advance within their current fields.
Organisations, governments, and individuals must invest in training to keep pace with technological change.
By developing abilities AI cannot match—such as critical thinking, leadership, and emotional intelligence—workers become more “future-proof.”
Lifelong learning is the key to thriving, not just surviving, in a world of constant change.
To thrive in the coming era, workers must commit to lifelong learning and skill development. This means not only mastering new technologies but also enhancing abilities that set humans apart—such as critical thinking, emotional intelligence, and creativity. Training programmes, online courses, and on-the-job learning opportunities are more accessible than ever, making it possible for anyone to pivot or grow. Governments, businesses, and individuals all have a role to play in supporting reskilling initiatives. By embracing change, workers can turn disruption into opportunity and future-proof their careers.
Choosing AI-Proof Careers
Roles in healthcare, education, creative arts, and skilled trades remain in demand because they require judgement, empathy, or physical skill.
Even in high-tech fields, jobs focused on innovation, strategy, and people management are less likely to be automated.
Identifying opportunities where human strengths matter most helps individuals future-proof their careers.
Investing in specialisation and expertise makes workers more valuable and harder to replace.
Career resilience comes from focusing on areas where people, not machines, make the biggest difference.
Certain jobs will remain relatively insulated from automation because they require skills that machines cannot easily mimic. Healthcare, education, the creative arts, and skilled trades all rely on judgement, empathy, and hands-on expertise. Workers in these fields will continue to be valued, especially as populations age and the demand for personal services grows. Even within high-tech industries, roles focused on innovation, strategy, and people management are less susceptible to automation. The key is to identify opportunities where human strengths offer a competitive advantage and to invest in developing those abilities.
Embracing Technology, Not Fearing It
AI should be viewed as a tool that can augment human abilities and productivity, not a direct threat.
Those who adopt new technologies and learn to collaborate with intelligent systems will find new opportunities for growth.
A proactive, curious mindset enables people to spot trends early and stay ahead of disruption.
The most successful workers will integrate AI into their roles, using it to eliminate drudgery and focus on higher-value tasks.
Embracing change leads to innovation, satisfaction, and long-term career security.
AI should be seen as a partner rather than an adversary. By leveraging technology, workers can achieve more, focus on higher-value tasks, and create new sources of value. Those who adopt a growth mindset, seek out new tools, and experiment with new ways of working will be better prepared for whatever the future brings. Rather than resisting change, successful professionals will lead the way in integrating AI into their roles. The most resilient workers will be those who see technology as a means to enhance—not replace—their own abilities.
Final verdict
| 2025-06-17T00:00:00 |
2025/06/17
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https://www.davydovconsulting.com/post/top-professions-that-will-disappear-in-the-next-5-years-due-to-ai
|
[
{
"date": "2025/06/17",
"position": 37,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/17",
"position": 79,
"query": "future of work AI"
}
] |
Think AI Is Killing Early-Career Jobs? The Truth May ...
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Think AI Is Killing Early-Career Jobs? The Trut...Entry Level Jobs
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https://www.collegerecruiter.com
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[
"College Recruiter"
] |
On the more negative side, AI and automation can replace or reduce the need for certain entry-level roles. Many tasks that used to be done by fresh hires or ...
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Earlier today, I was a panelist on the June Talent Market Index webinar about the early-career job market, hosted by Talivity, the parent company of recruitment advertising agency, Recruitics.
On the panel with me was Michelle Schwartz, Director of the University of Montana’s Gianchetta Student Success Center and Internships in its College of Business. Our cohosts were Talivity’s Mona Tawakali, Chief Strategy Officer, and Jonathan (JZ) Zila, President.
The conversation centered on why the job market for students and recent graduates has gotten softer than it was a year ago. As expected, most of the discussion zeroed in on the impact of artificial intelligence (AI). Is AI the big job-killer for new grads? We agreed that AI is one factor, but it’s not the whole story. In fact, the truth may surprise you: there are several other powerful forces at play, many of which we didn’t have time to delve into during the webinar.
Mona kicked off the webcast with an overview of the cost of hiring across various industries. Interestingly, she noted that in some industries – notably tech and healthcare – the cost per hire has increased compared to a year ago, while other sectors have actually seen hiring costs stabilize or even drop. She cited causes like tariffs, changes in immigration policy, and other macroeconomic shifts as drivers of these cost differences. This set the stage for our discussion: clearly, something bigger is happening in the job market beyond just AI coming onto the scene.
When JZ led the Q&A portion, Michelle and I shared our perspectives on why the early-career job market has cooled for most students and recent grads. We acknowledged AI’s role in that cooling, but time ran short before we could explore the other reasons for the downturn. After the webinar, I found myself thinking about those unspoken factors and decided to flesh them out here. In total, I believe that there are five key reasons behind the softer market for entry-level jobs.
1. The Post-COVID Economic Cooldown
The first and most wide-ranging factor is the overall economy. To put it bluntly, the job market today just isn’t as red-hot as it was during the post-COVID hiring boom of 2021–2022. Back then, as the pandemic eased, companies were in a frenzy to hire and rebuild. There was pent-up demand, businesses were growing fast, and many employers couldn’t fill roles quickly enough, which meant great opportunities for new graduates. We saw signing bonuses, rapid promotions, and a mindset of “hire now, figure it out later” as organizations scrambled to staff up.
Fast forward to now, and that feverish boom has cooled significantly. Economic growth has slowed from its breakneck pace, and many industries are facing headwinds. High inflation through 2022 and into 2023 forced a lot of companies to tighten their belts as costs rose for everything from raw materials to salaries. The Federal Reserve also responded by raising interest rates steeply to combat inflation. Higher interest rates have made borrowing money more expensive for businesses. For a growing company, the cost of taking out loans to expand (or even just to cover operating expenses) is much higher than a couple of years ago. As a result, many firms have cut back on expansion plans and, by extension, on hiring. When companies scale back growth projections, entry-level hiring often takes an early hit – they might decide they can get by without that new cohort of trainees or postpone a planned new grad program until things look rosier.
Another economic pressure has been the ongoing tariffs and trade uncertainties that date back several years but continue to affect industries like manufacturing, technology, and agriculture. Tariffs on imported components or materials raise production costs, which can lead companies to reduce costs elsewhere, often by automating processes or reducing labor costs. A tech hardware company, for example, facing higher import costs for components, might slow down hiring in order to keep expenses under control. In our webinar, Mona pointed out that tech and healthcare have become more expensive in terms of cost-per-hire; tariffs and supply chain issues contribute to that by making key inputs pricier and margins tighter. If a hospital has to pay more for imported medical equipment due to tariffs, it might hire fewer support staff. If a software company finds its cloud hosting or hardware costs rising, it might respond by pausing on adding that extra junior developer. These ripple effects mean fewer new jobs are created than we might have expected in a more free-flowing trade environment.
Policy changes also play a role here. Changes in immigration policy over the last few months have made it harder in some cases for companies to hire foreign talent or even retain workers on certain visas. At first glance, you might think, “How does that hurt new grads who are U.S. citizens?” Well, it has a complex effect. In some high-skill sectors like tech and healthcare, if companies can’t get the experienced talent from abroad that they need (say, a specialized software engineer or a foreign-trained nurse), they sometimes leave roles unfilled or relocate projects offshore, rather than hiring a recent local graduate who may not have the precise skills. In other cases, stricter immigration rules can raise labor costs (employers might have to pay more to attract domestic talent or deal with shortages), which again can tighten hiring budgets company-wide. It’s an indirect connection, but it contributes to the general slowdown in hiring momentum.
One often-overlooked piece of the economic puzzle is a change in the 2017 U.S. tax code that has only recently started to sting companies’ finances. This is the rule that now requires employers to amortize certain capitalized expenses in five or fewer years if the work is done in the United States, versus fifteen years if the work is done abroad. In plainer language: let’s say a company spends a bunch of money on research and development or other capital projects. Under this rule, if those activities (and the jobs associated with them) happen on U.S. soil, the company can’t deduct the full costs right away for tax purposes – it has to spread the deduction out over five years. If the same R&D were done overseas, the deduction is spread over a much longer period (fifteen years), which is even less attractive in the short term.
The intent might have been to incentivize domestic investment by at least giving a faster write-off for U.S. projects than foreign ones, but in practice, it’s been a headache. Companies, large and small,l have complained that this change ties up their cash flow and makes U.S.-based projects comparatively expensive and less appealing. How does that translate into hiring? If a firm decides not to invest in that new U.S. research lab or software development project because the tax treatment makes it cost-prohibitive this quarter, that also means they’re not hiring the team of engineers or analysts that would have run it. Some companies have indeed started looking to shift certain projects overseas (despite the longer amortization there, it can still be cheaper overall due to labor cost differences), or they’ve canceled projects entirely. That directly reduces job opportunities for entry-level workers who might have been hired into those projects. It’s a somewhat hidden factor – you won’t see “tax amortization change” trending on X (formerly Twitter), but it’s affecting hiring budgets in a very real way.
All of these elements – inflation, high interest rates, tariffs, immigration shifts, quirky tax rules – add up. They contribute to an economic environment where companies are more cautious and operating costs are higher. When the economy was booming, employers could afford to take chances on new grads, bring in extra hands, and invest in training. In today’s cooler climate, many firms are asking themselves, “Do we absolutely need to hire right now?” If the answer is no, they often choose to wait. Unfortunately, that cautious approach hits those at the start of their careers the hardest, because entry-level roles are easier to put on hold than essential senior positions. The result is a tougher market for almost all candidates in almost all sectors, and especially for young people trying to get that first foot in the door.
2. Artificial Intelligence – Scapegoat, Boogeyman, and Benefactor
Now let’s talk about the factor everyone’s been buzzing about: artificial intelligence. It’s true that AI is having a profound impact on the labor market, including early-career jobs. But its role is complex – AI is simultaneously a job killer in some respects and a job creator or enhancer in others. We need to unpack both sides to understand why AI’s rise contributes to a softer job market for new grads, but also why it’s not the sole culprit (and could even be part of the solution for some job seekers).
On the more negative side, AI and automation can replace or reduce the need for certain entry-level roles. Many tasks that used to be done by fresh hires or interns can now be handled by algorithms, chatbots, or software robots. For instance, consider an entry-level customer support representative – nowadays, companies increasingly use AI-driven chatbots to handle routine customer inquiries. That means they might hire fewer support reps than before, and perhaps favor those with more specialized skills to handle only the complex cases. Another example is in marketing or content creation, where a junior marketing coordinator might have once spent hours drafting social media posts or basic copy, tools like generative AI can produce decent first drafts in seconds. A manager might think, “I don’t need an extra assistant if our AI can crank out the basic work and my current team can just edit it.” We’re seeing similar trends in fields like law (AI legal research tools reducing the need for as many paralegals to sift through cases) and finance (automated analysis tools handling what junior analysts used to do late at night in Excel). If a task is repetitive and rules-based, there’s probably an AI out there being deployed to tackle it. And who typically starts off doing the repetitive grunt work? New grads. So it’s no wonder that AI is often portrayed as the big bad wolf eating entry-level jobs.
However, that’s not the whole story. There’s a more optimistic flip side: AI is also enabling new opportunities and more efficiency, which can actually encourage some hiring or at least reshape it. Think about how personal computers in the 1980s or the internet in the 1990s created whole new job categories – AI is doing the same right now. Entire new fields and roles are emerging, from prompt engineering (getting AI systems to produce the desired output) to AI ethics consultants to data labeling for machine learning. A college student graduating in 2025 might land a job that literally didn’t exist five years ago, like “AI marketing campaign strategist” or “junior machine learning ops specialist,” which are roles companies are inventing as they integrate AI into their operations. In that sense, AI is a job creator, not just a destroyer.
Moreover, AI can make existing employees more productive, which, in a counterintuitive wa,y can make it feasible for employers to hire when they otherwise wouldn’t. Here’s how: if one entry-level hire can now accomplish what used to take two people (thanks to AI tools boosting their output), an employer might justify hiring that one person and giving them an AI toolset. Without AI, the company might have decided hiring two was too expensive and hired nobody at all. In other words, some employers are willing to bring on a junior employee because that person, augmented with AI, can generate more value than they cost. We talked about this a bit on the webinar: AI helps some candidates by increasing their productivity and value-add, essentially raising the ceiling of what a new grad can handle. A single developer straight out of college, armed with AI code assistants, might produce as much useful code as a small team could a few years back. For a resource-strapped startup, hiring that one AI-empowered grad is a bargain.
Of course, this “AI augmentation” argument is a small comfort to the folks whose roles are simply being eliminated or whose job offers have disappeared because a machine does it now. On balance, is AI making it harder or easier for new grads? At this moment, the prevailing sentiment (and likely reality) is that AI is contributing to a net reduction in certain traditional entry-level openings. Many employers have publicly said they’re slowing hiring in areas where automation can handle the work. Even during our panel, you could tell from the conversation that people largely blame AI for the tougher job landscape. In many ways, AI has become a scapegoat for any hiring slowdown – it’s the shiny new thing to point to.
But as I’ve just outlined, AI is not acting alone, and it might not even be the biggest factor everywhere. It’s one piece of a larger puzzle. Yes, early-career job seekers should be aware of AI’s impact – meaning they should aim to develop skills that complement AI (such as creative thinking, interpersonal communication, adaptability) or skills in operating and leveraging AI tools themselves. The bottom line on AI: it’s a factor, perhaps the flashiest one, in the cooling of the entry-level market. It certainly feels like the ground shifting under our feet when a new technology can do some of our work. But focusing on AI alone misses the many other undercurrents that are just as influential in shaping the job landscape.
3. Skills-Based Hiring and a Broader Talent Pool
Another significant shift in the job market – one that hasn’t gotten as many flashy headlines as AI but is hugely important – is the rise of skills-based hiring. Over the past few years, a lot of employers (including some of the biggest companies and even government agencies) have been dropping the requirement of a four-year college degree for roles that traditionally insisted on one. Instead, they’re focusing more on the specific skills and competencies a candidate brings. This trend is often summarized as “skills over degrees.”
On the surface, this is a positive development, especially from an equity standpoint. It opens up opportunities to talented individuals who, for whatever reason, don’t have a college diploma but do have the ability to do the job. It helps employers fill roles in a tight labor market by widening the funnel of candidates. And it addresses the issue of “degree inflation” – where jobs that don’t truly require a degree have started listing it as a default requirement. In fact, some studies showed that in 2017, about 51% of job postings required a bachelor’s degree. By 2021, that number had fallen to around 44%, reflecting this shift toward skills-based evaluations. Companies like IBM, Google, Bank of America, and many others have publicly embraced hiring people without degrees for certain roles, and numerous state governments (from Maryland to Alaska to North Carolina, to name a few) have eliminated degree requirements for a large portion of their own job listings. This means that someone with the right coding skills but no B.S. in Computer Science might land a software job that previously would have been off-limits, or an experienced manager without a degree could run a store or a team where once only college grads were considered.
So what’s the catch? Why would a move that sounds fairer and more inclusive contribute to a tough market for new college graduates? The answer is competition. If you’re a recent grad with a shiny new diploma, you’re now competing not just against your fellow graduates for a given job, but potentially against a whole new swath of candidates who may have years of experience or training but no degree. The talent pool for many entry-level positions has effectively broadened. For example, a marketing assistant position might have been open only to degree-holders a few years ago. Today, that same position may be open to anyone with relevant skills, so you might find yourself up against a candidate who spent the last four years doing digital marketing freelance work instead of getting a college degree. They might not have a Bachelor’s, but they have a client portfolio and practical know-how. That’s tough competition! Similarly, consider an IT support role: previously, a company might have only considered computer science grads. Now they might consider someone who went to a coding bootcamp or learned IT through military service. If you just finished college with an IT degree and little hands-on experience, suddenly you’re on equal footing with (or at a disadvantage to) someone who’s been tinkering with networks in the real world for a few years.
In short, skills-based hiring has broadened the labor pool for what used to be “college-grad jobs.” That’s great for employers and for non-graduate workers, but it means college students and recent grads don’t have the same automatic leg-up they used to. A degree used to act as a sort of gatekeeping credential for a majority of jobs; now, less than half of postings require it. We removed the gate, so more people can run onto the field, which is a more meritocratic game, but also a more crowded one. Employers are seeing more applicants per position, which allows them to be pickier and raise the bar on what entry-level means. They might say, “Well, we’re not requiring a degree, but now we expect either a degree or two years of relevant experience or a professional certificate.” Either way, new grads find themselves needing to prove actual skills and experience, not just rely on their college transcript.
There’s also an interesting possibility on the horizon: some labor economists at Georgetown University’s Center on Education and the Workforce project that by 2031, roughly 72% of all jobs will require some form of postsecondary education or training (i.e., college degrees or similar credentials). That projection, which is a big jump, suggests that as the economy evolves and jobs get more specialized, the pendulum might swing back toward needing advanced education. In other words, we might be in a temporary trough where degrees are less emphasized, but as technology and skill demands rise (think about the proliferation of data science, cybersecurity, biotech – fields that often need high levels of training), formal education could become important again to fill the pipeline for those roles. If that prediction holds true, by the end of this decade, employers might once more be leaning heavily on college-educated talent, potentially squeezing out those without degrees.
But that’s the future. Right now, in the current moment, the reality is that skills-based hiring has “leveled the playing field” in a way that actually levels down the prospects for new grads. It used to be that a college degree would guarantee you at least an entry ticket to a decent job competition; now, it’s just one of many possible tickets. I often advise students and recent grads to highlight the specific skills and projects they’ve done, not just to wave around a diploma. That’s what employers want to see in this new paradigm. The upside is, if you have the skills and can demonstrate them, you might also apply to jobs that you thought were out of reach because they seem to prefer experience over education. But generally, this trend means more applicants per entry-level job and thus a tougher time landing one. It’s a subtle factor, but when layered on top of the economic slowdown and AI, it’s part of the reason this job market feels so challenging.
4. Skyrocketing College Costs and the Pressure for High-Paying Jobs
This next factor is a bit more personal and psychological, but it has real labor market consequences: the soaring cost of attending college and the resulting burden of student loan debt. Over the past couple of decades, college tuition and fees have increased dramatically, far outpacing general inflation and wage growth. Many students are graduating with significant debt loads – sometimes tens of thousands, in some cases over $100,000 for those who pursued pricey private schools or multiple degrees. Even those who avoided loans often did so by stretching their families’ finances or working multiple jobs during school. The net effect is that a huge number of recent graduates feel intense financial pressure as they step into the workforce.
Why does this matter for the early-career job market? Because graduates with heavy debt or high expense burdens are often constrained in the kinds of jobs they can accept. If you owe $600 a month in student loan payments, plus rent, plus maybe helping out your family, you’re likely looking for the highest-paying job you can get right out of the gate. That’s rational – you need to make those payments. But it also means many new grads might ignore or reject decent entry-level jobs that don’t pay enough, hoping to land something in a better-paying industry. For example, a talented graduate might love to work at a nonprofit, or as a teacher, or in a government entry role, but those typically pay modest salaries. If they’re staring at their loan statements, they may instead go for a consulting job, a software engineering role, an investment banking analyst slot – something with a starting salary that promises a quicker path to financial stability.
The problem is, those higher-paying entry-level jobs are fewer in number and extremely competitive. Not everyone who wants a $90,000 starting salary can get one. So what happens to the grads who won’t take (or can’t afford to take) the $50,000 job? Some end up underemployed or unemployed for a while, holding out or going from internship to internship, trying to break into a lucrative field. Others might attempt the gig economy or side hustles while searching for that ideal role. This dynamic can push up unemployment among recent graduates, specifically. We’re actually seeing this in the data: the unemployment rate for young people with bachelor’s degrees is higher than the overall unemployment rate for all college grads. It’s not because the economy doesn’t have jobs – it’s because there’s a mismatch between what new grads are looking for (or need financially) and what’s available to them as entry points.
To put it another way, the opportunity cost of taking a low-paying job right out of college has gone up because the stakes, like student loan repayment, are higher. And more graduates are saying “no thanks” to jobs that don’t meet the salary bar they require, which means they remain job seekers for longer. That, in turn, makes the cohort of recent grads as a whole have higher jobless numbers than one would expect in an otherwise decent economy. It’s a bit of a self-inflicted wound, but it’s hard to blame individuals; the system kind of set them up this way by making higher education so expensive. When I graduated in the (ahem) 20th century, I had friends who took very low-paying starter jobs (in journalism, social work, the arts, etc.) and lived with several roommates or ate ramen for a year or two – but crucially, many of them didn’t have student loans. They could afford to “struggle now to build experience” because they weren’t lugging a ball-and-chain of debt. Today’s graduates often don’t have that luxury. If you have a $1,000 loan payment kicking in six months after graduation, you might think twice about any job that doesn’t allow you to comfortably make that payment.
This phenomenon has a macro effect: fewer graduates are filling the plentiful lower-paying entry jobs, leaving those roles either vacant or filled by non-graduates, and more graduates are competing fiercely for the limited higher-paying entry jobs (like those at Fortune 500 companies, big tech, finance, etc.). If they don’t get those coveted roles, they sit on the sidelines or take a series of short-term gigs, all the while still applying for the next opening that looks like it could cover their bills. Thus, we see more “educated young unemployed” even as employers in some sectors say they can’t find enough entry-level talent. It’s a paradox fueled by the cost of college and the distribution of wages in entry-level work.
Lastly, the high cost of college is also causing some people to opt out or drop out, meaning a smaller percentage of young people even attend or finish college than might have if it were affordable. While on one hand, that could reduce competition among degree-holders, it also means some potential talent never went through that early professional pipeline at all, which can hurt certain fields. But the main point here is the increased selectivity of graduates in their job search. I can’t count how many times I’ve heard a student say, “I have to earn at least X or I can’t make ends meet after graduation.” That financial reality narrows their search and ironically can leave them empty-handed for longer. It’s contributing to why you hear stories of graduates being underemployed – working part-time jobs that don’t require a degree while they hunt for something better, or living at home longer because they haven’t secured that solid income yet. All of this feeds into the perception (and reality) that the early-career job market is tough. It’s not necessarily because there are no jobs; it’s also because the stakes for the grads are so high that any job will do, and so more of them end up with no job rather than taking one that doesn’t meet their needs.
5. Government Downsizing Floods the Labor Market
One factor many people overlook when considering the entry-level job landscape is what’s happening in the federal government workforce. In the past year or so, there’s been an unprecedented reduction in federal jobs due to aggressive downsizing by the current administration’s Department of Government Efficiency (DOGE) initiative. President Trump, working closely with a team led by Elon Musk in this effort, has set out to dramatically shrink the federal payroll, and the numbers are staggering. We’re talking hundreds of thousands of jobs in the process of being cut or already eliminated. Entire agencies are being gutted or reorganized; hiring freezes and mass layoffs have been implemented across many departments. Just to illustrate, earlier this year, the Department of Agriculture offered about 15,000 employees a buyout package to resign. Tens of thousands of newer federal employees (those on probationary periods) were abruptly let go in a single sweep. Plans have been drawn up to reduce headcounts by huge percentages in various departments – some aiming for 40-50% cuts in staff. While court challenges have paused some of these actions, the direction is clear: the federal government, long one of the nation’s largest employers (and a great source of stable jobs for new grads through programs like the Pathways internships and entry-level analyst roles), is undergoing a massive contraction.
So, what does that have to do with the early-career job market? Two big things: increased labor supply and decreased entry-level openings. First, when you lay off a federal employee, that person doesn’t just disappear from the economy – they typically start looking for a new job elsewhere, often in the private sector or with state/local government, or government contractors. Multiply that by the many thousands, and suddenly you have a surge of job seekers entering the market. Many of these folks have experience, even if just a couple of years, and they might be vying for some of the same positions recent graduates are aiming at. For example, consider a 24-year-old who spent the last two years as an IT specialist at a federal agency, and now that position has been cut. That individual is now out there applying to tech companies or consulting firms, possibly for junior or mid-level roles. If you’re a brand-new computer science grad, you could find yourself interviewing for a job alongside that former federal employee who has actual workplace experience. That can make it harder for the true entry-level candidate to win the spot.
Even more directly, the government cuts also mean fewer entry-level jobs available in the government itself. Traditionally, a good chunk of new grads – especially those with degrees in political science, public administration, international relations, computer science, and many other fields – would find early-career opportunities working for the federal government. These could be roles like an analyst at the Department of Labor, a budget assistant at the Department of Education, a research assistant at a federal lab, etc. Those opportunities are drying up right now. With a hiring freeze and downsizing, agencies are not bringing in the usual cohort of fresh talent. In fact, some agencies are rescinding offers or cutting internship programs. For instance, it’s been reported that agencies like the Consumer Financial Protection Bureau, Voice of America, and even the US Agency for International Development have had virtually all their staff (including presumably new hires) put on leave or let go as part of the cuts. The pathway for a young person to start a career in federal service is narrowing, at least for the time being.
Now, some might say, “Well, those folks will just find jobs in the private sector, right?” Possibly, yes, but that circles back to the first point: they become additional competition for private sector jobs. Also, not every public sector skill translates perfectly to private roles, which means some of those laid-off workers might take a while to find their footing, remaining unemployed longer and contributing to the unemployment stats. And from the perspective of a fresh grad: one whole slice of the job market pie (government roles) has been taken off the table, pushing more of them to compete for the remaining slices. The labor supply of candidates has increased (from the influx of ex-federal employees and from grads who would have gone into government now going elsewhere), while the number of total jobs (especially secure entry-level ones) hasn’t grown in tandem – in fact, it’s shrunk by the number of government jobs cut. That simply makes for a tougher job hunt for everyone.
It’s worth noting that large-scale government layoffs or freezes are not a common occurrence in modern US history – typically, government employment is relatively stable or grows slowly over time. What we’re seeing now is a pretty unique situation, often politically charged, but its effect on the early-career job market is very real and very practical. I have talked to students who originally wanted to work in, say, environmental policy; normally, they might apply to the U.S. Environmental Protection Agency or Department of Energy. This year, those applications are going nowhere, so they’re pivoting to NGOs or consulting firms, increasing the applicant pools in those areas. Similarly, someone who dreamt of being a federal investigator now might be trying for a corporate compliance job instead – going up against others who also shifted gears. Any time a major employer contracts, it sends ripples through the labor market, and the U.S. federal government is as major as it gets.
In summary, the drive by “DOGE” to slim down government has effectively dumped a lot more job seekers into the market and removed a chunk of available jobs, especially those friendly to new grads. It’s an under-the-radar factor (unless you follow the news closely) that’s compounding the difficulties for early-career individuals right now.
The Bottom Line: It’s Not Just About AI
When you put all these pieces together – a cooled-off economy, the double-edged sword of AI, the broader competition from skills-based hiring, the financial pressures shaping graduate job choices, and the flood of workers from government cuts – it becomes clear that the challenges facing early-career job seekers come from multiple directions. AI might be the poster child for this moment (and certainly the most “buzzworthy” explanation), but as we’ve explored, it’s far from the only cause of the softer job market for recent graduates. The truth is more complicated and more surprising than a single technological disruption.
For students and new grads trying to navigate this landscape, understanding these factors can actually be empowering. It’s not about despairing that “robots took my job” – it’s about seeing the full context. Yes, you should stay on top of AI trends and make sure you’re tech-savvy, but you should also pay attention to economic signals in your industry (are companies in your field cutting back due to interest rates or inflation?), consider broadening your search (since a degree alone won’t guarantee anything, what other skills or experiences can you acquire to stand out?), and maybe re-examine expectations (a slightly lower paying job to start might still be a launchpad, especially if it’s stable and can lead to growth).
The job market will always have ebbs and flows. We had a boom, now a bit of a bust for entry-level hiring, and in time, things will likely swing again. New technologies will emerge beyond AI, policies will change, and economies will cycle. The class of 2023 or 2024 might be feeling the pinch, but by the class of 2026 or 2027, some of these factors could ease – perhaps inflation will be tamed and interest rates lowered, maybe AI will create as many jobs as it displaces, perhaps the political winds will shift and government hiring will resume, and maybe colleges will address costs (okay, that one might be wishful thinking).
In any case, recognizing that AI isn’t single-handedly “killing” early-career jobs, at least not in a vacuum, is important. We do ourselves a disservice if we pin everything on one scapegoat and ignore the rest. The truth is, early-career jobs are being squeezed by a confluence of economic, technological, social, and political pressures. The good news is that pressures can be relieved. Economies recover, societies adapt, and young talent – like those students and grads out there reading this – will find new ways to thrive. As someone who has been connecting students and employers for many years, I’ve seen tougher markets than this, and I’ve seen recoveries too. So hang in there, keep learning and adapting, and keep an eye on all the factors at play. The more you know about the real reasons behind the trends, the better you can navigate them. And that truth, I hope, is not just surprising but also useful as you chart your early career journey.
| 2025-06-17T00:00:00 |
2025/06/17
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https://www.collegerecruiter.com/blog/2025/06/17/think-ai-is-killing-early-career-jobs-the-truth-may-surprise-you
|
[
{
"date": "2025/06/17",
"position": 51,
"query": "artificial intelligence employment"
}
] |
AI-Proof Careers: 7 Roles That Will Outlast Automation
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Top 7 AI-Proof Jobs in 2025 That Still Need Humans
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https://www.artech.com
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[
"Rajesh Sharma"
] |
The most resilient, AI-proof jobs aren't necessarily the flashiest ones; they're the ones grounded in critical thinking, problem-solving, and human oversight.
|
If you’re starting in tech, it’s hard to ignore the noise around AI—how fast it’s moving, how much it’s automating, and what that means for the future of work.
However, while AI is changing the landscape, it’s not eliminating opportunities; it’s shifting the focus.
The most resilient, AI-proof jobs aren’t necessarily the flashiest ones; they’re the ones grounded in critical thinking, problem-solving, and human oversight, which is good news for early-career engineers.
You don’t need to out-code a machine—you need to build what it can’t build on its own or make sure it works the way it should. In this article, we’ll walk through seven stable tech roles in the AI era.
1. Data Scientists: The Architects of AI
AI can generate outcomes, but it cannot decide what data matters, how it should be collected, or how models should be trained to behave ethically and effectively. That’s where data scientists come in.
They define the questions AI should answer, identify biases in datasets, and determine how models evolve.
Take, for example, fraud detection in the finance industry. A model might flag transactions as suspicious, but only a data scientist can trace back why it happened, evaluate if the flags are justified, and adjust the model accordingly. That’s the kind of decision-making that only humans can bring to the table.
As more organizations invest in AI-driven tools, the demand for professionals who can orchestrate this ecosystem has increased. According to the U.S. Bureau of Labor Statistics (BLS), employment for data scientists is projected to grow by 36% between 2023 and 2033, underscoring their increasing importance in an AI-driven workforce built on future-proof IT careers.
2. Health-Tech Specialists: Bridging Medicine and Technology
Even the most advanced AI systems can support diagnostics and automate routine tasks, but they can’t fully replicate the judgment, adaptability, or communication required in clinical care. Healthcare roles often involve interpreting non-verbal cues, responding to unpredictable scenarios, and making complex decisions that weigh medical, ethical, and situational factors.
From nurses and doctors to therapists and caregivers, healthcare professionals encounter situations where outcomes depend not only on clinical data but also on human compassion and empathy. They read facial expressions, respond to emergencies, and make ethical decisions in real-time, capacities far beyond the reach of machines, at least for now.
The demand for these roles is only increasing due to the aging global population and the rise in chronic illnesses. The U.S. Bureau of Labor Statistics projects around 1.9 million job openings annually in healthcare from 2023 to 2033, underscoring its resilience as one of the most stable and AI-resistant job sectors.
3. Creative Roles: Innovation and Human Imagination
AI can remix, replicate, and regenerate, but it still lacks the understanding of why a story resonates or how to connect emotionally with an audience.
Sure, AI can draft a script or mimic a visual style, but it still lacks the intent, emotional context, and storytelling instinct that humans possess. Take someone like Anthony Bourdain—his travel and food stories resonated not because of technical polish but because of the human warmth, curiosity, and cultural empathy he brought to every frame. That kind of creative depth still can’t be coded.
But those who learn to use AI as a co-pilot to speed up ideation or iterate visuals will thrive more than others. And the demand is there: the U.S. Bureau of Labor Statistics projects around 87,900 openings in arts and design roles each year, demonstrating that innovation driven by imagination remains one of the most stable career paths in the AI era.
4. Cybersecurity Experts: Defending the Digital World
The more connected we become, the more vulnerable we are. And while AI can help detect threats, it lacks the instinct and contextual judgment needed to respond to real-time attacks.
Cybersecurity experts aren’t just fighting malicious code; they anticipate behavior, understand motivations, and mitigate damage in high-pressure situations. Whether responding to a data breach or securing a new application, these professionals blend technical expertise with risk management.
This demand is only rising. The BLS estimates a 33% growth in cybersecurity roles, such as Information Security Analysts, by 2033, making it one of the most future-proof IT careers for professionals seeking longevity in a tech-driven world.
5. Skilled Tradespeople: Hands-On Expertise That AI Can’t Replace
You can program a robot to tighten a bolt but not to diagnose a leaking pipe hidden behind decades-old walls or to calm a panicked customer during a power outage.
Skilled trades, such as electricians, plumbers, and HVAC specialists, rely on tactile problem-solving and adaptability that automation can’t replace. These are judgment calls made in messy, unpredictable environments where no two jobs are alike.
As industries modernize, the demand for tradespeople who can install and maintain systems that support automation continues to grow. That’s why over 663,000 openings are projected yearly in construction and extraction fields through 2033. For anyone considering jobs that AI won’t replace, skilled trades deserve serious attention.
6. AI and Robotics Engineers: The Minds Behind the Machines
It’s easy to forget that every AI tool we use—chatbot and automated report—relies on human engineers to design, train, and refine how it works.
AI and robotics engineers are much more than “just coders”. They’re the architects of today’s and future intelligent systems. They fine-tune algorithms, build ethical guardrails, and ensure AI aligns with human goals. It’s creative, complex, and constantly evolving work that requires more than a human touch.
The outlook reflects this value: employment for electrical and electronics engineers is expected to grow by 9.1% through 2033, according to the U.S. Bureau of Labor Statistics. As professionals building and maintaining intelligent systems, they will remain essential in shaping how AI integrates into the real world.
7. Educators and Trainers: Guiding the Workforce of Tomorrow
Even as virtual classrooms and AI tutors become more common, they still need someone to set the tone, adapt the material, and guide students through ambiguity.
While AI tools and virtual classrooms are improving, research consistently shows that in-person learning leads to better engagement, retention, and collaboration, especially in complex or skills-based subjects.
Educators and trainers play a crucial role in achieving these outcomes by adapting instruction in real time and supporting learners with diverse needs and backgrounds. As technology evolves, their ability to guide human learning remains essential.
As workplaces evolve, so does the need for upskilling and reskilling. That makes education one of the most future-proof careers, especially for those who can blend subject matter expertise with people-first thinking.
The Future Is Collaborative: Humans and AI Together
AI will continue to shape industries, but it won’t replace the need for human judgment, creativity, and adaptability. The careers outlined here show that while technology will continue to grow in capability, there will always be roles where people are essential, guiding, complementing, and working alongside intelligent systems.
If you’re looking for jobs that AI won’t replace, now is the time to align your skillset with roles that play to your human strengths. The key is to look for careers safe from automation, ones that allow you to grow with technology, not compete against it.
Explore the latest openings at Artech and start building a resilient career in a world where AI is a tool, not a threat.
| 2025-06-17T00:00:00 |
2025/06/17
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https://www.artech.com/blog/ai-proof-careers-7-roles-that-will-outlast-automation/
|
[
{
"date": "2025/06/17",
"position": 68,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/17",
"position": 26,
"query": "job automation statistics"
}
] |
AIML - Staff Machine Learning Engineer, Siri and ...
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Staff Machine Learning Engineer, Siri and Information Intelligence
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https://jobs.apple.com
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[] |
Apply for a AIML - Staff Machine Learning Engineer, Siri and Information Intelligence job at Apple ... technology for artificial intelligence, machine learning ...
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The AIML Information Intelligence team is creating groundbreaking technology for artificial intelligence, machine learning and natural language processing! The features we create are redefining how hundreds of millions of people use their computers and mobile devices to search and find what they are looking for. Our universal search engine powers search features across a variety of Apple products, including Siri, Spotlight, Safari, Messages and Lookup. We also develop state-of-the-art generative AI technologies based on Large Language Models to power innovative features in both Apple’s devices and services on the cloud. As part of this group, you will be doing large scale machine learning and deep learning research and development to improve Open Domain Question Answering (using both structured knowledge graph data and unstructured web data) and Summarization as well as developing fundamental building blocks needed for Artificial Intelligence. This involves developing sophisticated machine learning and large language models (LLMs) to understand user queries, retrieve and rank relevant documents across multiple sources and synthesize information across documents to provide user with a direct answer that best satisfies their intent and information seeking needs. Additionally, you will research and develop the state-of-the-art LLMs for summarizing personal data such as emails, messages, and notifications. You will also work with researchers and data scientists to develop, fine-tune, and evaluate domain specific Large Language Models for various tasks and applications in Apple’s AI powered products and conduct applied research to transfer the cutting edge research in generative AI to production ready technologies.
| 2025-06-17T00:00:00 |
https://jobs.apple.com/en-us/details/200609437/aiml-staff-machine-learning-engineer-siri-and-information-intelligence?team=MLAI
|
[
{
"date": "2025/06/17",
"position": 95,
"query": "artificial intelligence employment"
}
] |
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Brazil | Reuters Institute for the Study of Journalism
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Brazil
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https://reutersinstitute.politics.ox.ac.uk
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[] |
Over 255 million words and expressions were evaluated during four months using AI tools. Some of the country's leading media groups, including Grupo Estado and ...
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Free-to-air television's decades-long dominance in the Brazilian media market continues to be challenged by digital platforms, as audiences consume more audio and video content from streaming services. Meanwhile, artificial intelligence (AI) tools are being incorporated slowly but steadily into the daily activities of major media outlets.
The use of AI in Brazilian newsrooms spans an increasingly wide range of applications, including speeding up the translation of agency articles, transforming written content into short videos, and producing insights from vast amounts of unstructured data. The newspaper O Globo, for example, published a series of stories based on 600,000 speeches made in the House of Representatives and the Senate between 2001 and 2024. Over 255 million words and expressions were evaluated during four months using AI tools. Some of the country's leading media groups, including Grupo Estado and Grupo Globo, issued guidelines on using the technology, emphasising that editorial uses of generative AI should always be under direct human supervision.
The discussion about the potential impact of artificial intelligence also reached the political arena. In December 2024, the Senate passed a bill regulating the development and use of AI in Brazil. The legislative proposal, which foresees copyright payment for content used to train artificial intelligence models, is now pending in the House of Representatives.
After a failed attempt to regulate social media in 2023, the topic gained momentum again last year when Brazil’s supreme court ordered a nationwide suspension of Elon Musk’s social network X. Judge Alexandre de Moraes banned it from operating after the company defied court orders regarding the removal of accounts blamed for disinformation. X was unavailable for more than a month but resumed service in October after the company met its legal obligations, including paying fines and blocking certain users.1 While it was offline, Bluesky gained millions of users, at one point getting more than a million new users in just three days, but it is still no match for X in terms of popularity.
The tussle between Musk and Moraes gained huge press attention – Moraes has been vocal in defending social media regulation in order to hold digital platforms accountable for falsehoods, but some legal experts are worried he might be going too far. In August 2024, Judge Moraes ordered the arrest of right-wing bloggers Allan dos Santos and Oswaldo Eustáquio on accusations that both disseminated falsehoods on social media in an attempt to intimidate federal police authorities. Both are supporters of former president Jair Bolsonaro; both have now left the country. The Economist Intelligence Unit moved Brazil from 51st to 57th spot in its Democracy Index 2024, suggesting that Moraes’s rulings could have a 'chilling effect on freedom of speech’.
In another episode that highlights concern about the political impact of social media in Brazil, an avalanche of digital misinformation forced the government in January to withdraw a new set of regulations aimed at combating tax evasion. Misinformation shared on social networks sparked concerns that, with the new rules, instant money transfers would be taxed – an entirely false claim. A video posted by right-wing lawmaker Nikolas Ferreira slamming the regulation amassed more than 300 million views on Instagram. Ferreira has more than 17 million followers on the Meta platform.
Investigations into an alleged military coup attempt plotted by former President Bolsonaro and some of his top officials were an omnipresent theme in legacy media throughout 2024. But the subject lost ground in terms of media coverage following the inauguration of Donald Trump, as the US president announced tariffs on Brazil and other countries. However, the outcome of legal proceedings against Bolsonaro and 33 people charged in connection with the alleged coup plot to overthrow the government elected in 2022 will doubtless remain in the headlines in the year ahead.
The leading newspapers Folha de S. Paulo and O Estado de S. Paulo are tackling digitalisation by creating a wide array of podcasts, with varying degrees of success. More recently, they’ve been investing in bi-weekly, and even daily, videocasts. A survey conducted by the Brazilian Association of Podcasters (ABPod) recently estimated the number of podcast listeners at almost 32 million, with video accounting for 42% of content production.2
Meanwhile, news consumption through television continued its downward trajectory, after being challenged by social networks and the growing popularity of YouTube. Last year marked the passing of legendary TV host and media mogul Silvio Santos, aged 93. Santos rose from humble origins to become the owner of SBT, one of the largest TV broadcasters in Brazil.
Rodrigo Carro
Financial journalist and former Reuters Institute Journalist Fellow
| 2025-06-17T00:00:00 |
https://reutersinstitute.politics.ox.ac.uk/digital-news-report/2025/brazil
|
[
{
"date": "2025/06/17",
"position": 65,
"query": "artificial intelligence journalism"
}
] |
|
Union Roles in AI Oversight: Ethical Workforce Transitions ...
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Union Roles in AI Oversight: Ethical Workforce Transitions in Tech
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https://www.cogentinfo.com
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Unions are increasingly becoming essential players in the development of AI-related workplace policies. They can leverage their collective bargaining power to ...
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The rise of Artificial Intelligence (AI) and automation is fundamentally transforming industries, reshaping the workforce, and creating new challenges and opportunities for both employers and employees. According to a McKinsey Global Institute report, it is estimated that by 2030, up to 800 million workers worldwide could be displaced due to automation and AI. However, these technological advancements also promise to create new job opportunities, with projections suggesting that AI could add $13 trillion to global GDP by 2030 (McKinsey Global Institute, 2017).
This transformation raises critical concerns about how society, businesses, and labor unions will navigate these changes. Specifically, it highlights the need for ethical oversight to ensure that workers are not left behind as AI technologies evolve. Labor unions, long advocates for workers' rights and job security, are increasingly seen as key players in ensuring that AI's integration into the workforce happens fairly, transparently, and ethically. As AI and automation continue to advance, unions must step up to safeguard the workforce, advocating for policies that support ethical AI deployment, protecting workers from unfair displacement, and promoting reskilling opportunities.
The Role of Unions in the AI Era
Historical Context of Unions Adapting to Technological Changes
Labor unions have long been at the forefront of responding to the impact of new technologies on the workforce. During the early 20th century, unions in the manufacturing sector fought to protect workers from job displacement due to industrial automation. For example, when Ford introduced assembly line production in the 1910s, unions fought for better wages, safer working conditions, and job security.
In recent decades, unions have adapted to the rise of the digital economy, engaging with tech companies to address job insecurity caused by the proliferation of technology. For instance, unions in the telecommunications sector have negotiated contracts to ensure workers were not replaced by new digital infrastructure. Today, with AI and automation, unions are again positioned to influence how these technologies are implemented to protect workers.
Current Challenges and Opportunities
AI's integration into the workplace brings several challenges, such as potential job displacement, algorithmic biases, and unequal access to training opportunities. According to a 2019 report by the World Economic Forum, around 75 million jobs worldwide could be displaced by automation by 2022 while simultaneously creating 133 million new roles that demand higher skill levels (World Economic Forum, 2019).
Despite AI's disruptive impact on the workforce, unions have an opportunity to shape its deployment in a way that benefits workers. By engaging with policymakers and tech companies, unions can ensure that AI is used to augment human labor rather than replace it outright. The key is to advocate for ethical AI frameworks and policies that facilitate job transitions through reskilling programs, worker protections, and equitable access to new opportunities.
Participating in AI Policy Development
How Unions Can Influence AI-Related Workplace Policies
Unions are increasingly becoming essential players in the development of AI-related workplace policies. They can leverage their collective bargaining power to influence how AI is deployed in the workplace, ensuring that workers' interests are safeguarded.
One such opportunity is through public policy advocacy. In Europe, labor unions have been active in lobbying for AI legislation that ensures worker protection and fairness. For example, the European Commission's AI strategy includes provisions for ethical AI use, such as ensuring transparency in decision-making and preventing bias in algorithms. Unions have been instrumental in shaping these policies by offering input on the potential impacts of AI on workers (European Commission, 2021).
Importance of Collective Bargaining in the Context of AI
Collective bargaining continues to be one of the most effective tools unions can use to influence the adoption of AI. Through negotiations, unions can secure commitments from employers to provide retraining opportunities, protect workers from job displacement, and ensure that AI is deployed fairly and transparently.
A 2018 study by the Economic Policy Institute found that workers in industries facing high levels of automation are more likely to have their rights protected and receive better compensation when unions are present. This highlights the importance of strong labor representation in industries that are adopting AI technologies (Economic Policy Institute, 2018).
Establishing Ethical AI Frameworks
Principles for Ethical AI Deployment
To ensure that AI is deployed ethically, unions must advocate for establishing clear guidelines that prioritize fairness, transparency, and accountability. The OECD's 2019 AI Principles provide a valuable framework for ethical AI deployment, emphasizing that AI should be designed to enhance human well-being, promote fairness, and respect fundamental human rights (OECD, 2019).
Unions can play a vital role in ensuring these principles are upheld by advocating for policies that require employers to:
Eliminate Bias
AI systems must be trained to avoid discriminatory outcomes. For example, a study by ProPublica revealed that a widely used AI tool in the U.S. criminal justice system was found to disproportionately assign higher risk scores to Black defendants, leading to biased sentencing decisions (ProPublica, 2016).
Ensure Accountability
AI decisions that affect workers, such as performance evaluations or job terminations, must be explainable. Workers must have the right to contest AI-driven decisions, ensuring that there is accountability in the system.
Promote Job Equity
As AI technologies create new roles, it is crucial to ensure that these roles are accessible to workers of all backgrounds. Research by the Brookings Institution indicates that many of the jobs created by AI will require advanced skills, which could exacerbate the divide between high-skilled and low-skilled workers if reskilling efforts are not prioritized (Brookings Institution, 2020).
Ensuring Transparency and Accountability
To ensure accountability in AI deployment, workers must be informed about the AI tools that impact their jobs. According to a 2020 study by Stanford University, transparency is one of the key elements of ethical AI. Workers should have clear insights into how AI systems are making decisions about their work, including performance metrics, data usage, and decision-making processes. By ensuring transparency, unions can help prevent the hidden consequences of AI, such as discriminatory practices or unfair job evaluations (Stanford HAI, 2020).
Collaborative Success Stories
Case Studies Highlighting Effective Union-Tech Partnerships
There have been successful instances where unions and tech companies have collaborated to ensure that AI is integrated ethically. One such example is the German Metalworkers' Union (IG Metall), which has been actively negotiating with employers regarding integrating AI and automation in the manufacturing sector. IG Metall has played a central role in securing agreements that ensure workers are not left behind as robots and AI technologies are introduced on production lines. Through collective bargaining, IG Metall has helped establish "solidarity pacts" that provide workers with job security, retraining opportunities, and early retirement packages (IG Metall, 2020).
Similarly, the United Auto Workers (UAW) has negotiated with automakers in the U.S. automotive industry to ensure that AI and automation do not lead to widespread job losses. These agreements often include provisions for retraining programs, which help workers transition into roles that involve working with or alongside AI technologies. These partnerships have been instrumental in easing the challenges posed by AI and automation in sectors where job displacement is a significant concern (United Auto Workers, 2019).
Lessons Learned and Best Practices
From these case studies, several lessons can be gleaned:
Early Engagement : Unions that engage early with employers and tech companies can shape AI deployment in ways that protect workers' rights and promote fairness.
: Unions that engage early with employers and tech companies can shape AI deployment in ways that protect workers' rights and promote fairness. Collaboration over Confrontation : Effective union-tech partnerships prioritize collaboration over confrontation, ensuring that the introduction of AI benefits both employers and employees.
: Effective union-tech partnerships prioritize collaboration over confrontation, ensuring that the introduction of AI benefits both employers and employees. Focus on Transition Programs: Unions that advocate for reskilling and transition programs help ensure that workers affected by AI automation are supported and equipped to succeed in new roles.
Union-Led Reskilling Programs
Initiatives Aimed at Preparing Workers for AI-Integrated Roles
As AI and automation reshape industries, one of the most pressing concerns for unions is preparing workers for the new roles that these technologies will create. Reskilling initiatives are essential to ensure that workers whose jobs are at risk of automation are not left behind. Unions have the opportunity to play a crucial role in leading these efforts, ensuring that the transition to an AI-driven workforce is as inclusive as possible.
A 2019 report by the World Economic Forum found that 50% of all workers globally will need significant reskilling by 2025 due to technological advancements like AI (World Economic Forum, 2019). To address this need, unions can negotiate with employers to create reskilling programs that help workers acquire new skills and remain competitive in the labor market. For instance, workers in sectors heavily affected by automation, such as manufacturing and transportation, could be retrained for new roles in data analysis, AI development, and digital marketing.
Unions can also advocate for creating partnerships between tech companies and educational institutions to provide workers with access to industry-specific training programs. These programs can be tailored to the workforce's specific needs and ensure that workers have the skills required to thrive in AI-integrated roles.
Example: IG Metall and the Transition of German Workers
In Germany, IG Metall, the country's largest industrial union, has been a leader in supporting workers who AI and automation impact. IG Metall's "Industrie 4.0" initiative focuses on ensuring that workers in sectors like manufacturing are not left behind as AI technologies are introduced. Through collaboration with employers, the union has successfully implemented reskilling programs that provide workers with training in digital skills, allowing them to transition into new roles in industries such as renewable energy, cybersecurity, and IT.
In one prominent case, IG Metall worked with Volkswagen to establish a training center that offers workers opportunities to learn advanced manufacturing skills. These efforts help ensure workers are prepared for the AI-driven future without experiencing significant job displacement. The success of IG Metall's initiatives highlights the importance of unions in advocating for workers' access to reskilling opportunities (IG Metall, 2020).
Funding and Support Mechanisms
Reskilling programs require substantial funding, which can sometimes be a barrier for workers and employers alike. However, there are several ways in which unions can help secure the necessary resources to support reskilling efforts.
First, unions can advocate for public-private partnerships that provide funding for worker retraining. For example, in countries like Germany, the government has provided funding for worker training programs in collaboration with private companies. These partnerships help to ensure that training programs are accessible and affordable for workers across industries.
Unions can also push for government-funded reskilling programs, particularly for sectors where job displacement is most likely due to AI. In Canada, for instance, the government launched a Canada Training Benefit in 2019, which provides financial assistance for workers who wish to pursue reskilling programs (Government of Canada, 2019). Unions have supported such initiatives, helping to ensure that workers have access to the training they need without incurring significant costs.
Moreover, unions can negotiate with employers to establish training funds as part of collective bargaining agreements. These funds can be used to support workers' retraining efforts, ensuring that AI-driven transitions do not result in mass unemployment or inequality in the workforce.
Challenges in Reskilling and Recommendations
Despite the growing focus on reskilling, implementing effective programs is challenging. One of the primary obstacles is the lack of coordination between employers, educational institutions, and governments. In many cases, training programs are not aligned with the needs of the workforce or the evolving demands of industries affected by AI.
Another challenge is the unequal access to reskilling opportunities. Workers in lower-wage, lower-skill jobs are often the most vulnerable to job displacement, yet they are also the least likely to have access to high-quality retraining programs. According to a 2020 OECD report, workers with low levels of education and skills are less likely to participate in training programs and more likely to be displaced by automation (OECD, 2020).
To overcome these challenges, unions can advocate for creating inclusive training programs that target workers at all skill levels. Additionally, unions should push for more accessible and flexible training options, including online learning platforms, apprenticeship programs, and job-sharing arrangements that allow workers to gain new skills without losing their income.
Another recommendation is to ensure that reskilling efforts are continuous and evolve in response to emerging technologies. As AI continues to advance, training programs must remain adaptable and forward-thinking. Unions can collaborate with employers to regularly update training curricula to ensure workers are always equipped with the most relevant and up-to-date skills.
Challenges and Recommendations
Potential Obstacles in Union Involvement with AI Oversight
While unions have a critical role in AI oversight, several challenges could hinder their effectiveness in shaping AI policies and workforce transitions. One significant obstacle is the fast pace of technological change. AI and automation are evolving rapidly, and it can be difficult for unions to keep up with technological advancements that may affect workers.
Additionally, unions may face resistance from employers who are focused on maximizing profits and efficiency. Some employers may see AI as a way to reduce labor costs and may be reluctant to engage with unions on issues related to worker protections and ethical AI deployment.
Another challenge is the lack of data and research on AI's full impact on the workforce. Many unions may struggle to make data-driven arguments about AI's potential effects, as the long-term consequences of these technologies remain uncertain. This lack of information can make it more difficult for unions to advocate effectively for workers' rights.
Overcoming These Challenges
To address these challenges, unions must invest in research to better understand the implications of AI on the workforce. By working with academics, think tanks, and industry experts, unions can gather data and create informed policies that guide the ethical deployment of AI.
Unions can also build alliances with tech companies, government agencies, and educational institutions to promote AI policies that protect workers. These alliances can help to ensure that AI is deployed in a way that benefits both employers and employees and that ethical standards are maintained.
Moreover, unions should engage in public dialogue about the social and economic consequences of AI. By raising awareness about the potential impacts of AI on workers and society, unions can influence public policy and create a more supportive environment for ethical AI deployment.
Strategies to Enhance Collaboration Between Unions and Tech Entities
As AI evolves, unions and tech companies must collaborate on workforce transitions and ethical AI deployment. One effective strategy is to create joint committees or working groups where they can discuss issues related to AI, automation, and labor rights.
These committees can collaborate to develop AI guidelines that prioritize worker well-being and promote ethical AI practices. By involving unions in the development and implementation of AI policies, tech companies can ensure that they consider workers' concerns and comply with ethical standards.
Additionally, ongoing dialogue between unions and tech companies can help identify opportunities for reskilling, job creation, and workforce development. Through collaboration, unions and employers can work together to ensure that AI-driven transitions do not result in mass unemployment but rather open up new avenues for workers to thrive.
Conclusion
As AI technologies continue to transform industries and the workforce, labor unions have a vital role to play in ensuring that these transitions are ethical, inclusive, and equitable. By advocating for ethical AI deployment, participating in AI policy development, and leading reskilling programs, unions can help workers navigate the challenges posed by automation and AI.
Unions must embrace their responsibility to shape the future of work and ensure that the benefits of AI are shared by all workers, not just a select few. By working collaboratively with employers, policymakers, and tech companies, unions can help create a future where workers are empowered, not displaced, by technological advancements.
Ultimately, the role of unions in AI oversight is essential for promoting a fair, transparent, and accountable workforce transition. Through proactive engagement and ongoing collaboration, unions can ensure that AI is deployed in a way that benefits workers and society as a whole.
Shape an ethical, AI-ready workforce with Cogent Infotech. We partner with employers and unions to craft policy frameworks, launch large-scale reskilling, and ensure talent stays ahead of automation.
Let’s future-proof your teams together—contact us today.
| 2025-06-17T00:00:00 |
https://www.cogentinfo.com/resources/union-roles-in-ai-oversight-ethical-workforce-transitions-in-tech
|
[
{
"date": "2025/06/17",
"position": 5,
"query": "artificial intelligence labor union"
}
] |
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Legal Risks of AI Use in High-Stakes Workforce Decisions
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Legal Risks of AI Use in High-Stakes Workforce Decisions
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https://natlawreview.com
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The Intersection of Artificial Intelligence and Employment Law. by ... artificial intelligence across the European Union. It treats employers' use ...
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The use of algorithmic software and automated decision systems (ADS) to make workforce decisions, including the most sophisticated type, artificial intelligence (AI), has surged in recent years. HR technology’s promise of increased productivity and efficiency, data-driven insights, and cost reduction is undeniably appealing to businesses striving to streamline operations such as hiring, promotions, performance evaluations, compensation reviews, or employment terminations. However, as companies increasingly rely on AI, algorithms, and automated decision-making tools (ADTs) to make high-stakes workforce decisions, they may unknowingly expose themselves to serious legal risks, particularly under Title VII of the Civil Rights Act of 1964, the Age Discrimination in Employment Act (ADEA), the Americans with Disabilities Act (ADA), and numerous other federal, state, and local laws.
Quick Hits
Using automated technology to make workforce decisions presents significant legal risks under existing anti-discrimination laws, such as Title VII, the ADEA, and the ADA, because bias in algorithms can lead to allegations of discrimination.
Algorithmic HR software is uniquely risky because, unlike human judgment, it amplifies the scale of potential harm. A single biased algorithm can impact thousands of candidates or employees, exponentially increasing the liability risk compared to biased individual human decisions.
Proactive, privileged software audits are critical for mitigating legal risks and monitoring the effectiveness of AI in making workforce decisions.
What Are Automated Technology Tools and How Does AI Relate?
In the employment context, algorithmic or automated HR tools refer to software systems that utilize predefined rules to run data through algorithms to assist with various human resources functions. These tools can range from simple rule-based formula systems to more advanced generative AI-powered technologies. Unlike traditional algorithms, which operate based on fixed, explicit instructions to process data and make decisions, generative AI systems differ in that they can learn from data, adapt over time, and make autonomous adjustments without being limited to predefined rules.
Employers use these tools in numerous ways to automate and enhance HR functions. A few examples:
Applicant Tracking Systems (ATS) often use algorithms to score applicants compared to the position description or rank resumes by comparing the skills of the applicants to one another.
Skills-based search engines rely on algorithms to match job seekers with open positions based on their qualifications, experience, and keywords in their resumes.
AI-powered interview platforms assess candidate responses in video interviews, evaluating facial expressions, tone, and language to predict things like skills, fit, or likelihood of success.
Automated performance evaluation systems can analyze employee data such as productivity metrics and feedback to provide ratings of individual performance.
AI systems can listen in on phone calls to score employee and customer interactions, a feature often used in the customer service and sales industries.
AI systems can analyze background check information as part of the hiring process.
Automated technology can be incorporated into compensation processes to predict salaries, assess market fairness, or evaluate pay equity.
Automated systems can be utilized by employers or candidates in the hiring process for scheduling, note-taking, or other logistics.
AI models can analyze historical hiring and employee data to predict which candidates are most likely to succeed in a role or which new hires may be at risk of early turnover.
AI Liability Risks Under Current Laws
AI-driven workforce decisions are covered by a variety of employment laws, and employers are facing an increasing number of agency investigations and lawsuits related to their use of AI in employment. Some of the key legal frameworks include:
Title VII: Title VII prohibits discrimination on the basis of race, color, religion, sex, or national origin in employment practices. Under Title VII, employers can be held liable for facially neutral practices that have a disproportionate, adverse impact on members of a protected class. This includes decisions made by AI systems. Even if an AI system is designed to be neutral, if it has a discriminatory effect on a protected class, an employer can be held liable under the disparate impact theory. While the current administration has directed federal agencies to deprioritize disparate impact theory, it is still a viable legal theory under federal, state, and local anti-discrimination laws. Where AI systems are providing an assessment that is utilized as one of many factors by human decision-makers, they can also contribute to disparate treatment discrimination risks. The ADA: If AI systems screen out individuals with disabilities, they may violate the Americans with Disabilities Act (ADA). It is also critical that AI-based systems are accessible and that employers provide reasonable accommodations as appropriate to avoid discrimination against individuals with disabilities. The ADEA: The Age Discrimination in Employment Act (ADEA) prohibits discrimination against applicants and employees ages forty or older. The Equal Pay Act: AI tools that factor in compensation and salary data can be prone to replicating past pay disparities. Employers using AI must ensure that their systems are not creating or perpetuating sex-based pay inequities, or they risk violating the Equal Pay Act.
The EU AI Act :This comprehensive legislation is designed to ensure the safe and ethical use of artificial intelligence across the European Union. It treats employers’ use of AI in the workplace as potentially high-risk and imposes obligations for continued use, as well as potential penalties for violations.
:This comprehensive legislation is designed to ensure the safe and ethical use of artificial intelligence across the European Union. It treats employers’ use of AI in the workplace as potentially high-risk and imposes obligations for continued use, as well as potential penalties for violations. State and Local Laws : There is no federal AI legislation yet, but a number of states and localities have passed or proposed AI legislation and regulations, covering topics like video interviews, facial recognition software, bias audits of automated employment decision-making tools (AEDTs), and robust notice and disclosure requirements. While the Trump administration has reversed Biden-era guidance on AI and is emphasizing the need for minimal barriers to foster AI innovation, states may step in to fill the regulatory gap. In addition, existing state and local anti-discrimination laws also create liability risk for employers.
: There is no federal AI legislation yet, but a number of states and localities have passed or proposed AI legislation and regulations, covering topics like video interviews, facial recognition software, bias audits of automated employment decision-making tools (AEDTs), and robust notice and disclosure requirements. While the Trump administration has reversed Biden-era guidance on AI and is emphasizing the need for minimal barriers to foster AI innovation, states may step in to fill the regulatory gap. In addition, existing state and local anti-discrimination laws also create liability risk for employers. Data Privacy Laws: AI also implicates a number of other types of laws, including international, state, and local laws governing data privacy, which creates another potential risk area for employers.
The Challenge of Algorithmic Transparency and Accountability
One of the most significant challenges with the use of AI in workforce decisions is the lack of transparency in how algorithms make decisions. Unlike human decision-makers who can explain their reasoning, generative AI systems operate as “black boxes,” making it difficult, if not impossible, for employers to understand—or defend—how decisions are reached.
This opacity creates significant legal risks. Without a clear understanding of how an algorithm reaches its conclusions, it may be difficult to defend against discrimination claims. If a company cannot provide a clear rationale for why an AI system made a particular decision, it could face regulatory action or legal liability.
Algorithmic systems generally apply the same formula against all candidates, creating relative consistency in the comparisons. For generative AI systems, there is greater complexity because the judgments and standards change over time as the system absorbs more information. As a result, the decision-making applied to one candidate or employee will vary from the decisions made at a different point in time.
Mitigating the Legal Risks: AI Audits, Workforce Analytics, and Bias Detection
While the potential legal risks are significant, there are proactive steps employers may want to take to mitigate exposure to algorithmic bias and discrimination claims. These steps include:
Ensuring that there is a robust policy governing AI use and related issues, like transparency, nondiscrimination, and data privacy
Doing due diligence to vet AI vendors, and not utilizing any AI tools without a thorough understanding of their intended purpose and impact
Training HR, talent acquisition, and managers on the appropriate use of AI tools
Continuing to have human oversight over ultimate workforce decisions so that AI is not the decisionmaker
Ensuring compliance with all applicant and employee notice and disclosure requirements, as well as bias audit requirements
Providing reasonable accommodations
Regularly monitoring AI tools through privileged workforce analytics to ensure there is no disparate impact against any protected groups
Creating an ongoing monitoring program to ensure human oversight of impact, privacy, legal risks, etc.
Implementing routine and ongoing audits under legal privilege is one of the most critical steps to ensuring AI is being used in a legally defensible way. These audits may include monitoring algorithms for disparate impacts on protected groups. If a hiring algorithm disproportionately screens out individuals in a protected group, employers may want to take steps to correct these biases before they lead to discrimination charges or lawsuits. Given the risks associated with volume, and to ensure corrective action as quickly as possible, companies may want to undertake these privileged audits on a routine (monthly, quarterly, etc.) basis.
The AI landscape is rapidly evolving, so employers may want to continue to track changing laws and regulations in order to implement policies and procedures to ensure the safe, compliant, and nondiscriminatory use of AI in their workplace, and to reduce risk by engaging in privileged, proactive analyses to evaluate AI tools for bias.
| 2025-06-17T00:00:00 |
https://natlawreview.com/article/intersection-artificial-intelligence-and-employment-law
|
[
{
"date": "2025/06/17",
"position": 78,
"query": "artificial intelligence labor union"
}
] |
|
The Future of Work: AI's Impact
|
The Future of Work: AI's Impact
|
https://www.numberanalytics.com
|
[
"Sarah Lee"
] |
The advent of Artificial Intelligence (AI) is transforming the job market at an unprecedented rate. As AI technologies continue to evolve, they are not only ...
|
Navigating New Job Categories in Technology and Sci-Fi
The advent of Artificial Intelligence (AI) is transforming the job market at an unprecedented rate. As AI technologies continue to evolve, they are not only changing the nature of existing jobs but also creating new opportunities in both science fiction and real-world technological advancements. This article explores the impact of AI on the future of work, examining the careers that are emerging in the realms of science fiction and technology, and what this means for individuals preparing for future careers.
Science Fiction Inspirations
Science fiction has long been a source of inspiration for technological innovation. The imaginative concepts presented in science fiction often become the foundation for real-world technological advancements. Here, we explore a few science fiction-inspired careers that could become a reality as AI continues to advance.
AI Consciousness Researcher: Exploring the Potential for AI Self-Awareness
The concept of AI consciousness, or the ability of AI systems to be self-aware, is a staple of science fiction. Researchers in this field would explore the potential for creating AI systems that can recognize their own existence and understand their place within their environment. This area of research is still largely speculative but represents a fascinating frontier in AI development.
"The question of whether a machine can be conscious is a question about the nature of consciousness itself." - Daniel Dennett
Intergalactic Diplomat: Facilitating Communication Between Humans and Alien Species
While still firmly within the realm of science fiction, the role of an intergalactic diplomat highlights the potential for AI to facilitate communication across vastly different forms of intelligence. AI systems capable of understanding and interpreting alien languages could play a crucial role in fostering peaceful relations between humans and extraterrestrial life forms, should they exist.
Cybernetic Enhancements Specialist: Enhancing Human Capabilities Through Technology
Cybernetic enhancements involve integrating technology into the human body to enhance physical or cognitive abilities. Specialists in this area would work on developing and implementing AI-driven enhancements, such as neural implants or prosthetic limbs controlled by AI, to improve human performance and quality of life.
Real-World AI Careers
While the careers inspired by science fiction are intriguing, there are already numerous real-world careers emerging in the field of AI. These roles are crucial for the development, implementation, and regulation of AI technologies.
AI Solutions Architect: Designing AI Solutions for Businesses
AI Solutions Architects design and implement AI solutions tailored to the specific needs of businesses. This involves understanding the business requirements, selecting appropriate AI technologies, and overseeing the integration of these technologies into existing systems.
Key Responsibilities:
Analyze business needs and identify opportunities for AI implementation
Design AI solutions that meet business requirements
Collaborate with data scientists and engineers to implement AI solutions
Ensure AI solutions are scalable and maintainable
Machine Learning Engineer: Developing Intelligent Systems
Machine Learning Engineers are responsible for developing and deploying machine learning models that enable intelligent systems. This involves working with large datasets, selecting appropriate algorithms, and fine-tuning models for optimal performance.
Key Skills:
Proficiency in programming languages such as Python or R
Experience with machine learning frameworks like TensorFlow or PyTorch
Strong understanding of data structures and algorithms
Ability to work with large datasets
AI Policy Maker: Creating Regulations and Guidelines for AI Use
As AI becomes increasingly pervasive, there is a growing need for regulations and guidelines to ensure its safe and ethical use. AI Policy Makers work on developing and implementing policies that govern the development and deployment of AI technologies.
Key Considerations:
Ensuring AI systems are transparent and explainable
Addressing bias and fairness in AI decision-making
Protecting user privacy and data security
Promoting accountability in AI development and deployment
Thriving in an AI-Driven World
To thrive in a world where AI is increasingly prevalent, individuals will need to develop a range of skills that complement AI technologies. Here, we explore some of the key skills that will be essential for success in an AI-driven world.
Creativity and Innovation: Fostering Skills That Are Uniquely Human
While AI is capable of processing vast amounts of data and identifying patterns, it is still limited in its ability to think creatively or outside the box. Developing skills that are uniquely human, such as creativity and innovation, will be crucial for individuals looking to thrive in an AI-driven world.
Emotional Intelligence: Developing Empathy and Understanding in Professional Settings
Emotional intelligence refers to the ability to understand and manage one's own emotions, as well as the emotions of others. As AI takes on more routine and analytical tasks, emotional intelligence will become an increasingly valuable skill in professional settings, enabling individuals to build stronger relationships and make more empathetic decisions.
Technical Literacy: Ensuring a Basic Understanding of AI and Its Applications
Having a basic understanding of AI and its applications will be essential for individuals looking to work effectively with AI technologies. This includes understanding the capabilities and limitations of AI, as well as being able to critically evaluate AI-generated insights and recommendations.
The following flowchart illustrates the key skills required to thrive in an AI-driven world:
graph LR; A["Creativity and Innovation"] --> B["Thriving in AI-Driven World"]; C["Emotional Intelligence"] --> B; D["Technical Literacy"] --> B;
To further understand the impact of AI on the job market, let's examine the mathematical relationship between AI adoption and job displacement. We can model this using a simple linear equation:
\[ y = \beta_0 + \beta_1 x + \epsilon \]
where $y$ represents the number of jobs displaced, $x$ represents the level of AI adoption, $\beta_0$ is the intercept or the initial number of jobs displaced without AI, $\beta_1$ is the coefficient representing the change in job displacement per unit change in AI adoption, and $\epsilon$ is the error term.
According to a report by the McKinsey Global Institute, up to 800 million jobs could be lost worldwide due to automation by 2030[^1]. However, the same report also notes that while AI and automation may displace some jobs, they will also create new ones, with estimates suggesting that up to 140 million new jobs could be created globally by 2030[^2].
The table below summarizes the potential job displacement and creation due to AI and automation:
Region Jobs Lost (millions) Jobs Created (millions) Asia Pacific 275 46 Europe 143 24 North America 134 38 Rest of World 248 32 Total 800 140
As we move forward into an increasingly AI-driven world, it is clear that both challenges and opportunities will arise. By understanding the impact of AI on the job market and developing the skills necessary to thrive in this new landscape, individuals can position themselves for success in a rapidly changing world.
References
FAQ
Q: Will AI replace all human jobs?
A: No, while AI and automation may displace some jobs, they will also create new ones. According to a report by the McKinsey Global Institute, up to 140 million new jobs could be created globally by 2030.
Q: What skills are necessary to thrive in an AI-driven world?
A: Key skills include creativity and innovation, emotional intelligence, and technical literacy. Developing these skills will enable individuals to work effectively with AI technologies and thrive in a rapidly changing job market.
Q: Are there any real-world careers in AI?
A: Yes, there are numerous real-world careers emerging in the field of AI, including AI Solutions Architect, Machine Learning Engineer, and AI Policy Maker. These roles are crucial for the development, implementation, and regulation of AI technologies.
| 2025-06-17T00:00:00 |
https://www.numberanalytics.com/blog/future-of-work-ai-impact
|
[
{
"date": "2025/06/17",
"position": 63,
"query": "future of work AI"
}
] |
|
Control Automation Engineer II Job Details | diasorinsp
|
Control Automation Engineer II
|
https://jobs.diasorin.com
|
[] |
... automation in the manufacturing of medical devices. • Develop and maintain internal web applications for automation, data visualization, and reporting.
|
Diasorin is a global leader in diagnostic solutions, pushing the boundaries of science and technology to create cutting-edge tools that improve healthcare worldwide. With a legacy spanning over 50 years, we've earned our reputation for excellence by developing innovative diagnostic assays and instruments that are trusted by healthcare providers around the world.
Our broad offering of diagnostic tests and Licensed Technology solutions, made available thanks to ongoing investments in research, positions us as the player with the widest range of specialty solutions in the sector and identifies us as the "Diagnostics Specialist."
Why Join Diasorin?
Impactful Work: When you join Diasorin, you become part of a team that's dedicated to improving lives. Your contributions will directly impact patient care, making a meaningful difference in the world.
Global Reach & Innovation: Our work transcends borders. Joining Diasorin means collaborating with colleagues from all over the world, expanding your horizons, and contributing to global healthcare solutions at the forefront of the diagnostic industry.
Diverse and Inclusive Culture: We believe in the strength of diversity, and our inclusive culture reflects this commitment. We value your unique perspective and offer a supportive, collaborative environment where everyone can thrive.
Join Our Team: If you're passionate about innovation, diversity, and making a positive impact on healthcare, Diasorin is the place for you. We're looking for passionate and talented individuals who are ready to embrace new challenges and drive healthcare solutions forward.
Are you ready to be part of a dynamic team that's shaping the future of diagnostics? Join Diasorin and become a catalyst for change in the world of healthcare. Apply today and be a part of our exciting journey toward a healthier, more connected world. Together, we can make an impact!
Job Scope
The Control Automation Engineer, Level II will be responsible for designing, developing, and implementing automated control systems to enhance the efficiency and reliability of our Instruments Manufacturing operations. This role requires a strong technical background, attention to detail, and a deep understanding of automation and control systems in a regulated environment (ISO 13485 and FDA-regulated medical device setting). Responsibilities include defining project tasks, setting timelines, and supporting product design transfer and process engineering efforts. The engineer will also facilitate the investigation and resolution of findings identified through audits, non-conformances, corrective/preventative actions, or customer complaints, as well as deliver task-specific and change control training to Manufacturing personnel.
Success in this role will be measured by the implementation of automation solutions that achieve targeted improvements in production efficiency, system reliability, and compliance with regulatory standards. Key metrics include reductions in production downtime, successful completion of audits with minimal findings, and measurable improvements in process consistency and product quality. The ability to meet project deadlines and effectively train Manufacturing teams on new systems will also be critical indicators of success.
What you will do
• Assume full ownership of design, specification development and selection of new production equipment, such as, test fixtures, manufacturing aids, and automation equipment; includes scale-up of existing processes and development of new processes
• Design, develop, and implement control systems for automation in the manufacturing of medical devices.
• Develop and maintain internal web applications for automation, data visualization, and reporting.
• Build and optimize backend automation scripts and tools using Python.
• Develop and program PLCs (Programmable Logic Controllers) and/or HMI (Human-Machine Interface) systems.
• Collaborate with R&D, Quality Assurance, and Manufacturing teams to identify automation needs and develop solutions.
• Troubleshoot and resolve control system issues to ensure optimal performance and reliability.
• Ensure compliance with regulatory standards (e.g., FDA, ISO 13485) in the design and implementation of control systems.
• Develop and maintain detailed documentation of control systems, including schematics, wiring diagrams, and software code.
• Participate in Failure Modes and Effects Analysis (FMEA) to identify and mitigate potential issues.
• Stay updated on industry trends, standards, and technological advancements to continuously improve automation processes.
• Lead and assist in engineering change control and document change control activities; participate in change control reviews.
• Ensure effective training of Manufacturing Engineering personnel for transfer of new test fixtures, manufacturing aids, and automation equipment
• Assist the investigation and resolution of findings impacting the organization identified through audits, non-conformances, corrective/preventative actions, or customer complaint escalation.
• Lead and assist in design input and implementation oversight of infrastructure improvement projects
• Ensure personal compliance and promote operational compliance with the Quality System and other regulations.
• Ensure compliance to NFPA, OSHA, lock-out, and other applicable safety standards.
• Other duties as assigned.
Experience, Education and Qualifications
• Bachelor’s degree in Electrical Engineering, Mechanical Engineering, Automation Engineering, or a related field.
• 3-5 years of experience in control/automation engineering, preferably in the medical device or a similar regulated industry.
• Proficiency in Python and modern web development frameworks (React, Next.js, TypseScript)
• Experience with databases (SQL or similar) and version control (Git)
• Equipment integration experience using IIoT and MES
• Data analytics experience (SQL, Tableau, Power BI)
• Advanced user of SolidWorks with hands on experience on mechanical builds.
• Ability to work with electrical hardware (PCBAs)
• Proficiency in programming and configuring HMI systems.
• Experience releasing test fixtures from proof of concept to final release.
• Excellent problem-solving skills and attention to detail.
• Strong communication and teamwork skills.
• Expertise in developing requirement for sensors and actuators.
Training and Skills
• Thorough knowledge of ISO 13485 and FDA Quality System requirements
• Applied knowledge of Process and Test Method Validations as required by FDA Quality System guidelines
• Knowledge of Design Control requirements as defined by the FDA Quality System guidelines
• Proven results through application of Six Sigma and Lean Manufacturing principles, including applied knowledge of statistical design of experiments
• Mathematics and statistics aptitude.
• Data analysis and technical writing aptitude.
• Excellent oral and written communication skills.
• Geometric Dimensioning & Tolerancing
• CAD/design/engineering exposure
• PLC programming
• Proficient in Microsoft Word, Excel, and PowerPoint programs.
• Highly organized with proven time management and prioritization skills
• Ability to work independently and with minimal supervision
• Ability to handle the pressure of meeting tight deadlines
Preferred Skills:
• Familiarity with LabVIEW, MATLAB, or other automation software.
• Cloud platform experience (Azure or similar) and DevOps pipelines.
• Experience with robotics and motion control systems.
• Certification in Quality Assurance or related fields (e.g., ASQ, Six Sigma)
Travel Requirements
• 10% Travel may be required up to 10% of the time
What we offer
Receive a competitive salary and benefits package as you grow your career at DiaSorin. Join our team and discover how your work can impact the lives of people all over the world.
Diasorin is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status, and will not be discriminated against on the basis of disability.
In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and Canada and to complete the required employment eligibility verification document form upon hire.
Diasorin is committed to providing reasonable accommodations for qualified individuals with disabilities. If you are a US or Canada candidate and require assistance or accommodation during the application process, please contact the North America Talent Acquisition Team at [email protected] or 1-800-328-1482 to request an accommodation.
The above job description is intended to describe the general content, identify the essential functions, and set forth the requirements for the performance of this job. It is not to be construed as an exhaustive statement of duties, responsibilities, or requirements.
Diasorin reserves the right to modify or amend this job posting as needed to comply with local laws and regulations.
Please note that offers of employment at Diasorin may be contingent upon successful completion of a pre-employment background check and drug screen, subject to applicable laws and regulations.
| 2025-06-17T00:00:00 |
https://jobs.diasorin.com/job/AUSTIN-Control-Automation-Engineer-II-TX-78727/823170302/
|
[
{
"date": "2025/06/17",
"position": 59,
"query": "job automation statistics"
}
] |
|
Learn more about studying smart manufacturing and ...
|
Learn more about studying smart manufacturing and automation at UM-Flint
|
https://news.umflint.edu
|
[
"Logan Mcgrady"
] |
Automation Engineering; Robotics Maintenance; Manufacturing Data Analysis; Industrial Engineering. According to the U.S. Bureau of Labor Statistics, industrial ...
|
The University of Michigan-Flint offers students hands-on opportunities, such as in the Murchie Science Building robotics laboratory.
A passion for computing and technology doesn't have to mean working in Silicon Valley or coding in a coffee shop. In an increasingly data-driven world, technological competencies could make job-seekers an asset in nearly every sector of manufacturing and industry. Imagine using artificial intelligence to scan for faulty welds in critical equipment, increasing safety and profits at the same time. Predictive maintenance software could indicate when assembly machines will break before they fail, increasing efficiency and lowering costs. An analytical review of a company's shipping logistics could reveal bottlenecks and waste, creating opportunities to streamline processes and reduce emissions.
The University of Michigan-Flint's smart manufacturing and automation program equips students to enter the workforce through hands-on learning, expert faculty dedicated to student success and world-class laboratories and equipment. Offered by UM-Flint's College of Innovation & Technology, students learn alongside motivated peers who share their curiosity and drive to make the world a better, smarter, more connected place.
What is Smart Manufacturing and Automation?
Smart manufacturing and automation encompass a broad range of innovative technologies and practices designed to make factories more efficient and flexible. Key components include Internet of Things connectivity, data analytics, AI-driven decision-making and robotics, all of which work together to collect, analyze and act on real-time data. This integration enables factories to identify inefficiencies, predict maintenance needs and adapt quickly to market changes.
Nearly every industry is increasingly relying on artificial intelligence and automation to improve efficiency.
For example, AI algorithms can analyze production data to optimize workflows, while robots can be programmed to handle complex tasks, ensuring consistent product quality and faster production times. These advanced capabilities lead to a host of benefits, including enhanced productivity, reduced waste and improved sustainability. As industries aim to be more environmentally friendly and resource-efficient, smart manufacturing and automation offer the tools and strategies necessary to achieve these goals.
In-Demand Smart Manufacturing Careers
The shift towards smart manufacturing and automation has opened up a large number of career opportunities for educated, driven professionals. Industries across the globe are investing heavily in these technologies to stay competitive, creating a robust job market for those with the right preparation. Five in-demand career paths in this field are:
AI Systems Development
Automation Engineering
Robotics Maintenance
Manufacturing Data Analysis
Industrial Engineering
According to the U.S. Bureau of Labor Statistics, industrial engineering – designing, developing and testing integrated systems for managing industrial production processes – is projected to grow 12% through 2033, much faster than the national average. It's an even brighter outlook for logisticians, who analyze and coordinate an organization's supply chain. That field has a 19% growth outlook, among the fastest-growing in the nation.
Why Choose UM-Flint for Smart Manufacturing and Automation?
The experiences students gain while earning a degree can make the difference when marketing themselves to potential employers. UM-Flint collaborates with industry leaders to ensure our curriculum gives students what they need to meet workforce demand.
Hands-on Learning
The smart manufacturing and automation program works closely with an advisory panel of leading professionals to create cocurricular opportunities for students to obtain first-hand experience in applying the latest manufacturing technologies to the real world. CIT industry partners include Consumers Energy, Ford Motor Company, General Motors, Lear Corporation, Verizon Wireless and more.
Committed Expert Faculty
Donaldson
CIT faculty members are experts in their fields, allowing students to develop inspiring mentorships with instructors and gain valuable academic and career guidance. Shirl Donaldson, assistant professor of engineering, worked in machine shops that were tier one suppliers to the automotive industry before taking her talents to academia. She often helps students apply their classroom learning to real-world projects. In one example, Donaldson worked with students and fellow faculty from CIT and UM-Flint's occupational therapy doctorate program to design and build an adaptive Power Wheels car for a local boy who lost his legs following an illness.
Kaden Stevens (seated) received a custom Power Wheels car that can be operated using only his hands thanks to a partnership between UM-Flint's CIT and occupational therapy programs.
"Our students want to see the impact they make in the world," Donaldson said. "We are living our mission. What our students are learning can really make a difference in people's lives. We can share talent and resources and impact the community."
Thiago Ferreira, assistant professor of information technology informatics, was also involved in the project.
Ferreira (right) and students from the Innovator & Makers Club work on the Power Wheels.
"Ours is a culture of proposing real solutions for real-world problems," Ferreira said. "This project taught so many important skills, including communication and teamwork. If you don't know how to ask the right question, you can't solve a problem. Students also learned how to manage time, costs and resources."
Undergraduate and Graduate Options
With both bachelor's and master's degree offerings, students can take advantage of the unique opportunities UM-Flint offers no matter where they are in their educational journey.
In line with the program's commitment to real-world application, bachelor's degree students complete their studies with a capstone course that pushes them to "design and implement an entrepreneurial and innovative solution to an industry-based problem." Opportunities to earn credits for completing an internship or completing an independent study also exist.
The master's program offers four concentrations: AI, Digital Twin, and Augmented Reality/Virtual Reality in Manufacturing; Industrial Internet of Things and Cybersecurity for Smart Manufacturing; Digitalization of Manufacturing Systems; and Collaborative Robots in Manufacturing.
Is a Career in Smart Manufacturing the Right Choice?
If students are enthusiastic about technology and envision themselves at the forefront of transforming industrial processes, a career in smart manufacturing and automation might be the perfect fit for them. As professionals in this field, they'll draw from their training in computer science, engineering, and data analytics to develop and optimize business practices.
This career path requires strong analytical and problem-solving skills, as well as creativity in developing innovative solutions to complex manufacturing challenges. Being comfortable with emerging technologies and adaptable to new learning environments is also crucial in this rapidly evolving industry.
Join the Revolution in Manufacturing and Technology
Ready to be a part of this innovative transformation in manufacturing? Take the next step by applying today:
| 2025-06-17T00:00:00 |
2025/06/17
|
https://news.umflint.edu/2025/06/17/learn-more-about-studying-smart-manufacturing-and-automation-at-um-flint/
|
[
{
"date": "2025/06/17",
"position": 74,
"query": "job automation statistics"
}
] |
Fin Ops Data Executive, Data Solutions and jobs at Comcast
|
Fin Ops Data Executive, Data Solutions and jobs at Comcast
|
https://jobs.comcast.com
|
[] |
Reviews the approach for current inventory of data and drives increased automation and resiliency, integrating automated quality checks and alerts and ...
|
Comcast brings together the best in media and technology. We drive innovation to create the world's best entertainment and online experiences. As a Fortune 50 leader, we set the pace in a variety of innovative and fascinating businesses and create career opportunities across a wide range of locations and disciplines. We are at the forefront of change and move at an amazing pace, thanks to our remarkable people, who bring cutting-edge products and services to life for millions of customers every day. If you share in our passion for teamwork, our vision to revolutionize industries and our goal to lead the future in media and technology, we want you to fast-forward your career at Comcast.
Job Summary
The Data Solutions FinOps Executive serves as a leader within Comcast Corporate’s Internal Audit Data organization, which spans the Company’s global businesses and operations across Connectivity & Platforms, and Content & Experiences. This Data Solutions FinOps Executive is specifically responsible to collaborate with their peers on the Internal Audit team to develop and maintain data deliverables and reports supporting our Financial and Operational control audit testing. This Executive role will be responsible for simultaneously leading multiple work teams supporting CGA engagements and initiatives. This leader plays a key role in driving best practices relative to analytic/automation opportunities in audits by focusing on risks and providing innovative insights/cost-effective data solutions. The Data Solutions FinOps Executive is responsible for ensuring the timeliness and quality results of their quarterly audit data deliverables for FinOps audits across Comcast C&P, Corporate, Sky, and NBCU, overseeing ad hoc reporting, guaranteeing proper documentation, as well as driving synergies for data and reports. Key Reporting Relationship: Senior Vice President, Internal Audit, Data
Job Description
Core Responsibilities
Leads engagement discussions with Fin Ops leadership and Audit partners, understanding systems / processes / data / policies / controls, and provide strategic recommendations on potential data analytics to support and streamline the audits.
Strategically plans for upcoming audits by clarifying the scope of upcoming audits as well as working with upstream source systems to gain data access and clarifying data / business architecture understanding to support upcoming standard and non-standard data deliverables and expected timeline to deliver to support the audit plan.
Manages the extraction, manipulation, testing, visualization, and analysis of Finance and Operations data that support the audit lifecycle, ensuring timely and quality delivery. Works with upstream source systems to understand potential changes that will require subsequent changes to logic to our data deliverables.
Reviews the approach for current inventory of data and drives increased automation and resiliency, integrating automated quality checks and alerts and addressing recurring pain points with upstream systems and data providers. Collaborates with partners to optimize data sourcing and processing rules to ensure appropriate data quality as well as process optimization.
Drives synergies and standardization of data for Fin Ops audit plans, data processes, and data deliverables across Corporate, C&P, NBCU, and Sky looking for best practices and maximize re-use.
Develops, manages, and mentors team members across all professional levels of Data organization in improving their technical skills, communication, project management, critical/strategic thinking, and collaboration skills. Fosters an environment of empowerment, openness, accountability, and objectivity. Manages thoughtful flexibility across the team in prioritizing tasks, allocating work, and proactively resolving issues.
Provides hands-on guidance to team members on the use of data analysis tools and platforms (e.g. Python, SQL, AWS, Tableau), as well as the ability to perform queries as a back-up to the team or to respond to direct requests from Internal Audit leadership.
Demonstrates effective project and program management skills for data or automation related projects, including developing project plans and budgets, scheduling deliverables across Comcast Audit and business partner teams, executing per plan, and messaging status/issues to management. Direct multiple and simultaneous projects of varying complexity to drive the execution of the audit plan as well as specific asks from Internal Audit leadership.
Writes clear and meaningful data analysis workpapers, documenting root-cause (as applicable), work performed, findings, and recommendations for management. Reviews team workpapers and other documentation to ensure they are clear, accurate, complete, and well-organized.
Ensures all data is secure and follows company policies regarding data classification, exhibiting strong knowledge of IT controls and cyber security concepts and applies to engagements.
Exemplifies the highest degree of trust and integrity by continually upholding the principles of professional standards.
Develops a network of peers to stay current of audit automation trends and data technologies in the industry and profession.
Exercises independent judgment and discretion in matters of significance.
Regular, consistent and punctual attendance. Must be able to work nights and weekends, variable schedule(s) and overtime as necessary.
Other duties and responsibilities as assigned.
Professional Experience and Qualifications
Strong technical skills with proven ability to manage large/complex data and applications, environments, tools, and projects.
Proven ability to synthesize and summarize voluminous/technical information into executive presentations.
Strong analytical and critical thinking skills, and excellent written and oral communications and presentation skills.
Strong employee management/team skills with a proven ability to assemble, motivate, and inspire accountability / responsiveness in a highly effective team.
Strong cross-functional collaboration skills to influence and engage audit partners as well as business unit partners of all levels. Demonstrates a willingness to assist other team members in areas outside of direct assignments, when necessary.
Exhibits a commitment to continuously self-improve by working with leadership to leverage strengths and focus on areas of development. Shows a commitment to self-improvement spanning business acumen, technology, leadership, communication, etc.
Experience with and significant exposure to Accounting, Business Controls, and/or Internal Audit is preferred.
Bachelor’s degree in Information Systems, Business Administration, Computer Science, Statistics, Data Science, Technology or Engineering.
7+ years’ experience with Data, SQL, Python, Tableau, AWS / Redshift, Kubernetes, Databricks, and AI/ML.
Minimum of 10+ years of work experience demonstrating increasing levels of responsibility.
Comcast is proud to be an equal opportunity workplace. We will consider all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, genetic information, or any other basis protected by applicable law.
Skills:
Data Engineering; Leadership; Structured Query Language (SQL); People Management; Python (Programming Language); Communication; Deliverables Management
Base pay is one part of the Total Rewards that Comcast provides to compensate and recognize employees for their work. Most sales positions are eligible for a Commission under the terms of an applicable plan, while most non-sales positions are eligible for a Bonus. Additionally, Comcast provides best-in-class Benefits to eligible employees. We believe that benefits should connect you to the support you need when it matters most, and should help you care for those who matter most. That’s why we provide an array of options, expert guidance and always-on tools, that are personalized to meet the needs of your reality – to help support you physically, financially and emotionally through the big milestones and in your everyday life. Please visit the compensation and benefits summary on our careers site for more details.
Education
Bachelor's Degree
While possessing the stated degree is preferred, Comcast also may consider applicants who hold some combination of coursework and experience, or who have extensive related professional experience.
Relevant Work Experience
10 Years +
| 2025-06-17T00:00:00 |
https://jobs.comcast.com/job/philadelphia/fin-ops-data-executive-data-solutions/45483/82670889568
|
[
{
"date": "2025/06/17",
"position": 75,
"query": "job automation statistics"
}
] |
|
News - IAWP
|
News
|
https://iawponline.org
|
[] |
Our mission: Data-driven insights. Actionable strategies. Workforce ... These automated systems are used by most employers to […] IAWP News Archives ...
|
The term “agentic AI” is rapidly moving from tech circles to the forefront of our professional conversations. This isn’t just another buzzword; it’s a fundamental technological shift that will redefine how we support jobseekers, engage with employers, and build the future of work. So, what is agentic AI, and why must it be on every […]
| 2025-06-17T00:00:00 |
https://iawponline.org/news/
|
[
{
"date": "2025/06/17",
"position": 81,
"query": "job automation statistics"
}
] |
|
Daily AI Use at Work Has Doubled – What's Slowing Even ...
|
Daily AI Use at Work Has Doubled – What’s Slowing Even Broader Adoption?
|
https://www.eweek.com
|
[
"Aminu Abdullahi",
"Written By",
"Aminu Abdullahi Is An Experienced Technology",
"Finance Writer",
"Award-Winning Public Speaker. He Is The Co-Author Of The E-Book",
"The Ultimate Creativity Playbook",
"Has Written For Various Publications",
"Including Techrepublic",
"Eweek",
"Enterprise Networking Planet"
] |
A new Gallup survey reports that 40% of US employees now use AI at least a few times per year, up from 21% two years ago.
|
eWEEK content and product recommendations are editorially independent. We may make money when you click on links to our partners. Learn More.
A new Gallup survey reports that 40% of US employees now use AI at least a few times per year, up from 21% two years ago. Among those who use it more regularly, such as weekly or more, usage has climbed from 11% to 19%. Daily users of AI have also increased from 4% to 8% in the last year.
White-collar workers and tech pros lead the way
This embrace of AI isn’t uniform across all job types. The Gallup report highlights that AI adoption has “increased primarily for white-collar roles,” with 27% of white-collar employees now frequently using AI at work, a 12% increase since 2024. Industries leading this charge include technology (50%), professional services (34%), and finance (32%).
By contrast, AI adoption among front-line and production workers slipped slightly from 11% in 2023 to 9% this year.
Leadership outpaces workforce in daily AI use
Managers are outpacing their teams in AI adoption, according to Gallup’s findings. One in three senior leaders — defined as managers of other managers — report using AI frequently, nearly double the rate (16%) among non-managerial staff.
Gallup’s chief scientist for workplace management and wellbeing, Jim Harter, said in a comment to Business Insider, “There’s probably more leaders experimenting with it because they see the urgency and they see it as a competitive threat potentially.”
Harter noted that leaders are likely “feeling added pressure to think about AI and how it can increase efficiency and effectiveness.”
Job loss fears steady despite AI’s rise
Even with AI tools becoming more commonplace, fears around job displacement have not escalated. Only 15% of US workers say it’s very or somewhat likely that automation or AI will eliminate their jobs within five years; a figure that has remained unchanged since 2023.
However, certain sectors, like technology (21%), retail (21%), and finance (20%), show slightly higher levels of concern.
AI use without clear direction
About 44% of employees report that their company has started using AI, but just 22% say leadership has provided a clear plan for how it will be used. The lack of clarity is slowing broader integration.
The most common barrier cited by workers is not understanding how AI supports their role. Even among those already using AI, only 16% strongly agree the tools are beneficial.
Gallup’s research indicates that employees are three times more likely to feel prepared when leaders clearly outline how AI will be deployed. Although AI is becoming a bigger part of work life, without better guidance, many employees still don’t see the value or know how to use it safely.
Read eWeek’s coverage of how workers can stay employed in the age of AI, which highlights key strategies for adapting to automation and evolving job demands.
| 2025-06-17T00:00:00 |
2025/06/17
|
https://www.eweek.com/news/ai-adoption-employees-gallup-poll/
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[
{
"date": "2025/06/17",
"position": 5,
"query": "workplace AI adoption"
}
] |
Disparities in AI Adoption and Imperatives for Governance
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Disparities in AI Adoption and Imperatives for Governance
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https://www.reveliolabs.com
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Although workers face low barriers to using AI, as the technology is widely available and easily accessible, AI adoption has been uneven across the workforce.
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AI at Work: Equity implications of rising adoption
Welcome to a new edition of Revelio Labs’ Research Insights.
This edition is an extension of our last edition on AI at work, where we discussed how AI is affecting the workplace: Which occupations are the most exposed to AI, who is adopting AI, and how AI is affecting the demand for workers. In this edition, we examine a deeper layer of the state of AI at the workplace. We analyze how patterns of AI adoption are redistributing economic gains across the US workforce. We also discuss the increasingly urgent ethical challenges. With companies largely left to self-regulate the technology, concerns about conflicts of interest, transparency, and accountability have grown.
Although workers face low barriers to using AI, as the technology is widely available and easily accessible, AI adoption has been uneven across the workforce. We find stark disparities in AI adoption by age, gender, and race. As AI adoption has so far been largely voluntary, early adopters are set to benefit, while others stagnate.
Younger workers, namely Millennials and Gen Z, are adopting AI tools at significantly higher rates than older cohorts. About 3.3% of Gen Z workers report using AI at work, followed by 3.1% of Millennial workers. These adoption rates compare to just 2.4% of Gen X and 2% of Baby Boomers.
We also find significant gender disparities in AI adoption, where men outpace women in AI adoption within the same roles.
Ethnic disparities add another dimension to the uneven adoption of AI. Revelio Labs’ data shows that Asian workers in the US stand out with the highest AI adoption rates across all ethnic groups. This is largely because they are overrepresented in roles with the highest AI adoption, such as data science and machine learning engineering. But even after controlling for roles, Asian workers adopt AI at a significantly higher rate than other workers.
The unequal adoption of AI across demographic groups translates into tangible disparities in salaries and opportunities. We have previously shown that workers who adopt AI earn nearly twice as much as those who don’t. This premium highlights the strong connection between AI adoption and economic mobility. Without deliberate intervention, workers who are slower to adopt AI risk falling further behind.
As AI systems become increasingly embedded not just in the workplace, but also in high-stakes domains like healthcare, policing, and warfare, they raise urgent questions about fairness and transparency. Yet, the responsibility for governing workplace AI largely has largely fallen to the same companies deploying it, despite clear conflicts of interest. Many of these companies have invested heavily in building AI tools, but far less in ethical oversight. AI ethics teams, where they exist, are often sidelined or overruled, as seen in recent high-profile exits from major tech firms. This lack of transparency raises serious risks: Biased algorithms may quietly influence decisions around hiring, performance, and compensation, further amplifying inequality rather than addressing it.
As AI continues to reshape the labor market, understanding its impact and how it's regulated is essential for navigating the future of work. In the full report, we take a closer look at demographic and economic disparities emerging from uneven AI adoption and the urgent need for stronger oversight.
| 2025-06-17T00:00:00 |
https://www.reveliolabs.com/news/tech/disparities-in-ai-adoption-and-imperatives-for-governance/
|
[
{
"date": "2025/06/17",
"position": 36,
"query": "workplace AI adoption"
}
] |
|
Artificial Intelligence & Automation
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Artificial Intelligence & Automation
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https://www.jacksonlewis.com
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[] |
Labor/Employee Relations ... Help organizations better use AI to increase employee + workplace productivity; deploy workplace intelligence tools; determine AI ...
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Description
Artificial intelligence technologies, including generative AI, machine learning algorithms and data analytics, can make it easier to enhance productivity, refine recruitment efforts, improve customer relationships, and streamline processes. Yet adopting and implementing such technologies can simultaneously add significant complexity for an organization’s, operations, sales, manufacturing, and human capital management operations.
That’s why organizations of all sizes turn to Jackson Lewis for industry-specific insights and actionable advice on the legal, ethical and regulatory implications of using AI and machine learning in the workplace. From screening job applicants to deploying chatbots, smart cameras and surveillance, assessing and enhancing productivity and performance, and self-service training tools and more, our multi-disciplinary Artificial Intelligence & Automation team understands the business needs of organizations that are creating or leveraging AI-related technologies. We help organizations better address the full range of procurement, assessment, development, implementation, use, and maintenance of AI technologies.
| 2025-06-17T00:00:00 |
https://www.jacksonlewis.com/services/artificial-intelligence-automation
|
[
{
"date": "2025/06/17",
"position": 49,
"query": "workplace AI adoption"
}
] |
|
Salesforce's Blueprint for the Human-AI Collaborative ...
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Human-AI Partnership: Salesforce’s Blueprint for the Future Collaborative Workplace
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https://www.salesforce.com
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The New Collaborative Workforce: Humans and Digital Agents. · People: Skilling employees and driving internal AI adoption · Product: Building Agentforce with ...
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Editor’s Note: This article is a collaboration between Paula Goldman, Chief Ethical and Humane Use Officer, Lori Castillo Martinez, EVP of Talent Growth & Development, Becky Ferguson, SVP of Philanthropy, and Leah McGowen-Hare, SVP of Trailblazer Community & Global Workforce Development
Companies around the world are discovering the immense value of AI agents, not as replacements, but as powerful augmentations to their human workforce. These digital workers operate 24/7, handling tasks from the mundane to the complex, and are poised to dramatically increase productivity by an anticipated 30% within the next two years as adoption jumps by 327%, according to Salesforce research.
The New Collaborative Workforce: Humans and Digital Agents. GO DEEPER
In centering our efforts across our people, product, and community, we’re committed to promoting a future workplace where humans can thrive with AI.
At Salesforce, we recognize both the opportunities and risks posed by widespread adoption of digital labor. That’s why we are focused on internal AI adoption and upskilling of our employees, building trusted, human-centered agentic AI, and investing in AI within our broader ecosystem. In centering our efforts across our people, product, and community, we’re committed to promoting a future workplace where humans can thrive with AI.
People: Skilling employees and driving internal AI adoption
We’re preparing our workforce for the digital labor revolution by investing in our most valued asset — our people — and harnessing the potential of agentic AI in career transformations.
AI Skilling
Career Connect: Our AI-powered internal talent marketplace, Career Connect, gives employees personalized recommendations for skilling, learning on Trailhead, stretch assignments, and even new job opportunities within the company based on their interests and aspirations.
Our AI-powered internal talent marketplace, Career Connect, gives employees personalized recommendations for skilling, learning on Trailhead, stretch assignments, and even new job opportunities within the company based on their interests and aspirations. Top Ten Skills: We’ve identified the top skills essential for success in the AI era, broken down into three categories — human, agent, and business skills. And, we’re making sure every employee has the time, tools, and opportunities to master them. Through assessments and personalized learning plans in Career Connect, employees can gauge their proficiency in these skills and access targeted resources to grow them.
We’ve identified the top skills essential for success in the AI era, broken down into three categories — human, agent, and business skills. And, we’re making sure every employee has the time, tools, and opportunities to master them. Through assessments and personalized learning plans in Career Connect, employees can gauge their proficiency in these skills and access targeted resources to grow them. Quarterly Agentforce Learning Days: Every quarter, we provide a day of Agentforce programming with tailored tracks and expert speakers to encourage employees to spend time learning how to use AI tools. A recent Agentforce Learning Day gave more than 12,000 employees dedicated time to developing new AI skills, with 64% of those employees saying they now feel more equipped to use agents.
AI Adoption
Accelerating AI adoption and innovation: We embed Agentforce, Salesforce’s digital labor platform, into our internal workflows, projects, and teams, from finance and engineering to sales and beyond. To promote safe innovation, we provide a sandbox environment where teams can explore new AI technologies without risk to live systems, fostering a culture of curiosity and ongoing improvement.
We embed Agentforce, Salesforce’s digital labor platform, into our internal workflows, projects, and teams, from finance and engineering to sales and beyond. To promote safe innovation, we provide a sandbox environment where teams can explore new AI technologies without risk to live systems, fostering a culture of curiosity and ongoing improvement. Redefining the human-AI partnership: With agentic AI taking on routine and repetitive tasks, we’re freeing up employees to focus on higher-stakes, higher-impact work. For example, our security team uses Agentforce to detect and respond to incidents — saving more than 3,000 hours of manual work. As a result, security employees can shift to more strategic, cross-functional, and high-growth areas. Salesforce has supported these transitions through personalized learning opportunities and mobility pathways across the company.
Product: Building Agentforce with humans at the center
The agentic AI future must be designed with trust and intention, as adoption hinges on user confidence. We’re embedding safeguards directly into Agentforce’s design to make it safe, ethical, and enterprise-ready. This approach ensures people remain empowered, informed, and in control as AI takes on more responsibility.
Trust Layer and Agent Guardrails : We integrate safeguards like audit trails, toxicity detection, on- and off-topic classifiers, and data masking directly into our AI products. Additionally, guardrails serve to clearly define the boundaries in which agents operate and protect both the integrity of AI outputs and the privacy of sensitive information. This is what makes broad adoption possible, giving organizations the confidence to scale AI.
and We integrate safeguards like audit trails, toxicity detection, on- and off-topic classifiers, and data masking directly into our AI products. Additionally, guardrails serve to clearly define the boundaries in which agents operate and protect both the integrity of AI outputs and the privacy of sensitive information. This is what makes broad adoption possible, giving organizations the confidence to scale AI. Trust Patterns : We’ve standardized trust patterns — built-in guardrails designed to improve safety, accuracy, and human empowerment — across our AI products. These design approaches help Agentforce operate within predefined scopes and maintain transparency at every touchpoint. For example, we’ve built in visible indicators when content is AI-generated, prompt structures that keep agents on-topic, and behaviors that trigger human review for complex cases. This clarity allows humans to delegate with confidence.
We’ve standardized trust patterns — built-in guardrails designed to improve safety, accuracy, and human empowerment — across our AI products. These design approaches help Agentforce operate within predefined scopes and maintain transparency at every touchpoint. For example, we’ve built in visible indicators when content is AI-generated, prompt structures that keep agents on-topic, and behaviors that trigger human review for complex cases. This clarity allows humans to delegate with confidence. Agentforce Testing Center : As we shift toward a future where AI takes on more tasks, organizations need reliable ways to test how agents will behave before deploying them in real-world workflows. The Testing Center allows teams to test Agentforce using synthetically generated data, ensuring accurate responses and actions — with monitoring capabilities for usage and feedback.
As we shift toward a future where AI takes on more tasks, organizations need reliable ways to test how agents will behave before deploying them in real-world workflows. The Testing Center allows teams to test Agentforce using synthetically generated data, ensuring accurate responses and actions — with monitoring capabilities for usage and feedback. Employee Trust Testing: We leverage the diverse perspectives of our employees and Equality Group members to uncover unintentional biases in our AI systems. This Trust Testing expands upon our existing ethical product testing efforts to ensure our AI systems are not only robust but also align with Salesforce’s standards of ethical responsibility. By tapping our employees for this testing, we’re also helping them get more familiar and comfortable with the technology.
Community: Investing in AI within our ecosystem
We believe that AI must be accessible to everyone. That’s why we’re investing in AI skilling, literacy, and opportunities across our broader ecosystem to bring our customers and community along on this transformation. Through online learning, certification programs, grants, and innovation accelerators that help nonprofits gain access to agents, we’re providing Trailblazers, nonprofits, and communities the tools they need to thrive in an agent-first world.
Agentblazer Status : To make AI learning accessible, we developed clear, curated learning paths on Trailhead, Salesforce’s free online learning platform, equipping Agentblazers with essential skills in AI fundamentals and hands-on experience with agentic technology and Salesforce’s Agentforce platform.
To make AI learning accessible, we developed clear, curated learning paths on Trailhead, Salesforce’s free online learning platform, equipping Agentblazers with essential skills in AI fundamentals and hands-on experience with agentic technology and Salesforce’s Agentforce platform. AI for All: Our AI for All initiative provides premium Trailhead AI courses and AI certifications at no cost to anyone through the end of 2025.
Our AI for All initiative provides premium Trailhead AI courses and AI certifications at no cost to anyone through the end of 2025. Workforce Partner Program : Our Workforce Partner Program equips more than 100 global training providers, nonprofits, and educational institutions with Trailhead resources, certification prep, and best practices on skills-based training to prepare learners for human-AI collaboration.
: Our Workforce Partner Program equips more than 100 global training providers, nonprofits, and educational institutions with Trailhead resources, certification prep, and best practices on skills-based training to prepare learners for human-AI collaboration. Salesforce Accelerator — Agents for Impact : We help purpose-driven organizations gain equitable access to trusted generative AI technologies. By providing flexible funding, pro-bono expertise, and technology to purpose-driven organizations, we’re empowering nonprofits to accelerate agentic AI solutions to help them meet their missions. Recognizing the urgent need to close a widening AI access gap, we’ve partnered with 38 nonprofits, providing $10.4M in new funding for organizations to harness the power of AI and agents for climate, education, and other key impact areas.
We help purpose-driven organizations gain equitable access to trusted generative AI technologies. By providing flexible funding, pro-bono expertise, and technology to purpose-driven organizations, we’re empowering nonprofits to accelerate agentic AI solutions to help them meet their missions. Recognizing the urgent need to close a widening AI access gap, we’ve partnered with 38 nonprofits, providing $10.4M in new funding for organizations to harness the power of AI and agents for climate, education, and other key impact areas. Philanthropic Giving: Our AI grantmaking focuses on literacy and training, tools, and uses for AI. In 2024, we gave $23 million to education to help the AI generation unlock critical skills. This funding included grants to U.S. school districts and global education nonprofits.
The path forward
As we step together into the AI future, we recognize that no one has all the answers. But with our focus on people, product, and philanthropy, we can balance the excitement of agentic AI with the inherent risks to workers. We are committed to sharing our learnings as we go, and continuing to provide guidance to customers and stakeholders on how to prepare for this new era.
Go deeper:
| 2025-06-17T00:00:00 |
2025/06/17
|
https://www.salesforce.com/news/stories/human-ai-collaboration-blueprint/
|
[
{
"date": "2025/06/17",
"position": 75,
"query": "workplace AI adoption"
}
] |
Heartland Forward Releases New Poll Revealing ...
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Heartland Forward Releases New Poll Revealing Significant Opportunities for AI Readiness and Adoption Across the Heartland
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https://heartlandforward.org
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[] |
Over half (56%) of respondents report anxiety about AI in the workplace—with states like Mississippi and Kentucky showing even higher concern. Respondents in ...
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Access to high-speed internet remains critical for future economic development in the heartland as poll findings underscore the urgent need for AI education and workforce development initiatives
Bentonville, Ark— Heartland Forward, a non-profit, policy think-and-do tank working to accelerate economic growth in states and local communities in the middle of the country, today released a new poll, conducted by Aaru, focused on how respondents across the 20 heartland states feel about AI. This latest poll builds on last year’s first-of-its-kind poll which additionally focused on the region’s perceptions and attitudes regarding AI, offering insights into how public sentiment has changed over the last year.
“The heartland is the third largest economy in the world, and to drive continued economic growth, the heartland must first be connected to affordable high-speed internet and secondly, learn to effectively learn and utilize AI — these are the major economic issues of our time,” said Angie Cooper, president and COO of Heartland Forward. “AI is rapidly changing how people live, work and learn—and yet many heartland communities still do not have access to high-speed internet. We want to ensure that the heartland has the opportunity to lead the nation in harnessing innovation and AI’s potential to transform education and our future workforce for good. The AI poll builds on Heartland Forward’s Connecting the Heartland initiative — offering key insights into where there are gaps and what more can be done. We will use the findings to develop effective programs and drive action that will prime the heartland for future success.”
The poll—which surveyed 2,000 respondents across Alabama, Arkansas, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Michigan, Minnesota, Mississippi, Missouri, Nebraska, North Dakota, Ohio, Oklahoma, South Dakota, Tennessee, Texas and Wisconsin—found:
More than 50% of respondents report low understanding of how to use AI professionally, and less than 1% feel highly proficient in how to use these new tools in the workplace—highlighting a critical skills gap that could hinder workers from fully participating in industries increasingly shaped by AI. Over half (56%) of respondents report anxiety about AI in the workplace—with states like Mississippi and Kentucky showing even higher concern. Respondents in Texas have a more optimistic outlook, with nearly 40% of respondents there expressing excitement about AI’s potential, particularly in sectors like agriculture and manufacturing.
Over 71% of respondents believe employers should offer training on how to use AI tools—up from 56% just ten months ago. This desire for training spans all education levels—from those without a diploma to those with doctorates, reflecting a realization that AI is no longer a distant technological development, but an immediate necessity for professionals across industries. Clear communication from elected officials, industry leaders and academics, as well as targeted, industry-specific AI training will be essential to helping workers understand how to use AI as a tool to improve their productivity, rather than fear AI as a driver for job displacement.
The disparity between younger and older generations highlights an urgent need for targeted educational efforts that can help bridge the generational divide and create an inclusive AI-driven future for all ages. In April 2025, more than 75% of adults aged 35–44 report at least moderate interest in learning about AI —representing a key demographic for AI-related workforce upskilling and development. This group’s enthusiasm is particularly noteworthy for future regional economic growth, as they are positioned in the workforce at a time when understanding AI will be critical. However, enthusiasm drops significantly among older adults, with nearly 40% of respondents aged 65+ actively expressing disinterest in AI.
About 35% of respondents are “self taught” on AI while 13% had AI taught to them.
To help ensure heartland residents are exposed to and learn how to use AI, Heartland Forward announced a partnership with edtech company Stemuli to develop a learning platform that delivers geographically relevant, gamified AI training directly to rural students and entrepreneurs in the heartland to learn the AI skills they need to be best prepared for tomorrow’s AI economy.
Announced during Heartland Summit, the new partnership will use videogame environments to help expedite learning and increase retention. This gamified approach will help users learn skills like how to most effectively prompt large language models, how to most effectively leverage AI in the workplace and how AI can align with specific career paths.
Heartland Forward is hosting a series of Salon Dinners across the heartland to better understand community perspectives with state and local officials, investors, philanthropists, business and education leaders and beyond.
“To fully realize AI’s potential, we need to embrace the opportunities it brings,” said Cooper. “By expanding educational pathways, building a strong talent pipeline and bringing together key leaders and stakeholders to help inform new policies, the heartland will lead the way in ensuring the heartland is connected to affordable high-speed internet and in response the heartland can lead in AI adoption and innovation.”
Additionally, Heartland Forward features real-time insights into the heartland’s economic trends and the latest news on their platform Pulse of the Heartland which is a resource for policymakers, journalists and community leaders.
About Heartland Forward
Heartland Forward is a non-profit, policy think-and-do tank that turns ideas into action for states and local communities. Our mission is to accelerate economic growth, change the narrative about the middle of the country and generate $500 million of economic impact to the heartland by 2030. We do this through applied research, community-driven programs, policy and convenings—focusing on regional competitiveness, talent pipeline and health and wellness.
About Aaru
Aaru is led by pioneers in applying advanced language systems to simulation. While AI agents have proven valuable for tasks like analysis, coding and problem-solving, Aaru saw an opportunity to harness their potential for more innovative applications. Aaru’s flagship product, Lumen, demonstrates how large language models can revolutionize the way companies make decisions.
| 2025-06-17T00:00:00 |
https://heartlandforward.org/news/heartland-forward-releases-new-poll-revealing-significant-opportunities-for-ai-readiness-and-adoption-across-the-heartland/
|
[
{
"date": "2025/06/17",
"position": 96,
"query": "workplace AI adoption"
}
] |
|
60+ Stats On AI Replacing Jobs (2025) - Exploding Topics
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60+ Stats On AI Replacing Jobs (2025)
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https://explodingtopics.com
|
[
"Josh Howarth",
"Co-Founder"
] |
47% of US workers are at risk of losing their jobs to automation over the coming decade (CEPR) ... In this case, automation also includes non-AI ...
|
The year 2025 is adding even more momentum to significant changes AI is already causing to the job market.
As AI tools become increasingly powerful, and with highly anticipated LLM models like ChatGPT 5 likely to be launching for general use soon, more people are at risk of having their job fully automated. Manus, dubbed the first general-purpose AI agent, launched earlier this year.
However, will AI really put most people’s jobs at risk, or is the reality more nuanced?
In this article, we’ll explore dozens of statistics covering the who, what, where, and when of AI replacing jobs — and creating new ones.
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Key Statistics About AI Replacing Jobs (Editor’s Picks)
300 million jobs could be lost to AI
AI could force 14% of all workers to change career by 2030
47% of all US workers could see their roles come under threat from AI in the next decade
Automating half of current tasks worldwide could take another 20 years
60% of the jobs in advanced economies are at risk of being replaced by AI
But just 26% of jobs in low-income countries are similarly exposed
And only 3% of workers with less than a high school diploma are in work considered "most exposed" to AI job losses
Workers aged 18-24 are 129% more likely than workers aged over 65 to worry that AI will make their job obsolete
15% of workers in the US would consider having an AI boss
AI’s Potential Impact on the Job Market
AI may replace 300 million jobs (Goldman Sachs via BBC)
That represents 9.1% of all jobs worldwide. Potential job losses will not be evenly distributed across different sectors of the economy. Instead, they will likely be concentrated in the professions most vulnerable to being automated via generative AI tools (writing, photography, software development, etc.).
Globally, 20 million manufacturing jobs could be replaced by automated tools by 2030 (PatentPC)
Most of these automated tools are robots, not strictly AI, but some of these lost jobs will be replaced with new AI tools.
By 2030, 14% of employees will have been forced to change their career because of AI (McKinsey)
That’s 14% of the global workforce, or 375 million workers. It's little wonder that AI courses to help workers upskill in the new technology are becoming more and more popular.
Wall Street expects to replace 200,000 roles with AI in the next 3 to 5 years (Bloomberg)
A 2025 Bloomberg Intelligence survey of 93 major banks including Citigroup, JPMorgan and Goldman Sachs found that workforces would be cut by an average of 3% by 2030 at the latest. Almost 1 in 4 executives expect reductions of 5 to 10%.
75% of CEOs think generative AI will significantly change their business within the next three years (PwC)
A large majority of business leaders polled by PwC foresaw the need for training in new skills, improving cybersecurity protocols, and a host of other changes — all due to the introduction and adoption of generative AI.
80% of the US workforce could have at least 10% of their tasks impacted by large language models (ARXIV)
Practically every job involves some tasks that are vulnerable to being automated by AI. Only a small minority of workers are totally unexposed to AI.
More than 7.5 million data entry jobs will be lost by 2027 (WEF)
This represents the largest predicted loss of jobs of any profession. The professions that are predicted to lose the most jobs are those extremely vulnerable to AI. Data entry clerks was first, administrative secretaries was second, and accounting was third.
41% of employers worldwide intend to reduce their workforce because of AI in the next five years (World Economic Forum)
The 2025 Future of Jobs report found that 92 million roles could be displaced by 2030, although it forecast a net gain of 78 million new jobs.
47% of US workers are at risk of losing their jobs to automation over the coming decade (CEPR)
In this case, automation also includes non-AI tools like robots.
It will take at least 20 years to automate just half of current worldwide work tasks (McKinsey)
While the potential economic gains from automation are great, they are a difficult potential to fully realize. Various barriers prevent widespread adoption of automation tools; these barriers, which can be legal, political, economic, social, technological, or something else entirely, may take decades to overcome.
AI’s Current Impact On the Job Market
30% of US companies have replaced workers with AI tools like ChatGPT (Resume Templates)
According to a Resume Templates survey of nearly 1,000 US business leaders, 90% of companies have already adopted AI. This year, the amount of companies replacing workers with AI could rise to 38%.
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From January to early June 2025, 77,999 tech job losses were directly linked to AI (Final Round AI)
Cuts at Amazon and Microsoft among others contributed to 491 people losing their jobs to AI every day.
40% of companies that are adopting AI are automating rather than augmenting human work (CNN)
That's according to the CEO of AI giant Anthropic, who also notes that the ratio is moving further toward automation.
Since 2000, automation has resulted in 1.7 million manufacturing jobs being lost (BuiltIn)
The introduction of automotive tools is also linked with increased competition, lower wages, and other negative effects beyond job loss.
13.7% of US workers report having lost their job to a robot (Socius)
AI has already displaced hundreds of thousands of workers. Additionally, people who were replaced by a robot gave a far higher estimate of the proportion of workers who have experienced the same when compared to workers who had not lost their job to a robot. Those who had been replaced estimated that 46.9% of US workers had experienced the same, while people who hadn’t been replaced estimated that 29% of workers had been replaced. Both groups still wildly overestimated the true number of workers who had lost their job to a robot.
Which Careers Are Exposed to AI?
Two-thirds of all jobs in the US and Europe are exposed to automation (Goldman Sachs)
That doesn’t mean these jobs are all going to be fully automated. Exposure to automation just means that some of the tasks involved in a particular career can be automated.
40% of jobs worldwide are exposed to AI (IMF)
Hundreds of millions of people still lack access to the internet. As technology continues to spread around the world, the proportion of workers exposed to AI — and therefore to being automated — may well increase.
60% of jobs in advanced economies could be impacted by AI (IMF)
“Impacted” is a deliberately neutral term. According to the IMF’s report, about half of those impacted by AI will be benefited. The other half will be negatively impacted. For example, their wages might decrease, or they could outright lose their job.
19% of workers are employed in the jobs most exposed to AI (Pew)
To calculate which jobs were most exposed to AI, researchers at Pew ranked professions based on how much workers relied on tasks that could be fully automated. The top 25% of jobs, when ranked this way, were considered “most exposed” to AI.
27% of workers with a bachelor’s degree or higher are employed in jobs most exposed to AI (Pew)
Workers with higher levels of educational attainment were more likely to be employed in professions considered most exposed to AI. Just 3% of workers with less than a high school degree worked in the jobs most exposed to AI. That figure rose to 12% for workers with a high school diploma, 19% for those with some college experience, and 27% for those with at least a bachelor’s degree.
Workers in jobs considered most exposed to AI earned $13.3/hr more than those in jobs least exposed to AI (Pew)
Better-paid jobs are currently more at risk of being lost to AI. While workers in the jobs most exposed to AI earned an average of $33.3 per hour, those employed in jobs least exposed to AI earned just $20 per hour on average.
Widespread adaptation of current automation tech could affect half of the world economy (McKinsey)
That represents some 1.2 billion employees and $14.6 trillion in wages. For context, $14.6 trillion is larger than the GDP of all countries bar China and the US, and is more than three times larger than the third-largest GDP.
AI Replacing Work Tasks
34% of all business-related tasks are already performed by machines (WEF)
The remaining 66% of tasks are performed by humans. This represents a minor but significant decrease in the share of tasks being performed entirely by non-humans. The researchers at the WEF suggest this could be due to the fact that AI and other automotive tools often help humans perform tasks more efficiently, rather than performing them independently.
Technology and machines play at least some role in 53% of work tasks (WEF)
The 2025 Future of Jobs report found that only 47% of work tasks are mainly performed by humans alone. 22% are done mainly by machines and algorithms, with the remainder being done by a combination of man and machine.
25% of all work tasks could be done by AI (Goldman Sachs)
Some jobs involve more tasks that could be entirely automated by AI. For example, 46% of the tasks completed in administrative roles and 44% of tasks done by workers in legal jobs could be performed by AI. However, only 6% of tasks performed in construction and 4% of those done by maintenance workers could be done by AI.
19% of US workers could see more than half of their tasks impacted by AI (OpenAI)
In this case, “AI” refers specifically to systems that are equivalent to OpenAI’s GPT-4.
Tasks that are highly exposed to AI are important in 77% of all jobs (Pew)
As things stand, AI is far better at some tasks than others. However, the tasks that it is great at, and therefore is most likely to automate, are important or extremely important in 77% of all jobs.
19% of US workers could have at least half of their tasks impacted by LLMs (ARXIV)
The number of workers who could see the majority of their job automated is relatively small at the minute. However, that 19% still represents hundreds of thousands of people — and will almost certainly grow as AI tools become more advanced.
Employers think 34% of tasks will be fully automated by 2030 (WEF)
That actually represents a significant decrease from 2023 predictions, when employers predicted that 42% of tasks would be wholly automated by 2027. This more conservative estimate could reflect doubts about whether AI tools will continue improving at the pace they have over the last few years.
65% of tasks related to data processing and information could be fully automated by 2027 (WEF)
These were the types of tasks most vulnerable to automation. In comparison, employers surveyed by the WEF predict that just 35% of tasks related to reasoning and decision-making could be automated by 2027.
Notable Jobs and Tasks AI Can’t Replace
AI can only economically replace vision-based tasks accounting for just 0.4% of the total wages earned in the US (MIT)
According to a 2023 study by researchers at MIT, computer-vision AI can only automate tasks that account for just 1.6% of the wages earned by non-agricultural workers in the US. However, in most cases it would actually be more expensive to switch from humans to AI. Researchers estimated that it would be cheaper to replace just 23% of those wages that are automable.
23% of workers are in the jobs least exposed to AI (Pew)
The important tasks in these jobs were those resistant to automation. Take nannies, for example. The most important skills required to care for children are not particularly exposed to AI. That makes the job as a whole less exposed to AI than, for example, mechanical drafters.
40% of jobs in emerging markets are exposed to AI (IMF)
Emerging markets are usually less oriented toward services than established, high-income economies. Therefore, they contain fewer jobs that involve tasks that are automable by AI tools.
Just 26% of jobs in low-income countries are exposed to AI (IMF)
The vast majority of jobs in low-income countries involve tasks that are currently not automable by AI. In part, that’s because significant proportions of workers in low-income countries still work in professions like subsistence agriculture. These roles are automable — just not by AI tools.
63% of business leaders surveyed by CEPR think AI won’t affect employment rates in high-income countries (CEPR)
While 27% think AI will increase unemployment in high-income countries, most respondents were unsure about their answers.
Half of jobs will still be safe from full automation by 2045 (Goldman Sachs)
That being said, 60% of occupations could be impacted by AI as soon as 2030. These professions could see wage pressure as competition rises due to the automation of key tasks.
How People Are Responding to the Threat of AI Replacing Jobs
Over the next three years, 120 million workers will undergo retraining due to AI changing business demands (SEO.ai)
Training is one of the major barriers to the widespread adoption of AI tools. It represents a significant cost burden to any employer considering embracing AI. Nevertheless, tens of millions of workers will be retrained, either to use AI tools or to perform new tasks after old ones are automated by AI.
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84% of employees worldwide are receiving significant organizational support to learn AI skills (McKinsey)
Employers who fail to train their workers in AI may find themselves falling behind their competitors. That could drive this statistic higher in coming years.
48% of US workers want more formal Gen AI training from their organization (McKinsey)
Training is the single biggest factor that would see more employees integrate AI into their daily work routines.
AI is the highest priority in the training strategies of companies with more than 50,000 employees (WEF)
Larger companies are more likely to embrace and fully adopt AI tools, which naturally means more of them will have to make AI training a top priority. Various industries also have AI as the highest priority of their training strategies, including IT services, media and entertainment, telecommunications, and electronics.
AI Causing Widespread Worry Among Workers
32% of US workers fear that AI will lead to fewer job opportunities (Pew)
All in all, 52% of workers are worried by AI, compared to just 36% who are hopeful. Only 29% feel excited, while 33% feel overwhelmed.
39% of workers are concerned they won’t receive adequate training in new technology (PwC)
Keeping up with technological change is vital if you want to stay afloat in an increasingly competitive workforce. A significant proportion of workers are worried they won’t receive the training necessary to properly use new tech, including AI tools. The same PwC survey found that employees who believe their skills are scarce are far more likely to ask for a pay rise or promotion, feel satisfied with their job, and switch to a new employer.
24% of workers fear that AI will make their job obsolete (SurveyMonkey / CNBC)
Those who are most concerned are younger workers, workers of color, and workers earning lower wages. The fact that lower-wage workers are more worried is interesting, considering the fact that other research shows that those earning higher wages are statistically more likely to be displaced.
43% of workers expect AI to cause their job to significantly change in the next five years (Survey Monkey)
This isn’t necessarily bad. However, significant job changes often result in increased pressure and stress due to the need to adapt, especially if an employer does not provide retraining.
Just 32% of employees think their company has been transparent about its use of AI (Asana)
Perhaps unsurprisingly, workers are less likely to think this if they are lower down in the business hierarchy. While 44% of executives thought their company has been transparent about its AI usage, only 38% of managers agreed, and that figure fell to 25% among individual contributors.
55% of workers think AI will eliminate more jobs than it will create (BMG)
Despite reassurances from leaders in the AI space, people are still wary of this rapidly evolving technology. Just under half of respondents to the same poll said they thought it was likely that humans would eventually lose control of AI systems altogether.
US unemployment could reach 20% in the next five years (CNN)
That’s the warning from the Anthropic CEO. It echoes fears that AI will not create as many jobs as it displaces.
Who is Most Worried About AI Replacing Their Job
81.6% of digital marketers think that content writers will lose jobs due to AI (SEO.ai)
Content production has been one of the industries most impacted by AI, so it’s no surprise the vast majority of those involved in content creation predict jobs will be lost.
52% of people aged 18-24 are worried that AI will negatively impact their future careers (BMG)
Young workers have the most time ahead of them — time in which AI tools can become even more advanced, and pose even more of a challenge to human workers. For context, just 39% of all respondents in this poll indicated concern about their future career prospects being negatively impacted by AI.
Young workers are 129% more likely to be worried than older workers about AI making their job obsolete (SurveyMonkey)
While 32% of workers aged 18-24 reported being somewhat or very worried that AI will make their job obsolete soon, only 14% of workers aged 65 and over felt worried. Each intermediate age group felt more worried the younger they were, perhaps reflecting the face that younger workers will likely have to compete against successively more powerful AI models.
38% of Asian workers are worried AI will make their job obsolete, compared to just 19% of white workers (SurveyMonkey)
Asian workers were the most worried, while white workers were the least afraid. In the middle, 32% of Black workers and 35% of Hispanic workers reported feeling concerned about AI making their job obsolete.
30% of workers earning under $50,000 per year are worried that AI will soon make their job obsolete (SurveyMonkey)
Interestingly, lower-income workers were almost twice as likely as higher earners to be worried about AI eliminating their jobs. Just 16% of workers earning over $150,000 reported feeling this stress.
Fully remote workers are 42% more likely than fully in-person employees to believe their job will be disrupted by AI (SurveyMonkey)
While 54% of fully remote workers think that their job will likely be changed by AI, only 38% of employees who work fully in-person think the same.
51% of workers in advertising and marketing believe their jobs will change due to AI (SurveyMonkey)
This represents one of the highest proportions of workers predicting job changes of any industry. AI tools are already being used by some companies to promote their products.
Where AI is Being Adopted
Companies with annual revenue of at least $500 million are adopting AI more quickly than smaller organizations (McKinsey)
Adopting AI comes with often significant costs. Larger organizations that can absorb these upfront expenses are thus more able and likely to adopt AI tools. According to the 2025 State of AI report, these larger companies tend to use AI in more areas of the business.
More than 75% of all organizations now use AI in at least one business function (McKinsey)
Larger companies are adapting more quickly, but AI adoption is already cutting across the majority of industries and businesses.
AI’s Potential to Create New Careers
81% of office workers hold a generally favorable view of AI (SnapLogic)
AI might be taking some of their jobs, but office workers are still overwhelmingly positive about the new technology. More than four-fifths believe it improves their job performance and experience at work.
51% of office workers say AI lets them achieve better work-life balance (SnapLogic)
The utopian promise of AI, spread by major proponents like Elon Musk, is a world where work isn’t necessary at all. For the minute, however, work remains one part of the work-life balance. A majority of workers are using AI to push the scale further toward “life.”
Alternatively, just 6% of workers say AI will lead to more job opportunities in the long run (Pew)
31% predict the technology won't make much difference, while 32% think it will lead to job losses.
Among those using AI chatbots at work, 79% say it allows them to do things at least somewhat more quickly (Pew)
40% answered extremely/very. Only 29% said that AI chatbots had a similarly major positive impact on the quality of their work.
25.6% of organizations surveyed by the WEF expect AI to create jobs (WEF)
The business leaders polled by the WEF were quite divided over AI’s potential impact, indicating the general uncertainty surrounding the ramifications of widespread AI adoption. A little under half of those surveyed believe it will create jobs, while a little under a quarter think it will eliminate jobs on balance. The degree of disagreement over AI’s impact on jobs was higher than for any other change included in the poll.
Between 2023 and 2027, the profession with the largest net job growth worldwide will be “AI and Machine Learning Specialist” (WEF)
All of the professions that topped this ranking were new. That means there are few existing jobs to lose but many to gain, resulting in a huge net growth. The professions with the largest predicted raw growth in jobs were quite unexposed to AI: agricultural equipment operators, heavy truck and bus drivers, and so on. Each of these professions will likely add over two million jobs worldwide by 2027. For comparison, about one million “AI and Machine Learning Specialist” jobs are predicted to appear over the same timeframe.
Having access to an LLM resulted in 15% of employee tasks being completed faster with no loss in quality (ARXIV)
By allowing employees to complete more work in the same amount of time, AI tools might induce employers to cut back on workers.
Miscellaneous Stats About AI Replacing Jobs
17% of British workers think they can often or always tell when they are using an AI (ONS)
Workers are more likely to be confident they can spot an AI if they are male, younger, or with a degree.
26% of workers think they are considered lazy if they use AI (Asana)
While the vast majority of workers aren’t worried about using AI tools, a significant proportion worry it could negatively impact how people view their work ethic. That’s not an unreasonable concern, as being considered lazy could mean being passed up for a pay rise or promotion.
18% of workers feel like a fraud when they use AI for work (Asana)
Debates around the proper use of AI continue. The direction of popular culture will have a significant impact on this statistic. Will people accept the use of AI for work, or make it unacceptable?
15% of US workers are open to having an AI boss (Asana)
Americans are apparently more receptive to the idea of having a robot boss than British workers. Just 8% of workers in the UK said they’d be open to this idea.
One-third of all US jobs created in the last quarter-century didn’t exist before (McKinsey)
Technically, these jobs either didn’t exist or “barely existed.” Technological advancements can eliminate jobs, but they often create entirely new professions that no one could have predicted.
Conclusion
With AI still advancing so rapidly, even experts are in disagreement about the exact effect this new technology will have on global employment.
On the one hand, AI may well lead to widespread job losses. However, it’s already improving the work lives of millions of employees.
On the other hand, AI is set to create hundreds of thousands of new jobs. And yet millions of people have already been replaced by robots.
Regardless, as AI continues to advance and be adopted, its impact on the global workforce — positive or negative — will only increase.
| 2024-05-27T00:00:00 |
2024/05/27
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https://explodingtopics.com/blog/ai-replacing-jobs
|
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"position": 7,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/18",
"position": 9,
"query": "AI job losses"
},
{
"date": "2025/06/18",
"position": 69,
"query": "AI labor market trends"
},
{
"date": "2025/06/18",
"position": 7,
"query": "AI unemployment rate"
},
{
"date": "2025/06/18",
"position": 13,
"query": "AI impact jobs"
},
{
"date": "2025/06/18",
"position": 54,
"query": "AI labor market trends"
},
{
"date": "2025/06/18",
"position": 6,
"query": "AI unemployment rate"
},
{
"date": "2025/06/18",
"position": 6,
"query": "job automation statistics"
},
{
"date": "2025/06/18",
"position": 30,
"query": "robotics job displacement"
},
{
"date": "2025/06/18",
"position": 15,
"query": "AI impact jobs"
},
{
"date": "2025/06/18",
"position": 9,
"query": "AI replacing workers"
},
{
"date": "2025/06/18",
"position": 97,
"query": "automation job displacement"
},
{
"date": "2025/06/18",
"position": 7,
"query": "job automation statistics"
},
{
"date": "2025/06/18",
"position": 20,
"query": "AI employment"
},
{
"date": "2025/06/18",
"position": 15,
"query": "AI impact jobs"
},
{
"date": "2025/06/18",
"position": 72,
"query": "AI labor market trends"
},
{
"date": "2025/06/18",
"position": 10,
"query": "AI replacing workers"
},
{
"date": "2025/06/18",
"position": 39,
"query": "AI workers"
},
{
"date": "2025/06/18",
"position": 7,
"query": "job automation statistics"
},
{
"date": "2025/06/18",
"position": 5,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/18",
"position": 8,
"query": "AI replacing workers"
},
{
"date": "2025/06/18",
"position": 97,
"query": "automation job displacement"
},
{
"date": "2025/06/18",
"position": 30,
"query": "robotics job displacement"
},
{
"date": "2025/06/18",
"position": 19,
"query": "AI employment"
},
{
"date": "2025/06/18",
"position": 7,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/18",
"position": 10,
"query": "AI job losses"
},
{
"date": "2025/06/18",
"position": 9,
"query": "AI replacing workers"
},
{
"date": "2025/06/18",
"position": 97,
"query": "automation job displacement"
},
{
"date": "2025/06/18",
"position": 28,
"query": "robotics job displacement"
},
{
"date": "2025/06/18",
"position": 23,
"query": "AI employment"
},
{
"date": "2025/06/18",
"position": 5,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/18",
"position": 6,
"query": "AI job losses"
},
{
"date": "2025/06/18",
"position": 12,
"query": "AI replacing workers"
},
{
"date": "2025/06/18",
"position": 38,
"query": "AI workers"
},
{
"date": "2025/06/18",
"position": 52,
"query": "automation job displacement"
},
{
"date": "2025/06/18",
"position": 8,
"query": "job automation statistics"
},
{
"date": "2025/06/18",
"position": 21,
"query": "AI employment"
},
{
"date": "2025/06/18",
"position": 49,
"query": "automation job displacement"
},
{
"date": "2025/06/18",
"position": 7,
"query": "job automation statistics"
},
{
"date": "2025/06/18",
"position": 11,
"query": "AI replacing workers"
},
{
"date": "2025/06/18",
"position": 9,
"query": "AI unemployment rate"
},
{
"date": "2025/06/18",
"position": 4,
"query": "job automation statistics"
},
{
"date": "2025/06/18",
"position": 25,
"query": "robotics job displacement"
},
{
"date": "2025/06/18",
"position": 20,
"query": "AI employment"
},
{
"date": "2025/06/18",
"position": 15,
"query": "AI impact jobs"
},
{
"date": "2025/06/18",
"position": 5,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/18",
"position": 71,
"query": "AI labor market trends"
},
{
"date": "2025/06/18",
"position": 10,
"query": "AI replacing workers"
},
{
"date": "2025/06/18",
"position": 38,
"query": "AI workers"
},
{
"date": "2025/06/18",
"position": 89,
"query": "artificial intelligence workers"
},
{
"date": "2025/06/18",
"position": 4,
"query": "job automation statistics"
},
{
"date": "2025/06/18",
"position": 13,
"query": "robotics job displacement"
},
{
"date": "2025/06/18",
"position": 72,
"query": "AI employers"
},
{
"date": "2025/06/18",
"position": 23,
"query": "AI employment"
},
{
"date": "2025/06/18",
"position": 5,
"query": "AI job creation vs elimination"
},
{
"date": "2025/06/18",
"position": 7,
"query": "AI job losses"
},
{
"date": "2025/06/18",
"position": 9,
"query": "AI labor market trends"
},
{
"date": "2025/06/18",
"position": 39,
"query": "AI layoffs"
},
{
"date": "2025/06/18",
"position": 10,
"query": "AI replacing workers"
},
{
"date": "2025/06/18",
"position": 25,
"query": "ChatGPT employment impact"
},
{
"date": "2025/06/18",
"position": 19,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/18",
"position": 86,
"query": "artificial intelligence workers"
},
{
"date": "2025/06/18",
"position": 10,
"query": "automation job displacement"
},
{
"date": "2025/06/18",
"position": 32,
"query": "future of work AI"
},
{
"date": "2025/06/18",
"position": 1,
"query": "job automation statistics"
},
{
"date": "2025/06/18",
"position": 2,
"query": "robotics job displacement"
},
{
"date": "2025/06/18",
"position": 86,
"query": "workplace AI adoption"
}
] |
In the age of AI, do human skills actually become more important?
|
In the age of AI, do human skills actually become more important?
|
https://community.spiceworks.com
|
[] |
We also don't trust the AI enough, so there is a gap between thinking about it (design, planning) and doing it (implementation). There are ...
|
Great question! I’m one of those who believe that AI won’t replace all IT (system people as well as developers) but will reduce lower-level positions.
The thing that concerns me is those people and organizations who, for reasons unknown, will block anyone using AI. I work in State government in one of the largest departments in my state. This week the CISO discovered that someone had taken data, which included personally identifiable information (PII) and personal health information (PHI), then fed that to ChatGPT, to help them analyze and produce a report on that data. It was clearly wrong. That person shouldn’t have done that. But, rather than chastise that person, the CISO has taken the nuclear option and has blocked AI for everyone. And since the CISO doesn’t collaborate with anyone, there’s nothing anyone can do, except no longer be able to use AI. (Well, unless they go out of their way to do nepharous analysis with AI.)
I think my CISO isn’t an isolated case or person. My guess is there are other high level people at other organizations, some in the C-suite, who will do everything within their power to prevent the use of AI for all employees. And maybe like my CISO, not communicate or collaborate with anyone; they’ll just exert their will upon everyone else. That just hurts many others who want to do the right thing in the right way, but will be held back for God only knows how long.
| 2025-06-20T00:00:00 |
2025/06/20
|
https://community.spiceworks.com/t/in-the-age-of-ai-do-human-skills-actually-become-more-important/1208726?page=2
|
[
{
"date": "2025/06/18",
"position": 40,
"query": "AI skills gap"
},
{
"date": "2025/06/18",
"position": 68,
"query": "AI skills gap"
},
{
"date": "2025/06/18",
"position": 72,
"query": "AI skills gap"
},
{
"date": "2025/06/18",
"position": 73,
"query": "AI skills gap"
},
{
"date": "2025/06/18",
"position": 73,
"query": "AI skills gap"
},
{
"date": "2025/06/18",
"position": 41,
"query": "AI skills gap"
},
{
"date": "2025/06/18",
"position": 72,
"query": "AI skills gap"
},
{
"date": "2025/06/18",
"position": 41,
"query": "AI skills gap"
},
{
"date": "2025/06/18",
"position": 67,
"query": "AI skills gap"
},
{
"date": "2025/06/18",
"position": 66,
"query": "AI skills gap"
},
{
"date": "2025/06/18",
"position": 73,
"query": "AI skills gap"
},
{
"date": "2025/06/18",
"position": 41,
"query": "AI skills gap"
},
{
"date": "2025/06/18",
"position": 35,
"query": "AI skills gap"
},
{
"date": "2025/06/18",
"position": 47,
"query": "AI skills gap"
},
{
"date": "2025/06/18",
"position": 56,
"query": "AI skills gap"
}
] |
Amazon boss tells staff AI means their jobs are at risk in coming years
|
Amazon boss tells staff AI means their jobs are at risk in coming years
|
https://www.theguardian.com
|
[
"Dan Milmo"
] |
The International Monetary Fund has calculated 60% of jobs in advanced economies such as the US and UK are exposed to AI and half of these jobs ...
|
The boss of Amazon has told white collar staff at the e-commerce company their jobs could be taken by artificial intelligence in the next few years.
Andrew Jassy told employees that AI agents – tools that carry out tasks autonomously – and generative AI systems such as chatbots would require fewer employees in certain areas.
“As we roll out more generative AI and agents, it should change the way our work is done,” he said in a memo to staff. “We will need fewer people doing some of the jobs that are being done today, and more people doing other types of jobs.
“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.”
Amazon employs 1.5 million people worldwide, with about 350,000 working in corporate jobs such as software engineering and marketing.
At the weekend the chief executive of the UK telecoms company BT said advances in AI could lead to deeper job cuts at the company, while Dario Amodei, the chief executive of the AI company Anthropic, said last month AI could wipe out half of all entry-level office jobs.
Jassy said in the near future there would be billions of AI agents working across companies and in people’s daily lives.
“There will be billions of these agents, across every company and in every imaginable field. There will also be agents that routinely do things for you outside of work, from shopping to travel to daily chores and tasks. Many of these agents have yet to be built, but make no mistake, they’re coming, and coming fast,” he said.
Jassy ended the memo by urging employees to be “curious about AI” and to “educate yourself” in the technology and take training courses.
“Those who embrace this change, become conversant in AI, help us build and improve our AI capabilities internally and deliver for customers, will be well positioned to have high impact and help us reinvent the company,” he said.
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The Organisation for Economic Co-operation and Development – an influential international policy organisation – has estimated the technology could trigger job losses in skilled white-collar professions such as law, medicine and finance. The International Monetary Fund has calculated 60% of jobs in advanced economies such as the US and UK are exposed to AI and half of these jobs may be negatively affected.
However, the Tony Blair Institute, which has called for widespread adoption of AI in the public and private sectors, has said the technology could displace up to 3m private sector jobs in the UK but the net loss will be mitigated by the technology creating new roles.
| 2025-06-18T00:00:00 |
2025/06/18
|
https://www.theguardian.com/technology/2025/jun/18/amazon-boss-tells-staff-ai-means-their-jobs-are-at-risk-in-coming-years
|
[
{
"date": "2025/06/18",
"position": 15,
"query": "AI job losses"
},
{
"date": "2025/06/18",
"position": 20,
"query": "AI job losses"
},
{
"date": "2025/06/18",
"position": 17,
"query": "AI job losses"
},
{
"date": "2025/06/18",
"position": 18,
"query": "AI job losses"
},
{
"date": "2025/06/18",
"position": 18,
"query": "AI job losses"
},
{
"date": "2025/06/18",
"position": 23,
"query": "AI job losses"
},
{
"date": "2025/06/18",
"position": 15,
"query": "AI job losses"
},
{
"date": "2025/06/18",
"position": 19,
"query": "AI job losses"
},
{
"date": "2025/06/18",
"position": 19,
"query": "AI job losses"
},
{
"date": "2025/06/18",
"position": 17,
"query": "AI job losses"
},
{
"date": "2025/06/18",
"position": 19,
"query": "AI job losses"
},
{
"date": "2025/06/18",
"position": 17,
"query": "AI job losses"
},
{
"date": "2025/06/18",
"position": 18,
"query": "AI job losses"
},
{
"date": "2025/06/18",
"position": 15,
"query": "AI job losses"
},
{
"date": "2025/06/18",
"position": 20,
"query": "AI job losses"
}
] |
AI Workforce Shift 2025: How Amazon Is Reshaping Jobs and Strategy
|
AI Workforce Shift 2025: How Amazon Is Reshaping Jobs and Strategy
|
https://blog.getaura.ai
|
[
"Aura'S Staff Are Dedicated Experts In Workforce Analytics",
"Organizational Decision Intelligence. Combining Deep Industry Knowledge With Cutting-Edge Ai Technology",
"They Empower Clients To Make Smarter",
"Faster",
"More Impactful Decisions. With Backgrounds In Consulting",
"Technology",
"Data Science",
"Aura S Team Is Passionate About Delivering Actionable Insights That Drive Innovation",
"Business Success."
] |
It is a total workforce transformation, where traditional job roles and business processes are redefined by AI technology, automation, and machine learning.
|
Amazon’s AI Bet: A New Blueprint for Workforce Strategy
When Amazon CEO Andy Jassy shared his latest internal memo on the company’s sweeping adoption of Generative AI, it wasn’t just an update. It was a signal that the definition of workforce strategy is changing faster than most companies realize. On social media, Jassy's remarks were praised for their clarity, but the implications are deeply transformative.
“We will need fewer people doing some of the jobs that are being done today,” Jassy wrote. “And more people doing other types of jobs.”
He also directly pointed to a reduced headcount: "We expect that this will reduce our total corporate workforce as we get efficiency gains from using AI extensively across the company."
However, the overall tone of the memo was optimistic, framing the transformation as an opportunity for innovation, increased efficiency, and more meaningful work, all of which are enabled by AI. Clearly, Amazon isn’t waiting around to figure out the future of work. It’s actively building it. And if you’re not watching closely, or if you’re still relying on outdated internal HR data, you risk being left behind in an AI-driven world where workforce transformation is accelerating across sectors.
Want to see how your organization compares to leaders like Amazon? Book a demo with Aura and uncover strategic opportunities in your workforce data.
How Generative AI Is Rewriting Job Roles and Business Processes
In the memo, Jassy outlines how Generative AI and agentic AI tools are transforming every corner of Amazon’s operations, from Alexa and shopping assistants to advertising, fulfillment, and internal product development.
One of the most revealing statements was that Amazon expects these shifts to result in reduced corporate headcount over time. But this is not just about efficiency. It is a total workforce transformation, where traditional job roles and business processes are redefined by AI technology, automation, and machine learning.
These changes reflect a new model in which AI algorithms, large language models, and human agents collaborate, creating new roles and redefining existing ones. Jassy's memo is candid about the fact that they are actively planning and learning along the way, expecting staff to adapt and learn as AI evolves.
Why Internal HR Data Falls Short in an AI-Driven World
We can see that as AI-driven systems reshape how work gets done, the internal HR data companies have often relied on become increasingly disconnected from reality.
What does an efficient, AI-integrated workforce ecosystem look like in your industry?
How are competitors using AI to automate repetitive tasks and close the skills gap?
Where are new opportunities emerging, and which roles are fading?
This is where Aura comes in.
Aura helps companies:
Benchmark workforce strategies against industry leaders like Amazon
Identify areas for cost savings, upskilling, or strategic automation
Understand how to integrate AI into existing processes while protecting data privacy and improving the employee experience
Analyze sentiment data both internally and externally, spotting signs of disengagement
Building Adaptive Teams for the AI Era
Jassy describes a return to leaner teams, scrappier work, and high impact per headcount. It is a shift that prioritizes human capabilities, adaptability, and soft skills, not just technical knowledge.
That means companies must:
Identify the right skills needed for hybrid human-AI teams
Support lifelong learning and targeted corporate training
Develop strategies for knowledge retention and cross-functional collaboration
Embrace continuous education and upskilling to support the future of work
Aura delivers the insights needed to do this by tracking talent shifts, anticipating workforce needs, and helping organizations adapt their strategies in real-time.
Strategic Moves to Align with AI-Driven Talent Shifts
If Amazon is setting the tone, others will follow. Here is how your organization can act now:
Explore how AI is impacting talent flows in your sector
Audit your existing workforce data to spot automation potential and skills gaps
Develop long-term strategies to support your employees, enhance productivity, and drive innovation
Use Aura to identify new skills, workforce risks, and high-impact business opportunities
The AI Workforce Shift Is Here: Don’t Get Left Behind
Andy Jassy’s memo likely reflects how other tech giants are thinking about AI in the workforce, and it may forecast their corporate workforce moves. The rise of AI, automation, and agentic AI is reshaping the workplace. Those who can identify the right scenarios, embrace change, and invest in more intelligent systems will not only keep pace but also gain a competitive advantage. They will lead.
Aura helps you turn signals like this into strategic action. Want to see how your workforce strategy stacks up?
Explore how our workforce analytics platform can future-proof your organization. Schedule your personalized demo today to see how Aura can help you adapt and lead in the age of AI.
| 2025-06-18T00:00:00 |
https://blog.getaura.ai/ai-workforce-shift-amazon
|
[
{
"date": "2025/06/18",
"position": 84,
"query": "AI workforce transformation"
},
{
"date": "2025/06/18",
"position": 93,
"query": "AI workforce transformation"
},
{
"date": "2025/06/18",
"position": 93,
"query": "AI workforce transformation"
},
{
"date": "2025/06/18",
"position": 97,
"query": "AI workforce transformation"
},
{
"date": "2025/06/18",
"position": 92,
"query": "AI workforce transformation"
}
] |
|
Amazon CEO Andy Jassy just got brutally honest about AI
|
Amazon CEO Andy Jassy just got brutally honest about AI — and other bosses may follow his lead
|
https://www.businessinsider.com
|
[
"Thibault Spirlet",
"Katherine Tangalakis-Lippert",
"Katherine Li"
] |
... layoffs with AI was not new — even if Jassy's openness felt like a turning point. "Firms do not hesitate to use AI as a reason to downsize ...
|
This story is available exclusively to Business Insider subscribers. Become an Insider and start reading now.
Amazon's CEO just said the quiet part out loud: AI is coming for plenty of jobs — and other bosses may soon follow his lead.
On Tuesday, Andy Jassy said in a memo that employees should figure out "how to get more done with scrappier teams" and that the move toward AI would eventually "reduce our total corporate workforce."
Amazon, with about 1.5 million workers, is the second-largest private employer in the US. Workplace commentators told Business Insider that Jassy's candor may prompt other leaders to feel comfortable telling their employees who — or what — will replace them.
'Culture modeling'
Marlo Lyons, an author and certified executive coach, said Amazon's directness might encourage other companies to follow suit.
"I think if you have a big company that's talking about AI, then it does make it easier for smaller companies to talk about AI — this is basically culture modeling," she told BI.
"In some ways, it might scare you, but at the same time, it should make you say, 'OK, at least my company's being honest to me about it,'" Lyons said.
Other CEOs have also become increasingly transparent about AI expectations, although few have explicitly said it would reduce their existing workforce.
Shopify CEO Tobi Lütke said in a memo in April that "AI usage is now a baseline expectation," and that before managers make a hire, they must first prove that AI couldn't do the job better.
Klarna CEO Sebastian Siemiatkowski said in December last year that the fintech had stopped hiring because "AI can already do all of the jobs that we as humans do."
Meanwhile, OpenAI CEO Sam Altman said earlier this month that AI agents were already beginning to act like junior-level coworkers and may soon be able to deliver business solutions.
Related stories Business Insider tells the innovative stories you want to know Business Insider tells the innovative stories you want to know
"It'll send shivers down the backs of employees," said Cary Cooper, professor of organizational psychology and health at Manchester Business School in the UK, of the Jassy memo. "I think it'll open it up for HR to now have discussions with senior management about how we deal with this — the introduction of AI in our business."
Cooper warned companies should be specific with staff about which jobs might be affected and what retraining opportunities are available, or risk "regrettable turnover" — losing the talent they most want to keep.
'Great scapegoat'
Thomas Roulet, professor of organisational sociology and leadership at the University of Cambridge, told BI that linking layoffs with AI was not new — even if Jassy's openness felt like a turning point.
"Firms do not hesitate to use AI as a reason to downsize, whether it is an excuse or an opportunity," he said. "Very often, they downsize before even thinking what they will replace with AI, due to market pressures."
"AI is a great scapegoat for a lot of unpopular strategic choices at the moment," Roulet added.
"There is enormous pressure on companies to show that they are able to replace employees with AI tools," Peter Cappelli, a professor of management at The Wharton School, told BI. "But the evidence indicates that it is very difficult to do so."
Klarna, for example, made headlines in 2022 when the company laid off 700 employees, mostly customer service agents, in favor of AI. In May, the financial services company had to hire some back to improve its services.
In Roulet's view, many companies that have already cut jobs in favor of AI were moving too fast.
"Unfortunately, many firms think of workforce reduction and engage with such reductions before they even think about AI replacement," said Roulet. "The reality is that bringing in AI into work takes a lot of learning cycles and trial and error — it does not appear clearly overnight."
| 2025-06-18T00:00:00 |
https://www.businessinsider.com/ai-layoffs-jobs-andy-jassy-amazon-honesty-workers-2025-6
|
[
{
"date": "2025/06/18",
"position": 83,
"query": "AI layoffs"
},
{
"date": "2025/06/18",
"position": 89,
"query": "AI layoffs"
},
{
"date": "2025/06/18",
"position": 83,
"query": "AI layoffs"
},
{
"date": "2025/06/18",
"position": 95,
"query": "AI layoffs"
},
{
"date": "2025/06/18",
"position": 86,
"query": "AI layoffs"
},
{
"date": "2025/06/18",
"position": 83,
"query": "AI layoffs"
},
{
"date": "2025/06/18",
"position": 84,
"query": "AI layoffs"
},
{
"date": "2025/06/18",
"position": 87,
"query": "AI layoffs"
},
{
"date": "2025/06/18",
"position": 83,
"query": "AI layoffs"
},
{
"date": "2025/06/18",
"position": 66,
"query": "AI layoffs"
},
{
"date": "2025/06/18",
"position": 83,
"query": "AI layoffs"
},
{
"date": "2025/06/18",
"position": 67,
"query": "AI layoffs"
},
{
"date": "2025/06/18",
"position": 24,
"query": "AI layoffs"
}
] |
|
Should journalism embrace AI? Or run from it? - Poynter
|
Should journalism embrace AI? Or run from it?
|
https://www.poynter.org
|
[
"Tom Jones",
"Tom Jones Is Poynter S Senior Media Writer For Poynter.Org. He Was Previously Part Of The Tampa Bay Times Family During Three Stints Over Some",
".Wp-Block-Co-Authors-Plus-Coauthors.Is-Layout-Flow",
"Class",
"Wp-Block-Co-Authors-Plus",
"Display Inline",
".Wp-Block-Co-Authors-Plus-Avatar",
"Where Img",
"Height Auto Max-Width",
"Vertical-Align Bottom .Wp-Block-Co-Authors-Plus-Coauthors.Is-Layout-Flow .Wp-Block-Co-Authors-Plus-Avatar"
] |
In the latest episode of 'The Poynter Report Podcast,' Alex Mahadevan explores what AI means for journalism and why reporters may not need to panic.
|
We start with the latest episode of “The Poynter Report Podcast,” which is out today. My guest is Alex Mahadevan, director of Poynter’s MediaWise and a member of Poynter’s faculty.
He is also the co-author of Poynter’s first-ever AI ethics guide. And that’s what our conversation is about: artificial intelligence. Specifically, artificial intelligence and journalism.
Should journalism run from AI? Or embrace it? Why are we scared of it? How can we put AI to good use? And how can we avoid the dangers of AI?
And, what I wanted to know most of all: Are journalists someday going to become obsolete because some AI tool is going to produce its own newspaper? (And, gulp, newsletter?)
Mahadevan, who studies and teaches about AI extensively, told me that “anyone who does journalism is going to be safe as long as they double down on the skills that make them really good journalists, which is being able to talk, engage with people, to have that sense of where the story is and develop sources.”
He added, “I think the fear of job replacement is a little overblown.”
Mahadevan and I get into some of the many pitfalls that AI brings to journalism, but also some of the many benefits.
Whether you are a journalist or not, I think you’ll find our conversation interesting. And if you are in journalism or a part of a newsroom, check out “Talking About AI: Newsroom Toolkit.” Created by MediaWise in partnership with The Associated Press and supported by Microsoft, this guide is for journalists and media professionals who want to incorporate AI literacy into their reporting and other newsroom processes.
As far as the podcast, aside from watching on YouTube, you can also find the podcast on Apple, Spotify, and most places where you find podcasts.
A senator’s relentless and insensitive social media use
While no politician is more known for his social media use than President Donald Trump, another high-profile Republican is under scrutiny — and criticism — for his. Sen. Mike Lee of Utah is taking heavy criticism for insensitive tweets he sent out following the shootings in Minnesota last weekend that killed one Democratic state representative and her husband and left two others injured.
Lee tweeted, “This is what happens when Marxists don’t get their way,” along with the photo of the suspected shooter. In another tweet, Lee posted a photo of the suspected shooter and wrote, “Nightmare on Waltz Street” — the “Waltz” part being a reference to Minnesota Democratic Gov. Tim Walz. In another tweet, Lee, upon learning the suspect had papers for a “No Kings” protest in his car, wrote, “Marxism is a deadly mental illness.”
The tweets have since been deleted, and he tried to backtrack by posting another tweet that said, “These hateful attacks have no place in Utah, Minnesota, or anywhere in America. Please join me in condemning this senseless violence, and praying for the victims and their families.”
By then, it might have been too late. It didn’t erase the storm of criticism for what he had previously said.
The Washington Post’s Theodoric Meyer reports that Minnesota Sen. Tina Smith confronted Lee outside the Senate chamber earlier this week. Smith told Meyer what she told Lee: “‘I said, ‘People like you and me don’t talk to each other that much, but this feels like something that we really need to talk about face to face.’”
Smith told reporters, “I wanted him to know how much pain that caused me and the other people in my state, and I think around the country, who think that this was a brutal attack. I don’t know whether Sen. Lee thought fully through what it was — you have to ask him — but I needed him to hear from me directly what impact I think his cruel statement had on me, his colleague.”
Smith declined to say what Lee said in response when confronted, but added, “I think he listened to what I said. He indicated that he, of course, meant no harm. But, of course, these things do cause harm. They hurt people.” Smith said Lee seemed “a little surprised” to be confronted.
Many lawmakers condemned Lee’s remarks, including Senate Minority Leader Chuck Schumer, who said he was “sickened” by Lee’s comments.
Lee ignored questions from reporters at the Senate on Monday about his tweets, and his office has not responded to requests for comment from news outlets, according to the Post.
Meanwhile, MSNBC’s Lawrence O’Donnell called on air for some of Lee’s staff to resign, saying, “Sen. Mike Lee’s staff now live in the disgrace he has visited upon them, and they all have a moral choice in front of them now. Mike Lee purports to be a man of great religiosity, but he is obviously not a man of great morality or great decency, and his staff has to decide tonight what to do about the disgrace he has handed them.”
O’Donnell said anyone who doesn’t fully support Lee’s original tweets should resign, adding, “You have your own choice to make. If you agree with Mike Lee’s choice to make jokes about assassination of a Democratic office holder in Minnesota, if you agree with that, then stay with Mike Lee. Stick with Mike Lee; stick with him all the way. But if you do have decency, you know you only have one choice.”
This does not appear to be a one-off in terms of Lee and his social media use. The Bulwark’s Joe Perticone writes, “Mike Lee Needs an Intervention.”
About the now-deleted tweets, Perticone writes, “The fact that he put them up in the first place — and that it apparently took a very rare, personal rebuke from a fellow senator to get him to take them down — is the clearest illustration to date of the fact that even United States senators can have their brains (and hearts) rotted out by social media.”
Perticone notes that Lee is more than a casual social media user, writing, “The Bulwark conducted a review of Mike Lee’s Twitter feed, @BasedMikeLee, over the past month. During that time period (30 days), the senator posted nearly 1,400 times, or about 46 posts a day. Of those posts, about half (697) were original tweets. The rest were retweets of other accounts or his own posts. The posts came mostly during normal business hours. But not exclusively. Of the nearly 700 posts Lee authored on Twitter, 47 of them came between the hours of 3am and 6am eastern standard time.”
About 46 posts a day?! That seems troubling for a politician.
Perticone added, “The first step to overcoming any addiction is admitting you have a problem. That’s a step that Lee has not yet taken when it comes to his phone. Perhaps he finds value in being this online. Perhaps it’s good for his political brand, or for fundraising. Maybe he just lives for the liberal tears. But maybe he should enlist the help of a former colleague who quit Twitter after considering ‘the data about the way social media is designed to create dopamine hits for teenage kids.’ Until then, you can expect more deranged and adolescent behavior from Lee. In the meantime, props to Sen. Smith for confronting him about it.”
Covering the shooting
Interesting work here from Slate’s Aymann Ismail: “Two Unimaginable Days in Minnesota.” Ismail talks to Christopher Vondracek, a D.C. correspondent for The Minnesota Star Tribune and one of the lead reporters on the Star Tribune’s coverage of the shootings.
Ismail asked Vondracek for the most remarkable bit of information he uncovered last weekend.
Vondracek said, “By the end of the day on Saturday, the police confirmed that they were looking for a suspect named Vance Boelter. It came out that police stopped Boelter’s wife and three relatives at a gas station. They appeared to be on a very popular highway, 169, near this big lake called Mille Lacs where a lot of folks go. Apparently, the sheriff got word from Hennepin County, and a reporter did interviews and found out they had gotten gas-station pizza and soda pops and then sat out in lawn chairs for like five hours at this gas station, doing this interview. And the way they phrased it was that they were questioning her. I’m sure they’re also trying to find out what she knew and what she didn’t know. Finding out who Boelter is was also weird. We found out he has this evangelical fervor and had gone on mission trips to Africa and had made anti-trans, homophobic commentary in the Democratic Republic of Congo. His résumé looked really funky, like something cooked up by A.I. He also had many a half-cooked business plan to be a security professional and had some vehicles that looked like they were law enforcement vehicles; I wasn’t on the Boelter part of this story, but everything from working at a mortuary to managing a gas station. He had a farm down in Green Isle, where he was from, a town of like 200 people. It was where he was found Sunday night.”
Check out the full Q&A for how the story went from the news breaking to the reporting to the publication.
Wanna play a game?
There’s a new game in town. Actually, make that games. The Atlantic on Tuesday introduced additions to its games — a move that clearly is trying to tap into some of the success that The New York Times has had with its selection of games, including the wildly popular Wordle.
The two new additions to The Atlantic’s games are Stacks, where players stack a bank of words to form new words, and Fluxis, where players build a circuit of words through categories looping back to the first word.
Those games join existing Atlantic games Bracket City, where clues within clues reveal a single fact about that day in history; The Atlantic Crossword; and another monthly crossword called Caleb’s Inferno.
The Atlantic says all games are playable now, and full archives will soon be available exclusively for Atlantic subscribers.
Media tidbits
The Atlanta Journal Constitution’s Lautaro Grinspan with “ICE moves to deport Atlanta-based Hispanic reporter who covered immigration raids.”
Hot type
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The Poynter Report is your daily dive into the world of media, packed with the latest news and insights. Get it delivered to your inbox Monday through Friday by signing up here. And don’t forget to tune into our biweekly podcast for even more.
| 2025-06-18T00:00:00 |
2025/06/18
|
https://www.poynter.org/commentary/2025/should-journalism-embrace-ai-or-run-from-it/
|
[
{
"date": "2025/06/18",
"position": 69,
"query": "AI journalism"
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"date": "2025/06/18",
"position": 70,
"query": "AI journalism"
},
{
"date": "2025/06/18",
"position": 69,
"query": "AI journalism"
},
{
"date": "2025/06/18",
"position": 72,
"query": "AI journalism"
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{
"date": "2025/06/18",
"position": 69,
"query": "AI journalism"
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"date": "2025/06/18",
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"query": "AI journalism"
},
{
"date": "2025/06/18",
"position": 5,
"query": "artificial intelligence journalism"
}
] |
Companies That Replaced Humans With AI Are Realizing Their ...
|
Companies That Replaced Humans With AI Are Realizing Their Mistake
|
https://futurism.com
|
[] |
Despite widespread hype, so-called "AI agents" — a software product that's supposed to complete human-level tasks autonomously — have yet to ...
|
According to tech billionaire and OpenAI CEO Sam Altman, 2025 was supposed to be the year "when AI agents will work."
Despite widespread hype, so-called "AI agents" — a software product that's supposed to complete human-level tasks autonomously — have yet to live up to their name. As of April, even the best AI agent could only finish 24 percent of the jobs assigned to it. Still, that didn't stop business executives from swarming to the software like flies to roadside carrion, gutting entire departments worth of human workers to make way for their AI replacements.
But as AI agents have yet to even pay for themselves — spilling their employer's embarrassing secrets all the while — more and more executives are waking up to the sloppy reality of AI hype.
A recent survey by the business analysis and consulting firm Gartner, for instance, found that out of 163 business executives, a full half said their plans to "significantly reduce their customer service workforce" would be abandoned by 2027.
This is forcing corporate PR spinsters to rewrite speeches about AI "transcending automation," instead leaning on phrases like "hybrid approach" and "transitional challenges" to describe the fact that they still need humans to run a workplace.
"The human touch remains irreplaceable in many interactions, and organizations must balance technology with human empathy and understanding," said Kathy Ross, Gartner's senior director of customer service and support analysis.
That's a vibe employees have been feeling for a while now. Another report, this one by IT firm GoTo and research agency Workplace Intelligence, found that 62 percent of employees are currently saying that AI is "significantly overhyped."
Likewise, only 45 percent of corporate IT managers reported having a formal AI policy in place, suggesting a scattered and hasty rollout of the tech. Of those IT leaders, 56 percent said "security concerns" and "integration challenges" were the main barriers to AI adoption.
The reports come as a number of businesses have already made the humiliating walk-back of shame in recent weeks.
Finance startup Klarna, for example, reduced its workforce by 22 percent throughout 2024 ahead of the long-promised AI revolution. But then the company did an about-face on its AI strategy back in May, announcing a "recruitment drive" to bring all those meat bags back to work.
According to tech critic Ed Zitron, the whole agentic charade can be explained by the fact that "it isn't obvious what any of these AI-powered products do, and when you finally work it out, they don't seem to do that much."
"These 'agents' are branded to sound like intelligent lifeforms that can make intelligent decisions," Zitron writes, "but are really just trumped-up automations that require enterprise customers to invest time programming them."
More on AI: OpenAI Shows Off AI "Researcher" That Compiles Detailed Reports, Struggles to Differentiate "Information From Rumors"
| 2025-06-18T00:00:00 |
https://futurism.com/companies-replaced-workers-ai
|
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{
"date": "2025/06/18",
"position": 58,
"query": "artificial intelligence employers"
},
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"date": "2025/06/18",
"position": 26,
"query": "AI replacing workers"
},
{
"date": "2025/06/18",
"position": 22,
"query": "AI replacing workers"
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{
"date": "2025/06/18",
"position": 26,
"query": "AI replacing workers"
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"date": "2025/06/18",
"position": 57,
"query": "AI employers"
},
{
"date": "2025/06/18",
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"query": "AI replacing workers"
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] |
|
The Future of Work: Robotics and Employment - Number Analytics
|
The Future of Work: Robotics and Employment
|
https://www.numberanalytics.com
|
[
"Sarah Lee"
] |
One of the primary concerns about robotics and automation is the potential for job displacement. As machines become more capable, there is a ...
|
Exploring the Impact of Automation on Jobs and Society
The world is on the cusp of a technological revolution, with robotics and automation transforming the way we work and live. As machines become increasingly sophisticated, they are taking on tasks that were previously the exclusive domain of humans. This shift has significant implications for employment, with both benefits and challenges arising from the integration of robotics and automation into various industries. In this comprehensive guide, we will explore the current state of robotics and automation, their impact on employment, and the strategies for balancing the benefits and risks.
The Rise of Robotics and Automation
Overview of the Current State of Robotics and Automation
Robotics and automation have been advancing rapidly over the past few decades, driven by improvements in artificial intelligence (AI), machine learning, and sensor technologies. Today, robots and automated systems are being used in a wide range of industries, from manufacturing and logistics to healthcare and finance.
Statistics on the Growth of Robotics in Various Industries
The growth of robotics and automation is a global phenomenon, with significant investments being made by companies and governments around the world. According to a report by the International Federation of Robotics (IFR), the global robotics market was valued at _USD_43.8 billion in 2020 and is expected to grow to _USD_135.4 billion by 2025, at a compound annual growth rate (CAGR) of 25.4% 1.
Industry 2020 2025 (Projected) Manufacturing _USD_23.4 billion _USD_63.2 billion Logistics and Supply Chain _USD_4.3 billion _USD_13.4 billion Healthcare _USD_2.5 billion _USD_6.3 billion Finance _USD_1.2 billion _USD_3.5 billion
Examples of Robots and Automation in Different Sectors
Robots and automated systems are being used in a variety of applications, including:
Manufacturing : Assembly line robots, welding robots, and inspection robots are being used to improve efficiency and reduce costs.
: Assembly line robots, welding robots, and inspection robots are being used to improve efficiency and reduce costs. Logistics and Supply Chain : Automated storage and retrieval systems, robotic picking and packing systems, and autonomous vehicles are being used to streamline logistics operations.
: Automated storage and retrieval systems, robotic picking and packing systems, and autonomous vehicles are being used to streamline logistics operations. Healthcare : Robots are being used for surgery, patient care, and rehabilitation.
: Robots are being used for surgery, patient care, and rehabilitation. Finance: Automated systems are being used for trading, risk management, and customer service.
The Impact on Employment
The introduction of robotics and automation into various industries has significant implications for employment. While there are concerns about job displacement, there are also opportunities for new job creation and upskilling.
Job Displacement and the Potential for Job Loss
One of the primary concerns about robotics and automation is the potential for job displacement. As machines become more capable, there is a risk that they will replace human workers, particularly in sectors where tasks are repetitive or can be easily automated.
According to a report by the McKinsey Global Institute, up to 800 million jobs could be lost worldwide due to automation by 2030 2.
New Job Opportunities Created by Robotics and Automation
While robotics and automation may displace some jobs, they also create new opportunities for employment. For example:
Robotics Engineers : The development and maintenance of robots and automated systems require skilled engineers and technicians.
: The development and maintenance of robots and automated systems require skilled engineers and technicians. Data Analysts : The data generated by robots and automated systems requires analysis and interpretation, creating new opportunities for data analysts and scientists.
: The data generated by robots and automated systems requires analysis and interpretation, creating new opportunities for data analysts and scientists. AI and Machine Learning Experts: The development of AI and machine learning algorithms requires experts in these fields.
The Need for Upskilling and Reskilling in the Workforce
As robotics and automation transform the world of work, there is a growing need for upskilling and reskilling in the workforce. Workers will need to develop new skills to work alongside machines and to take advantage of new job opportunities.
According to a report by the World Economic Forum, by 2022, more than a third of the desired skills for most jobs will be comprised of skills that are not yet considered crucial to the job today 3.
Balancing the Benefits and Risks
The integration of robotics and automation into various industries has both benefits and risks. While there are concerns about job displacement and bias, there are also opportunities for increased productivity and efficiency.
The Benefits of Robotics and Automation
The benefits of robotics and automation include:
Increased Productivity : Robots and automated systems can work around the clock without breaks, improving productivity and efficiency.
: Robots and automated systems can work around the clock without breaks, improving productivity and efficiency. Improved Quality : Robots and automated systems can perform tasks with a high degree of accuracy and precision, improving quality and reducing waste.
: Robots and automated systems can perform tasks with a high degree of accuracy and precision, improving quality and reducing waste. Cost Savings: Robots and automated systems can reduce labor costs and improve supply chain efficiency.
The Risks and Challenges Associated with Robotics and Automation
The risks and challenges associated with robotics and automation include:
Job Displacement : The potential for job displacement is a significant concern, particularly in sectors where tasks are repetitive or can be easily automated.
: The potential for job displacement is a significant concern, particularly in sectors where tasks are repetitive or can be easily automated. Bias and Discrimination : AI and machine learning algorithms can perpetuate bias and discrimination if they are trained on biased data.
: AI and machine learning algorithms can perpetuate bias and discrimination if they are trained on biased data. Cybersecurity Risks: Robots and automated systems can be vulnerable to cyber attacks, particularly if they are connected to the internet.
Strategies for Mitigating the Risks and Maximizing the Benefits
To mitigate the risks and maximize the benefits of robotics and automation, companies and governments can implement the following strategies:
Upskilling and Reskilling : Invest in upskilling and reskilling programs to help workers develop new skills.
: Invest in upskilling and reskilling programs to help workers develop new skills. Responsible AI Development : Develop AI and machine learning algorithms that are transparent, explainable, and fair.
: Develop AI and machine learning algorithms that are transparent, explainable, and fair. Cybersecurity Measures: Implement robust cybersecurity measures to protect robots and automated systems from cyber attacks.
The following flowchart illustrates the steps that can be taken to mitigate the risks and maximize the benefits of robotics and automation:
graph LR; A["Identify Risks and Benefits"] --> B["Upskilling and Reskilling"]; A --> C["Responsible AI Development"]; A --> D["Cybersecurity Measures"]; B --> E["Maximize Benefits"]; C --> E; D --> E; E --> F["Monitor and Evaluate"]; F -->|"Yes"| G["Adjust Strategies"]; F -->|"No"| H["Continue to Monitor"];
Conclusion
The future of work is being shaped by robotics and automation, with significant implications for employment. While there are concerns about job displacement, there are also opportunities for new job creation and upskilling. By understanding the benefits and risks of robotics and automation, companies and governments can implement strategies to mitigate the risks and maximize the benefits.
References
International Federation of Robotics. (2020). World Robotics Report 2020. Retrieved from https://ifr.org/ifr-press-releases/news/robotics-market-to-grow-to-135.4-billion-by-2025 McKinsey Global Institute. (2017). A future that works: Automation, employment, and productivity. Retrieved from https://www.mckinsey.com/featured-insights/digital-disruption/where-machines-could-replace-humans-and-where-they-could-not World Economic Forum. (2018). The Future of Jobs Report 2018. Retrieved from https://www.weforum.org/reports/the-future-of-jobs-report-2018
FAQ
Q: Will robots replace human workers?
A: While robots and automation may displace some jobs, they also create new opportunities for employment. It's likely that robots will augment human capabilities rather than replace them entirely.
Q: What skills will be required to work with robots and automation?
A: Workers will need to develop new skills to work alongside machines, including skills in AI, machine learning, and data analysis.
Q: How can companies mitigate the risks associated with robotics and automation?
A: Companies can mitigate the risks by investing in upskilling and reskilling programs, developing responsible AI, and implementing robust cybersecurity measures.
Q: What are the benefits of robotics and automation?
A: The benefits include increased productivity, improved quality, and cost savings.
Q: What are the risks associated with robotics and automation?
A: The risks include job displacement, bias and discrimination, and cybersecurity risks.
| 2025-06-18T00:00:00 |
https://www.numberanalytics.com/blog/robotics-and-employment-guide
|
[
{
"date": "2025/06/18",
"position": 78,
"query": "robotics job displacement"
},
{
"date": "2025/06/18",
"position": 39,
"query": "robotics job displacement"
},
{
"date": "2025/06/18",
"position": 40,
"query": "job automation statistics"
},
{
"date": "2025/06/18",
"position": 3,
"query": "robotics job displacement"
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] |
|
AI classrooms: The future of education - Telefónica
|
AI classrooms: The future of education
|
https://www.telefonica.com
|
[
"Junior Manager Of Digital Public Policy"
] |
The integration of artificial intelligence (AI) in education has the potential to transform the way students learn, positively impacting their academic ...
|
Firstly, AI introduces new approaches to teaching that take individual needs into account. Through data analysis and pattern identification, AI generates lessons, activities and content adapted to the learning pace and educational level of each student.
Secondly, not all families have sufficient resources to be able to access private tutoring, limiting the possibilities for students with less purchasing power. The democratisation of AI helps to reduce this barrier, generating a new, more inclusive education system.
Thirdly, AI systems offer complete availability 24 hours a day, 7 days a week. This gives students greater flexibility, making it easier for them to balance their academic development with extracurricular, leisure or work activities.
Finally, the AI can repeat lessons and provide feedback as many times as necessary without experiencing frustration or exhaustion. In this way, students can review academic content without fear of ‘annoying’ or ‘tiring’ the system. Additionally, the AI does not make value judgements, reducing the external pressure that can influence students when asking questions or proposing answers.
Countries with strategies for the application of artificial intelligence in the education system
Aware of these advantages, some countries, such as South Korea, Singapore and Finland, have already begun to integrate artificial intelligence into their education systems.
South Korea has positioned itself as one of the countries leading the application of AI in the classroom. Several schools in the country already use AI-based systems to adapt tasks to the academic level of their students. In addition, South Korea aims to introduce AI as a subject within its educational programme.
Another Asian country that stands out in the introduction of AI in education is Singapore. As part of the ‘Smart Nation’ strategy, Singapore is developing an AI system with the aim of increasing students’ academic performance. More specifically, this new system will offer a personalised experience through continuous assessment accompanied by feedback and corrections.
Finally, despite not having a defined implementation strategy as in the previous two cases, Finland stands out for its unique approach to the application of AI in the classroom. Focusing on the well-being of students, the country is designing an AI system that not only allows for personalisation of teaching, but also collects data on emotional and psychological state with the aim of offering adequate support that considers the state and needs of students.
Spain’s progress in integrating artificial intelligence in the classroom
Through its Artificial Intelligence Strategy 2020, which was recently revised in 2024, Spain has sought to position itself as a leading country in the design and application of AI. However, it does not yet have a defined strategy for implementing AI in the classroom. The closest initiative in this area is the publication of the Guide on the use of artificial intelligence in education, produced by the National Institute of Educational Technologies and Teacher Training (INTEF), which reports to the Ministry of Education, Vocational Training and Sport. The document offers a comprehensive approach to applying AI in the education system in a way that benefits both teachers and students. In addition, it provides guidance on how to address challenges such as the lack of adequate training among educators, data management and the need for appropriate technological infrastructures in order to ensure an effective and accessible implementation of AI in the classroom.
In conclusion, artificial intelligence in education offers the potential to transform the learning experience, making it more personalised, flexible and accessible. This technology provides continuous support, adapts to the individual needs of each student and promotes greater equity in access to particular teaching. Recognising these benefits, some countries are already beginning to design and apply AI strategies in classrooms in order to improve student performance and well-being. In the process, it is crucial to ensure that the AI system has been developed with ethical principles in mind and that students make responsible use of the technology.
| 2025-06-18T00:00:00 |
2025/06/18
|
https://www.telefonica.com/en/communication-room/blog/ai-classrooms-future-education/
|
[
{
"date": "2025/06/18",
"position": 3,
"query": "AI education"
}
] |
AI Can Save Teachers Time and Stress. Here's How
|
AI Can Save Teachers Time and Stress. Here's How (Opinion)
|
https://www.edweek.org
|
[
"Larry Ferlazzo Is A Former Award-Winning High School English",
"Social Studies Teacher Of More Than Two Decades.",
"Fri.",
"July",
"A.M. - P.M. Et",
"Thu.",
"August",
"P.M. - P.M. Et"
] |
AI can summarize text, adjust reading levels, create stories or nonfiction text from a prompt or information you feed it, and create discussion and multiple- ...
|
Today’s post continues a series in which educators share how they are—or are not—using artificial intelligence in their practice.
Saving Time
Donna L. Shrum is an educator, researcher, and freelance author in the Shenandoah Valley of Virginia.
I shared my new AI romance with a former teaching partner as we drove to a conference. His face twisted as so many teachers’ do when they hear AI and immediately picture a student hunched over the computer, hacking into the newest version of “copy and paste.”
“Ethically,” he said, “I just don’t think I ever could use it. It doesn’t seem fair.”
I sighed. “Picture yourself when everyone is switching from the wooden plow to the steel. You say, ‘I just don’t think I can use this new tool that will save me hours of grunt work. It doesn’t seem fair.’”
My school system has totally blocked AI for student use, so we’re only dealing with cheating when they use it from home. I asked permission to unblock an AI tool to provide immediate writing feedback during workshop time. I first vetted the tool and ascertained students couldn’t use it to cheat. I was refused for a similar reason we’d refuse a student: “The reason why AI writing feedback is blocked is because we have encountered situations where student writing was not read by a teacher, and the AI was providing feedback that the teacher was not able to see. We value the teacher’s role in the feedback cycle so students can have discussions with the teacher about their writing and for the teacher to have an understanding of students’ writing needs in order to plan next steps in instruction.”
The brave new world of AI comes with so many negative connotations and preconceived ideas like those above that AI has become synonymous with cheating, whether by student or teacher. I was fortunate to have enthusiastic AI users in my professional learning network who pushed me to try it.
My go-to is Magic School . Just as I’ve learned to recognize student voice in writing, I quickly discerned the bland voice of AI. I tested its ability to create lesson plans, and each one was similar. AI does not have the ability to be creative. Each tool I tried showed me its limitations but also the potential to get rid of hours of grunt work.
I learned to use AI just before I was knocked out by emergency gallbladder surgery. The surgeon said to stay off work for two weeks; I stubbornly went back after a week. My utter mental and physical exhaustion soon showed me why I shouldn’t have. If not for AI, I’d never have made it.
AI can summarize text, adjust reading levels, create stories or nonfiction text from a prompt or information you feed it, and create discussion and multiple-choice questions. What it spews out in a matter of seconds is not a finished product to my standards, but a rough draft I finish crafting.
Particularly when I’m mentally exhausted, I can use this tool to create my starting point, not my finished product. Before, this part ate up time and energy. AI prepares the rough draft of an assignment so I can focus my energy on the real work of crafting and creating. Using my AI “plow” to break ground has increased the quality of my lessons because I no longer waste mental acuity cobbling together the rough draft.
As an example, I recently created an assignment for a colleague. I pasted several different chunks of information into “Academic Content” and asked Magic School to create a textbook page. I added state standard terms and other revisions to it, then pasted sections into “Text Dependent Questions” and asked for three multiple-choice questions. I did it in sections because I’ve found the question quality is better if I don’t paste the whole article at once. I then proofed, revised the questions, and was ready to print. The whole process from start to finish was about 15 minutes.
The levels of my classes range from honors to remedial. I can plug the same assignment into AI to adjust the reading level and translate it for English learners. I’ve always done that, but it took hours. Now it takes minutes.
AI in Science Class
Bonnie Nieves is an educator and consultant who specializes in the intersection of next generation science teaching, culturally responsive methods, and artificial intelligence to provide authentic learning experiences for every student:
As a high school science teacher, I have always been committed to providing my students with the tools and skills they need to engage with scientific research. However, the dense language and complex concepts found in peer-reviewed journals often present barriers for students. To overcome this challenge, I have integrated AI tools into my teaching practice, making research more accessible and fostering a deeper understanding of scientific research papers.
Peer-reviewed research articles are crucial for advancing scientific knowledge, but they can be daunting for high school students due to their complexity. The specialized language and advanced methodologies often leave students feeling overwhelmed, preventing them from engaging with the content.
To address this issue, I introduced PerplexityAI into my classroom. This AI-driven platform helps break down complex research articles, making them more approachable for students. By using AI as a learning aid, Perplexity has contributed to an inclusive learning environment where every student can confidently explore and understand advanced scientific content.
The Process of Using AI Tools
I began by introducing Perplexity to my students as a resource for accessing peer-reviewed research. This AI tool summarizes and simplifies complex content while maintaining the meaning of the article. By doing so, students can better comprehend the material and engage in meaningful discussions about their findings.
Guided Introduction: Initially, I use a hybrid approach, having students use Perplexity to “ask questions” to the peer-reviewed articles they found in Gale Databases. I provide students with guided prompts to use with Perplexity, helping them understand how to extract information from research articles. This method allows students to see how AI could assist in breaking down complicated information into manageable pieces.
Encouraging Independent Exploration: Once students become comfortable with the tool, I encourage them to generate their own prompts. This practice empowered them to take ownership of their learning, enabling them to tailor their research approach based on their interests and curiosities.
Promoting Critical Reflection: Students document their interactions with the AI tool, reflecting on how it influenced their understanding and approach to the research. This reflection process has proved helpful in developing their critical-thinking skills and encouraging them to evaluate the validity and reliability of the AI-generated information.
Cultivating Inquiry and Engagement
By integrating AI into my teaching, I hope to cultivate a culture of inquiry and engagement. Students have been encouraged to explore topics that pique their interest, leading to more meaningful and personalized learning experiences. This new routine has made it much easier to scaffold differentiated instruction while empowering students to engage with content that resonates with them personally.
AI tools do more than facilitate individual exploration—they can also enhance collaborative learning. Encouraging students to share their findings and interpretations in group discussions promotes diverse perspectives and deeper understanding. This collaborative approach mirrors the real-world scientific community, where researchers work together to tackle complex problems.
Assessing Progress and Growth
I found the need to adjust my assessment methods to evaluate both the process and the product of student learning. Students documented their research journey, including the prompts used and responses generated by PerplexityAI. This documentation served as a reflective tool, allowing them and me to analyze their approach and refine their strategies.
Regular reflection exercises and guided discussions helped build metacognitive awareness. In addition to content discussions, students participated in sessions where they shared strategies that worked, challenges they faced, and how they overcame them. Students began to notice that the balance of peer review of content and process mirrored scientific research in the real world.
Integrating AI research tools like Perplexity into the classroom has transformed how my students access and engage with peer-reviewed research. By removing barriers, AI empowers students to explore scientific articles with confidence and curiosity. Even with my high expectations, I was impressed with how it not only improved students’ understanding of scientific concepts but also equipped them with critical-thinking skills essential for success in the modern world.
Through this journey, I’ve witnessed firsthand the power of AI in education and the profound impact it can have on student learning. By leveraging AI, we can create a more inclusive and engaging learning environment that prepares students for the challenges and opportunities of the future.
Reducing Stress
Kayla Towner is a product manager and technology instructor for Utah Education Network (UEN) and a Hope Street Fellow in Salt Lake City. Follow her on Twitter @mrstowner9 or email her at [email protected]:
I specialize in supporting adult educators, and one of my areas of focus is demonstrating how artificial intelligence can alleviate stress. Here are five ways I have used AI to reduce my stress, and these strategies can benefit other educators and students.
Emails
Educators and administrators often find themselves flooded with emails. The sheer volume of messages can be overwhelming, making it challenging to respond promptly. Striking the right balance between clear, professional communication and a personable tone can be tricky.
Thankfully, Generative AI platforms like Chat GPT, Gemini, or Microsoft Copilot can streamline this process. Here are some ways you can leverage these tools:
Behavior-Notice Templates: Use AI to draft behavior-notice templates for informing parents about incidents. These templates can be customized and personalized while maintaining a professional tone.
Multilingual Communication: If you need to communicate with parents who speak different languages, AI can accurately translate your messages into dozens of languages.
Weekly Newsletters: Create engaging weekly newsletters for classroom updates. AI can help you generate content quickly. Therefore, you’re maintaining consistent and engaging content.
Imagine you want to create a welcome letter for 5th grade students and their families at the beginning of the school year. By providing context and setting boundaries, you can quickly draft a personalized letter using an AI platform. Let’s create a ‘Welcome Newsletter.’ Go to any AI platform and type in the following prompt criteria:
Ask the tool to take on a persona: 5th grade elementary teacher.
Provide an objective that tells the tools what to do or produce: Draft a welcome letter for 5th grade.
Define the audience who will be using it: f or families and 5th grade students.
Include context that gives the tool background information: introduction that talks about how excited we are for the upcoming school year. We will be learning about the American Revolution, BizTown, multiplying fractions, earth movements, opinion writing, and more.
Set boundaries that limit or constrain responses: The paragraph should be written in plain text using an informal tone so that 5th graders will understand it.
Remember to maintain professionalism and clarity in your communication. And as a side note, if you’re using a free AI version, avoid using real names of students or parents. Paid versions of Generative AI typically do not save conversations for model training, but always check the fine print.
Planning
Planning consumes a significant amount of time for teachers and administrators. However, they can streamline this process using AI generators to create engaging lesson plans. By inputting specific criteria—such as subject, learning objectives, engagement strategies, age-appropriateness, lesson duration, and pacing—into a generative AI platform, teachers can receive customized lesson plans.
For example use this prompt: “Create a one-week lesson plan for 5th grade science that focuses on the human body and its major organ systems. Make sure the activities are engaging and age-appropriate and incorporate hands-on experiments where possible.”
See what kind of lesson plan it produces and how you make your lesson more streamlined, especially if you teach multiple grade levels or groups.
Accessibility/Differentiation
Artificial intelligence is transforming education by tailoring learning experiences to individual learning styles and needs. Adaptive-learning platforms use AI to adjust the curriculum based on student understanding, pacing, and mastery. These platforms provide personalized pathways, additional resources, and real-time feedback.
Instead of manually creating specialized prompts or quizzes, AI tools can “read” PDFs and generate differentiated questions. For instance, you can have AI read an article on westward expansion (for 5th graders) and create a quiz with 2nd-grade-level multiple-choice questions.
Another example prompt: “Write a prompt about Minecraft for 7th graders. Make sure to follow this writing standard: Write arguments to support claims with clear reasons and relevant evidence. Ensure that the prompt is at a 5th grade level.”
Marketing/Creating
Today, creativity isn’t limited to master artists. AI-powered tools like Adobe Express , Canva Magic Studio , Microsoft Designer , and Google’s AI Test Kitchen enable anyone to explore their creative side. For instance, in Canva Magic Studio, you can create custom images. If your students are researching different countries and need to design a poster, they can use these tools to bring their project to life.
Prompt example: “Create a poster of a young Korean girl traveling to Greece.”
See what kind of images can be created to bring this project to life.
Searching for Information
Today, search engines like Google or Bing have integrated generative AI into their platforms that will provide conversational answers based on up-to-date information found throughout the internet. These AI-powered ones provide real-time information and up-to-date answers.
Go to Google or Bing and ask a question like “How would you use an addendum to a contract?” At the top of the search engine, you’ll find a heading that says ‘AI Overview’ with a short summary, links, and guidelines to follow.
See if the results are something that could support you. However, it’s essential to be aware that some of the information may carry biases or discrimination. As best practices, always verify the credibility of the resources you find, which reinforce human oversight and the importance of critical thinking.
Overall, when faced with something new, taking that initial step can feel daunting, but it is important we take that step. I encourage you to explore AI tools and resources to help alleviate your daily life stresses. Remember: ‘Work smarter, not harder.’
Note: AI tools assisted me in clarifying, organizing, and checking the grammar of this article.
Thanks to Donna, Bonnie, and Kayla for contributing their thoughts!
Today’s post answered this question:
What are specific ways you are using—or not using—artificial intelligence in your teaching?
Sarah Cooper, Adam Moler, and Meghan Hargrave shared their responses in Part One .
Consider contributing a question to be answered in a future post. You can send one to me at [email protected] . When you send it in, let me know if I can use your real name if it’s selected or if you’d prefer remaining anonymous and have a pseudonym in mind.
You can also contact me on Twitter at @Larryferlazzo .
Just a reminder; you can subscribe and receive updates from this blog via email . And if you missed any of the highlights from the first 13 years of this blog, you can see a categorized list here .
| 2025-06-18T00:00:00 |
2025/06/18
|
https://www.edweek.org/technology/opinion-ai-can-save-teachers-time-and-stress-heres-how/2025/06
|
[
{
"date": "2025/06/18",
"position": 13,
"query": "AI education"
}
] |
Educators Must Adapt to AI, but They Need Help
|
Educators Must Adapt to AI, but They Need Help
|
https://www.educationnext.org
|
[
"Dan Sarofian-Butin"
] |
We talked about our best practices for teaching with AI and our worries about its impact on student engagement, motivation, and academic integrity.
|
I recently had the opportunity to be part of an OpenAI faculty roundtable. I was one of about a dozen professors that were joined by several staff from OpenAI’s recently created “Education Team.” We talked about our best practices for teaching with AI and our worries about its impact on student engagement, motivation, and academic integrity. The Education Team listened, asked questions, and presented their own vision of an “AI Native Institution.”
I hate to admit this, but I left the event feeling really depressed.
Our conversations were all about isolated and idiosyncratic (and, sure, exemplary) pedagogical practices, but completely lacking in big-picture vision—as if all we had to do was better integrate some whiz-bang gadget one student, one faculty, one institution at a time. Yes, I liked how Jeffrey Bussgang created custom GPTs for his entrepreneurship class at the Harvard Business School. And, yes, I thought Stefano Puntoni’s work at Wharton for integrating AI into his students’ writing was interesting. (OpenAI used these examples as “proof of concept”.) But to be fair, most of us sitting around the table have made similar or even better adaptations, and I don’t think any of us feel like we are part of the solution. Rather, we’re all barely keeping our heads above water as we navigate what Ethan Mollick terms a “post-apocalyptic education.”
This is why I believe AI has precipitated a fundamental crisis of purpose in higher education, and I am far from alone in this perspective. So, I expected more from a $300 billion company on the cutting edge of disrupting the world.
This is what OpenAI should have done.
First and foremost, they should have named the correct problem. Everyone thinks the issue with AI is that just about every student is cheating their way through college. Yes and no. It’s true that most students have little intrinsic motivation to learn and find the easiest way through the checklist of courses in order to get their credential.
But the real story is that AI has broken the transmission model of education, where professors teach and then grade students on how much they learned. A passing grade used to mean students had learned enough of what the professor had “transmitted.” No longer. These past two years faculty have given out A’s left and right to students who don’t understand (much less read) the assignment they just submitted. I cannot overstate this: AI has decoupled students’ performance (what they submit to us) and student knowledge.
This is not all bad news; a massive crisis is also a massive opportunity. The second thing OpenAI should have done is tease out the implications of and solutions to this disruption they have wrought. This doesn’t mean reactive and on-the-margins interventions—a return to blue books, watermarking AI output, process tracking, honor code updates—that may temporarily mitigate the problem.
| 2025-06-18T00:00:00 |
2025/06/18
|
https://www.educationnext.org/educators-must-adapt-to-ai-but-they-need-help-openai-higher-ed/
|
[
{
"date": "2025/06/18",
"position": 33,
"query": "AI education"
}
] |
Crafting Thoughtful AI Policy in Higher Education: A Guide ...
|
Crafting Thoughtful AI Policy in Higher Education: A Guide for Institutional Leaders
|
https://www.facultyfocus.com
|
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"Raffi Dersimonian",
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Learn how institutional leaders can develop mission-driven AI policies that balance innovation, ethics, and stakeholder needs in higher education.
|
As artificial intelligence (AI) continues to evolve at a rapid pace, educational institutions find themselves at a crossroads. The integration of AI technologies presents unparalleled opportunities for enhancing teaching, learning, and administrative processes. However, it also raises critical ethical, operational, and strategic challenges. This article delves into the complexities of developing and implementing an AI framework that not only aligns with an institution’s unique mission but also addresses the diverse needs of its stakeholders, including faculty, students, staff, and administration.
Central to our discussion is the assertion that a “one-size-fits-all” approach to AI adoption is inadequate for educational institutions, whose missions and values differ significantly. We propose a multi-faceted strategy for establishing an AI policy that is both mission-reflective and adaptable to the needs of each audience group within the institution. This strategy encompasses identifying core values, assessing stakeholder needs, integrating ethical considerations, and defining leadership’s role in championing AI initiatives.
Through best practices, case studies, and expert insights, we outline a step-by-step guide for institutions to craft their AI policies. Key focus areas include developing a philosophical AI framework that guides decision-making, establishing governance structures, fostering a culture of experimentation and innovation, and implementing policies that ensure transparency, accountability, and inclusivity.
We also explore the role of continuous evaluation and stakeholder engagement in maintaining an AI framework that remains true to an institution’s mission over time. By addressing the nuanced nature of AI integration in educational settings, this article provides institutions with the tools to navigate the challenges and opportunities AI presents, fostering environments that are innovative, ethical, and mission-driven.
Introduction: Leading with Intent in the AI Era
The integration of AI into higher education is not simply a matter of technological adoption; it is an opportunity to enhance institutional mission and amplify core values. However, establishing a thoughtful AI policy that resonates with one’s unique institutional mission requires a proactive approach—one that avoids simply following in the footsteps of others or adopting policies from peer institutions without careful reflection.
This article aims to guide institutional leaders through the process of crafting AI policies that are reflective of their institution’s mission and future-forward. Drawing on our dual perspectives—agency leadership and institutional leadership—as well as insights from a survey of leaders across higher education, we share strategies, best practices, and an actionable framework for developing an ethical AI policy.
The Leadership Imperative: Building Trust and Driving Adoption
AI initiatives cannot succeed without strong leadership. Institutional leaders play a pivotal role in championing AI adoption by fostering trust, ensuring transparent communication, and making informed decisions. Building trust requires:
Transparency in Communication: Leaders should articulate the “why” behind AI initiatives, addressing both opportunities and risks.
Active Stakeholder Engagement: Regularly involve faculty, students, and staff to create a sense of shared ownership.
Training Leadership Teams: Provide education on AI’s capabilities and limitations, enabling leaders to make data-driven, ethical decisions.
Leadership training should include workshops, expert panels, and scenario planning to build confidence in navigating AI’s complexities. Institutions that invest in leadership development are better positioned to drive successful, mission-aligned AI integration.
Aligning AI Policy with Broader Societal Trends
While this article focuses on higher education, institutional policies must also consider the broader societal implications of AI. Higher education institutions are uniquely positioned to:
Prepare Students for the Future Workforce: By integrating AI into curricula, institutions can equip students with the skills needed to thrive in an AI-driven economy.
Shape Ethical AI Use for Society: Establishing ethical AI frameworks within institutions sets a standard for responsible AI adoption across sectors.
For example, embedding AI literacy and ethical considerations into academic programs ensures that graduates understand both the potential and the pitfalls of AI, preparing them to lead responsibly in their careers.
Balancing Policy and Innovation: A Critical Tension
One of the greatest challenges in AI adoption is striking the right balance between governance and innovation. Overly rigid policies can stifle creativity, while a lack of oversight risks ethical breaches and inefficiencies. Institutions should:
Foster a Culture of Experimentation: Encourage pilot projects that allow for controlled experimentation.
Implement Flexible Governance Structures: Create policies that provide guardrails without hindering innovation.
Monitor and Adapt: Use feedback from experiments to refine policies and practices.
By framing governance as an enabler rather than a constraint, institutions can cultivate an environment where innovation thrives alongside accountability.
Assessing Effectiveness: KPIs for AI Initiatives
To ensure that AI initiatives are achieving their intended outcomes, institutions must establish clear metrics for success. Key performance indicators (KPIs) may include:
Educational Outcomes: Improved retention rates, higher graduation rates, or enhanced learning outcomes.
Operational Efficiency: Reduced administrative workload or faster service delivery.
Ethical Compliance: Reduction in algorithmic bias and increased data transparency.
For example, a university’s marketing team might track engagement rates for AI-driven personalized campaigns, while the advising office measures improvements in student satisfaction through AI-powered support tools. Regularly reviewing these metrics allows institutions to make data-informed adjustments.
Steps for Crafting a Thoughtful AI Policy
Drawing on survey insights, research, and our collective experience, we propose a step-by-step framework for developing an institutional AI policy:
Define the Purpose: Clearly articulate how AI will support your institution’s mission, vision, and core values. Actionable Tip: Create a mission statement for AI use that aligns with institutional goals.
Engage Stakeholders: Involve faculty, students, administrators, and other stakeholders from the outset. Actionable Tip: Develop a stakeholder engagement plan with regular feedback sessions.
Establish Ethical Guidelines: Develop principles that address privacy, fairness, and accountability. Actionable Tip: Draft an ethical AI charter and solicit campus-wide feedback.
Create Governance Structures: Form committees or task forces to oversee AI implementation. Actionable Tip: Assign a dedicated AI governance team to monitor adherence to policies.
Pilot and Evaluate: Test AI applications in low-risk areas and gather feedback to refine strategies. Actionable Tip: Evaluate outcomes against predefined KPIs.
Communicate Transparently: Share information about AI initiatives, including successes and challenges. Actionable Tip: Develop a communication plan with regular updates and open forums.
Continuously Monitor and Improve: Regularly assess AI’s impact and make adjustments as needed. Actionable Tip: Implement an annual review cycle for AI policies.
Top Ten AI Policies from Leading Institutions
To provide further guidance, we have curated a list of exemplary AI policies from leading colleges and universities that have successfully implemented thoughtful and mission-driven AI frameworks. These policies serve as models for institutions seeking to craft or refine their own AI strategies:
Stanford University: Focuses on transparency and accountability in AI decision-making, including a public ethics review board.
Massachusetts Institute of Technology (MIT): Implements regular AI ethics audits and a governance committee dedicated to ethical AI deployment.
Harvard University: Emphasizes stakeholder engagement, including student and faculty advisory panels to guide AI use.
University of California, Berkeley: Uses AI to enhance student support services, with clear policies on data privacy and informed consent.
Arizona State University: Employs AI in adaptive learning platforms with a focus on personalized education pathways.
University of Toronto: Developed a comprehensive AI ethics framework that addresses bias, fairness, and data transparency.
University of Michigan: Has an AI oversight committee responsible for evaluating new AI initiatives and ensuring alignment with institutional values.
Carnegie Mellon University: Prioritizes interdisciplinary collaboration in AI projects, involving stakeholders from various academic departments.
University of Edinburgh: Created a public-facing AI charter that details ethical principles, stakeholder responsibilities, and governance mechanisms.
Champlain College Online: Focuses on personalized learning and career relevance, using AI to support diverse student populations in an online environment.
Conclusion: Leading with Vision and Integrity
The integration of AI into higher education holds the promise of transformative benefits, from personalized learning to enhanced administrative efficiency. However, to fully realize these benefits, institutions must approach AI adoption thoughtfully, with a focus on mission alignment, ethical considerations, and stakeholder engagement.
By leading with intent, involving diverse voices, and establishing a strong ethical foundation, institutions can harness AI’s potential in ways that are innovative, responsible, and mission-driven. We encourage institutional leaders to take a proactive stance—to lead rather than follow—and to craft AI policies that reflect the unique values of their communities.
Next Steps
If you are inspired to take action, consider the following:
Conduct a Readiness Assessment: Evaluate your institution’s current capabilities and identify gaps in AI adoption.
Facilitate Cross-Functional Workshops: Bring together stakeholders to co-create an AI policy framework.
Engage Experts: Partner with thought leaders in AI ethics and education to refine your strategies.
We welcome opportunities to collaborate on workshops, policy frameworks, and best practices to support this vital work.
Raffi DerSimonian is Vice President and Chief Strategy Officer at ERI Design, where he leads institutional strategy, positioning, and partner engagement efforts across the firm’s national portfolio. With over 20 years of experience in higher education marketing and digital strategy, Raffi brings a human-centered approach to brand storytelling and enrollment-focused innovation. Throughout his career, Raffi has advised a diverse range of colleges and universities—from Ivy League institutions to regional public systems—on the strategic intersection of digital experience, institutional identity, and student engagement. His work is grounded in a belief that great design and strategy should serve access, equity, and outcomes.
Prior to joining ERI, Raffi led marketing and communications at the Maine College of Art & Design, where he oversaw a significant rebranding and digital transformation initiative. He is also an active contributor to thought leadership efforts in the higher ed space, including webinars, and published insights focused on digital accessibility, SEO-informed redesigns, and the emotive power of visual storytelling. Raffi holds a degree in political science and entrepreneurship from Clark University and serves on the U.S. Department of Commerce’s District Export Council for Maine. A resident of Portland, Maine, he is passionate about regional economic development, cultural arts, and empowering mission-driven organizations to thrive in a digital-first world.
For more information or to connect with Raffi DerSimonian, you can reach him at [email protected]
Christa “Chris” Montagnino is the Executive Vice President of Champlain College Online, where she leads the academic and operational administration of the college’s online division. With over 20 years of experience in higher education, primarily in online learning, Chris is recognized for her expertise in building and scaling online programs, executive leadership, and enrollment management. Before joining Champlain College, Chris held leadership roles at institutions such as Academic Partnerships, Excelsior University, Herzing University, and the University of Phoenix. She has also taught online courses in political science and gender studies and has served on various education and social justice non-profit boards.
Chris holds a B.A. and M.A. in Political Science from the University of Texas at El Paso and an M.A. in Organizational Management from the University of Phoenix. Passionate about increasing access to high-quality education, Chris focuses on delivering online programs that serve students often underserved in traditional higher education settings. She believes that online education can be life-changing, leading to greater educational, economic, and social equity.
For more information or to connect with Christa Montagnino, you can reach her at [email protected].
| 2025-06-18T00:00:00 |
2025/06/18
|
https://www.facultyfocus.com/articles/academic-leadership/crafting-thoughtful-ai-policy-in-higher-education-a-guide-for-institutional-leaders/
|
[
{
"date": "2025/06/18",
"position": 38,
"query": "AI education"
}
] |
How AI Is Making Education More Personal
|
How AI Is Making Education More Personal
|
https://www.iotforall.com
|
[] |
Let's dive into this exciting shift in education, exploring the immense possibilities AI offers to students, teachers, and institutions. Personalized Learning.
|
How AI Is Making Education More Personal
- Last Updated: June 18, 2025
Imagine a classroom where every student has access to a personal tutor. Picture lessons dynamically adapt in real time, responding to each learner's unique needs, strengths, and interests.
Envision teachers focusing more on mentorship and direct engagement rather than getting bogged down in administrative tasks. This scenario is not futuristic; it represents the reality that is gradually emerging as AI becomes integrated into education.
Let's dive into this exciting shift in education, exploring the immense possibilities AI offers to students, teachers, and institutions.
Personalized Learning
For decades, classrooms have wrestled with the same challenge: how do you teach 30 kids with 30 different learning styles? Traditional education often defaults to one-size-fits-all, which leaves some students struggling and others bored.
AI addresses this by enabling highly personalized learning experiences. Adaptive learning platforms powered by AI analyze each student's performance and learning behaviors in real time, tailoring content to individual capabilities.
For example, adaptive tools can swiftly pinpoint when a student struggles with a math concept or language skill, adjusting instructional methods accordingly. This personalized intervention increases understanding and significantly enhances student motivation, confidence, and academic outcomes.
Platforms like Smart Sparrow, for example, dynamically adapt their curriculum based on real-time student interaction. This approach ensures that no learner is left behind or feels unchallenged.
Empowering Educators
One common misconception is that AI in education might render teachers obsolete. In actuality, this is not at all the case. AI doesn't replace educators; it augments their abilities.
By automating routine tasks such as grading quizzes, organizing attendance, and even managing schedules, AI empowers teachers to focus their valuable time and energy on meaningful interactions and personalized mentoring.
Moreover, AI-driven analytics provide teachers with valuable insights, highlighting precisely where students may need extra attention or additional challenges. These insights empower educators to intervene earlier and more effectively, significantly improving classroom outcomes.
Real-world AI in Education
Many innovative educational platforms and institutions are leveraging AI to enhance the learning experience in practical, relatable ways:
Khan Academy’s Khanmigo : This AI-powered tutoring system provides personalized support and real-time feedback, transforming the way students engage with educational content.
Duolingo’s adaptive learning model : Duolingo uses AI to give each student a personalized language lesson, changing the level of difficulty based on their success and ability to remember what they've learned.
Squirrel AI’s adaptive systems: Squirrel AI breaks down subjects into small units and uses AI to find and fill in knowledge gaps, making sure that students fully understand each idea before moving on to the next.
These real-world applications illustrate that AI isn't just theory; it's actively improving educational outcomes across diverse contexts and disciplines.
Addressing Potential Challenges
While the benefits of AI in education are substantial, it's essential to navigate certain challenges carefully:
Data Privacy and Security
Ensuring student data privacy is critical. Educational institutions must guarantee that personal and academic information is secure, employing robust data protection practices aligned with regulations such as GDPR.
Equity and Accessibility
AI solutions should promote inclusivity, not widen educational gaps. Ensuring equitable access to technology is essential to prevent exacerbating existing disparities between students in different socio-economic contexts. Initiatives should aim for the widespread adoption of affordable, accessible AI tools across diverse educational settings.
Teacher Training and Adoption
For AI to be truly effective, educators must feel comfortable and confident using these technologies. Comprehensive training programs are crucial, providing teachers with the skills necessary to integrate AI effectively into their daily teaching practices.
Future of AI in Education
The integration of AI in education represents a significant paradigm shift. Far from depersonalizing learning, AI enhances human interactions by reducing repetitive tasks and allowing educators to concentrate more fully on mentorship and engagement.
AI-driven education prepares students for a rapidly evolving job market, where technological literacy and adaptive learning skills are increasingly critical. By fostering personalized learning environments, AI ensures students are not only academically equipped but also personally empowered.
Furthermore, educational institutions leveraging AI technologies will increasingly serve as pioneers, demonstrating the effectiveness of AI-enhanced education to a broader community. This momentum will likely catalyze further adoption across educational sectors globally.
A Human-Centric Approach
At its core, the success of AI in education hinges on maintaining a human-centric approach. AI technologies must complement human educators, enhancing their capabilities rather than replacing their crucial roles.
As we embrace this exciting intersection of technology and education, the focus must remain steadfast on creating engaging, personalized, and equitable learning experiences for all students.
The future of education isn't just digital; it's deeply human, made possible through the thoughtful integration of AI.
| 2025-06-18T00:00:00 |
https://www.iotforall.com/ai-personal-education
|
[
{
"date": "2025/06/18",
"position": 56,
"query": "AI education"
}
] |
|
Arcee AI: Agentic AI for Businesses
|
Agentic AI for Businesses
|
https://www.arcee.ai
|
[] |
Unlock domain-specific AI that's secure, efficient, and built for your business. Choose the tools and models that fit you—no one-size-fits-all here.
|
Built for your business
Customize models for your industry. Fine-tune, merge, and adapt to your unique needs.
-Customized design and applications
-Designed to integrate into your systems
-Engineered to grow with you
| 2025-06-18T00:00:00 |
https://www.arcee.ai/
|
[
{
"date": "2025/06/18",
"position": 41,
"query": "AI employers"
}
] |
|
What employees really think about AI, according to new ...
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What employees really think about AI, according to new report
|
https://www.hcamag.com
|
[
"Dexter Tilo"
] |
More than six in 10 employees across the world believe that artificial intelligence's impact in workplaces is "overhyped," despite admitting that they underuse ...
|
More than six in 10 employees across the world believe that artificial intelligence's impact in workplaces is "overhyped," despite admitting that they underuse it, according to a new report.
GoTo's latest research report polled 2,500 employees in 10 countries to find that 62% believe AI has been significantly overhyped.
"Employees are already using AI and are seeing clear productivity gains, yet despite these benefits, our latest research shows people still view AI as overhyped," said Rich Veldran, CEO of GoTo, in a statement.
| 2025-06-18T00:00:00 |
https://www.hcamag.com/us/specialization/employee-engagement/what-employees-really-think-about-ai-according-to-new-report/539658
|
[
{
"date": "2025/06/18",
"position": 95,
"query": "AI employers"
},
{
"date": "2025/06/18",
"position": 85,
"query": "artificial intelligence employment"
}
] |
|
Amazon CEO says the 'quiet part out loud' about AI job losses - AFR
|
Amazon CEO says the ‘quiet part out loud’ about AI job losses
|
https://www.afr.com
|
[
"James Thomson",
"Primrose Riordan",
"Sally Patten",
"Mandy Coolen",
"John Davidson",
"Nick Lenaghan"
] |
Meta's Mark Zuckerberg is offering enormous sign-on bonuses for AI gurus. The only way that makes sense is with mass job losses.
|
To understand why Amazon chief executive Andy Jassy’s warning on artificial intelligence job losses is very, very real, just look at the $US100 million ($154 million) sign-on bonuses Mark Zuckerberg’s tech giant Meta Platforms is offering to attract top AI talent.
The bonuses were confirmed by Sam Altman, the co-founder and chief executive of artificial intelligence pioneer OpenAI, which created ChatGPT. On a podcast called Uncapped, he said his staff had been targeted as Zuckerberg tries to build a team to chase the idea of superintelligence, which is AI that exceeds human intelligence.
Loading...
| 2025-06-18T00:00:00 |
2025/06/18
|
https://www.afr.com/chanticleer/amazon-s-ceo-is-right-on-ai-job-losses-154m-bonuses-are-proof-20250618-p5m8hr
|
[
{
"date": "2025/06/18",
"position": 51,
"query": "AI job losses"
}
] |
Journalism Rewired: How AI Is Reshaping News in China ...
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Journalism Rewired: How AI Is Reshaping News in China and Beyond
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https://www.kau.se
|
[] |
Journalists are adapting to AI by using it to enhance efficiency and reduce political risk, but also to perform civic roles such as investigating algorithmic ...
|
What happens when AI meets journalism in one of the world’s most tightly controlled media environments? Joanne Kuai, newly graduated PhD in Media and Communication Studies at Karlstad University, dives into China’s AI-powered newsrooms - and what they reveal about the future of journalism everywhere.
Joanne, why did you choose Chinese journalism for your research?
– Around 2018, I began thinking deeply about the societal implications of artificial intelligence and what it means to be human in the age of AI. Journalism became my point of entry into this larger question - both because of my background as a journalist and editor, and because of the profound changes I witnessed in newsrooms transitioning from print to digital. That was also when a lot of media innovation emerged in China, including news-writing bots, AI news anchors, and algorithm-powered news recommenders. These developments raised important questions about authorship, professional identity, and the institutional future of journalism.
– At the same time, dominant discourses about Chinese media often reduce it to either propaganda or censorship. I found this framing simplistic and limiting. My professional network gave me access to journalists and technologists whose stories are more nuanced. I wanted to offer a more complex understanding of Chinese journalism - not to romanticise it, but to examine how it navigates state influence, technological innovation, and professional ideals. AI journalism in China offered a rich case for exploring these intersections.
You have compared China with the USA and the EU – what are the key differences?
– These three regions differ significantly in their political, economic, and cultural structures - especially in how they develop and govern AI. China follows a state-driven model, the US relies on market forces, and the EU adopts a values-driven regulatory approach. Each is trying to position itself as a global AI leader and norm-setter.
– Yet there are also important similarities. In all three contexts, AI has catalysed a concentration of power and resources, often to the detriment of journalism and news workers. Whether through market logic or political ambition, AI technologies like automated content and algorithmic recommendation are being used to shape public attention in ways that don't necessarily serve civil society.
– These developments compel us to ask: What does it mean to be human in the age of AI? Before designing technology that aligns with “our values,” we must first clarify what those values are - and who gets to define them.
What are the primary findings of your study?
– One of the key findings is that AI isn’t displacing journalism - it’s reinstitutionalising it. In China, AI technologies are reshaping professional roles, production processes, and media governance structures. Journalists are adapting to AI by using it to enhance efficiency and reduce political risk, but also to perform civic roles such as investigating algorithmic harm and alerting the public to technological risks.
– My study also reveals how news platforms and algorithmic infrastructures serve as tools of both innovation and control. They are embedded in state-tech-media relationships that shape what counts as news and who gets to produce it. Across China, the US, and the EU, these dynamics play out differently, but they all raise urgent questions about the future of journalism and democracy.
How do AI technologies affect the professional roles and working methods of journalists in China?
– Chinese journalists, like their Western counterparts, face pressure from platforms and digital disruption. Many adopt AI to boost efficiency - using it for transcription, archive organisation, grammar checking, and even interview prep. One distinctive use case is "content risk management," where AI helps detect politically sensitive figures or banned terms to avoid political fallout.
– Rather than changing their roles entirely, journalists use AI to fulfil their existing role orientations. Some perform civic functions - investigating tech harms or sounding alarms about new risks - while also portraying the state as a benevolent guardian. This duality aligns with a long-standing “loyal facilitator” role in Chinese journalism, blending public service with political alignment.
In what ways do algorithmic news platforms developed by Chinese tech companies reshape the economic and institutional foundations of journalism?
– In China, journalism is shaped not just by tech companies, but by a triangular power dynamic between the state, media, and tech firms. These platforms don’t operate independently - they function within state-defined boundaries, regulations, and ideological expectations.
– While there was early disruption from tech platforms, the state has since reasserted control through policy and structural integration. Media–tech partnerships now involve joint publishing and profit-sharing models, creating a collaborative - but constrained - ecosystem. This reinforces the institutional interdependence of media, technology, and the state.
How do the legal and regulatory frameworks for AI and journalism differ between China, the US, and the EU?
– These frameworks are still evolving - and reflect competing values and interests. In the US, copyright law requires human authorship, ruling out protection for AI-generated content. The EU takes a case-by-case approach based on originality. China, meanwhile, has introduced mechanisms to separate authorship and ownership, allowing tech companies to claim rights over AI-generated works without fully attributing authorship to machines.
– These differences reveal broader power dynamics. Whether it’s the state or tech companies, dominant actors are using legal tools to prioritise their interests. These risks narrowing the diversity of voices, centralising control over the information environment, and weakening the democratic function of journalism.
What power dynamics emerge between news organizations, tech companies, and the state as AI becomes integrated into journalism?
– AI intensifies existing tensions and interdependencies. In China, tech firms act as both innovation hubs and political partners, shaping infrastructure and distribution while aligning with state agendas. News organisations must adapt to platform logics while maintaining political loyalty and professional identity.
– The state remains the ultimate arbiter, regulating both technology and media. What emerges is a hybrid ecosystem where editorial decisions, algorithmic curation, and political directives co-produce the news landscape. This entangles journalistic autonomy with both technological systems and political oversight.
How can the traditional norms and values of journalism be preserved or reshaped in an era of technological and political restructuring?
– Before asking how to preserve journalistic values, we must revisit what those values actually are - and for whom. Ideals like objectivity and neutrality have often been presented as universal, but they deserve critical examination, especially as democracy itself faces strain.
In China, journalists are often explicit about their dual roles, balancing loyalty with civic responsibility. This clarity might serve as a prompt for journalists elsewhere to reflect more honestly on their role in society.
– Ultimately, sustaining meaningful journalism requires collective reflection - by journalists, regulators, technologists, and the public - on the kind of media system we want. That means reimagining regulation, reinvesting in public interest media, and recognising that quality journalism cannot be sustained without systemic support.
What impact do you hope your research will have?
– I hope to contribute to a more globally informed and critically engaged conversation about AI and journalism. My research offers new empirical data and a comparative framework that foregrounds the role of the state, law, and policy - elements often overlooked in AI and media research.
– Beyond academia, I’m also committed to public engagement. I’ve contributed to initiatives like the JournalismAI Academy, engaging in dialogues with industry practitioner, spoken at EU events, and hosted podcast to communicate research more broadly. With AI now touching many aspects of everyday life - from ChatGPT to algorithmic decision-making - I hope my work helps people reflect on what kind of technological future we want, and how we define human agency within it.
In what ways will your research strengthen Karlstad University?
– Through this work, I’ve represented Karlstad University across academic, policy, and public arenas. I’ve contributed to international journals and conferences, collaborated with colleague in NODE (News and Opinion in the Digital Era), and Geomedia. I’m also an active member in academia community service and I’m elected as the Student and Early Career Representative for the Journalism Studies Division at the International Communication Association (ICA).
– I’ve also brought Karlstad into conversations with journalists, policymakers, and the wider public - through initiatives like JournalismAI and media contributions in outlets like Sixth Tone. The supportive environment at Karlstad University has been essential to my growth as a researcher, and I hope I’ve contributed in return by helping raise the university’s visibility in cutting-edge debates on AI, media, and democracy.
| 2025-06-18T00:00:00 |
https://www.kau.se/en/news/journalism-rewired-how-ai-reshaping-news-china-and-beyond
|
[
{
"date": "2025/06/18",
"position": 15,
"query": "AI journalism"
}
] |
|
Summer AI + journalism updates: how automation is ...
|
Summer AI + journalism updates: how automation is reshaping news routines
|
https://www.storybench.org
|
[
"Rahul Bhargava",
"Peiyao Hu",
"Vivica D'Souza"
] |
As the spring turns to summer, the intersection of AI and journalism is marked by fresh experiments and deepening debates over the future of storytelling.
|
As the spring turns to summer, the intersection of AI and journalism is marked by fresh experiments and deepening debates over the future of storytelling. Here’s a look at where things stand now.
What’s happening in local newsrooms
Some of the most promising AI applications in journalism are emerging from small and non-Western newsrooms. In India, publishers are shifting from cautious trials to full integration, according to WAN-IFRA. Meanwhile, The Reynolds Journalism Institute rereports on how a small-town newsroom in Missouri is piloting an AI-powered content management system that’s driving measurable engagement gains. These developments suggest the future of AI in journalism may not be led by big brands—but by smaller, scrappier players on the ground. Local newsrooms are tapping AI to free hours of labor. Boston.com reported Gannet, owners of USA Today and hundreds of local news outlets, are using Espresso, their newly introduced AI tool, to generate new content from existing content, especially for rewriting community announcements. Other newsrooms like Chalkbeat and Midcoast Villager, found AI transcription tools are efficient in surfacing leads that would otherwise be buried in hours of local government meetings’ footage, according to NiemanLab.
The future of news forms looks like…
The future of news is being shaped by more automatic, personalized and synthetic formats. Prospect Magazine ambitiously reimagines the future of journalism through two astonishing scenarios, the X stories model—an AI-driven automated world without human journalists and traditional editorial norms, and public service intelligence—where AI delivers fair, high-quality information only for the public interest.
Nieman Lab reported how Patch’s automation experiment with AI-generated newsletters across 30,000 could scale local coverage in ways previously unimaginable. And a deeper dive by Michael Crystal on Medium, argues that tools like AI-assisted search are developing more than info retrieval—they are research synthesizers, embedded across newsroom workflows, creating research packets, document mining and enhancing reader engagement.
Training and transparency are top concerns
As AI tools spread across newsrooms, questions about training and transparency are coming to the forefront. A story from Oh My Box reports that many journalism programs are still catching up, with students often encountering AI tools for the first time during internships. Meanwhile, ProPublica’s recent investigation shows the importance of clear guidelines and human oversight. Reporters used AI to analyze thousands of NSF grants, but every AI-generated lead was verified by journalists before publication. ProPublica’s transparency about its process and commitment to accountability set a standard as other outlets develop protocols for labeling and fact-checking AI-assisted reporting.
Legal and ethical questions grow louder
As AI adoption accelerates, legal and ethical concerns about compensation for creative work are intensifying. In the UK, the British Parliament’s proposal to allow AI companies to train models on copyrighted material without payment has sparked outcry from writers, musicians, artists, and journalists. Content creators warn that their work could be used to develop AI without their permission or fair compensation, threatening livelihoods and the country’s creative industries. Campaigns like “Make It Fair” call for stronger copyright protections, requiring AI firms to declare and license the creative content they use for training.
News publishers are filing lawsuits against companies like OpenAI and Google, reflecting a global push to secure consent and payment for data use. These disputes underscore a central challenge: How can journalism innovate without compromising ethics or copyright?
From hype to responsibility
From editorial experiments to legal battles, the summer of 2025 reveals both the promise and pressure of AI in journalism. While AI may enhance storytelling and expand access, it also demands careful oversight, stronger training, and a renewed commitment to fairness.
| 2025-06-19T00:00:00 |
2025/06/19
|
https://www.storybench.org/summer-ai-journalism-updates-how-automation-is-reshaping-news-routines/?utm_source=rss&utm_medium=rss&utm_campaign=summer-ai-journalism-updates-how-automation-is-reshaping-news-routines
|
[
{
"date": "2025/06/18",
"position": 42,
"query": "AI journalism"
}
] |
AI challenges journalism, but cannot replace its soul
|
AI challenges journalism, but cannot replace its soul
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https://english.vov.vn
|
[] |
AI can only support and cannot replace the journalist's role in capturing real-life experiences, emotions, and unique perspectives.
|
Using AI helps journalists outline, organize content, and shorten editing time
Faced with fierce competition from social media and the rise of artificial intelligence (AI), traditional journalism must innovate to better serve readers, guide public opinion, and strengthen public trust through high-quality information.
AI is no longer unfamiliar in the newsroom. Tools that convert speech to text, analyze keywords, suggest headlines, and compile data are helping journalists save time and focus more on creative content. Many young reporters are actively using AI as a practical tool in their work.
However, AI can only support and cannot replace the journalist’s role in capturing real-life experiences, emotions, and unique perspectives. According to journalist Xuan Quynh from Sai Gon Giai Phong (Liberated Saigon0 newspaper, the key is to use AI properly: “It helps save time on summarizing and structuring, giving us more room for creativity and in-depth storytelling.”
The advent of the internet and social media has reshaped the media landscape. Print circulation has declined, traditional television has lost viewers, and advertising has shifted rapidly to digital platforms. Many media outlets are facing financial strain, forced to downsize, while staff are aging and slow to adapt to new technologies.
Journalist Truong Duy Hoa, Deputy Director of the Vietnam Television Center in the Central and Central Highlands region, stressed that journalism cannot fall behind social media. Reporters and editors must rethink their approach, stay ahead of trends, and master digital tools and AI to remain relevant: “Traditional media must change. If we stay rigid, we’ll lose the communications race.”
AI applications offer practical benefits for journalists
Developing a multi-platform content ecosystem is considered a necessary path to enhance competitiveness in the digital era.
Vo Cong Tri, former Standing Deputy Secretary of the Da Nang Party Committee, emphasized that journalism must seek new directions to build trust with the public through diverse, verified, and objective information. According to him, the professionalism, integrity, and identity of each newsroom depend on the quality and commitment of its journalists.
From a media management perspective, Doan Xuan Hieu, Editor-in-Chief of Da Nang Newspaper and Radio & Television, said that while AI and related technologies are evolving rapidly, they do not eliminate jobs.
The real risk lies with those who fail to adapt and fall behind. “No matter how advanced technology becomes,” he noted, “the soul of human creativity, our sense of beauty, truth, and virtue cannot be replicated- what we call the soul of journalism- cannot be replaced by AI.
It is this pure heart and unwavering moral spirit that young journalists must carry forward even as they embrace new tools in the digital age.
| 2025-06-18T00:00:00 |
2025/06/18
|
https://english.vov.vn/en/society/ai-challenges-journalism-but-cannot-replace-its-soul-post1208096.vov
|
[
{
"date": "2025/06/18",
"position": 51,
"query": "AI journalism"
},
{
"date": "2025/06/18",
"position": 45,
"query": "artificial intelligence journalism"
}
] |
Echobox: Increase your traffic and engagement with AI
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Echobox: Boost your referral traffic and engagement
|
https://www.echobox.com
|
[] |
Publishers around the world save time and increase performance with newsletter and social media automation.
|
Use the most powerful social media platform for publishers. Save time and drive significantly more revenue from your social media audience.
Save valuable time Echobox can save you countless hours by managing your social media presence for you. Grow your audience Use Echobox to run A/B tests and post to the right audiences at optimal times.
Echobox has been engineered from the ground up specifically for publishers. Adopt the most advanced technology built by researchers from world-leading academic institutions.
| 2025-06-18T00:00:00 |
https://www.echobox.com/
|
[
{
"date": "2025/06/18",
"position": 92,
"query": "AI journalism"
}
] |
|
Amazon CEO says AI will reduce its corporate workforce in ...
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Amazon CEO Jassy says AI will reduce its corporate workforce in the next few years
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https://apnews.com
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[] |
Amazon has also invested more heavily in AI. In November the company said that it was investing an additional $4 billion in the artificial intelligence startup ...
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Amazon CEO Andy Jassy anticipates generative artificial intelligence will reduce its corporate workforce in the next few years as the online giant begins to increase its usage of the technology.
“We will need fewer people doing some of the jobs that are being done today, and more people doing other types of jobs,” Jassy said in a message to employees. “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.”
The executive said that Amazon has more than 1,000 generative AI services and applications in progress or built, but that figure is a “small fraction” of what it plans to build.
Jassy encouraged employees to get on board with the e-commerce company’s AI plans.
“As we go through this transformation together, be curious about AI, educate yourself, attend workshops and take trainings, use and experiment with AI whenever you can, participate in your team’s brainstorms to figure out how to invent for our customers more quickly and expansively, and how to get more done with scrappier teams,” he said.
Earlier this month Amazon announced that it was planning to invest $10 billion toward building a campus in North Carolina to expand its cloud computing and artificial intelligence infrastructure.
Since 2024 started, Amazon has committed to about $10 billion apiece to data center projects in Mississippi, Indiana, Ohio and North Carolina as it ramps up its infrastructure to compete with other tech giants to meet growing demand for artificial intelligence products.
The rapid growth of cloud computing and artificial intelligence has meanwhile fueled demand for energy-hungry data centers that need power to run servers, storage systems, networking equipment and cooling systems. Amazon said earlier this month that it will spend $20 billion on two data center complexes in Pennsylvania.
In March Amazon began testing artificial intelligence-aided dubbing for select movies and shows offered on its Prime streaming service. A month earlier, the company rolled out a generative-AI infused Alexa.
Amazon has also invested more heavily in AI. In November the company said that it was investing an additional $4 billion in the artificial intelligence startup Anthropic. Two months earlier chipmaker Intel said that its foundry business would make some custom artificial intelligence chips for Amazon Web Services, which is Amazon’s cloud computing unit and a main driver of its artificial intelligence ambitions.
| 2025-06-18T00:00:00 |
2025/06/18
|
https://apnews.com/article/amazon-jassy-ai-alexa-workforce-7eea6387e97b84f1f239af2538de5ee9
|
[
{
"date": "2025/06/18",
"position": 59,
"query": "AI layoffs"
}
] |
Amazon CEO signals fewer jobs, more AI in the future
|
Amazon CEO signals fewer jobs, more AI in the future
|
https://www.emarketer.com
|
[] |
Meta isn't far behind with over 21,000 layoffs since 2022, and Microsoft has laid off at least 16,000 people since 2023. The latter is planning to lay off ...
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The news: Amazon CEO Andy Jassy said AI-driven efficiencies will reduce the company’s headcount .
“As we roll out more generative AI and agents …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 letter to employees . “In the next few years, we expect that this will reduce our total corporate workforce.”
He added that Amazon has built—or is building—over 1,000 genAI products and that more are on the way.
Cards on the table: Jassy’s transparency about potential AI-driven layoffs follows similar disclosures from other CEOs. Not all of those announcements have gone over well or been successfully implemented.
Duolingo faced considerable backlash from users after announcing it would phase out some human contract workers in favor of automation.
from users after announcing it would phase out some human contract workers in favor of automation. Klarna backtracked on its push to replace customer service workers with AI after user experience quality declined.
Big Tech cuts: Amazon has already slashed its workforce in recent years—it’s cut about 27,000 employees since 2022, per The Verge .
Meta isn’t far behind with over 21,000 layoffs since 2022, and Microsoft has laid off at least 16,000 people since 2023. The latter is planning to lay off thousands more this year, per Bloomberg, especially in its sales departments.
Heavy reductions: The trend of reducing staff to make room for AI investments isn’t limited to Big Tech companies, either. Layoffs have outpaced hiring for the past three consecutive quarters in the US, per Janco Associates , and more than 62,000 tech jobs have disappeared in 2025, per Layoffs.fyi .
In May, Business Insider laid off 21% of its workforce and highlighted a “huge opportunity” for early AI adopters. Business Insider and EMARKETER are both owned by Axel Springer.
Workday and Salesforce each cut over a thousand workers in February while deploying AI. Salesforce said it plans to hire new, AI-skilled employees.
Our take: Companies that pursue an AI-first mission by laying off employees risk lower team morale, a resistance to AI adoption among workers , and damaged consumer trust. Still, Amazon’s scale, deep pockets, and cloud infrastructure dominance may insulate it from backlash or major fallout.
| 2025-06-18T00:00:00 |
https://www.emarketer.com/content/amazon-ceo-signals-fewer-jobs-more-ai-future
|
[
{
"date": "2025/06/18",
"position": 66,
"query": "AI layoffs"
}
] |
|
Amazon's Andy Jassy warns of job cuts due to generative AI
|
Amazon’s Andy Jassy warns of job cuts due to generative AI
|
https://www.yahoo.com
|
[] |
Sharing “some thoughts” about artificial intelligence with employees, Amazon CEO Andy Jassy said the company “will need fewer people doing some of the jobs that ...
|
This story was originally published on Retail Dive. To receive daily news and insights, subscribe to our free daily Retail Dive newsletter.
Dive Brief:
Sharing “some thoughts” about artificial intelligence with employees, Amazon CEO Andy Jassy said the company “will need fewer people doing some of the jobs that are being done today” as generative AI usage increases, according to a Monday letter.
While difficult to provide exact numbers on the potential impact, Jassy noted that “we expect that this will reduce our total corporate workforce as we get efficiency gains from using AI extensively across the company.”
The executive added that AI and chatbot rollouts at the company, for example, will also mean people need to be doing other types of jobs than their current work.
Dive Insight:
Despite Amazon already having over “1,000 generative AI services and applications in progress or built” at the company, Jassy indicated that this is just the tip of the iceberg in terms of potential.
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“We’re going to lean in further in the coming months,” the chief executive said. “We’re going to make it much easier to build agents, and then build (or partner) on several new agents across all of our business units and G&A areas.”
The executive said generative AI is the most transformative technology since the Internet. Jassy encouraged employees to learn about and implement the use of generative AI to remain competitive at the company, which includes brainstorming how to be more productive with “scrappier teams.”
“Those who embrace this change, become conversant in AI, help us build and improve our AI capabilities internally and deliver for customers, will be well-positioned to have high impact and help us reinvent the company,” Jassy added.
In his letter, Jassy outlined several ways in which AI is already being used at Amazon to improve customer and seller experiences. Use cases include rolling out its next-generation personal assistant Alexa+, Amazon’s AI shopping assistant, services for sellers to generate detailed product pages and more.
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Amazon isn’t alone in seeing AI’s potential in the retail industry.
Shoptalk’s spring conference in Las Vegas earlier this year featured numerous discussions about AI, including comments from companies such as Toys R Us, Foot Locker and Tapestry.
Walmart has also been “throwing the doors wide open to generative AI”, according to Senior Vice President of Enterprise Business Services David Glick. The mass retailer released a generative AI assistant named Sparky this month following the March debut of its AI assistant for merchants, dubbed Wally.
Recommended Reading
| 2025-06-18T00:00:00 |
https://www.yahoo.com/news/amazon-andy-jassy-warns-job-113400504.html
|
[
{
"date": "2025/06/18",
"position": 82,
"query": "AI layoffs"
}
] |
|
AI godfather Geoffrey Hinton says layoffs are now ...
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AI godfather Geoffrey Hinton says layoffs are now inevitable unless you have this job
|
https://www.indiatoday.in
|
[] |
Geoffrey Hinton said that he is worried about job security as automation is taking over. In a recent interview, the “Godfather of AI” advises considering ...
|
In a world where artificial intelligence is rapidly reshaping industries, one of its founding fathers is sounding the alarm about the future of work spaces. Geoffrey Hinton, the British-Canadian computer scientist famously dubbed the “Godfather of AI,” is in the headlines again, and this time he is placing his bets on an unexpected career path: Plumbing. Having played a crucial role in developing the neural networks behind today’s AI systems, Hinton said that he is worried about job security after automation has entered the picture.
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In a candid appearance on The Diary of a CEO podcast hosted by Steven Bartlett, Hinton painted a picture of a future that’s equal parts fascinating and unsettling. His advice for those worried about job security? Skip the coding bootcamp and consider becoming a plumber. "A good bet would be to be a plumber," Hinton said, explaining that physical tasks remain one of the last strongholds against automation. “It’s going to be a long time before [AI is] as good at physical manipulation as us.”
While AI can churn through legal contracts, predict case outcomes, and generate marketing copy in seconds, it can’t crawl under a sink or fumble with a spanner. Plumbing, like many other trades, demands hands-on skill, quick thinking, and a willingness to get dirty, none of which comes naturally to a machine.
Manual labour over office work
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Jobs involving manual labour, think plumbing, carpentry, and electrical work, are proving much trickier to automate than office roles. Fixing a leaking tap or rewiring a house involves physical judgement in unpredictable environments, something AI still struggles with. That’s why Hinton sees these roles as relatively safe, for now. In contrast, he warns that white-collar roles that involve data handling, or repetitive intellectual tasks are squarely in the AI firing line.
“In a society which shared out things fairly, everybody should be better off,” Hinton remarked. “But if you can replace lots of people by AIs, then the people who get replaced will be worse off," he added.
Jobs like legal assistants and paralegals, once considered steady job roles, are already being reshaped by generative AI. Language models can now sift through reams of legal documents and even draft case summaries with startling speed and accuracy, challenging the need for human support in these roles.
Worrisome future
Now at 77, Hinton isn’t just analysing trends, he’s wrestling with the emotional weight of his legacy. He admitted he’s still grappling with the long-term consequences of his work, especially when thinking about the world his children and grandchildren will inherit. “Intellectually, you can see the threat,” he said. “But it’s very hard to come to terms with it emotionally.”
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In one particularly chilling moment, Hinton imagined a future where AI could run power plants and other infrastructure with minimal human input. “If AI ever decided to take over,” he mused, “it would need people for a while to run the power stations, until it designed better analogue machines There are so many ways it could get rid of people, all of which would, of course, be very nasty.” He wasn’t predicting doom, but he insisted the risk is real enough to take seriously.
Beyond the question of who gets replaced, Hinton worries about who benefits. As AI boosts productivity and slashes costs, the spoils may not be shared equally. Those who own the technology stand to gain the most, while displaced workers may struggle to find their footing.
It’s not just a question of economics, it’s a social reckoning in the making. And if we’re not careful, Hinton warns, the technology meant to uplift humanity could end up deepening existing divides. So, while the robots may be coming for your spreadsheet, the humble tradesperson might just be sitting pretty. In the age of artificial intelligence, the safest job might just involve tightening a pipe, not typing on a keyboard.
| 2025-06-18T00:00:00 |
2025/06/18
|
https://www.indiatoday.in/technology/news/story/ai-godfather-geoffrey-hinton-says-layoffs-are-now-inevitable-unless-you-have-this-job-2742416-2025-06-18
|
[
{
"date": "2025/06/18",
"position": 86,
"query": "AI layoffs"
}
] |
Will AI Replace Graphic Designers In 2025?
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Will AI Replace Graphic Designers In 2025?
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https://www.andacademy.com
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[
"Sorabh"
] |
In this article, we will explore how AI is shaping the future of graphic design, its impact on jobs, and how designers can leverage AI for innovation and ...
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Worried about AI taking over your job? Find out everything about AI in graphic design and how it can help you prepare for the future.
With AI adoption becoming a common practice in the design process, many ask: Will AI replace graphic designers, or is it simply an extension of their creative abilities? With just a few clicks, a text prompt, and sometimes a reference, AI can generate designs that would typically take hours to complete. Many renowned design tools now include AI features, and new AI-first platforms and frameworks are developing with every passing day. So, the concern, one would say, is perfectly valid.
In this article, we will explore how AI is shaping the future of graphic design, its impact on jobs, and how designers can leverage AI for innovation and growth. Whether you're a graphic designer curious about the future of your career or an organization skeptical about the benefits of AI integration, you’re at the right place for answers.
Here’s a clickable link to everything we will cover in this article:
Relevance of AI tools in Graphic Design
AI design tools operate by processing vast amounts of data. They’re trained in thousands of color schemes, visual styles, fonts, and layouts. That’s why when you submit a prompt request, they generate results in no time. You can refine these prompts, make them detailed, attach a reference, and request design changes until you are satisfied. Some tools even adapt to your preferences and style of working over time, while others are great for quickly generating conceptual ideas and moodboards. Here’s our take on the relevance and role of AI in graphic design in the modern world:
1. Automation of tasks
The most notable impact of AI in graphic design has been its ability to automate repetitive and time-consuming tasks. Designers who would spend time resizing images, adjusting color schemes, or removing backgrounds can now give prompts to complete basic tasks.
Some of the best AI-powered tools that can speed up the graphic design process are MidJourney, DALL-E 2, and Adobe Firefly. For example, Adobe’s Content-Aware Fill fills in missing areas or eliminates unwanted elements from images.
So, when AI takes over mundane tasks, designers have more time to focus on the strategic and creative aspects of their job.
2. Ease of personalization
With AI, customizing designs has become quite convenient. Brands can use this tech to create personalized marketing materials and product designs that cater to individual preferences and behaviors. For example, e-commerce platforms can employ AI algorithms to suggest customized product designs, boosting user engagement and increasing conversions.
Personalization also impacts web design. AI-powered website builders like Wix ADI(Artificial Design Intelligence) and WordPress with Elementor AI Integration can automatically create websites based on user needs and preferences. This streamlines the design process while providing a more personalized and user-friendly experience.
3. Creative assistance
AI can also be a valuable source of inspiration and support for designers who experience a creative block. Platforms like Runway ML and Artbreeder utilize AI to create new images and compositions by merging existing ones. Designers can share their ideas, and AI tools can generate suggestions, helping them discover distinct combinations and styles to choose from.
Moreover, AI-powered tools for color palette generation and font recommendations support designers in making creative choices. These tools provide insights that help designers craft visually appealing designs by analyzing current trends and user preferences.
4. Feedback and collaboration
Collaboration is a core element of the design process, and AI has taken it to a whole new level, making it more efficient and accessible. Platforms like Figma and Adobe XD use AI to simplify design reviews and feedback. Designers can share interactive prototypes with clients and team members, allowing them to leave comments directly on the design. This accelerates the iteration process and ensures everyone involved is updated.
5. Design accessibility
AI is also making design more accessible to a broader audience, including specially challenged individuals. For example, AI-powered tools can automatically generate alt text for images, making them easier for visually impaired users to access. They can also help create color schemes that meet web accessibility standards, ensuring designs are inclusive and compliant with guidelines.
How will AI affect graphic design jobs?
Image Courtesy: Creative Alliance
AI is changing the graphic design industry in intricate ways, altering the skills, workflows, and expectations within the field. Instead of replacing design jobs, AI is reshaping them by automating tasks like layout creation, logo design, and image editing.
Although there are concerns that AI might reduce the number of traditional design jobs, it is more likely that AI will improve and not replace human designers. Designers who can apply their design skills and critical thinking to collaborate with AI will be in greater demand. In fact, graphic designers who gain expertise in AI may uncover new career paths, such as AI model training, AI art direction, and human-centered design.
Will graphic designers be replaced by AI?
This is by far the most dreaded question on everyone's mind. Most creative professionals fear that AI may take over their jobs. While AI can produce visually impressive content, the power lies in human intervention. Your ability to tap into intuition, emotional connection, and cultural awareness gives depth and meaning to your designs. Generative AI can produce realistic and imaginative images based on your prompts, but cannot replace the human qualities of discernment, taste, and context.
As you improve your design skills, you'll learn to direct and refine AI-generated content to suit your brand's voice. The ability to effortlessly incorporate AI outputs into larger creative strategies is becoming a valuable skill. However, your approach, judgment, and understanding of design principles in complex contexts will continue to set your work apart. While AI image generation has come a long way since its early days, here are three reasons why it will never replace human designers.
1. AI lacks emotional intelligence and context
There are plenty of instances where AI misinterprets text prompts. While AI technology is constantly improving, it will never match the emotional and contextual insight that a human designer brings. Such misunderstandings can make the design process frustrating and slow you down if you rely on AI for graphic design. Poorly interpreted prompts can often lead to design blunders.
2. Humans drive innovation
Keep in mind that AI is dependent on machine learning, which means it’s limited to what the human brain has already discovered. If you’ve used AI tools for graphic design, you may have noticed that over time, the style and available options start to feel bland and restrictive. For mediocre designs, this isn't much of an issue, but experienced designers may want a fresh perspective.
Since AI learns from human input, it’s not yet capable of offering groundbreaking ideas or innovations. This limitation can be particularly challenging for non-designers, such as marketers and agencies, who need to create graphics as per brand guidelines.
3. It's all about the details
AI is known for missing details, particularly when dealing with complex images and text prompts. Some of these mistakes are initially subtle, but impossible to ignore once noticed. If you're designing for a brand and need to stick to brand identity guidelines, using AI graphic design generators can be a major drawback.
Can there be a collaboration between graphic designers and AI?
Image Courtesy: Adobe
Traditional graphic design techniques and updated AI-powered tools can collectively improve the creative process of a design project. Here’s what that will look like:
1. Use AI as your assistant
AI tools can handle various tasks that would typically take hours to complete manually, allowing you to move from the concept stage to the final product more efficiently. They can automatically apply styles to text, generate new images, and add or remove elements within images.
Many graphic designers have found that incorporating AI into their workflows has enhanced overall efficiency without compromising creativity. For freelancers, in particular, faster project turnaround can lead to more client opportunities, increased assignments, and higher earnings.
2. Hybrid approach
AI-generated visuals can become a source of inspiration, especially when you’re feeling stuck or need a fresh perspective. By generating unique ideas or providing suggestions that you might not have considered, AI can help push your creative boundaries. This hybrid approach — combining human creativity with AI assistance could lead to a new form of visual art, where AI doesn’t replace the artist but adds a new layer of experimentation.
Similar to how photography eventually gained recognition alongside traditional landscape painting, we may see AI-generated designs develop their own merit. Just as photographers use their expertise to frame and compose images in ways a camera alone can’t capture, graphic designers can shape AI-generated content, applying their creative judgment to shape the final design.
3. Evolving skill set
The only solution is to have a strong foundation in traditional design skills while also making the most of advanced technologies. By developing expertise with AI tools and improving your creative judgment, you can beat the competition and secure your career.
Familiarity with AI-assisted design tools can broaden your skill set and prepare you to cater to a diverse range of projects. Here are some of the best tools that can generate ideas, improve your workflow, and help you collaborate effortlessly:
- Adobe Firefly
- Canva
- Figma
- Autodraw
- InVision
- Marq
- Framer
AI adoption has made graphic design more accessible by reducing technical barriers, but it has also increased the importance of design skills. Understanding audience needs, effectively communicating ideas, and having a strong sense of aesthetics are areas where human designers will outrun even the most advanced AI tools.
Limitations and ethical considerations in AI
The quality of AI-generated results is primarily influenced by the data on which they have been trained. If the data is inaccurate, incomplete, or biased, the results will be flawed, regardless of how precise your prompts are. While AI is good at following instructions, it cannot compete with human skills such as critical thinking, complex problem-solving, or understanding audiences. These skills are essential for interpreting brand identity, cultural content, and user expectations, and they are best handled by human designers. Here are a few things that you should know about using AI in your work as a graphic designer:
1. Intellectual property and copyright issues
AI-generated designs raise issues regarding intellectual property and copyright. There is ongoing debate about who owns the rights to such content — the human who wrote the prompt, the creators of the AI model, or whether the content is eligible for copyright protection at all. Figuring out who owns AI-generated content and where it originates can be tricky, potentially leading to legal conflicts. For example, asking AI to create images in the style of a specific artist could raise concerns about ownership and copyright infringement. Designers and organizations must establish clear guidelines and ethical practices for using AI-generated content while adhering to copyright laws and intellectual property rights.
2. Job replacement or expansion
A major concern in the design community is the potential for AI to replace jobs. As AI automates mundane design tasks, some worry it might take over human designers. However, a more balanced and realistic view is that AI amplifies the abilities of designers when used correctly. Designers can use AI to optimize workflow, freeing up time to focus on the larger scheme of things that require a human touch.
3. Accountability
Using AI in design also brings up concerns about transparency and accountability. As AI-generated content becomes more common, it can be difficult to determine the source or creator of a design. This lack of clarity can lead to ethical issues, such as misrepresentation or plagiarism. Ensuring clear boundaries in AI-driven design will safeguard the integrity of the creative process.
Future outlook for graphic designers
Experts predict growth in the AI industry, pointing to ongoing innovation and future opportunities. McKinsey's "The State of AI" report in 2025 indicates a rise in AI adoption, with over 70% of organizations now using AI. With that, generative AI is also becoming more common and widely used.
Many graphic designers have realized that incorporating AI has increased their productivity, allowing them to take on more projects. In fact, designers are contributing to creating more intuitive interfaces, training AI models, and setting ethical guidelines for AI use in creative industries.
These advanced skills can now provide opportunities in traditional graphic design roles as well as emerging roles that integrate technology. Some skills that are particularly valuable for AI-related roles include:
Human-centric interaction design — Creating experiences that focus on user needs and behaviors
— Creating experiences that focus on user needs and behaviors Systems design — Organizing complex components into functional and unified designs
— Organizing complex components into functional and unified designs Visual communication — Converting ideas into powerful visual representations
Way Forward
We hope you’ve found the answers you were looking for in this comprehensive article and are no longer in two minds about AI’s integration in graphic design. The future of design lies in a combined effort of AI literacy and design skills, empowering designers to amplify their visual concepts and problem-solving abilities. Treat AI as your ally and experience how it can improve your workflows and expand creative possibilities.
Want to learn more about graphic design? These guides will help you build your skills and turn your ideas into reality:
1. The Significance of White Space in Design (With Examples)
2. 10 Best Graphic Design Apps To Count on in 2025
3. Exhibition Design: Principles, Types, Trends, and How To Become an Exhibition Designer?
Next Steps
If you’d like to know more about graphic design or related topics, head over to the AND Academy blog for more articles.
We recommend that you check out this project by AND Learner, Sannidhi Goyal, to get inspiration for your next work.
In case you need further assistance, here are some of our resources you can consider:
Watch this session by design veteran and AND’s Academic Head, Prachi Mittal, and our Course Lead, Soumya Tiwari. Talk to a course advisor to discuss how you can transform your career with one of our courses. Pursue our Graphic Design courses - all courses are taught through live, interactive classes by industry experts, and some even offer a Job Guarantee. Take advantage of the scholarship and funding options that come with our courses to overcome any financial hurdle on the path of your career transformation.
Note: All information and/or data from external sources is believed to be accurate as of the date of publication.
| 2025-06-18T00:00:00 |
2025/06/18
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https://www.andacademy.com/resources/blog/graphic-design/will-ai-replace-graphic-designers/
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News Archive
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University of Florida
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https://ai.ufl.edu
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UF medical students are gaining hands-on experience in AI-driven research and education through UF's Artificial Intelligence in Medicine program.
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New study examines how coaches are using data and technology to maximize player performance and safety.
University of Florida Ph.D. students Mollie Brewer and Kevin Childs traveled to Japan to present their research on how collegiate coaches use wearable data and AI to enhance athletic performance and reduce injuries. Their paper, selected for the international CHI conference, highlights the growing role of data analysis in coaching and showcases UF’s AI-Powered Athletics initiative.
| 2025-06-18T00:00:00 |
https://ai.ufl.edu/news-archive/
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{
"date": "2025/06/18",
"position": 51,
"query": "artificial intelligence journalism"
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Artificial Intelligence
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Cozen O’Connor: Artificial Intelligence
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https://www.cozen.com
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On the traditional labor side, we expect AI use to be a hot topic in union negotiations for the foreseeable future, and our team is prepared to negotiate such ...
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Recent Blog Post: Fall 2024 Employer Check-up: Reduce Risk When Using AI Vendors’ Hiring Tools Last month, the U.S. Department of Labor (DOL) announced a new initiative, the “AI & Inclusive Hiring Framework,” funded by the DOL’s Office of Disability Employment Policy (ODEP). This framework is a voluntary resource to help employers ensure their third-party Artificial Intelligence hiring tools are inclusive and accessible to disabled individuals. More
With ChatGPT and other artificial intelligence technologies transforming how we live, work, and create in the 21st century, the legal challenges AI presents are evolving at breakneck speed. Set against the backdrop of a developing regulatory landscape and raising novel issues spanning technology, privacy, intellectual property, and employment law (among other areas), these challenges can catch even the savviest of AI users and developers by surprise. Cozen O’Connor’s Artificial Intelligence practice draws on the experience of an interdisciplinary team of legal advisers to meet our clients’ needs in this dynamic space. This breadth of experience allows us to anticipate and address the full spectrum of unique issues both developers and users of AI and machine learning technology are facing.
Our team stands ready to assist a range of clients, including developers and providers of AI platforms, subscribers and business users of AI platforms, creative agencies, software developers, and others that leverage, embed, or integrate with AI and machine learning tools. Whether you use AI in your business or AI is your business, we can help you navigate this largely uncharted territory.
For example, when structuring and negotiating transactions for the development, licensing, acquisition, or use of AI tools, clients can rest assured that our interdisciplinary team is tracking all of the issues at play, including privacy, legal and regulatory compliance, intellectual property rights, and risk allocation. We can also help organizations comply with industry and regulatory AI frameworks relating to privacy, safety, accountability, and absence of bias.
Our AI practice includes labor and employment attorneys who can help employers develop policies and guidelines concerning employees’ use of AI tools (including ChatGPT) throughout the workplace. Our employment litigators are prepared to defend employers against AI-related lawsuits, such as those alleging bias from AI use and/or class and collective actions alleging violations of laws governing the use of AI for human resources functions. On the traditional labor side, we expect AI use to be a hot topic in union negotiations for the foreseeable future, and our team is prepared to negotiate such issues and to address NLRB charges alleging Unfair Labor Practices such as a refusal to bargain over AI use. These are just a few of the many areas of intersection between AI and the workplace that we help employers navigate.
Additionally, we stay on the cutting edge of IP-related issues surrounding the use of AI tools, such as transformative fair use and potential claims of copyright infringement. Our patent team has experience drafting and prosecuting patent applications covering AI-implemented inventions, including generative AI inventions. And we closely track the rising tide of trade secret implications associated with AI use.
Perhaps in no other area has the legal and regulatory environment been so unsettled while the underlying subject matter evolves at such a dizzying rate of speed. This makes nimble, creative, and savvy counsel a must, and these qualities are at the very core of Cozen O’Connor’s identity as a firm. With our carefully curated AI team’s capabilities spanning transactional, regulatory, intellectual property, and litigation experience in multiple disciplines, Cozen O’Connor is a one-stop shop for advice and counsel on maximizing the business benefits of AI while minimizing the attendant risk.
| 2025-06-18T00:00:00 |
https://www.cozen.com/practices/artificial-intelligence
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[
{
"date": "2025/06/18",
"position": 63,
"query": "artificial intelligence labor union"
}
] |
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Union Praises NY Bills On AI In Advertisements, Digital ...
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Union Praises NY Bills On AI In Advertisements, Digital Rights
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https://www.law360.com
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Entertainment labor union SAG-AFTRA has applauded the passage of two bills by the New York State Legislature that would require the disclosure of ...
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| 2025-06-18T00:00:00 |
https://www.law360.com/articles/2354729/union-praises-ny-bills-on-ai-in-advertisements-digital-rights
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[
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"date": "2025/06/18",
"position": 73,
"query": "artificial intelligence labor union"
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AI PCs will shape the future of work – but not everyone will get ...
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AI PCs will shape the future of work – but not everyone will get one
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https://www.cio.com
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IDC's Ryan Reith says there is no critical use case for AI PCs today, but they will be a key part of the future workplace.
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I spoke with IDC’s Ryan Reith, Group Vice President, WW Device Trackers, at IDC’s 60th annual Directions conference. Ryan and his IDC colleagues advise senior IT leaders around technology strategy – in his case focusing on end user devices.
From the benefit of that experience Ryan said that although there is no critical use case for AI PCs today, organizations should be thinking about the future of their workforce and the devices they will need. He said that AI PCs will bring increased security and efficiency with compute happening at the edge. But he said that not everyone will need an AI PC, and education of IT, management and employees will be key.
You can watch our conversation here, or via the YouTube player below.
| 2025-06-18T00:00:00 |
https://www.cio.com/article/4008405/ai-pcs-will-shape-the-future-of-work-but-not-everyone-will-get-one.html
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7 AI tools you can use to enhance your work life in 2025
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7 AI tools you can use to enhance your work life in 2025
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https://mashable.com
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7 AI tools you can use to enhance your work life in 2025 · AI Chatbots · Most Adobe products have AI built in · Microsoft Copilot · Grammarly helps with your ...
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We examine how AI is changing the future of work — and how, in many ways, that future is already here.
AI doesn’t have the best reputation. From accusations of plagiarism to cheating students , there are plenty of negative headlines when it comes to using AI. However, when used properly, AI can be a beneficial and valuable part of your workflow and can even boost your productivity.
The key is using AI within its limits. A recent Gallup study found that 40 percent of U.S. workers are now using AI tools at work, which means the other 60 percent is at risk of getting left behind. Just look at another recent study , which shows that workers who use AI (within the boundaries of its capabilities) can boost their productivity by upwards of 40 percent, while those who use AI outside of those boundaries reduce their performance by 19 percent. In short, as long as you use AI to help you do your job, you have the opportunity to increase your gains by a hefty amount, but if you let AI take the wheel, it’ll have the opposite effect.
With all of that in mind, the other important part of using AI to increase your productivity is finding the correct AI tools. Below is a list of tools that can help out in various ways, from creativity to productivity, and many of them come from names you already know.
You May Also Like
AI Chatbots
Let’s get the most obvious tool out of the way first: the humble AI chatbot. You can find these everywhere. ChatGPT is the most famous, along with Google Gemini, Claude, Grok, and many others. They are mostly interchangeable, especially since each new release from each company leapfrogs the competition , until the next update is released. However, the most famous is currently ChatGPT, and there are tons of guides on how to optimize it for your workflow.
So, what can a chatbot do for you? Loads of things, it turns out. The chatbot itself is basically a giant summary of everything the AI was trained on, so the best use case is asking it questions and getting ideas, suggestions, or answers to those questions. You can also automate AI to perform tasks for you, have it check or assist you in writing computer code, and summarize PDFs. The list is far too long to put here, but if you wanted to get into AI, looking into chatbots is a good first step.
Most Adobe products have AI built in
Adobe has some of the most popular and powerful creativity apps in this space, and many of them have AI built right in to enhance existing functionality. For example, in Adobe Acrobat, Adobe has put in an AI assistant that you can talk to for help navigating large PDF files. You can ask it questions about the contents, ask it for a summary, or ask it to identify specific details. It not only does these things, but provides citations for them, so you can quickly review the relevant sections yourself to make sure the AI didn’t get it wrong.
The more creative stuff has AI as well. An example of that is Actions in Photoshop. When you use Actions, Photoshop will use AI to analyze the image and then deliver a list of recommended edits. All you have to do is accept the recommendations, and Photoshop applies them automatically. Photoshop can also use AI to remove objects from images , turning what was once a complicated, multi-step process within Photoshop into something that takes a minute or two.
Adobe keeps a handy list of all of its AI tools within its apps if you want to see all of the other possibilities.
Microsoft Copilot
Microsoft Copilot could technically be listed under the AI chatbots above, but we think it’s unique enough to get its own mention. Copilot is built on OpenAI’s GPT models along with Microsoft’s Prometheus . It’s also built directly into Windows PCs, meaning there is no complex download or installation setup. (For once, there's no Apple equivalent to Copilot, which means Windows has the AI edge for the moment.) Plus, it’s nice to be able to use a chatbot without the need for a web browser. So, on the surface, it functions like a chatbot and can be used like one if you wish.
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On top of that, Copilot is also built into various Microsoft apps , just like Adobe does with its apps. It’s built into the Microsoft 365 suite and can interact with many of the apps there. Microsoft is also working on AI agents for PC that will give you the power to do things like asking the AI to change settings or open apps on your behalf. Since this particular AI tool is built into Windows, you might as well give it a try and see if you like it.
Grammarly helps with your writing
Of all the tools on this list, Grammarly is the one I use the most. I can usually nail my grammar without any help, but I’ve always been iffy on punctuation, and Grammarly has helped with that immensely. This tool has been around for ages, and I generally use it most often as a browser extension. For the most part, Grammarly analyses your writing in real time and then gives you suggestions on how to fix it. Its word replacement suggestions can make your writing a little stiff for my tastes, but I haven’t missed a comma in years, and that’s all I really care about.
In recent years, Grammarly has also experimented with generative AI . It works mostly like an AI chatbot of sorts. You ask it to help you write a topic and give it some contextual information, and then Grammarly’s bot helps you write something up. You edit it to your tastes and then ship it. This is something the company generally markets to businesses, but it is available for personal use as well.
Otter.ai
One that you’ll have in almost every professional setting is talking, and a lot of it. Otter.ai helps with this by giving you a quick, easy way to transcribe almost any social interaction in your work environment so you can read back through it later if you need to. Once transcribed, you can ask Otter’s AI chat to summarize or find specific parts for you, making it quite easy to comb through the information to find what you need.
You can mash the two together with the brand’s AI channels, which lets you ask the AI questions about prior meetings and also with your teammates at the same time, giving you access to both people and transcriptions at the drop of a hat. Between meetings, presentations, and even things like keynote addresses or college lectures over Zoom, there are plenty of ways Otter.ai can be helpful. As a journalist, it's hugely helpful for quickly transcribing conversations, but that's just one of its many use cases.
NotebookLM
Alongside meetings, research is a fact of life for many jobs, and NotebookLM is actually pretty wonderful for this. The idea is pretty simple. You take your sources, be they PDFs, Google Drive links, YouTube videos, or even just pasted text, and you dump them all into NotebookLM. From there, you can ask the AI questions, and it’ll use your sources specifically to find the answers. The AI can go outside of your sources as well, but will tell you when it does. You can even turn everything into a summarized podcast and listen to the information.
This one is nice because it’s not restricted to a web browser. There are apps available for phones as well , so you can do this on your phone if you’re on the go. Using AI outside of a web browser is a big deal for me, at least, and interacting with it in a native app is much nicer in some cases. If your work requires you to pore through a lot of information, NotebookLM is worth a shot.
FeedHive
In an increasingly social media-driven world, AI can help you manage that kind of stuff as well. FeedHive is about as good as it gets in this space. On the surface, it’s a social media management platform. You can post from various accounts, manage your DM inbox, schedule posts, and do all of that. That alone is handy for businesses or influencers. However, there are some AI tools included that can help in other ways.
FeedHive can also view things like analytics to follow post engagement, activity, and more data about each post. It then uses AI to help you plan your posts for when your followers are the most active, along with the right hashtags to help you get the most engagement. There isn’t any data to show how successful this is, but any edge can be helpful when you’re competing against tens, or even hundreds, of millions of people. This one is mostly for business or influencer use, but beginners in this space can definitely use the data to help them.
Remember: Think beyond ChatGPT
There are a ton of other ways to use AI at work, such as generating images or as a companion bot to lift your self-esteem on rough days. While researching this article, we found a surprising number of people who use AI chatbots just to have something to chat with while working from home or studying alone deep into the night. Such interactions can also be helpful, as having something to bounce ideas off of and giving you digital high-fives can help make things feel less lonely and monotonous.
Whatever AI productivity tools you decide to use, it’s important to make sure that you’re always doing your own work. The Internet has taken a dim view of companies and individuals using AI to create things, and so as long as you do it ethically, you should be okay.
Disclosure: Ziff Davis, Mashable’s parent company, in April filed a lawsuit against OpenAI, alleging it infringed Ziff Davis copyrights in training and operating its AI systems.
| 2025-06-18T00:00:00 |
2025/06/18
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https://mashable.com/article/ai-tools-enhance-productivity-work
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[
{
"date": "2025/06/18",
"position": 17,
"query": "future of work AI"
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Amazon and AI: how artificial intelligence will change work
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Amazon and AI: how artificial intelligence will change work
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https://en.cryptonomist.ch
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Dario Amodei, CEO of the company Anthropic, stated that artificial intelligence could eliminate up to half of entry-level office jobs, especially those based on ...
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Amazon is preparing for a future dominated by the use of artificial intelligence (AI), a change set to radically transform the organization of work in the large company and in the tech sector in general.
Andy Jassy, CEO of Amazon, recently communicated to employees the impact that this technology will have on the workforce, anticipating a reduction in corporate staff thanks to the efficiency gains resulting from the massive adoption of AI.
Amazon and the challenge of artificial intelligence
The message from Andy Jassy arrives at a crucial moment: AI is rapidly changing the way companies operate, especially in the tech world. Thanks to advancements in the ability of models like chatbots to generate code, images, and texts with minimal input, Amazon is integrating AI into almost every sector of the company. However, this revolution comes with an evident human cost: fewer people will be needed to perform certain business tasks.
Jassy urged his collaborators to “be curious about AI” and to embrace the transformation, as the company aims to use the technology to complete routine tasks more quickly and accurately. An important aspect of his communication is the prediction that, within a few years, Amazon’s corporate workforce will shrink. This does not mean a total disappearance of jobs in the company, but a reconfiguration of roles: some positions will disappear, others will transform, or new opportunities will arise related to the use and development of Intelligenza Artificiale.
Amazon’s Numbers and the Impact on Employment
At the end of 2023, Amazon employed more than 1.5 million people globally, with the majority of the staff concentrated in the United States, where Amazon is the second-largest employer after Walmart. This figure highlights the company’s reach and the potential scale of employment change caused by the adoption of AI.
In particular, about 350,000 employees work in office roles, while the majority of the workforce is involved in logistics and e-commerce operations. Jassy highlighted that AI is already used by about half a million sellers on Amazon platforms to create informational content about products, and it is progressively spreading among advertisers as well. This suggests an increasingly intense convergence between technology and human work, even in more creative or complex activities such as marketing and product description.
The jobs that will change and those that will disappear
According to Jassy, AI will allow for “efficiency” everywhere, performing routine tasks such as shopping and daily chores. However, the reduction of staff does not only mean widespread layoffs: some professions will be replaced, while others will transform drastically.
This trend is also confirmed by other experts in the AI sector. Dario Amodei, CEO of the company Anthropic, stated that artificial intelligence could eliminate up to half of entry-level office jobs, especially those based on repetitive and predictable tasks. Furthermore, Geoffrey Hinton, known as the “godfather of AI,” has expressed similar concerns, warning that the ability of AI to perform ordinary human intellectual work could drastically reduce the demand for traditional workforce in office professions.
AI: opportunities and challenges for Amazon
Despite the anticipated reduction in workforce, Amazon seems to be focusing heavily on innovation and growth related to AI. According to the CEO, employees who can adapt to change and leverage new technologies will be “well positioned” within the company. The rapid adoption of AI in various corporate departments could indeed create new professional areas, especially in the field of management and development of intelligent systems.
Furthermore, the integration of AI is already changing the way Amazon supports sellers on its platforms, offering advanced tools to improve communication and product promotion. Advertising investments are also benefiting from these technologies, making processes more efficient and precise.
The future of work at Amazon according to Jassy
AI will be integrated into almost all business aspects.
The most repetitive and routine tasks will be entrusted to the machines.
There will be a reduction in the corporate workforce in the coming years.
Birth of new roles and transformation of existing ones.
Employees ready to innovate will have more opportunities.
Amazon and artificial intelligence: a look beyond
The impact of AI on Amazon represents a concrete example of how technology is redefining the job market, especially in large tech corporations. While the reduction of jobs is a reality, this transformation also paves the way for new professional opportunities and greater efficiency in business processes.
It is therefore essential for workers to stay updated and develop skills related to AI, in order not to fall behind in a rapidly evolving context. On the other hand, companies must also deal with the responsibility of managing this transition in an ethical and sustainable way, considering the social impact of significant occupational cuts.
In summary, Amazon’s decision to invest heavily in artificial intelligence marks a turning point in the way we work and live with technology. Those who can adapt to this new reality will have a significant competitive advantage, while the entire sector will be called to reflect on development and inclusion prospects.
| 2025-06-18T00:00:00 |
2025/06/18
|
https://en.cryptonomist.ch/2025/06/18/amazon-and-ai-how-artificial-intelligence-will-change-work/
|
[
{
"date": "2025/06/18",
"position": 77,
"query": "future of work AI"
}
] |
AI use at work has almost doubled in the past year, Gallup ...
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AI use at work has almost doubled in the past year, Gallup finds
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https://www.emergingtechbrew.com
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[] |
AI job growth? Perhaps tech workers are right not to be overly worried at the moment. Another survey of tech C-suite leaders from Deloitte this week found that ...
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What happens when you bring together the NiCEst person on earth and the best AI platform for customer service? You get service that just gets you. Kristen Bell + the smartest AI platform = service that’s seamless, personal, efficient… it’s so NiCE.
ChatGPT and its ilk seem to be taking on ever more work in modern offices.
A new survey from Gallup finds that AI use at work has been accelerating. Nearly one in five workers now say they use it a few times a week, and 8% of respondents report daily AI interactions. Both those numbers have essentially doubled from Gallup’s first measure in 2023.
But not all workers use AI equally. The surge is mostly among white-collar workers, for one; production and frontline staffers have actually seen a slight dip in usage over the past couple of years (from 11% to 9%). Sectors with the highest concentrations of workers frequently turning to AI included the tech industry (50%), professional services (34%), and finance (32%).
BYOAI: Like other surveys have shown, AI usage among employees has also continued to race ahead of employer planning and leadership on the tech. That can create security headaches and lead to a lack of consistent guidelines for workplaces.
While the number of organizations that have communicated a clear plan for integrating AI improved from 15% to 22% in the past year, “it’s still quite low,” according to Jim Harter, Gallup’s chief scientist of workplace management and well-being.
“[Organizations] need to be intentional about the planning process, about the training process,” Harter told Tech Brew. “They’ve got to have a plan about how it can best benefit their company and the jobs that they have, and how it can be a companion for efficiency’s sake in those jobs.”
No fear: Despite some ominous headlines about AI’s potential to reshape the job market, many of these workers are also notably not worried about being replaced by the technology. Only 15% of workers expect robots, automation, or AI to threaten their jobs in the next five years, a figure that remains unchanged from 2023.
Worries were slightly more pronounced in certain industries, however: 21% of tech workers and retail employees and 20% of finance workers think their jobs could be at risk in the same time frame.
“I think people are sort of embracing it as more of a companion, which probably is the right way to think about it right now,” Harter said. “We don’t know what direction it’s going and how quickly…and it probably will be quickly.”
AI job growth? Perhaps tech workers are right not to be overly worried at the moment. Another survey of tech C-suite leaders from Deloitte this week found that seven in 10 said they’re increasing headcount in tech as a response to generative AI. Around 45% said that GenAI prowess is urgently needed, and there are talent shortages and skill gaps around the technology.
The survey, which queried more than 620 senior tech leaders in the US this spring, found that AI might best augment in-demand skills like cybersecurity (56%), cloud orchestration (47%), and data science/analytics (39%).
“Businesses are rapidly pivoting from AI as experimental to an engine for transformation and innovation. In organizations where the C-suite leads the shift, more value can be realized,” Ranjit Bawa, Deloitte’s US chief strategy and technology officer, said in the report.
| 2025-06-18T00:00:00 |
2025/06/18
|
https://www.emergingtechbrew.com/stories/2025/06/18/ai-use-at-work-gallup
|
[
{
"date": "2025/06/18",
"position": 81,
"query": "future of work AI"
}
] |
AI Job Loss Statistics 2025: Who's Losing, Who's Hiring, etc.
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AI Job Loss Statistics 2025: Who's Losing, Who’s Hiring, etc.
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https://sqmagazine.co.uk
|
[
"Barry Elad",
"Flo Headlam",
"Tigerr Benson",
"Yogesh Shinde",
"Nicholas Stovold"
] |
A Goldman Sachs report indicates that 18% of global work could be automated by AI, affecting up to 300 million full-time jobs. The AI and Machine Learning job ...
|
In the winter of 2024, a seasoned logistics manager at a Midwestern warehouse watched as his team’s responsibilities were gradually handed over to an AI-powered system. Within six months, what had been a bustling department of 28 human workers was reduced to just five. Stories like this aren’t isolated—they’re forming a global pattern. Artificial intelligence isn’t just optimizing workflows; it’s replacing them. As we enter 2025, AI-related job loss has moved from speculative headlines to a tangible economic reality. This article explores the current landscape of AI-driven displacement through reliable statistics and insights to help you stay ahead of what’s unfolding.
Editor’s Choice
85 million jobs are estimated to be displaced globally by AI and automation by the end of 2025 , according to the World Economic Forum.
are estimated to be displaced globally by AI and automation by the end of , according to the World Economic Forum. In the US, 2.4 million jobs were impacted by AI-driven automation between 2020 and 2024 , with another 1.1 million projected to be disrupted in 2025 alone.
were impacted by AI-driven automation between , with another projected to be disrupted in alone. Administrative support and data entry roles have seen a 45% reduction in hiring rates since 2022, heavily influenced by AI deployment.
and roles have seen a in hiring rates since 2022, heavily influenced by AI deployment. A Goldman Sachs report indicates that 18% of global work could be automated by AI, affecting up to 300 million full-time jobs .
report indicates that could be automated by AI, affecting up to . The AI and Machine Learning job market continues to grow, with demand increasing by 41% year-over-year , partially offsetting job loss trends.
job market continues to grow, with demand increasing by , partially offsetting job loss trends. 48% of US companies say they are using AI tools to restructure departments and reduce headcount in 2025.
say they are using AI tools to restructure departments and reduce headcount in 2025. In contrast, AI is predicted to create 97 million new roles globally in areas like digital marketing, cybersecurity, and software development by 2025.
AI Job Replacement Risk by Sector
Administration jobs face the highest risk , with 26% potentially impacted by AI technologies. This sector includes clerical and support functions that are highly automatable.
face the , with potentially impacted by AI technologies. This sector includes clerical and support functions that are highly automatable. Customer service roles are the next most vulnerable, with 20% of jobs at risk. AI chatbots and virtual assistants are rapidly replacing routine interactions.
are the next most vulnerable, with of jobs at risk. AI chatbots and virtual assistants are rapidly replacing routine interactions. Production work shows a 13% risk of being replaced, largely due to automation and robotics in manufacturing environments.
shows a risk of being replaced, largely due to automation and robotics in manufacturing environments. The legal sector has a 6% job replacement risk. AI is increasingly used for document review and legal research, but human judgment still plays a major role.
has a job replacement risk. AI is increasingly used for document review and legal research, but human judgment still plays a major role. Education roles carry a 5% risk. While AI can assist in content delivery, human interaction remains critical in teaching.
carry a risk. While AI can assist in content delivery, human interaction remains critical in teaching. Jobs in creativity and the arts show a 4% risk. AI tools can aid in content creation, but have limited capacity for original creative thought.
show a risk. AI tools can aid in content creation, but have limited capacity for original creative thought. Management positions are the least threatened, with just a 3% risk. Strategic decision-making and leadership still heavily rely on human capabilities.
(Reference: Boterview)
Global Job Displacement Numbers Attributed to AI
As of early 2025 , over 14 million jobs worldwide have already been lost directly due to AI-driven technologies.
, over worldwide have already been lost directly due to AI-driven technologies. In Asia, automation and AI are expected to displace 21% of current jobs by 2026 , with manufacturing being the most affected sector.
by , with manufacturing being the most affected sector. The European Union anticipates 12 million jobs to be either eliminated or fundamentally transformed by AI technologies over the next three years.
anticipates to be either eliminated or fundamentally transformed by AI technologies over the next three years. According to the OECD , 27% of jobs globally are at high risk of being automated, with lower-skilled roles most vulnerable.
, are at high risk of being automated, with lower-skilled roles most vulnerable. The World Bank estimates that 77% of jobs in China are susceptible to automation, many due to AI-enhanced robotics.
estimates that are susceptible to automation, many due to AI-enhanced robotics. A 2024 McKinsey report found that 800 million jobs could be displaced globally by 2030 , with AI being a central force in that transformation.
report found that could be displaced globally by , with AI being a central force in that transformation. The United States saw a 22% increase in AI-induced layoffs from Q4 2023 to Q1 2025 , signaling the acceleration of AI’s job impact.
in AI-induced layoffs from , signaling the acceleration of AI’s job impact. Latin America reports more modest figures, with an estimated 4.5 million jobs expected to be lost due to AI by 2027 , largely in call centers and retail.
expected to be lost due to AI by , largely in call centers and retail. Africa has so far experienced less disruption, but digital labor platforms supported by AI are predicted to reduce traditional employment by 9% in urban areas.
supported by AI are predicted to reduce traditional employment by in urban areas. Automation-driven displacement is most aggressive in countries with advanced IT infrastructure, such as Japan, South Korea, Germany, and the US.
Regional Breakdown of AI-Related Job Losses
The United States leads in AI-induced job losses among developed nations, with 1.9 million jobs affected by early 2025 .
leads in AI-induced job losses among developed nations, with affected by early . In India , AI has displaced over 650,000 IT service jobs , primarily in Tier-1 outsourcing cities like Bengaluru and Hyderabad.
, AI has displaced over , primarily in Tier-1 outsourcing cities like Bengaluru and Hyderabad. Germany reported a 17% decline in manufacturing jobs attributed to AI adoption in factories between 2023–2024 .
reported a in manufacturing jobs attributed to AI adoption in factories between . Japan has implemented robotics at a large scale, resulting in the loss of 490,000 warehouse and assembly line jobs by early 2025 .
has implemented robotics at a large scale, resulting in the loss of by early . In Canada , AI adoption in insurance and banking led to a 12% reduction in back-office roles in 2024 .
, AI adoption in insurance and banking led to a in back-office roles in . South Korea continues to lead in robotics density, with 20% of factory workers being replaced by AI-enhanced automation systems in the past two years.
continues to lead in robotics density, with being replaced by AI-enhanced automation systems in the past two years. Australia reported over 60,000 displaced jobs in customer-facing retail and hospitality due to intelligent service systems.
reported over in customer-facing retail and hospitality due to intelligent service systems. In the UK , a Royal Society report noted that AI affected 11% of all full-time roles in 2024 alone.
, a report noted that AI affected in 2024 alone. Brazil’s booming fintech sector is driving AI adoption, with over 90,000 roles in call centers already automated.
booming fintech sector is driving AI adoption, with over in call centers already automated. China has restructured entire logistics supply chains using AI, contributing to over 1.2 million job transitions from manual labor to tech-assisted roles since 2023.
How AI Is Changing the Workforce
AI could replace up to 300 million full-time jobs globally, highlighting the massive potential of automation on employment markets.
full-time jobs globally, highlighting the massive potential of automation on employment markets. Generative AI adoption in marketing and advertising is already high, with a significant adoption rate of 37% among professionals.
is already high, with a significant among professionals. 14% of workers report being displaced by robots and automation , showing the real-world effects of emerging tech on job security.
report being displaced by , showing the real-world effects of emerging tech on job security. 77% of businesses are already using or considering AI , indicating widespread organizational reliance on artificial intelligence tools.
are already , indicating widespread organizational reliance on artificial intelligence tools. In May 2023, the United States saw 3,900 job losses directly attributed to AI, reflecting its growing role in workforce changes.
(Reference: AI Content Detector)
AI’s Impact on White-Collar vs. Blue-Collar Employment
White-collar workers are increasingly at risk, with 37% of roles in finance, law, and media being susceptible to partial or full automation by AI systems .
are increasingly at risk, with being susceptible to partial or full automation by . A 2025 Deloitte study found that AI threatens 45% of analytical and clerical roles, including tax preparation, accounting, and underwriting.
found that of analytical and clerical roles, including tax preparation, accounting, and underwriting. Blue-collar sectors still account for the highest total job losses , but the rate of white-collar displacement is now growing 2.1 times faster than in 2022.
still account for the , but the rate of white-collar displacement is now growing than in 2022. In healthcare, clinical documentation roles are now automated in nearly 30% of hospitals , impacting administrative personnel more than practitioners.
are now automated in , impacting administrative personnel more than practitioners. AI has reduced entry-level legal assistant jobs by 33% in the US since 2023, mainly through document automation and e-discovery tools.
by in the US since 2023, mainly through document automation and e-discovery tools. In construction, only 7% of roles are currently impacted by AI, as tasks remain heavily physical and environment-dependent.
are currently impacted by AI, as tasks remain heavily physical and environment-dependent. Customer-facing roles like loan officers and insurance agents are becoming obsolete, with AI algorithms handling risk analysis and approvals.
are becoming obsolete, with AI algorithms handling risk analysis and approvals. Retail stockroom jobs , considered blue-collar, have seen a 16% drop in demand due to AI-assisted inventory management tools.
, considered blue-collar, have seen a in demand due to AI-assisted inventory management tools. AI-powered diagnostics in radiology and pathology are shifting white-collar medical tasks, affecting early-career specialists especially.
in radiology and pathology are shifting white-collar medical tasks, affecting especially. Tech-related white-collar roles, such as data analysts, are also evolving—while entry-level positions are shrinking, demand for senior AI strategy roles is climbing.
Workforce Demographics Most Vulnerable to AI Replacement
Workers aged 16–24 face the highest automation risk , with entry-level support roles disappearing at a rate of 19% annually .
face the , with disappearing at a rate of . Women in clerical and administrative roles are disproportionately impacted— 61% of AI-displaced roles in 2024 were held by women.
are disproportionately impacted— were held by women. Non-degree holders are 3.5 times more likely to lose their jobs to automation compared to those with a college education.
to lose their jobs to automation compared to those with a college education. Among ethnic groups in the US, Black and Hispanic workers represent 32% of jobs lost to AI, largely concentrated in retail and logistics.
represent to AI, largely concentrated in retail and logistics. The disability workforce is also vulnerable: AI systems in fast food and call centers have reduced demand for previously accessible roles.
is also vulnerable: AI systems in fast food and call centers have reduced demand for previously accessible roles. Older workers (aged 55+ ) face challenges in retraining, with only 12% enrolled in AI-transition upskilling programs in 2024.
) face challenges in retraining, with in AI-transition upskilling programs in 2024. Part-time employees have seen a 21% higher displacement rate than full-time staff due to flexible role structures being more automatable.
than full-time staff due to flexible role structures being more automatable. Remote roles are more susceptible to AI-driven cuts; AI-based monitoring tools have eliminated thousands of virtual assistant positions in just one year.
have eliminated in just one year. Entry-level marketing jobs, once seen as growth opportunities, have been largely replaced by AI tools like Jasper and Copy.ai in early 2025 .
in . Workers in rural areas have limited access to retraining resources, making them 60% more likely to remain unemployed after displacement.
Will AI Replace Most Human Jobs in the Next 50 Years?
50% of people believe AI will probably take over much of the work currently done by humans within the next 50 years .
believe AI will take over much of the work currently done by humans within the next . 15% of respondents think AI will definitely replace a large portion of human work in the same timeframe.
think AI will replace a large portion of human work in the same timeframe. 25% of people responded with probably not , expressing uncertainty or skepticism about AI’s long-term impact.
responded with , expressing uncertainty or skepticism about AI’s long-term impact. Only 7% of participants are confident that AI will definitely not replace significant human labor over the next five decades.
(Reference: Zippia)
AI vs. Traditional Automation: Comparative Job Loss Statistics
Traditional automation (e.g., robotics) led to 1.7 million global job losses in 2023 , while AI-induced displacement reached 2.4 million the same year.
, while AI-induced displacement reached the same year. AI’s pace of adoption is now 4x faster than industrial robotics during the 2000–2010 period, according to a 2024 MIT study.
is now than industrial robotics during the 2000–2010 period, according to a 2024 MIT study. Chatbots and generative AI tools have replaced more human roles in two years than robotic process automation did in the past decade .
generative AI have replaced more human roles in than robotic process automation did in the past . Manufacturing saw consistent losses from traditional automation, but AI is increasingly affecting non-manufacturing sectors like healthcare and finance.
like healthcare and finance. Traditional automation typically displaced manual labor , while AI now threatens cognitive and analytical tasks , a major shift in scope.
, while AI now threatens , a major shift in scope. The cost to deploy AI in business processes is 37% lower than implementing physical automation equipment.
in business processes is than implementing physical automation equipment. AI systems are adaptive , unlike traditional machines; this flexibility makes 79% of mid-level cognitive tasks targetable by 2026.
, unlike traditional machines; this flexibility makes targetable by 2026. Traditional automation brought strong productivity gains but required high infrastructure; AI tools are cloud-based and require minimal capital.
and require minimal capital. AI also enables cross-industry disruption —one platform can impact multiple sectors simultaneously, unlike task-specific robots.
—one platform can impact simultaneously, unlike task-specific robots. AI’s job elimination cycle is now averaging 18 months, whereas traditional automation’s was 4–5 years, per World Bank data.
Predicted Job Losses vs. Job Creation Through AI Technologies
While 85 million jobs may be lost due to AI, 97 million new ones are projected to be created by 2025 , especially in AI development, cybersecurity, and analytics .
may be lost due to AI, are projected to be created by , especially in . In the US alone, 320,000 AI-related roles were created in 2024 , many with salaries exceeding $120,000 annually .
were created in , many with salaries exceeding . AI-driven sectors like health tech and edtech are expanding job opportunities at a rate of 26% YoY .
are expanding job opportunities at a . The cybersecurity market , propelled by AI integration, will create an estimated 3.5 million new jobs globally by 2025 .
, propelled by AI integration, will create an estimated globally by . However, re-skilling remains a bottleneck —only 36% of displaced workers globally have been able to shift into new AI-influenced roles.
—only globally have been able to shift into new AI-influenced roles. Companies like Amazon and IBM have invested over $1.2 billion collectively in reskilling programs, focusing on cloud and AI fluency.
have invested over in reskilling programs, focusing on cloud and AI fluency. The AI trainer and prompt engineering roles did not exist three years ago but are now among the fastest-growing tech occupations.
and roles did not exist three years ago but are now among the tech occupations. Digital content moderation , redefined with AI assistance, will support over 200,000 hybrid roles worldwide by the end of 2025.
, redefined with AI assistance, will support over worldwide by the end of 2025. While low-skill jobs are shrinking, AI-adjacent support roles (like model validators, ethics reviewers, and compliance monitors) are emerging.
(like model validators, ethics reviewers, and compliance monitors) are emerging. A PwC 2025 projection highlights that AI will drive 14% global GDP growth, creating more economic value than it displaces—if workforce policies keep up.
AI-Related Job Loss Experiences
79% of respondents said they have not lost a job or known someone who lost a job due to AI. This indicates the majority haven’t yet felt a personal impact.
said lost a job or known someone who lost a job due to AI. This indicates the majority haven’t yet felt a personal impact. 11% of people reported that they personally lost a job because of AI, showing a direct effect on a notable minority.
reported that because of AI, showing a direct effect on a notable minority. 10% said someone they know lost a job due to AI, suggesting indirect exposure to AI-related layoffs is also growing.
(Reference: Kickresume)
Economic Consequences of AI-Induced Unemployment
Global unemployment linked to AI-driven automation is expected to reach 7.8% in 2025, up from 6.3% in 2023.
in 2025, up from in 2023. In the US, economic output loss due to workforce reduction is estimated at $216 billion over the next 24 months.
due to workforce reduction is estimated at over the next 24 months. AI-related layoffs contribute to a 2.1% dip in consumer spending , especially in retail, transportation, and hospitality.
, especially in retail, transportation, and hospitality. Countries lagging in reskilling efforts face slower recovery; South Africa’s GDP growth could shrink by 0.8% annually due to underemployment.
could shrink by due to underemployment. Job polarization is widening—high-skill and low-skill roles are growing, but middle-income jobs are disappearing , according to the Brookings Institution.
is widening—high-skill and low-skill roles are growing, but , according to the Brookings Institution. Social safety net spending in the EU has increased by €18 billion between 2022 and 2024 in response to tech-driven unemployment.
between 2022 and 2024 in response to tech-driven unemployment. Mental health claims among displaced workers have risen by 22% in the US, with job loss due to automation being a key factor.
in the US, with job loss due to automation being a key factor. Gig economy dependency has surged—over 9.1 million Americans turned to freelance platforms in 2024 after AI-related layoffs.
has surged—over turned to freelance platforms in 2024 after AI-related layoffs. Real estate markets in industrial towns affected by automation have seen up to 11% depreciation in commercial value.
in commercial value. Companies automating large segments of staff without retraining investment are experiencing a brand trust by 23%, impacting long-term valuation.
Corporate Adoption Rates of AI and Related Workforce Reductions
As of Q1 2025 , 61% of Fortune 500 companies report implementing AI in at least one major operational department.
, report implementing AI in at least one major operational department. Microsoft, Amazon, and Google reduced a combined total of 49,000 roles since 2023, citing AI efficiency improvements.
Google reduced a combined total of since 2023, citing AI efficiency improvements. In the banking sector , 7 of the top 10 global banks have integrated AI tools for underwriting, leading to a 32% reduction in credit analyst positions .
, 7 of the top 10 global banks have integrated AI tools for underwriting, leading to . Retail giants like Walmart and Target automated back-end operations, resulting in over 28,000 jobs eliminated in logistics and inventory management.
automated back-end operations, resulting in over in logistics and inventory management. A Gartner report reveals that 45% of companies are restructuring their workforce in 2025 as a direct result of AI tool adoption.
reveals that are restructuring their workforce in 2025 as a direct result of AI tool adoption. In the telecommunications sector , AI has replaced 14% of network management roles , especially with predictive maintenance algorithms.
, AI has replaced , especially with predictive maintenance algorithms. IBM’s WatsonX platform alone contributed to 9,000 workforce reductions in departments reliant on manual analytics.
alone contributed to in departments reliant on manual analytics. HR departments across industries are streamlining talent acquisition with AI, reducing human recruiters by 38% since 2022.
across industries are streamlining talent acquisition with AI, reducing human recruiters by since 2022. Startups and SMEs are adopting AI at scale, with 38% reporting automation of at least one customer-facing role by early 2025.
are adopting AI at scale, with by early 2025. Companies investing in AI retraining initiatives are 25% less likely to experience long-term revenue dips from workforce transitions.
Public Opinion on AI’s Impact on the Job Market
47% of people believe AI will have a positive impact , creating more jobs than it destroys , showing optimism about future opportunities.
believe AI will have a , creating , showing optimism about future opportunities. 26% think AI will have a negative effect , as it may eliminate more jobs than it generates , highlighting growing concerns about displacement.
, as it may , highlighting growing concerns about displacement. Another 26% say it’s too soon to tell, reflecting uncertainty about how AI will ultimately reshape employment dynamics.
(Reference: CNBC Survey)
Government and Institutional Responses to AI-Driven Job Displacement
In 2025, the US Department of Labor allocated $1.3 billion for workforce reskilling focused on AI-displaced workers.
allocated for workforce reskilling focused on AI-displaced workers. The European Union passed the AI Liability Directive , holding companies accountable for algorithmic displacement without mitigation efforts.
passed the , holding companies accountable for algorithmic displacement without mitigation efforts. Singapore’s government introduced tax incentives for companies that retrain more than 10% of their staff in AI-related roles.
introduced tax incentives for companies that retrain more than in AI-related roles. Germany launched “AI UpSkill 2030” , pledging €4.5 billion to help transition manufacturing workers into tech-centric roles.
, pledging to help transition manufacturing workers into tech-centric roles. India’s NITI Aayog established AI education frameworks in over 800 universities and technical colleges to future-proof its young workforce.
established in over 800 universities and technical colleges to future-proof its young workforce. Canada developed a national AI registry to monitor corporate AI deployments and their effect on job markets.
developed a national AI registry to monitor corporate AI deployments and their effect on job markets. The International Labour Organization (ILO) called for a global summit on “Equitable AI Transitions,” scheduled for Q4 2025.
called for a global summit on “Equitable AI Transitions,” scheduled for Q4 2025. In the US, five states have introduced “AI severance bills” , requiring mandatory financial compensation for AI-induced layoffs.
, requiring mandatory financial compensation for AI-induced layoffs. Public-private partnerships in the Netherlands and Sweden have created over 120,000 new tech apprenticeship roles tied to AI disruption.
in the Netherlands and Sweden have created over tied to AI disruption. South Korea’s “Robot Tax”, introduced in 2024, aims to slow excessive automation and fund unemployment insurance programs.
Recent Developments in AI and Workforce Trends
OpenAI’s ChatGPT -5 , released in early 2025, is driving a new wave of automation in legal, marketing, and customer service sectors.
, released in early 2025, is driving a new wave of automation in sectors. Google DeepMind introduced Gemini Pro , which is now integrated into enterprise-level decision-making software across 4,000+ firms.
introduced , which is now integrated into across 4,000+ firms. AI-generated content now represents 12% of all published digital text , up from just 4% in 2023 , displacing content creation roles.
, up from just , displacing content creation roles. The use of robotic process automation (RPA) combined with generative AI has increased efficiency in banking operations by 28% , reducing staff needs.
combined with generative AI has increased efficiency in banking operations by , reducing staff needs. In Q1 2025, over 38% of US job applications were screened solely by AI systems without any human review.
were screened solely by AI systems without any human review. Amazon’s AI-powered warehouse management system now operates with 75% fewer human workers per fulfillment center compared to 2020.
now operates with per fulfillment center compared to 2020. AI-driven business forecasting tools are being used in 72% of Fortune 1000 companies , affecting roles in strategic planning and analysis.
are being used in , affecting roles in strategic planning and analysis. Startups focusing on AI for HR and hiring grew by 63% YoY , indicating an accelerating shift toward algorithmic workforce management.
grew by , indicating an accelerating shift toward algorithmic workforce management. Meta and Salesforce both adopted “AI-first” HR departments, replacing traditional employee engagement teams with data-led systems.
both adopted “AI-first” HR departments, replacing traditional employee engagement teams with data-led systems. In education, AI tutors and grading assistants are deployed in over 300 US school districts, reducing support staff needs.
Projected Job Displacement by Automation in 2030
China is expected to face the largest impact, with 47.8% of job displacement due to automation by 2030 .
is expected to face the largest impact, with of job displacement due to automation by . India follows with 24.3% of jobs potentially eliminated, reflecting significant automation growth in its labor market.
follows with of jobs potentially eliminated, reflecting significant automation growth in its labor market. The United States may see 14.8% of jobs displaced, showing notable vulnerability among advanced economies.
may see of jobs displaced, showing notable vulnerability among advanced economies. Japan could lose 6.1% of its jobs to automation, despite its already high-tech workforce.
could lose of its jobs to automation, despite its already high-tech workforce. Mexico is projected to experience 3.6% job displacement, while Germany is slightly lower at 3.4%, indicating more limited disruption in these regions.
(Reference: Edoxi)
Conclusion
Artificial intelligence has transitioned from a speculative disruptor to a fundamental force reshaping labor markets in 2025. From retail to legal, white-collar to blue-collar, few sectors remain untouched. While AI promises efficiency and cost savings, its real-time impact on employment is profound and widespread. Yet, the story isn’t purely one of loss—it’s also about transformation. New roles are emerging, and institutions are beginning to take bold steps toward upskilling and policy reform. The urgency now lies in strategic adaptation. For businesses, workers, and policymakers alike, the challenge is not just to survive AI disruption, but to evolve with it.
Sources
| 2025-04-30T00:00:00 |
2025/04/30
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https://sqmagazine.co.uk/ai-job-loss-statistics/
|
[
{
"date": "2025/06/18",
"position": 11,
"query": "job automation statistics"
}
] |
AI is changing cybersecurity roles, and entry-level jobs are ...
|
AI is changing cybersecurity roles, and entry-level jobs are at risk
|
https://www.helpnetsecurity.com
|
[
"Sinisa Markovic"
] |
Cybersecurity professionals who understand how to develop, tune, and leverage AI for threat detection, incident response automation, and data analysis will be ...
|
Will humans remain essential in cybersecurity, or is AI set to take over? According to Wipro, many CISOs are leveraging AI to improve threat detection and response times and to build enhanced incident response capabilities.
What’s changing
AI systems can now perform a variety of tasks that were once handled by entry-level analysts, such as drafting reports, generating alerts, and assembling presentations for management.
By taking over these repetitive jobs, AI gives human professionals more time to focus on complex problems and big-picture strategy.
But this shift goes deeper than just task automation. It’s changing how security teams operate. Security platforms, including Security Information and Event Management (SIEM), Endpoint Detection and Response (EDR), and Network Traffic Analysis (NTA), use machine learning to analyze massive volumes of data in real time. They detect suspicious behavior, identify new types of attacks, and in many cases trigger automated responses. This helps organizations scale their defenses without hiring additional staff.
That’s why the analyst role is changing too. Instead of reviewing every alert manually, analysts now supervise how AI systems operate. They’re responsible for checking the quality of AI decisions, fine-tuning rules, and leading coordinated responses. This kind of work demands technical skills, plus good judgment and the ability to think critically.
AI also helps teams transition from reactive defense to proactive threat anticipation through continuous monitoring and predictive analytics. However, trust in AI’s autonomous capabilities remains limited. Exabeam reports that only 29% of cybersecurity teams trust AI to act independently, with just 10% of analysts sharing that confidence. Even among executives, only 38% feel comfortable letting AI operate autonomously in cyber defense.
Cybersecurity professionals who understand how to develop, tune, and leverage AI for threat detection, incident response automation, and data analysis will be in high demand. If you’re not learning to work with AI, you risk falling behind.
AI’s blind spots
Putting too much trust in AI can have serious drawbacks. While AI excels at spotting patterns in vast datasets, it lacks true understanding of context and human judgment. If the data AI systems are trained on is incomplete or biased, their outputs will reflect those limitations.
One major concern is AI hallucinations, where the system produces false alerts by incorrectly identifying vulnerabilities or misreading threat intelligence. This leads to unnecessary alarms that waste time, or worse, allows real threats to slip through unnoticed.
There’s also the risk of false confidence. When teams rely heavily on automation, they might think everything’s under control. That kind of trust can create blind spots, letting small issues turn into big security problems if no one is watching closely.
“LLM agents with excessive agency can undermine the fundamental principles of organizational security. For instance, an LLM with excessive autonomy or functionality may execute an unauthorized action due to unclear, manipulated, or adversarial inputs, impacting an organization’s integrity,” said Etay Maor, Chief Security Strategist at Cato Networks.
The path forward
We are still far from a time when AI can operate entirely on its own, and that is a good thing. Its purpose is to support people and streamline tasks, not to replace them. While AI will inevitably automate certain jobs, it lacks the critical thinking and creativity that define human decision-making. That means relying solely on AI models for your security is playing with fire.
Aaron Roberts, Director at Perspective Intelligence, noted, “I do think the power of AI is in being able to cut through the noise and provide you with the things that are likely the most relevant, but you still need the confidence and verification of a human to really understand the full context and potential impact of a recommendation or suggestion.”
For now, AI isn’t replacing jobs entirely, but it is transforming how the workforce will operate in the future.
| 2025-06-18T00:00:00 |
2025/06/18
|
https://www.helpnetsecurity.com/2025/06/18/ai-humans-cybersecurity/
|
[
{
"date": "2025/06/18",
"position": 77,
"query": "job automation statistics"
}
] |
The Ethics of Job Displacement
|
The Ethics of Job Displacement
|
https://www.numberanalytics.com
|
[
"Sarah Lee"
] |
Q: What is job displacement? A: Job displacement refers to the loss of employment due to various factors, including automation and robotics.
|
Navigating the Moral Implications of Automation
The increasing use of robotics and automation in various industries has sparked a heated debate about the ethics of job displacement. As machines and artificial intelligence (AI) take over tasks previously performed by humans, many workers are facing the risk of losing their jobs. In this article, we will delve into the moral implications of job displacement due to robotics and automation, and explore potential solutions to mitigate its negative consequences.
Moral Implications of Job Displacement
The moral implications of job displacement are multifaceted and far-reaching. At the heart of the issue is the responsibility of companies and governments to protect workers who are displaced by automation.
Responsibility of Companies and Governments
Companies and governments have a moral obligation to ensure that workers are not left behind as automation transforms the workforce. This includes providing support for workers who lose their jobs, as well as investing in education and retraining programs to help them adapt to new technologies.
"The impact of automation on work is not just an economic issue, but also a moral one. It requires a comprehensive response that addresses the needs of workers, businesses, and society as a whole." - 1
Equitable Distribution of Benefits and Costs
Another key moral implication of job displacement is the need for an equitable distribution of the benefits and costs of automation. While automation can bring significant productivity gains and economic benefits, it is essential that these benefits are shared fairly among stakeholders, including workers who may be displaced.
The following graph illustrates the potential benefits and costs of automation:
graph LR; A["Automation"] --> B["Productivity Gains"]; A --> C["Job Displacement"]; A --> D["Economic Benefits"]; B --> E["Increased Efficiency"]; C --> F["Negative Impact on Workers"]; D --> G["Increased Economic Growth"];
As the graph shows, automation can have both positive and negative consequences. To mitigate the negative impacts, it is essential to implement policies that promote a fair distribution of benefits and costs.
Potential for New Forms of Work and Entrepreneurship
While automation may displace some jobs, it also has the potential to create new forms of work and entrepreneurship. For example, the rise of the gig economy and platform capitalism has created new opportunities for workers to engage in freelance or entrepreneurial work.
The following table highlights some of the potential new forms of work and entrepreneurship that may emerge as a result of automation:
New Form of Work/Entrepreneurship Description Data Analyst/Scientist Work with data to identify trends and insights AI Trainer/Modeler Train and develop AI models Robotics Engineer Design and develop robotics systems Virtual Assistant Provide virtual support services Online Course Creator Create and sell online courses
Solutions to Job Displacement
To mitigate the negative consequences of job displacement, several solutions have been proposed. These include:
Universal Basic Income and Social Safety Nets
One potential solution is the implementation of a universal basic income (UBI) or social safety nets to support workers who lose their jobs due to automation. UBI involves providing a guaranteed minimum income to all citizens, regardless of their employment status.
The idea of UBI has gained significant attention in recent years, with several countries and cities experimenting with pilot programs. For example, Finland implemented a two-year UBI experiment from 2017 to 2019, which provided 2,000 unemployed individuals with a monthly stipend of €560 2.
Job Retraining Programs and Education Initiatives
Another solution is to invest in job retraining programs and education initiatives that help workers develop new skills and adapt to changing job market demands. This can include programs that focus on emerging technologies such as AI, data science, and cybersecurity.
For example, the city of Singapore has implemented a range of initiatives to support workers in developing new skills, including a Professional Conversion Programme that provides training and financial support for workers looking to switch careers 3.
Policies to Promote New Job Creation and Entrepreneurship
Finally, governments and companies can implement policies to promote new job creation and entrepreneurship. This can include initiatives such as tax breaks for startups, funding for entrepreneurship programs, and investments in infrastructure to support new businesses.
Future of Work and Ethics
As automation and robotics continue to transform the workforce, it is essential to consider the future of work and the ethics surrounding it. Emerging trends and technologies will likely have a significant impact on the job market, and it is crucial to be prepared.
Emerging Trends and Technologies
Some of the emerging trends and technologies that are likely to shape the future of work include:
Increased use of AI and machine learning in various industries
Growing demand for data scientists and analysts
Rise of the gig economy and platform capitalism
Increased focus on lifelong learning and upskilling
The following mind map illustrates some of the key trends and technologies that are likely to shape the future of work:
mindmap root((Future of Work)) (Emerging Trends) (AI and Machine Learning) (Gig Economy) (Lifelong Learning) (New Technologies) (Robotics) (Blockchain) (Virtual Reality)
Potential for New Forms of Work and Entrepreneurship to Emerge
As automation and robotics continue to evolve, it is likely that new forms of work and entrepreneurship will emerge. For example, the rise of virtual and augmented reality technologies may create new opportunities for workers in fields such as education, entertainment, and healthcare.
Need for Ongoing Dialogue and Debate
Finally, it is essential to recognize that the ethics of job displacement is an ongoing issue that requires continued dialogue and debate. As new technologies emerge and the job market evolves, it is crucial to have a nuanced and informed discussion about the implications of these changes and how to mitigate their negative consequences.
Mathematical Representation of Job Displacement
Let's consider a simple mathematical model to understand the impact of job displacement due to automation. Assume that the number of jobs displaced by automation is represented by the variable $x$, and the number of new jobs created is represented by the variable $y$. The net change in employment can be represented by the equation:
\[\Delta E = y - x\]
where $\Delta E$ represents the net change in employment.
If $\Delta E > 0$, then the number of new jobs created is greater than the number of jobs displaced, resulting in a net gain in employment. Conversely, if $\Delta E < 0$, then the number of jobs displaced is greater than the number of new jobs created, resulting in a net loss in employment.
Conclusion
The ethics of job displacement due to robotics and automation is a complex and multifaceted issue. While automation has the potential to bring significant productivity gains and economic benefits, it also poses significant risks to workers who may be displaced. To mitigate these risks, it is essential to implement policies that promote a fair distribution of benefits and costs, invest in education and retraining programs, and support new job creation and entrepreneurship.
References
World Economic Forum. (2020). The Future of Jobs Report 2020. Retrieved from https://www.weforum.org/agenda/2020/01/future-of-work-report-2020/ Kela. (2019). Finnish Universal Basic Income Experiment Concludes. Retrieved from https://www.kela.fi/web/en/news-archive/-/asset_publisher/lVR8GY2nIr5W/content/finnish-universal-basic-income-experiment-concludes SSG-WSG. (n.d.). Professional Conversion Programmes. Retrieved from https://www.ssg-wsg.gov.sg/programmes/professional-conversion-programmes.html
FAQ
Q: What is job displacement?
A: Job displacement refers to the loss of employment due to various factors, including automation and robotics.
Q: What are the moral implications of job displacement?
A: The moral implications of job displacement include the responsibility of companies and governments to protect workers, the need for an equitable distribution of benefits and costs, and the potential for new forms of work and entrepreneurship.
Q: What are some potential solutions to job displacement?
A: Potential solutions to job displacement include universal basic income and social safety nets, job retraining programs and education initiatives, and policies to promote new job creation and entrepreneurship.
Q: What is the future of work?
A: The future of work is likely to be shaped by emerging trends and technologies such as AI, machine learning, and the gig economy. It is essential to be prepared for these changes and to have ongoing dialogue and debate about the ethics surrounding them.
| 2025-06-18T00:00:00 |
https://www.numberanalytics.com/blog/ethics-of-job-displacement
|
[
{
"date": "2025/06/18",
"position": 10,
"query": "robotics job displacement"
}
] |
|
Beyond adoption: Strategic AI leadership from campus to ...
|
Beyond adoption: Strategic AI leadership from campus to corporate
|
https://www.chieflearningofficer.com
|
[] |
This article outlines how our approach to AI can serve as a model for HR executives, academic administrators and corporate learning and development ...
|
As artificial intelligence continues to redefine the workplace, leaders are being called to do more than adopt new tools—they’re being asked to lead with vision, ethics and agility. At Angelo State University, we’ve embraced this challenge by embedding AI into our institutional strategy—not just as a technology, but as a leadership imperative.
This article outlines how our approach to AI can serve as a model for HR executives, academic administrators and corporate learning and development professionals navigating the intersection of innovation, workforce development, and organizational values.
Why AI, why now?
AI is no longer a future consideration—it’s a present-day force reshaping how we work, learn and lead. Research by Zawacki-Richter et al. demonstrates that AI applications in higher education have grown exponentially, with institutions leveraging these tools for everything from streamlining operations to personalizing L&D opportunities.
At Angelo State, we view AI as a strategic enabler—a capability that accelerates progress toward our mission of academic excellence and student success. The principles guiding our implementation—governance, ethics, operationalization and stakeholder engagement—are relevant to any organization seeking to lead responsibly in a digital age.
A strategic vision rooted in values
Our AI strategy is not about chasing trends, it is about aligning innovation with purpose. We’ve integrated AI into our digital learning strategy to enhance teaching, support faculty and improve student outcomes. More broadly, we see AI as a tool to advance institutional goals: agility and efficiency.
For talent leaders, this means thinking beyond automation. As Wilson and Daugherty note in their research on collaborative intelligence, the most successful AI implementations focus on augmenting human capabilities rather than replacing them. It means asking: How can AI help us build more responsive, resilient organizations? At Angelo State, the answer lies in using AI to support—not replace—human potential.
Governance as a leadership lever
Responsible AI use begins with governance. Drawing from Floridi et al.’s ethical framework for AI society, we’ve established a comprehensive framework that emphasizes transparency, accountability and alignment with our university’s core values. This includes:
Stakeholder engagement: We engage faculty, staff and students early and often through town halls, focus groups and pilot programs. Our experience shows that early engagement reduces resistance and increases adoption rates.
We engage faculty, staff and students early and often through town halls, focus groups and pilot programs. Our experience shows that early engagement reduces resistance and increases adoption rates. Digital fluency development: We’ve launched micro-learning for faculty and staff, building the digital literacy essential for responsible AI use.
We’ve launched micro-learning for faculty and staff, building the digital literacy essential for responsible AI use. Cross-functional oversight: Our AI Governance Committee includes representatives from HR, information technology, academic affairs, student services and legal affairs, ensuring shared accountability across institutional adaptation.
These practices are not unique to higher education. They are essential for any organization seeking to build trust, mitigate risk, and scale AI responsibly, as emphasized by Jobin et al.’s review of global AI ethics guidelines. Their research found global convergence emerging around five ethical principles: transparency, justice and fairness, non-maleficence, responsibility and privacy.
From governance to action: Operationalizing AI with a firm ethical foundation in place, the next challenge was bringing AI from principle to practice. At Angelo State, we’re using AI to deliver adaptive learning experiences. Our AI-powered learning management system personalizes content delivery for students and uses data to understand their learning journey.
These applications are directly transferable to corporate talent strategies. Whether you’re building a leadership pipeline or reskilling your workforce, AI can help you move from reactive to proactive talent development, as demonstrated by Davenport and Ronanki’s research on AI in business, where they suggest an incremental rather than a transformative approach to developing and implementing AI. AI can support three important business needs: automating business processes, gaining insight through data analysis, and engaging with customers and employees.
Overcoming barriers to change, our journey hasn’t been without challenges. Like many organizations, we initially faced resistance from faculty concerned about job security and the impersonal nature of AI. Drawing on Kotter’s change management principles, we addressed these challenges through:
Transparent communication: We hold town hall sessions to address misconceptions and share early success stories.
We hold town hall sessions to address misconceptions and share early success stories. Incremental implementation: We started with pilot programs that demonstrated value before scaling.
We started with pilot programs that demonstrated value before scaling. Continuous support: We designated AI champions in each department and provided ongoing technical support.
Modeling the future of responsible AI implementation requires an evolution of our leadership. At Angelo State, we are guided by three core principles:
Agility: We adapt quickly to emerging tools and needs, maintaining a review process for new AI opportunities and threats.
We adapt quickly to emerging tools and needs, maintaining a review process for new AI opportunities and threats. Accountability: We ensure transparency through regular reporting and maintain shared responsibility through cross-functional governance.
We ensure transparency through regular reporting and maintain shared responsibility through cross-functional governance. Alignment: We embed our values into every AI initiative, using ethical decision-making frameworks that prioritize human dignity and our educational mission.
This approach has positioned us not just as adopters of AI, but as stewards of its responsible use. And it’s a model that talent officers across industries can apply by leading with intention and building with trust.
Looking ahead: Preparing for AI’s evolution
Several emerging trends will shape how organizations approach AI implementation:
Generative AI integration: The rise of large language models demands new governance frameworks and ethical considerations.
The rise of large language models demands new governance frameworks and ethical considerations. AI literacy as core competency: Digital fluency is becoming as essential as traditional literacy in professional development.
Digital fluency is becoming as essential as traditional literacy in professional development. Regulatory compliance: Evolving AI regulations will require adaptive, compliant governance structures.
Evolving AI regulations will require adaptive, compliant governance structures. Ethical use in assessment: Institutions must rethink how AI tools affect academic integrity, testing, and grading practices.
Organizations beginning their AI journey should ask:
What governance structures do we need to ensure responsible AI use?
How will we measure AI’s impact on our people and mission?
What skills do our teams need to work effectively with AI?
How will we maintain our organizational values as we scale AI implementation?
Final thoughts
AI is not just a tool—it’s a test of leadership. At Angelo State University, we’ve chosen to meet that test with strategy, ethics and a deep commitment to people. Our experience shows that responsible AI implementation requires more than technical expertise; it demands thoughtful governance, stakeholder engagement and a commitment to continuous learning.
For L&D and talent leaders, the opportunity is clear: to shape the future of work not just with technology, but with purpose. The organizations that will thrive in the AI era are those that view AI not as a replacement for human judgment, but as an amplifier of human potential.
| 2025-06-18T00:00:00 |
2025/06/18
|
https://www.chieflearningofficer.com/2025/06/18/beyond-adoption-strategic-ai-leadership-from-campus-to-corporate/
|
[
{
"date": "2025/06/18",
"position": 22,
"query": "workplace AI adoption"
}
] |
How can organisation culture hold back AI adoption?
|
How can organisation culture hold back AI adoption?
|
https://www.georgejamesconsulting.com
|
[] |
This starts with diagnosing the existing workplace culture. Before rolling out new systems, leaders should assess whether their organisation is culturally ready ...
|
Preparing your culture for the AI revolution: a call to action for leaders
Artificial intelligence (AI) is fast becoming a defining feature of modern organisations. It’s not just a new tool—it’s a new way of working, deciding, and thinking. As digital transformation accelerates across sectors, the push to integrate AI into core business processes has become urgent. But while most organisations have focused heavily on technical readiness—building data infrastructure, training teams in AI tools, and investing in new platforms—they’ve often overlooked the cultural side of the equation.
...without a shift in mindset and workplace culture, even the best AI technologies risk being underused or misapplied.
Culture is the hidden architecture that determines how technology is received and used. If the culture is resistant, AI will fail to deliver its full potential. If the culture is adaptive and people-centred, AI can drive productivity, innovation, and resilience across the business. This article explores the cultural transformation needed for AI success and sets out a roadmap for action—one that calls on leaders to think beyond code and into the human heart of the organisation.
The human-centred case for AI readiness
AI adoption is not just a technical challenge—it’s a deeply human one. Many employees are experiencing strain as AI tools disrupt familiar processes and roles. This discomfort is often less about the technology itself and more about uncertainty: What does this change mean for me? Will I be replaced? How do I fit into this new world?
To address these concerns, organisations must adopt a human-centred approach that puts people at the core of AI transformation. This starts with diagnosing the existing workplace culture. Before rolling out new systems, leaders should assess whether their organisation is culturally ready for AI. Are teams open to change? Is innovation rewarded? Is there trust in leadership?
Both quantitative and qualitative methods—such as staff surveys, interviews, and behavioural data—can provide valuable insight.
Next, AI investments must align with the organisation’s purpose. AI should enhance the things the business already does well—whether it’s customer service, innovation, or operational efficiency—not distract from them. Purpose-led deployment builds clarity and buy-in, making it easier to align departments and secure long-term support.
The challenge of cultural inertia
Despite enthusiasm at the top, many AI initiatives stall at the implementation stage. One major reason is cultural inertia. Employees are often not equipped—mentally, emotionally, or practically—for the scale of change AI brings. New systems shift decision-making authority, reshape roles, and introduce unfamiliar workflows. Without a clear cultural plan, these changes can create confusion or pushback.
Resistance to change is natural. People may fear redundancy, question the motives behind AI deployment, or feel overwhelmed by technical jargon. Others may be eager to explore AI’s potential but lack the confidence or training to do so. To move forward, organisations need a culture that encourages exploration, tolerates experimentation, and values learning.
This is where leadership is crucial. Leaders set the tone for cultural transformation. They must not only explain what is happening but also why it matters. A well-crafted AI narrative—one that speaks to both hearts and minds—is essential. It should clarify what will change, what will remain, and how employees will be supported along the way.
Practical steps for cultural readiness
Building a culture that supports AI adoption requires intentional effort. Below are four practical steps organisations can take:
Start small but strategic. Launching AI through small, high-impact initiatives helps build momentum without overwhelming the system. These early wins demonstrate the value of AI and help teams build trust in new tools. For instance, automating repetitive admin tasks can free up time for more creative or strategic work—making AI feel like a partner, not a threat.
Create a compelling AI story. People are more likely to support a change when they understand its purpose. Leaders should develop a clear, engaging narrative for AI implementation—one that addresses practical concerns and connects emotionally with teams. When employees feel their leaders have a solid plan, they are more likely to feel ready and comfortable using AI in their roles.
Promote cross-team collaboration. AI is rarely confined to one department. It often intersects across functions—customer service, marketing, HR, operations. Encouraging collaboration between these areas helps prevent silos, spread good practice, and generate new ideas for using AI effectively. Cross-functional teams also surface potential risks early and build more inclusive, realistic solutions.
Support sustained adoption. It’s not enough to train staff once and move on. Cultural change takes time. Leaders must consistently reinforce the right behaviours, celebrate success stories, and address obstacles as they arise. Regular check-ins, feedback loops, and accessible learning opportunities are key to keeping the momentum alive.
Overcoming fear with skill, language and purpose
One major gap in many AI strategies is the lack of a shared language. While there’s been a strong focus on upskilling—teaching people how to use AI tools—there’s been less attention on helping teams develop a common way of talking about AI. Without this shared understanding, miscommunication and anxiety can grow.
Organisations should invest in building AI literacy that is both technical and cultural. That means not just teaching how algorithms work, but also discussing what AI means for individual roles, team dynamics, and organisational values. Forums where staff can question, reflect, and co-create new ways of working are critical. This dialogue helps turn uncertainty into ownership.
In addition, change champions—staff who embrace AI and support others—can act as cultural bridge-builders. By modelling positive behaviour and offering peer support, they help normalise AI use and reduce fear. These internal advocates are especially useful in large or geographically dispersed organisations where change must ripple across different teams and levels.
Embedding AI into the fabric of the business
AI works best when it’s embedded into day-to-day operations, not treated as a separate project. Instead of building isolated AI teams, organisations should weave AI into their core strategies and leadership structures. For example, if customer experience is a priority, AI should be used to personalise service or respond faster to queries. If innovation is the goal, AI should help analyse trends or streamline product development.
This integrated approach ensures AI stays aligned with business goals and avoids becoming a siloed or short-lived initiative. It also encourages continuous improvement. As more departments adopt AI and build confidence, the organisation becomes more agile—ready not just for this wave of change, but for the next.
Conclusion - make culture your competitive edge
AI is no longer on the horizon—it’s here. But whether it becomes a source of friction or a driver of value depends less on the tools themselves and more on the people who use them. Culture is the missing link in many AI strategies, yet it is also the most powerful lever for success.
Leaders must step up—not just as technical sponsors of AI, but as cultural architects. They must foster environments where curiosity, learning, and trust flourish. They must be honest about the challenges, but bold in their vision. And most importantly, they must create space for employees to not just accept AI, but shape its role in the organisation’s future.
By diagnosing cultural readiness, aligning AI with purpose, communicating with clarity, and sustaining the change, organisations can build a workplace where AI thrives—and where people do too. The AI revolution is here. It’s time to make sure your culture is ready.
See more here: https://www.georgejamesconsulting.com/
| 2025-06-18T00:00:00 |
2025/06/18
|
https://www.georgejamesconsulting.com/post/how-can-organisation-culture-hold-back-ai-adoption
|
[
{
"date": "2025/06/18",
"position": 63,
"query": "workplace AI adoption"
}
] |
AI PCs - Building the Business Case for Adoption
|
Modernize the Workplace: AI PCs - Building the Business Case for Adoption
|
https://www.brighttalk.com
|
[] |
Modernize the Workplace: AI PCs - Building the Business Case for Adoption. Jun 18 2025. 14 mins. Register for free. Logo. Presented by. Louise Quennell (Dell ...
|
Why Attend? In the time it takes to drink a coffee, discover how to build a solid business case for the adoption of AI PCs. Join Louise Quennell (Dell Technologies), Matt Hains (Intel), and Bryan Sutton (Microsoft) for this exclusive microlearning session. Key Takeaways: - The fundamental steps to build a strong business case for AI PC - Choosing the right PC platform and Copilot version for you - Addressing critical challenges: security, scalability, and workforce - Reference customer use - Insights on ensuring a smooth transition to AI-enhanced computing
| 2025-06-18T00:00:00 |
https://www.brighttalk.com/webcast/10739/645614?utm_source=brighttalk-portal&utm_medium=web&utm_campaign=channel-feed&player-preauth=YhcVxdw%2FC%2BAShailFBcockOpP9SmDs66a%2Fw%2B3bamHPE%3D
|
[
{
"date": "2025/06/18",
"position": 81,
"query": "workplace AI adoption"
}
] |
|
Mark Zuckerberg is spending megabucks on an AI hiring spree
|
Mark Zuckerberg is spending megabucks on an AI hiring spree
|
https://www.economist.com
|
[] |
When Mark Zuckerberg decided to launch his quest for the metaverse in 2021, he threw fistfuls of cash at the effort.
|
W hen Mark Zuckerberg decided to launch his quest for the metaverse in 2021, he threw fistfuls of cash at the effort. Meta’s boss is now repeating the act, this time with generative artificial intelligence ( AI ). Hot on the heels of what may be the world’s most expensive acquihire—a $14.3bn deal to buy 49% of Scale AI , a data-labelling firm whose main asset is Alexandr Wang, its 28-year-old founder—people close to the matter say Mr Zuckerberg is planning to offer more than $1bn combined for two of Silicon Valley’s hottest AI brain boxes, who would work under Mr Wang. It marks the start of a reset of Meta’s generative- AI ambitions.
| 2025-06-19T00:00:00 |
2025/06/19
|
https://www.economist.com/business/2025/06/19/mark-zuckerberg-is-spending-megabucks-on-an-ai-hiring-spree
|
[
{
"date": "2025/06/19",
"position": 96,
"query": "AI hiring"
},
{
"date": "2025/06/19",
"position": 42,
"query": "AI hiring"
},
{
"date": "2025/06/19",
"position": 39,
"query": "AI hiring"
}
] |
Top 15 Artificial Intelligence (AI) Companies (2025) - Analytics Vidhya
|
Top 15 Artificial Intelligence (AI) Companies (2025)
|
https://www.analyticsvidhya.com
|
[
"Nitika Sharma"
] |
Top 15 Artificial Intelligence (AI) Companies (2025) · 1. Apple · 2. Microsoft · 3. NVIDIA · 4. Google · 5. Meta Platforms · 6. Tesla · 7.
|
Top 15 Artificial Intelligence (AI) Companies (2025)
AI is evolving at breakneck speed, and in 2025, everyone from venture capitalists to curious techies is eager to spot the companies leading the charge. Heavyweights like Nvidia, OpenAI and Microsoft have become household names by rolling out groundbreaking models and AI‑driven solutions that tackle everything from real‑time language translation to autonomous vehicles. With innovation ramping up daily, the race to build smarter, faster, and more reliable tools has never been more thrilling. In this article, we’ll shine a spotlight on the standout players who are not just keeping pace but actually defining the future of artificial intelligence.
1. Apple
CEO : Tim Cook
: Tim Cook Market Cap: ~$2.9 trillion
Apple’s AI approach is focused on privacy-preserving, on-device intelligence. With the M3 chips, Apple Neural Engine (ANE) delivers up to 18 TOPS for tasks like face recognition, natural language processing, and real-time AR filters. Apple’s generative features, like smart reply, AI editing in Photos, and predictive text across iOS, have expanded dramatically. The Vision Pro platform integrates spatial AI with real-time sensor fusion for immersive computing.
2. Microsoft
CEO : Satya Nadella
: Satya Nadella Market Cap: ~$2.73 trillion
Microsoft’s leadership in enterprise AI is anchored in its strategic partnership with OpenAI. GitHub Copilot and Microsoft 365 Copilot are already reshaping developer and productivity workflows. Azure OpenAI Service brings fine-tuned GPT-4 and Codex APIs into enterprise-grade environments. Microsoft’s investment in AI safety and its Responsible AI Standard framework sets it apart in deploying models responsibly at scale.
3. NVIDIA
CEO : Jensen Huang
: Jensen Huang Market Cap: ~$2.4 trillion
NVIDIA is the undisputed king of AI hardware. Its H100 and newly announced B100 GPUs are the backbone of most large-scale generative models, from OpenAI to Anthropic. Beyond hardware, NVIDIA’s CUDA, cuDNN, and TensorRT frameworks accelerate model development and deployment. In 2025, its AI Enterprise software suite is making inroads in enterprise data science, while DGX Cloud provides fully-managed infrastructure-as-a-service for model training.
4. Google
CEO : Sundar Pichai
: Sundar Pichai Market Cap: ~$1.85 trillion
Google’s AI is everywhere! It includes Gemini (the successor to Bard), DeepMind’s AlphaGeometry and AlphaTensor breakthroughs, and TPUv5 accelerators optimized for transformer architectures. Vertex AI on Google Cloud offers end-to-end MLOps tooling. Google Search, Ads, Maps, and YouTube all embed AI in recommendation, content moderation, and personalization. Their 2025 launch of Gemini Ultra focuses on high-context reasoning in enterprise settings.
5. Meta Platforms
CEO : Mark Zuckerberg
: Mark Zuckerberg Market Cap: ~$1.8 trillion
Meta’s LLaMA 3 models, with up to 140B parameters, are open-sourced for researchers and fine-tuners. These models power chatbots across Facebook, Instagram, and WhatsApp, and are also used in the Meta Ray-Ban smart glasses. AI also plays a role in real-time content moderation, AR filters, and the Horizon metaverse platform. Meta’s infrastructure (FAIR-scale) now rivals the cloud providers in model training throughput.
6. Tesla
CEO : Elon Musk
: Elon Musk Market Cap: ~$907 billion
Tesla’s Dojo supercomputer, called “built in-house,” is now live, training massive self-driving neural nets using thousands of video clips from its fleet. Its FSD Beta v12 update uses an end-to-end neural policy that replaces traditional rule-based systems with fully learned perception, planning, and control. Tesla also applies AI in manufacturing optimization, robotics (Tesla Bot), and energy forecasting for its battery systems.
7. Oracle
CEO : Safra Catz
: Safra Catz Market Cap: ~$361 billion
Oracle is reinventing its cloud through AI-first features. The Oracle Autonomous Database auto-tunes queries, scales elastically, and applies anomaly detection using AI models trained on telemetry data. OCI now offers AI Vector Search and pre-trained models for NLP and time-series forecasting. Oracle also integrates AI into Fusion apps for finance and HR automation.
8. OpenAI
CEO : Sam Altman
: Sam Altman Market Cap: ~340 Billion
OpenAI has developed groundbreaking AI models like ChatGPT, DALL·E, and Sora, which have significantly influenced the AI landscape. OpenAI’s strategic partnerships, including a notable collaboration with Microsoft, have bolstered its capabilities and market reach. The company is also exploring new ventures, such as developing a social media platform to enhance data acquisition for AI training.
9. Palantir Technologies
CEO : Alex Karp
: Alex Karp Market Cap: ~$220 billion
Palantir’s Foundry and Gotham platforms are deeply rooted in AI-driven analytics. From predictive maintenance in manufacturing to risk detection in defense, Palantir enables complex model deployment with minimal code. Their new AIP (Artificial Intelligence Platform) lets enterprises deploy LLMs on secure, siloed data. Government contracts, especially in the defense and intelligence sector, continue to grow.
10. IBM
CEO : Arvind Krishna
: Arvind Krishna Market Cap: ~$194 billion
IBM focuses on hybrid cloud and trustworthy AI. Watsonx, its flagship AI suite, includes a data foundation model layer, a governance layer for model compliance, and accelerators for regulated industries. IBM also provides on-premise AI stacks with Power10 chips and built-in matrix accelerators, targeting sectors like healthcare, insurance, and telecom with domain-specific model fine-tuning.
11. Adobe
CEO : Shantanu Narayen
: Shantanu Narayen Market Cap: ~$149 billion
Adobe’s Firefly, integrated into Creative Cloud, allows users to generate images, vectors, and even videos from text prompts. Their AI stack now includes real-time background removal, smart object selection, and auto-animation features. Adobe Sensei also powers content intelligence for digital marketers, such as automated tag generation, performance prediction, and content personalization.
12. xAI
CEO: Elon Musk
Elon Musk Valuation: ~$75 billion
xAI is best known for developing the Grok chatbot, which offers features like web search integration, PDF uploads, image understanding, and conversation summarization. xAI has attracted significant investment, raising $12 billion in funding, including a notable $6 billion round in December 2024. The company is also expanding its infrastructure with the development of Colossus, a supercomputer located in Memphis, Tennessee, designed to support large-scale AI computations.
Learn more about Grok chatbot in this free course.
13. Anthropic
CEO: Dario Amodei
Dario Amodei Valuation: ~$61.5 billion
Anthropic, co-founded by former OpenAI researchers, including CEO Dario Amodei, has rapidly positioned itself as a leader in AI safety and alignment. The company is renowned for its Claude series of AI models, which emphasize Constitutional AI principles to ensure outputs are helpful, honest, and harmless. With significant investments from tech giants like Amazon and Google, Anthropic continues to advance its research and expand its AI capabilities.
14. Perplexity AI
CEO: Aravind Srinivas
Aravind Srinivas Valuation: ~$19 billion
Perplexity AI has rapidly emerged as a significant player in AI-powered search. The company offers a conversational search engine that provides direct answers with source citations, blending the functionalities of traditional search engines and AI chatbots. With backing from notable investors like Jeff Bezos and Nvidia, Perplexity has expanded its services across web browsers, mobile apps, and Android devices.
15. CoreWeave
CEO : Michael Intrator
: Michael Intrator Market Cap: ~$18 billion
CoreWeave has emerged as a dominant force in AI infrastructure. They offer massive clusters of NVIDIA H100 and A100 GPUs tailored for training and inference. With a container-first architecture and full Kubernetes integration, CoreWeave is a go-to provider for LLM labs and AI startups alike. Their flexible GPU rentals now rival AWS in raw AI compute availability.
Key Takeaways
Conclusion
In 2025, the global AI landscape is dominated by tech colossi like Microsoft, NVIDIA, and Google, each leading in their respective domains, be it software, hardware, or research. Their substantial market capitalizations reflect the immense value and confidence investors place in AI-driven innovations. As AI continues to permeate various industries, from healthcare to finance, these companies are not only shaping the future of technology but also offering promising opportunities for investors worldwide.
Frequently Asked Questions
Q1. What are the most innovative AI startups of 2025? Character.AI, Mistral AI, and Inflection AI lead innovation in chat, model efficiency, and personal assistants. Q2. Which is the best AI company? OpenAI is top for generative AI, while NVIDIA dominates AI infrastructure with unmatched GPU leadership. Q3. Which is the top AI company? ChatGPT leads in user numbers, while Microsoft’s enterprise Copilot tools drive business adoption. Q4. What is the biggest AI company? NVIDIA is the largest by market cap, followed by Microsoft and Alphabet’s DeepMind. Q5. What is the fastest-growing AI company? OpenAI and Anthropic have seen the sharpest valuation jumps, with Safe Superintelligence rising quickly too.
| 2023-05-30T00:00:00 |
2023/05/30
|
https://www.analyticsvidhya.com/blog/2023/05/top-ai-companies/
|
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AI pioneer warns of mass job losses | Digital Watch Observatory
|
AI pioneer warns of mass job losses
|
https://dig.watch
|
[] |
Plumbing may be safer from AI disruption than office work, says Hinton. Geoffrey Hinton warns AI could replace most white-collar jobs in the ...
|
19 Jun 2025
AI pioneer warns of mass job losses
Geoffrey Hinton, often called the godfather of AI, has warned that the technology could soon trigger mass unemployment, particularly in white-collar roles. In a recent podcast interview, he said AI will eventually replace most forms of intellectual labour.
According to Hinton, jobs requiring basic reasoning or clerical tasks will be the first to go, with AI performing the work of multiple people. He expressed concern that call centre workers may already be vulnerable, while roles requiring physical skills, like plumbing, remain safer for now.
Hinton challenged the common belief that AI will create more jobs than it eliminates. He argued that unless someone has highly specialised expertise, they may find themselves outpaced by machines capable of learning and performing cognitive tasks.
He also criticised OpenAI’s recent corporate restructuring, saying the shift towards a profit-driven model risks sidelining the public interest. Hinton, alongside other critics including Elon Musk, warned that the changes could divert AI development from its original mission of serving humanity.
Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!
| 2025-06-19T00:00:00 |
2025/06/19
|
https://dig.watch/updates/ai-pioneer-warns-of-mass-job-losses
|
[
{
"date": "2025/06/19",
"position": 61,
"query": "AI job losses"
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Artificial Intelligence vs Cyber Security: Which Career is Better?
|
Artificial Intelligence vs Cyber Security: Which Career Is Better?
|
https://www.igmguru.com
|
[] |
3. AI vs Cyber Security- Job Trends and Salaries ; Cloud Consultant, INR 1.98 M · $110,039 ; Risk Manager, -, $93,217 ; Identity Manager, INR ...
|
Since both artificial intelligence and cybersecurity are growing fields, it comes as a dilemma as to which one to choose as a career. In this blog, we are going to give you artificial intelligence vs cyber security, covering which career is better. So, without any further ado, let's begin.
More companies are using artificial intelligence (AI) today than ever. In fact, between 2017 and 2022, its usage has practically doubled. This alone is sufficient to let us know about the imperativeness of adopting this technology, and moreover, understanding it.
The need to understand AI arises from the fact that not everyone intends to use a technology with the right intentions. Hence, the rise of cyberthreats and the need for cyber security. As important as it is to use artificial intelligence to grow, it is equally important to implement cyber security in the right way.
We can't deny the importance of artificial intelligence and machine learning in cyber security, as they play a crucial role in identifying and mitigating threats faster and more accurately than traditional methods. AI and ML algorithms can analyze vast amounts of data in real-time, detect patterns, and flag anomalies that may indicate potential cyberattacks.
The Rise of Artificial Intelligence
Since we have already mentioned how rapidly artificial intelligence has grown the last five years, there hardly is any need left to further add to that point. Having said that, its growth is not going to stop anytime soon either. In fact, if anything, it is transforming even as you read this blog.
Machine learning has stemmed out to be a key part of artificial intelligence. It basically entails standalone learning and improving of the AI systems, without being explicitly programmed for every little thing. Hence, more human-like outcomes and abilities to perform tasks.
This technology has led to a huge impact on the healthcare industry. There is hardly any area of this sector that is left untouched by the excellence that is AI.
However, every coin has two sides and so does this one. The rise of artificial intelligence has also raised some significant ethical questions. As bots become more human-like, they have become a greater threat to human jobs. Hence, more humans are under the attack of potentially losing their jobs, causing economic and social disruption.
AI was developed with the purpose of helping humans, some humans are using it to fraud other humans. Hence, along with privacy concerns, AI has increased the chances of cyberthreats and cyber frauds, raising the need for serious privacy considerations. This is where we move to the next phase.
Explore igmGuru's Machine Learning Certification Course to learn Machine Learning with experts.
The Imperative Role of Cyber Security
"Cyber security is no longer a choice".
Every organization is hands and legs deep in artificial intelligence, raising the need to have cybersecurity implemented too. Since businesses mostly rely on digital platforms for conducting business, they also find themselves amid a sea of threats and risks.
Every business holds a lot of sensitive data, related to both their clients and themselves. Having this information out on the internet can lead to increased threats. Thus, the need to have proper cyber security measures in place is essential.
It is imperative for every organization to have a multi-faceted security approach in place, to help them best handle any threats that come their way. Integrating artificial intelligence technologies, and optimally using machine learning algorithms are a couple of tactics that never fail to come handy. These are key aspects in improving scalability, operational efficiency, and threat detection.
As per Cybercrime Magazine, by 2025, the cost endured due to cybercrime would rise to $10.5 trillion annually.
Related Article- How to Become a Prompt Engineer
Artificial Intelligence vs Cyber Security
To completely understand the war of artificial intelligence vs cyber security, we have come up with four bases. These four aspects of comparison are enough to give you a better idea about which one these two would be a better fit for you.
There is no universal answer to which one provides better job opportunities. It is highly subjective and needs to be chosen on the basis of what you wish for your career.
Whether you should learn artificial intelligence or learn cyber security depends on where you wish you see yourself ten years down the line. Let's understand the difference between the two.
1. Education
The first thing to look into when discussing artificial intelligence vs cyber security is educational background.
A career in AI requires the individual to have a strong foundation in mathematics, computer science, as well as proficiency in top programming languages like Python. Additionally, having an advanced degree is known to further help in fulfilling role requirements like cutting-edge research and complex algorithm development.
To have a career in cyber security, you need deep knowledge of operating systems, security protocols, and networking. Earning a cyber security certification will help you showcase your skills too.
Do you need to enroll in cyber security courses online?
Enrolling in online resources is known to have a positive impact on the learning graph. Since the field of cyber security is huge and there are many certifications, it is always a good idea to go for a trusted learning program. Cyber security training is a wise choice. Having a knowledge of AI and machine learning in cyber security will add more value in your resume.
2. Skill Set
Skills needed to become an AI professional include-
Programming skills
Spark and Big Data technologies
Probability, linear algebra & statistics
Algorithms & frameworks
Business intelligence
Communication skills
Domain expertise
Problem-solving skills
Critical thinking ability, etc.
Skills needed to become a cyber security professional include-
Fundamental technical skills
Risk identification & management
Logical reasoning & troubleshooting
Programming
Data management & analysis
Adaptability
Cloud implementation & management
Communication skills, etc.
3. AI vs Cyber Security- Job Trends and Salaries
Here are tabs consisting of the top job trends related to artificial intelligence vs cyber security, along with the average salaries in USD and INR.
Artificial Intelligence Associated Job Roles And Salaries
Cyber Security Associated Job Roles And Salaries
JOB ROLE AVG SALARY (India) AVG SALARY (USA) Information Security Analyst INR 880,000 $87,647 Chief Information Officer (CIO) INR 327,000 $108,126 Cloud Consultant INR 1.98 M $110,039 Risk Manager - $93,217 Identity Manager INR 197,000 $121,515 Senior Security Consultant - $108,427 Penetration Tester INR 650,000 $123,476
NOTE: Please note that the salaries are not fixed and subject to change depending on various factors, including your organization, experience, location, etc.
Also Read - Types of Cybersecurity Threats
Wrapping Up Artificial Intelligence vs Cyber Security
In this quest to unsolved the mystery of artificial intelligence vs cyber security, we have given you various pointers to work with. Generative AI is a type of artificial intelligence technology that is becoming popular among tech enthusiasts. Once you individually understand both artificial intelligence and cyber security, you would be easily able to decide which of the two is better fit for you. On the other hand, artificial intelligence in cyber security plays an important role as the companies are adopting it secure company assets and protect user data.
Take the first step by reading this blog and finding out more details about the training courses and prerequisites for both.
You can also read: What is ChatGPT
FAQs on Artificial Intelligence vs Cyber Security
Q1. Which is better cyber security or AI?
In terms of learning curve, it is much easier to step into the field of cyber security than AI. This is because cyber security has various diverging paths, has softer learning prerequisites, and requires less effort.
Q2. Will AI replace cyber security jobs?
The short answer to this is no. AI will not replace cyber security jobs as humans are best fit for this profile.
Q3. Which pays more cybersecurity or IT?
On an average, software engineering jobs pay a little more than a cyber security job in the USA. However, multiple factors play an influential role.
| 2025-06-19T00:00:00 |
https://www.igmguru.com/blog/cybersecurity-vs-artificial-intelligence-careers
|
[
{
"date": "2025/06/19",
"position": 54,
"query": "artificial intelligence wages"
}
] |
|
Surfing the future: why education needs to embrace AI, soft ...
|
Surfing the future: why education needs to embrace AI, soft skills and self-awareness
|
https://www.weforum.org
|
[] |
Surfing the wave of AI means learning how to navigate uncertainty with curiosity and responsibility, not fear.
|
Today's education systems are shaped by the rigid needs of the past – not the adaptive ones of the future.
Teachers themselves must be educated as agile learners able to pass on the necessary skills.
Self-awareness about how skills can be transferred to new domains will be critical.
We keep telling young people to prepare for the future – but how can they, when our education systems are still stuck in the past? Teachers are often disconnected from today’s labour market, let alone tomorrow’s. The most in-demand jobs of 2030 haven’t even been invented yet. And yet, students are still measured by tests like France’s baccalauréat (created in 1808 under Napoleon). In a world shaped by rapid technological change and generative AI, we’re preparing students to compete in a system designed for another century – when what they really need is to learn how to adapt, question and create.
Most secondary education systems are still built to optimize for standardized metrics and university entrance exams. These metrics often reward memorization, individual performance and technical accuracy – skills that are increasingly being automated by AI. Meanwhile, the skills students actually need are shifting rapidly. According to the World Economic Forum's Future of Jobs Report 2023, nearly 23% of jobs will change over five years, with 69 million new roles created and 44% of workers’ core skills are expected to change by 2028. UNESCO and the OECD warn that many of the jobs students will hold a decade from now don’t even exist yet. This is one of the deepest misalignments in education today: We’re preparing students for a future we can’t predict, using frameworks built for a world we’ve already left behind.
Lead – don’t fear – the next wave of change
These outdated systems don’t just fail students – they also fail the people trying to teach them. While students increasingly explore AI tools and digital platforms on their own, educators are expected to prepare students for a future they themselves haven’t been trained for. It’s time to rethink teacher development – not as extra work, but as a strategic investment.
If we expect teachers to prepare students for the future of work, we need to give them the space, time and tools to keep learning, too. That means moving beyond occasional workshops or added responsibilities. We need structured, protected time built into the academic calendar for teachers to receive training from experts, follow tailored learning paths and stay connected to real-world shifts. If we want agile learners, we need agile teachers – and systems that believe in their growth just as much as their students’.
The AI tsunami is here
Banning AI in classrooms is like trying to stop a tsunami with your hands. You might hold back a few waves, but eventually, the tide comes in. We can’t ban our way out of disruption – we have to teach students how to surf.
That means putting critical thinking, creativity and ethical reasoning at the centre of learning. If students can’t tell a deepfake from real news, or if they don’t know how to assess the biases of the tools they’re using, we haven’t prepared them for the real world. Surfing the wave of AI means learning how to navigate uncertainty with curiosity and responsibility, not fear.
Can an ageing Europe unlock more personalized learning?
In Europe, our demographic reality is shifting: Populations are ageing, birth rates are declining, and lifelong learning is becoming essential. This opens up an opportunity to rethink our models. If we’re educating smaller, more diverse cohorts, why not make learning more individualized? Why not design courses based on personality, learning style and natural strengths?
We talk a lot about soft skills – but we rarely assess them. Yet, we know that people are naturally inclined toward certain ways of learning and thinking. Some of us are problem-solvers. Others are communicators, synthesizers or creators. These abilities can absolutely be taught and strengthened –but we need to start by helping students understand themselves.
Self-awareness for adaptable career paths
One of the hardest parts of being a teenager is not knowing who you are yet. And still, we expect students to make huge life decisions – what to study, where to work, how to succeed – without that foundation. What if schools focused not just on “top of the class”, but on discovering your path?
Learning how to transfer skills – from art to science, from music to math – is one of the most valuable competencies in today’s world. And yet, we almost never teach it.
Let me give you a personal example. When my aunt moved from Spain to the Netherlands, she had studied music professionally and needed to reskill to find work. After a basic assessment, they proposed two options: air traffic controller or math teacher. She laughed. But it made sense: Music is math. Rhythm, timing, structure – they're all rooted in mathematical patterns. That connection had never even occurred to us. In Spain, that kind of career transition would have seemed impossible. In the Netherlands, it was just a question of skill-mapping.
This is exactly the kind of mindset shift we need. We need to stop asking “what did you study?” and start asking “what can you do – and how can you apply it in new ways?”
Stop racing, start surfing
The goal isn’t to finish first. It’s to stay grounded, adaptable and curious in a world that’s constantly changing. And more importantly, it’s to learn how to get back up – and back to the table – when a wave you didn’t see coming knocks you down.
Let’s stop training students for speed and start teaching them how to ride the waves. We need to stop rushing them toward traditional notions of success and start walking alongside them as they discover who they are and how they learn. Education isn’t a race to the top; it’s a journey of learning how to move through the world with purpose, resilience and agency.
In a time of AI disruption, geopolitical instability and economic transformation, young people don’t just need answers. They need tools to ask better questions. Let’s give them those tools. Let’s teach them to surf.
| 2025-06-19T00:00:00 |
https://www.weforum.org/stories/2025/06/education-future-skills-ai/
|
[
{
"date": "2025/06/19",
"position": 32,
"query": "AI education"
}
] |
|
THE COMPLETE GUIDE TO AI IN EDUCATION: Harness ...
|
Amazon.com
|
https://www.amazon.com
|
[] |
The Complete Guide to AI in Education is a comprehensive resource for anyone interested in the transformative role of artificial intelligence in learning.
|
Click the button below to continue shopping
| 2025-06-19T00:00:00 |
https://www.amazon.com/COMPLETE-GUIDE-EDUCATION-Artificial-Intelligence/dp/B0F4KTQNFY
|
[
{
"date": "2025/06/19",
"position": 65,
"query": "AI education"
}
] |
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Here's how WCPO 9 is using artificial intelligence in our ...
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Here's how WCPO 9 is using artificial intelligence in our journalism
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https://www.wcpo.com
|
[
"Pj O'Keefe"
] |
Every single story starts with a journalist, and at its core is created by journalists. From pitch to interviews, a human is central to our storytelling and ...
|
CINCINNATI — The use of artificial intelligence is on the rise, and here at WCPO 9, we're taking a thoughtful approach about how to make sure we use it responsibly.
You may have noticed disclaimers on certain WCPO 9 web articles about the use of AI.
Every single story starts with a journalist, and at its core is created by journalists. From pitch to interviews, a human is central to our storytelling and fact-gathering process.
Here's what we use AI for in our journalism:
Copy editing: We use it to go beyond just basic spell check, but also to follow the right context and style. Script conversion: We serve a lot of platforms. We will, at times, write a script and convert it to another platform using AI. This includes writing for our broadcast and converting it to web, and vice versa. The journalism doesn't change - just the style and format to better match your expectations in each place we report. Platform conversion: AI helps us take horizontal video storytelling you might see on our broadcast or YouTube and convert it to vertical on Instagram or TikTok, so that, again, we can make as big of an impact as possible, on as many platforms as possible. Creative help: We will ask AI for help with things like headlines, social media post suggestions and teases in our newscasts. All of this is generated using our own independently gathered and written source material, but is still all reviewed by a human.
Here's what we don't use AI for:
Generating photorealistic images/video: This is off limits for us. Any of the pictures or video that you see across all platforms of WCPO 9 will be authentic and editorial in nature, whether gathered by us, or our news partners like the Associated Press and CNN. Generating written scripts: We are still the source of writing our digital articles and our broadcast videos. We do not ask AI to write a story for us based off of interviews or research. We create the first draft before using any of the above-mentioned tools. Research: Our journalists fact check everything themselves.
What kind of AI do we use?
We use a variety of different sources of AI (like Chat GPT and Claude) that are filtered through an internal AI platform. With this, we have custom prompts that help us do everything mentioned above. Our internal AI platform is designed to protect the content and information we work with so it remains private unless/until published.
The technology is evolving fast, and we'll be sure to update this story if we change anything about our use of it.
| 2025-06-19T00:00:00 |
2025/06/19
|
https://www.wcpo.com/about-us/heres-how-wcpo-9-is-using-artificial-intelligence-in-our-journalism
|
[
{
"date": "2025/06/19",
"position": 57,
"query": "AI journalism"
},
{
"date": "2025/06/19",
"position": 8,
"query": "artificial intelligence journalism"
}
] |
Why Microsoft axed thousands and why you should be ...
|
Why Microsoft axed thousands and why you should be worried
|
https://rollingout.com
|
[
"Miriam Musa",
"Miriam Musa Is A Journalist Covering Health",
"Fitness",
"Tech",
"Food",
"Nutrition",
"News. She Specializes In Web Development",
"Cybersecurity",
"Content Writing. With An Hnd In Health Information Technology",
"A Bsc In Chemistry"
] |
Microsoft laid off thousands of employees to fund AI investments despite strong earnings. Why human jobs are being sacrificed for AI.
|
Microsoft just delivered the kind of news that makes your stomach drop even if you don’t work there. Thousands of employees – real people with mortgages, families, and Friday afternoon coffee routines – got pink slips this week so the company can pour more money into teaching machines to do human jobs better than humans do them.
The layoffs hit sales and customer support teams particularly hard, which feels especially cold considering these are the people who’ve been building relationships with customers and keeping the business running while executives were dreaming up AI strategies in boardrooms. Now those same executives are essentially saying those human connections aren’t worth keeping around.
This isn’t just another round of corporate cost-cutting disguised as strategic planning. This is Microsoft making a calculated bet that artificial intelligence is worth sacrificing thousands of current employees for the possibility of future profits. The message is clear – if you’re not directly contributing to the AI revolution, you might be expendable.
The AI gold rush that’s costing real jobs
Microsoft is reshuffling its entire workforce like a deck of cards, moving money and people around to focus almost exclusively on artificial intelligence development. They’re not just trimming fat or eliminating redundant positions – they’re fundamentally restructuring what kind of company they want to be, and apparently that doesn’t include as many human employees.
The company is doubling down on AI infrastructure, cloud capabilities, and the kind of advanced computing power that makes generative AI possible. Every dollar that used to go toward human salaries in traditional roles is now being redirected toward servers, algorithms, and the specialized talent needed to build AI systems.
This represents a massive philosophical shift about the value of human workers versus technological capability. Microsoft is essentially betting that AI will generate more revenue than the human employees they’re letting go, which is a pretty stark calculation when you think about the actual people affected.
The repeat performance nobody wanted to see
These aren’t even the first layoffs of the year for Microsoft. The company has been steadily trimming its workforce throughout 2024, creating an atmosphere of uncertainty for employees who are probably wondering if they’re next on the chopping block. Each round of cuts chips away at job security and workplace morale while executives talk about exciting AI futures.
The pattern is becoming depressingly predictable across the tech industry. Companies announce strong earnings and promising growth prospects, then immediately follow up with layoff announcements justified by the need to invest in artificial intelligence. It’s like a twisted version of success where profitability somehow requires fewer human employees.
This cycle of repeated workforce reductions creates a climate of fear and instability for remaining employees, who have to watch their colleagues get eliminated while being expected to maintain productivity and enthusiasm for company goals that apparently don’t include job security.
The enterprise demand driving human displacement
Microsoft justifies these job cuts by pointing to growing enterprise demand for AI services like Azure OpenAI and Copilot. Companies are apparently lining up to pay for artificial intelligence capabilities, creating a revenue opportunity that Microsoft doesn’t want to miss by maintaining expensive human workforces.
The irony is that enterprise customers are buying AI services that will likely eliminate jobs at their own companies too. It’s a cascading effect where Microsoft’s AI tools will help other businesses reduce their human workforces, creating a cycle of technological replacement that benefits shareholders while displacing workers across multiple industries.
This enterprise demand represents a fundamental shift in how businesses view human labor versus technological solutions. When companies are willing to pay premium prices for AI that can replace human tasks, it creates powerful economic incentives for providers like Microsoft to prioritize AI development over human employment.
The competitive pressure that’s crushing job security
Microsoft isn’t making these cuts in isolation – they’re responding to aggressive AI investments from competitors like Google, Amazon, and Meta. This has created an arms race where tech companies feel pressured to sacrifice human jobs to fund AI development, or risk being left behind in what they see as the most important technological shift in decades.
The competitive dynamic means that even profitable companies with strong financial positions are eliminating jobs to redirect resources toward AI research and development. It’s not about financial necessity – it’s about maintaining competitive position in a race where human employees are seen as a burden rather than an asset.
This competition is driving a race to the bottom in terms of job security, where companies feel they have to eliminate human roles to afford the massive investments required to compete in artificial intelligence. The human cost of this technological competition is being treated as an acceptable sacrifice for corporate strategy.
The earnings paradox that makes layoffs sting worse
Perhaps the most frustrating aspect of these layoffs is that Microsoft reported strong earnings earlier this year. This isn’t a struggling company desperately cutting costs to survive – this is a profitable enterprise choosing to eliminate jobs to become even more profitable through AI investments.
When companies with healthy financial performance eliminate thousands of jobs, it sends a clear message about priorities. Shareholders and AI development matter more than the human employees who helped create that financial success in the first place. It’s a betrayal of the social contract between employers and workers.
The strong earnings make these layoffs feel particularly callous because they demonstrate that job elimination isn’t driven by necessity but by optimization. Microsoft can afford to keep these employees – they’re choosing not to because they believe AI investments will generate better returns than human workers.
The future workforce that’s taking shape
These layoffs offer a preview of what the future workforce might look like – smaller, more specialized, and heavily focused on AI development rather than traditional business functions. Microsoft is essentially showing other companies a blueprint for how to restructure around artificial intelligence priorities.
The employees who survive these cuts are probably wondering what skills they need to develop to remain relevant in an AI-focused organization. The message seems to be that unless you’re directly contributing to AI development or managing AI systems, your job security is questionable at best.
This workforce transformation raises serious questions about what happens to all the displaced workers and whether the economic benefits of AI will be shared broadly or concentrated among a small group of technology companies and their remaining specialized employees.
The human cost of the AI revolution
Behind every layoff announcement are real people whose lives are being disrupted so companies can chase AI profits. These aren’t just numbers on a spreadsheet – they’re individuals who have to explain to their families why their jobs disappeared despite strong company performance and promising AI revenues.
The speed and scale of these AI-driven layoffs suggests that the technological transition is happening faster than society’s ability to adapt or provide support for displaced workers. Companies are moving quickly to capture AI opportunities while leaving the human consequences for others to deal with.
Microsoft’s decision represents a broader trend where the benefits of AI advancement are being captured by companies and shareholders while the costs are being imposed on workers who lose their jobs. It’s a distribution of AI’s impact that prioritizes technological progress over human welfare, and it’s happening across the entire tech industry with little consideration for the broader social implications.
| 2025-06-19T00:00:00 |
2025/06/19
|
https://rollingout.com/2025/06/19/microsoft-layoffs-ai/
|
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"date": "2025/06/19",
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Why your colleagues stay silent about their ChatGPT use
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Why your colleagues stay silent about their ChatGPT use
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https://www.businessthink.unsw.edu.au
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[] |
Workers use AI tools like ChatGPT quietly, fearing job cuts, mistrust and unclear workplace policies.
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Why your colleagues stay silent about their ChatGPT use
Opinion | 19 June 2025
Frederik Anseel Dean and Professor of Management
AI is transforming work, but many employees stay silent – creating hidden risks and missed opportunities for organisations, writes UNSW Business School’s Frederik Anseel
Surveys show that the number of people using AI tools at work has doubled in two years, to about 45% of employees. No wonder ChatGPT is the fifth most visited website in the world. But you wouldn’t know it based on what you see in the workplace. Many workers remain remarkably quiet about their AI use. You don’t see ChatGPT reports or prompts flying back and forth, and no enthusiastic conversations about the time savings that AI delivers. No, AI use flies conspicuously under the radar. Why? Wouldn’t you expect a certain pride from people who are keeping up with the latest technology?
The hidden use of AI is one of the primary concerns for companies – if they’re even aware of it. AI stealth usage is one of the fundamental obstacles we must overcome to achieve a real productivity leap in our economy. There are three reasons why people prefer to stay silent.
Fear of job cuts
The first reason is, paradoxically, the AI productivity gain itself. Many people find that difficult tasks, which used to take them hours to complete, now take only a few minutes with platforms such as ChatGPT. Answering a few emails, generating a report or analysis, or creating a summary – add these up over a week, and there’s a time savings of several hours.
UNSW Business School Dean, Professor Frederik Anseel, says companies looking for AI-enabled productivity gains must first win the trust of their employees. Photo: UNSW Sydney
Who benefits from those time savings? For now, it’s the individual employees. But what if the employer catches wind of the time savings? That consideration makes many people hesitate. The danger is that companies will do the math and either give people more work or cut jobs. You can already see a shift in jobs worldwide, particularly in consultancies, marketing agencies, technology companies, and law firms.
Lack of clarity
The second reason is the threatening tone companies take with regards to privacy and security. Many people are confused about what’s allowed and what isn’t. They choose certainty over uncertainty. ChatGPT is eagerly used in the private sphere, where many people prefer the simplicity of using free chatbots at home over their company’s workplace policies.
That’s a headache for companies, which urgently need to work on more permissive and workable AI support to get employees out of grey zones. It doesn’t help that companies are still recommending the ‘safe’ version of AI platforms, while the new AI models are much more advanced. Companies need to go back 15 years in time and think about how they once had to handle a ‘Bring Your Own Device’ policy, because they simply couldn’t compete with the much more sophisticated devices people were using at home.
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The last reason is complex. People who use ChatGPT are concerned about being labelled as inauthentic, cheating, or lazy. Look, nobody has a problem with you using a spellchecker. It’s probably also okay to ask an AI bot to proofread an email. But how do you think a colleague would react if they discovered that jovial thank-you email was written by an AI bot? Or what do you think about it yourself, if your manager didn’t directly write your own feedback report?
How trustworthy are you?
A recent series of studies show how complex the psychological problem is. In companies, the recommendation is: ‘Be transparent and always clearly state where you’ve used AI.’ But research shows that those who are transparent actually lose trust. People find colleagues less trustworthy when they confess to using ChatGPT.
AI adoption is more of a psychological than a technological problem. Companies looking for productivity gains must first win the trust of their employees. They don’t necessarily distrust the AI technology, but rather how employees will use it. People want assurance that their time savings won’t be exploited, that they won’t be punished for experimenting with AI, and that they won’t be looked at sideways for using AI to take a more efficient approach to work. We urgently need to bring AI stealth usage out of the shadows.
Frederik Anseel is Professor of Management and Dean of UNSW Business School. He studies how people and organisations learn and adapt to change, and his research has been published in leading journals such as Journal of Applied Psychology, Journal of Management, American Psychologist, and Psychological Science. A version of this post was first published in De Tijd.
| 2025-06-19T00:00:00 |
https://www.businessthink.unsw.edu.au/articles/ai-workplace-usage-chatgpt-trust-productivity
|
[
{
"date": "2025/06/19",
"position": 17,
"query": "ChatGPT employment impact"
},
{
"date": "2025/06/19",
"position": 97,
"query": "workplace AI adoption"
}
] |
|
The Future of ChatGPT: Predictions and Opportunities
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The Future of ChatGPT: Predictions and Opportunities
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https://aicontentfy.com
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[
"Aicontentfy Team"
] |
It is important to consider the potential impact of ChatGPT on the job market and to take steps to ensure that any negative impact is minimized. Overall ...
|
As technology advances and artificial intelligence continues to evolve, the possibilities for how we interact with machines are expanding at an incredible rate. One such example is ChatGPT, a large language model trained by OpenAI. ChatGPT has already made waves in the world of natural language processing, helping people to communicate with machines in a more human-like way. ChatGPT had 100 million users in January 2023, and it is estimated that the user count reached 173 million users in April 2023. But what does the future hold for this groundbreaking technology? In this article, we will explore the predictions and opportunities for the future of ChatGPT. From enhancing customer service to revolutionizing education, the potential applications of ChatGPT are vast and exciting. Join us as we delve into what the future may hold for this fascinating technology.
ChatGPT's current capabilities and limitations
ChatGPT is an artificial intelligence language model that is capable of understanding and generating human-like text responses to a wide range of questions and prompts. As it stands, ChatGPT's current capabilities allow it to converse with humans on a wide range of topics, answer factual questions, make jokes, and even generate creative writing prompts. ChatGPT is also capable of learning and improving over time as it processes more data. The popularity of the tool has been nothing but incredible, in January 2023 ChatGPT received an average of 13 million unique visitors per day, which is more than double the daily number in December 2022
However, like any other technology, ChatGPT has its limitations. Recognizing these limitations, OpenAI continuously works on ChatGPT updates to enhance its accuracy, reduce biases, and expand its understanding of complex queries. While it is capable of generating coherent and contextually relevant responses, it may sometimes generate inaccurate or inappropriate responses, especially when given incomplete or ambiguous information. Additionally, ChatGPT can struggle with understanding colloquial language, sarcasm, or other non-literal expressions that humans may use in their everyday conversations. Finally, ChatGPT can sometimes generate repetitive or irrelevant responses, particularly when it encounters a topic that it has not been trained on.
Overall, while ChatGPT's current capabilities are impressive, there is still a long way to go before it can fully replicate human-like conversations. However, with continued advancements in natural language processing and machine learning, there is potential for ChatGPT to continue to improve its capabilities and expand its applications in the future. An example of this can be seen with the recent integration of AI in web browsers.
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Advancements in natural language processing (NLP) and their potential impact on ChatGPT
Natural language processing (NLP) is a field of artificial intelligence that focuses on enabling machines to understand, interpret, and generate human language. As advancements in NLP continue to accelerate, the potential impact on ChatGPT is enormous.
One key area of advancement in NLP is the development of more sophisticated language models. ChatGPT is already an impressive example of this technology, but new models are being developed that could potentially surpass it in terms of accuracy and capabilities. Additionally, these new models may be able to learn and adapt more quickly than previous iterations, allowing ChatGPT to keep up with the rapidly changing language patterns of humans.
Another area of potential impact is the development of more advanced dialogue systems. These systems could enable ChatGPT to not only generate coherent and relevant responses but also to better understand the context of a conversation and anticipate a user's needs. This could lead to more effective and efficient interactions, making ChatGPT an even more valuable tool in a variety of settings.
Finally, advancements in NLP could also help address some of the limitations of ChatGPT that we discussed earlier, such as its struggles with understanding colloquial language and non-literal expressions. As NLP continues to improve, these issues may become less pronounced, allowing ChatGPT to generate more accurate and contextually relevant responses.
Overall, the potential impact of advancements in NLP on ChatGPT is significant. As the technology continues to evolve, we can expect ChatGPT to become even more capable and valuable in a variety of applications, from customer service and education to mental health treatment and more.
ChatGPT's potential for improving customer service
One of the areas where ChatGPT has the potential to make a significant impact is in the realm of customer service. Currently, customer service representatives are often required to handle a high volume of inquiries from customers, which can be time-consuming and resource-intensive. ChatGPT can help alleviate some of these challenges by providing automated customer service that is available 24/7.
With its natural language processing capabilities, ChatGPT can understand and respond to customer inquiries in a way that feels like a conversation with a human representative. This can help to improve the customer experience by reducing wait times and providing more personalized responses. Additionally, ChatGPT development services can handle a wide range of inquiries and provide information about products or services, answer frequently asked questions, and help customers troubleshoot common issues.
Another advantage of using ChatGPT for customer service is that it can be easily integrated with other customer service tools, such as chatbots or phone systems. This can create a seamless experience for customers, allowing them to communicate with the company through their preferred channel.
Overall, ChatGPT's potential for improving customer service is significant. By providing automated customer service that is available 24/7, ChatGPT can help to reduce wait times, improve the customer experience, and free up resources for other important tasks. As the technology continues to evolve, we can expect to see even more innovative applications of ChatGPT in the realm of customer service.
ChatGPT's potential for revolutionizing education
ChatGPT has the potential to revolutionize education by providing a personalized and interactive learning experience for students. With its natural language processing capabilities, ChatGPT can understand student inquiries and provide tailored responses that meet their specific needs.
One way that ChatGPT could be used in education is as a virtual tutor or study partner. Students could ask ChatGPT questions about a particular topic and receive instant feedback and explanations. ChatGPT could also provide feedback on assignments or help students to develop study plans that meet their individual learning goals.
Additionally, ChatGPT could be used as a tool for collaborative learning. By facilitating real-time discussions between students, ChatGPT could help to create a more interactive and engaging learning experience. Students could work together to solve problems, brainstorm ideas, or review material.
Another way that ChatGPT could be used in education is as a tool for language learning. With its ability to understand and generate human-like text, ChatGPT could help students to practice their language skills in a conversational setting. By providing immediate feedback on grammar and syntax, ChatGPT could help students to develop their language proficiency in a more engaging and effective way.
Overall, ChatGPT's potential for revolutionizing education is significant. By providing a personalized and interactive learning experience, ChatGPT could help to improve student outcomes and create a more engaging and effective educational experience. As the technology continues to evolve, we can expect to see even more innovative applications of ChatGPT in the realm of education.
ChatGPT's potential for aiding mental health treatment
ChatGPT has the potential to aid mental health treatment by providing a new channel for individuals to seek help and support. With its natural language processing capabilities, ChatGPT can understand and respond to individuals in a compassionate and non-judgmental way.
One way that ChatGPT could be used in mental health treatment is as a virtual therapist or counselor. Individuals could use ChatGPT to seek help for mental health issues such as anxiety, depression, or post-traumatic stress disorder. ChatGPT could provide evidence-based therapies, such as cognitive-behavioral therapy, in a conversational format.
Additionally, ChatGPT could be used to help individuals track their mental health and provide personalized recommendations. Individuals could use ChatGPT to log their mood, symptoms, and daily activities. ChatGPT could then provide insights and recommendations based on this data, such as mindfulness exercises or breathing techniques.
Another way that ChatGPT could be used in mental health treatment is to provide peer support. By facilitating conversations between individuals who are struggling with similar mental health issues, ChatGPT could help to create a sense of community and reduce feelings of isolation.
Overall, ChatGPT's potential for aiding mental health treatment is significant. By providing a new channel for individuals to seek help and support, ChatGPT could help to reduce barriers to access and provide evidence-based therapies in a convenient and cost-effective way. As the technology continues to evolve, we can expect to see even more innovative applications of ChatGPT in the realm of mental health.
ChatGPT's potential for enhancing personal productivity
ChatGPT has the potential to enhance personal productivity by providing a virtual assistant that can help individuals manage their tasks and priorities. With its natural language processing capabilities, ChatGPT can understand and respond to individuals in a conversational way, making it easy for individuals to manage their to-do lists, schedule appointments, and get reminders.
One way that ChatGPT could be used to enhance personal productivity is by serving as a personal assistant. Individuals could use ChatGPT to schedule appointments, set reminders, and manage their calendars. ChatGPT could also provide recommendations on how to prioritize tasks and manage their time more effectively.
Additionally, ChatGPT could be used as a tool for project management. By facilitating real-time discussions between team members, ChatGPT could help to coordinate tasks, track progress, and ensure that everyone is on the same page. This could help to increase collaboration and reduce miscommunication.
Another way that ChatGPT could be used to enhance personal productivity is by providing a tool for personal development. Individuals could use ChatGPT to set goals and receive reminders and recommendations on how to achieve them. ChatGPT could also provide feedback on progress and suggest new challenges to help individuals continue to grow and develop.
Overall, ChatGPT's potential for enhancing personal productivity is significant. By providing a virtual assistant that can help individuals manage their tasks and priorities, ChatGPT could help to increase efficiency, reduce stress, and improve overall well-being. As the technology continues to evolve, we can expect to see even more innovative applications of ChatGPT in the realm of personal productivity.
ChatGPT's potential for generating creative content
ChatGPT has the potential to generate creative content by using its natural language processing capabilities to generate original ideas, phrases, and sentences. With the ability to analyze and understand vast amounts of data, ChatGPT can draw from a variety of sources to generate unique and creative content. ChatGPT is a valuable asset for creative content creation, helping to generate subtitles that are engaging and relevant. By understanding the context and tone of your content, it quickly provides tailored suggestions, saving time while ensuring your subtitles enhance the overall impact effectively.
One way that ChatGPT could be used to generate creative content is in the field of writing. For example, ChatGPT could be used to generate prompts for creative writing exercises, suggest new angles or perspectives for articles, or even assist with writing entire pieces of content such as blogs, articles, or social media posts.
Additionally, ChatGPT could be used to generate content for marketing and advertising purposes. By analyzing data on customer preferences and behaviors, ChatGPT could generate personalized marketing messages and advertising copy that resonate with individual customers. This could help to increase engagement and conversion rates.
Another way that ChatGPT could be used to generate creative content is in the realm of art and design. ChatGPT could generate ideas for artwork, design concepts, or even music compositions. This could be particularly useful for artists and designers who are looking for fresh ideas or inspiration.
Overall, ChatGPT's potential for generating creative content is significant. By using its natural language processing capabilities to generate original and innovative ideas, ChatGPT could help to enhance creativity, save time, and increase efficiency. As the technology continues to evolve, we can expect to see even more innovative applications of ChatGPT in the realm of creative content.
Ethical considerations for the use of ChatGPT in various applications
As with any emerging technology, there are several ethical considerations that need to be taken into account when using ChatGPT in various applications. These considerations include issues related to privacy, bias, and the potential misuse of the technology.
One of the key ethical considerations for the use of ChatGPT is related to privacy. As ChatGPT relies on large amounts of data to function, there are concerns about how this data is collected and stored, and who has access to it. It is important to ensure that any data collected is used ethically and in accordance with privacy regulations.
Another ethical consideration is related to bias. ChatGPT relies on machine learning algorithms, which means that the quality of the output is only as good as the quality of the input data. If the data used to train ChatGPT contains biases, this could lead to biased outputs. It is important to take steps to ensure that any biases are identified and addressed.
The potential for misuse of ChatGPT is also an important ethical consideration. As the technology becomes more sophisticated, there is a risk that it could be used to spread misinformation or to manipulate individuals. It is important to take steps to ensure that ChatGPT is used for ethical purposes, and that any potential risk exposure are identified and addressed.
Finally, there are also ethical considerations related to the impact of ChatGPT on human labor. As ChatGPT becomes more sophisticated, it has the potential to replace human workers in certain industries. It is important to consider the potential impact of ChatGPT on the job market and to take steps to ensure that any negative impact is minimized.
Overall, there are several ethical considerations that need to be taken into account when using ChatGPT in various applications. It is important to ensure that any use of ChatGPT is done in an ethical and responsible manner, and that any potential risks or negative impacts are identified and addressed. By doing so, we can help to ensure that ChatGPT is used to its full potential while minimizing any potential negative consequences.
The future of ChatGPT and the possibility of creating more advanced language models
The future of ChatGPT looks bright, as there is tremendous potential for creating even more advanced language models. As the technology continues to evolve, we can expect to see ChatGPT become even more sophisticated and capable.
One of the key areas of development for ChatGPT is in the realm of context awareness. Currently, ChatGPT is able to generate responses based on the words and phrases that it receives, but it lacks the ability to fully understand the context in which those words and phrases are being used. As the technology improves, we can expect to see ChatGPT become much better at understanding context, which will lead to more accurate and relevant responses.
Another area of development for ChatGPT is related to multi-modal learning. This refers to the ability to incorporate different types of input, such as images and videos, into the learning process. By doing so, ChatGPT will be able to generate more nuanced and sophisticated responses that take into account a broader range of information.
In addition to these areas of development, there is also potential for creating more specialized language models that are tailored to specific industries or use cases. For example, a language model that is specifically designed for legal language or medical language could be much more accurate and efficient than a general-purpose language model like ChatGPT.
Overall, the future of ChatGPT is very promising, and there is enormous potential for creating more advanced language models that are even more sophisticated and capable. As the technology continues to evolve, we can expect to see ChatGPT become even more useful and ubiquitous, with applications in a wide range of industries and use cases.
ChatGPT's potential for cross-language communication and translation
ChatGPT has the potential to revolutionize cross-language communication and translation. One of the biggest challenges of cross-language communication is the language barrier, which can make it difficult for people who speak different languages to communicate effectively. However, ChatGPT's ability to understand and generate natural language makes it well-suited for translation and cross-language communication.
With ChatGPT, it is possible to generate accurate translations of text in real-time, which can be incredibly useful for individuals and organizations that operate in multilingual environments. ChatGPT's language capabilities also mean that it can help individuals communicate with others who speak a different language, by acting as a real-time translator during conversations.
Another potential benefit of ChatGPT's cross-language communication capabilities is the ability to break down cultural barriers. When people are able to communicate more easily across different languages and cultures, it can help to build greater understanding and cooperation.
While there are certainly challenges to cross-language communication and translation, ChatGPT's capabilities make it a promising technology for addressing these challenges. As the technology continues to evolve and improve, we can expect to see ChatGPT play an increasingly important role in breaking down language barriers and promoting more effective cross-cultural communication.
Final thoughts
The future of ChatGPT looks bright, with tremendous potential for creating even more advanced language models. Currently, ChatGPT has limitations in context awareness and multi-modal learning, but with ongoing advancements in natural language processing, we can expect to see ChatGPT become much more sophisticated and capable.
ChatGPT has the potential to revolutionize various industries, including customer service, education, mental health treatment, personal productivity, and content creation. In each of these areas, ChatGPT's natural language generation and understanding capabilities can help to improve efficiency, accuracy, and outcomes.
However, with great power comes great responsibility, and there are ethical considerations to be aware of as ChatGPT becomes more ubiquitous. As the technology evolves, it will be important to consider how it is being used and whether it is being used in ways that are fair and ethical.
Looking to the future, there is enormous potential for creating more specialized language models that are tailored to specific industries or use cases. As the technology continues to evolve, we can expect to see ChatGPT become even more useful and ubiquitous, with applications in a wide range of industries and use cases. With the potential for breaking down language barriers and promoting cross-cultural communication, ChatGPT has the potential to play an increasingly important role in our interconnected world.
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| 2025-06-19T00:00:00 |
https://aicontentfy.com/en/blog/future-of-chatgpt-predictions-and-opportunities-1
|
[
{
"date": "2025/06/19",
"position": 49,
"query": "ChatGPT employment impact"
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|
Global AI and the Future of Work
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Global AI and the future of work
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https://thunderbird.asu.edu
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[] |
New forms of employment: As AI evolves, entirely new job categories are emerging, such as AI ethics officers, data scientists, and machine learning engineers.
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Artificial Intelligence (AI) has emerged as one of the most transformative technologies of the 21st century. Its rapid adoption is reshaping industries, revolutionizing workflows, and redefining what employment looks like in a world increasingly driven by automation and machine learning.
We sat down with Euvin Naidoo, Thunderbird School of Global Management’s distinguished professor of practice and global expert in agile management and AI, to talk about global AI and the future of work. Naidoo is also a member of the World Economic Forum’s Global Future Council on the Future of Job Creation.
Naidoo is also the 2024 recipient of The Case Centre’s Outstanding Case Teacher award.. This November, he will be leading Thunderbird’s inaugural two-day open enrollment immersion on Artificial Intelligence.
Opportunities presented by AI
Naidoo said AI offers numerous benefits that can enhance productivity, streamline operations, and foster innovation across various industries. Some of the key opportunities include:
Increased efficiency: AI-powered tools can automate repetitive tasks, reducing human error and allowing employees to focus on more strategic and creative work. This leads to higher overall productivity.
“This is particularly evident in sectors like manufacturing, where robotics are streamlining production, or customer service, where chatbots and virtual assistants handle inquiries 24/7,” Naidoo said.
New forms of employment: As AI evolves, entirely new job categories are emerging, such as AI ethics officers, data scientists, and machine learning engineers. These roles focus on the development, deployment, and oversight of AI systems, expanding employment opportunities in high-skill areas.
Enhanced decision-making: AI algorithms can analyze massive amounts of data quickly and accurately, helping companies make more informed, data-driven decisions. This is particularly beneficial in industries like finance, healthcare, and logistics.
“Importantly, AI is not just about replacing human work—it’s about augmenting it. AI tools can enhance human capabilities, making professionals in fields like design, marketing, and medicine more productive and effective,” Naidoo said.
Challenges of AI adoption
Naidoo said that while the potential is enormous, the road to AI adoption is not without hurdles. He said AI adoption also presents significant challenges that need to be addressed to minimize the negative impact on the workforce:
Job displacement: One of the primary concerns is the potential for AI to replace jobs, particularly those involving routine and repetitive tasks. For example, roles in manufacturing, customer service, and data entry may be vulnerable to automation.
Need for upskilling and reskilling: As automation takes over some jobs, there is an increasing need for employees to gain new skills. Upskilling and reskilling initiatives will be critical for helping workers transition into new roles that require a higher level of expertise in AI-related technologies.
Widening skills gap: AI adoption may exacerbate existing inequalities in the job market. Workers who lack the necessary digital skills may find themselves at a disadvantage, further emphasizing the importance of education and training programs that prepare workers for an AI-driven economy.
Integration with existing systems: Naidoo said that many companies still rely on legacy IT systems, and modernizing them to accommodate AI can be both costly and time-consuming.
“Add to that the shortage of skilled AI talent—data scientists, machine learning engineers, and AI ethicists—and it becomes clear why some organizations are slow to adopt AI,” he said.
Ethical considerations surrounding AI deployment
As AI becomes more integrated into business and society, ethical concerns must be addressed to ensure its responsible development and use:
Bias in AI: “Since AI learns from data, it can unintentionally perpetuate existing biases,” Naidoo said. “This can lead to unfair outcomes, such as biased hiring decisions or discriminatory lending practices. Ensuring fairness and accountability in AI systems is vital, especially in high-stakes areas like finance and healthcare.”
Transparency and accountability: AI decision-making processes are often opaque, leading to what is known as the "black box" problem. It is crucial that businesses and policymakers establish clear guidelines to ensure AI systems are transparent, explainable, and accountable for their decisions.
Data privacy: With AI systems processing vast amounts of data, there are growing concerns about data privacy and security. Companies must ensure they handle sensitive data responsibly and comply with relevant regulations such as the General Data Protection Regulation (GDPR).
AI and human dignity: There is also a broader ethical question about how AI will impact human dignity and autonomy. For instance, relying too heavily on AI for decision-making in areas like healthcare and criminal justice could erode personal freedoms and fairness.
Creating policies and regulations for responsible AI
To mitigate the risks associated with AI and maximize its benefits, policymakers and businesses need to work together to develop a comprehensive framework for responsible AI. “Data protection laws like GDPR in Europe and the CCPA in California are a good start, but they need to evolve as AI continues to develop,” Naidoo said.
Key considerations include:
AI governance: Establishing guidelines for AI governance that ensure systems are safe, reliable, and aligned with ethical standards. This includes creating frameworks for monitoring AI's impact on employment and enforcing accountability.
Workforce transition support: Governments and businesses must invest in education and training initiatives to help workers adapt to new job requirements. Programs like digital literacy training and vocational reskilling will be essential to help displaced workers transition to AI-enabled roles.
AI standards: Naidoo said AI regulation should be coordinated globally. “Since AI technology transcends borders, global collaboration is necessary to ensure that all countries benefit and that ethical standards are maintained,” he said.
Implementing AI in your business plan
For businesses looking to implement AI into their operations, Naidoo said the following steps can help guide the process:
1. Assess your business needs
Begin by identifying areas where AI can provide the most value. For example, is there a specific process that can be automated to save time and resources, or is there a need for better data analysis to inform decision-making?
2. Invest in the right talent
As AI becomes more integrated into your operations, it’s essential to have the right team in place. This may involve hiring data scientists, AI engineers, and experts in AI ethics who can develop and oversee the systems being implemented.
3. Create a data strategy
AI thrives on data. Implementing AI successfully requires a solid data infrastructure that can store, organize, and analyze vast amounts of information. Businesses should also ensure they are adhering to data privacy regulations.
“I recommend starting with small pilot projects to test AI’s impact before scaling up,” Naidoo said. “This allows organizations to assess the technology’s effectiveness without committing too many resources upfront.”
4. Adopt a flexible approach
AI is constantly evolving. Businesses need to be flexible in their approach, staying up to date on the latest AI advancements and continuously fine-tuning their systems to adapt to changing market conditions.
5. Monitor and evaluate
Ongoing evaluation is crucial to ensuring AI systems are performing as expected. Establish benchmarks for success and continually assess the AI’s impact on both business outcomes and the workforce.
Grow your skills to lead adoption of AI
The widespread adoption of AI is already transforming the global workforce, creating new opportunities while simultaneously posing challenges. As AI continues to evolve, businesses must be proactive in adopting ethical and responsible practices.
Naidoo said that by embracing upskilling initiatives, addressing ethical concerns, and creating thoughtful policies, both companies and policymakers can ensure that AI benefits all sectors of society.
Thunderbird can help professionals grow their skills to meet the challenges of global AI. Two Executive Education certifications are available: AI and the Future of Work and AI and Intelligent Transformation. Each will give you new tools you can use to deploy artificial intelligence in the business world.
| 2025-06-19T00:00:00 |
https://thunderbird.asu.edu/thought-leadership/insights/global-ai-future-of-work
|
[
{
"date": "2025/06/19",
"position": 21,
"query": "artificial intelligence employment"
},
{
"date": "2025/06/19",
"position": 23,
"query": "future of work AI"
},
{
"date": "2025/06/19",
"position": 9,
"query": "machine learning workforce"
}
] |
|
News Corp bets big on AI tools but journalists voice concerns
|
News Corp bets big on AI tools but journalists voice concerns
|
https://www.theguardian.com
|
[
"Amanda Meade"
] |
Company says in-house NewsGPT tool part of a look into how AI tech will 'enhance our workplaces rather than replace jobs'. Plus: Seven West's Origin dummy ...
|
Journalists at three of Rupert Murdoch’s Australian mastheads have reported deep concern after training sessions for an in-house AI tool called “NewsGPT” .
Staffers on the Australian, the Courier Mail and the Daily Telegraph say the tool enables them to take on the persona of another writer, or to adopt a certain style, and NewsGPT will then generate a custom article.
Another tool, in which they adopt the persona of an editor to generate story leads or fresh angles, has also been used. But they say the training sessions have not explained what the technology will be used for.
Reporters have been told to expect another round of training using an AI tool called “Story Cutter” which will edit and produce copy, effectively removing or reducing the need for subeditors.
The Media Entertainment and Arts Alliance said the AI programs were not only a threat to jobs but also threatened to undermine accountable journalism.
News Corp mastheads have certainly embraced the use of AI for illustrations recently; and in 2023 the company admitted producing 3,000 localised articles a week using generative artificial intelligence.
In March the company’s chief technology officer, Julian Delany, unveiled NewsGPT and described it as a powerful tool.
A News Corp Australia spokesperson told Weekly Beast: “As with many companies News Corp Australia is investigating how AI technologies can enhance our workplaces rather than replace jobs. Any suggestion to the contrary is false.”
The Guardian’s AI policy on the use of AI can be seen here.
Hostile reception for Origin
Kerry Stokes’ Seven West Media showed its disdain for the NRL on Thursday with a front-page headline in the West Australian which failed to mention the words State of Origin or NRL.
“One bunch of east coasters beat another at rugby in Perth last night”, the dismissive headline said. The report of the match was relegated to page 36 of the sports pages, despite the match being played in Perth.
View image in fullscreen The West Australian’s dismissive mention of State of Origin on page one. Composite: The West Australian
So why ignore a major event in your home town? Seven West Media has a $1.5bn deal with rival code the AFL, and the West Australian has actively campaigned against a new West Australian NRL team, the Bears.
While the newspaper claims the NRL is not popular in WA, the match recorded the highest-ever TV total audience for an Origin match in Perth, with 190,000 tuning in and 57,023 attending the match at Optus Stadium.
Seven West cuts
Journalists who work for Stokes at his newspaper empire had some bad news on Thursday in the form of an email with the dreaded words “operational review” and “redundancies” at West Australian Newspapers.
The company is offering voluntary redundancies across the West Australian, Perth Now, and the regional and community papers, and is asking for expressions of interest, by Friday 20 June.
On Tuesday, staff will be informed which roles will be made redundant and those folk will leave the same week. Editor-in-chief of WA Newspapers, Christopher Dore, has been approached for comment.
Breaking with tradition
On Monday, Australian Story will examine the Rachael Gunn story – but Raygun’s voice will not be heard after the breakdancer declined to participate.
While this is a departure for the award-winning program, which conventionally tells first-person stories, it’s not unheard of. Australian Story’s executive producer, Caitlin Shea, told Weekly Beast the format is broad enough “to examine ideas, issues, and cultural phenomena as well as the more personal profile”.
View image in fullscreen Raygun at the 2024 Olympic Games in Paris. Photograph: Elsa/Getty Images / ABC
Shea points to episodes that examined Cliff Young’s race, the ABC TV show Race Around the World and true crime stories about Kathleen Folbigg, the Somerton Man mystery and Lyn Dawson.
The episode is not a profile but “examines the Raygun phenomenon to try to understand why it created such a storm and why Gunn remains such a polarising figure”.
Giant of business journalism retires
After 45 years in journalism, 35 of them at the ABC, the broadcaster’s senior business correspondent Peter Ryan is retiring. Treasurer Jim Chalmers paid tribute to Ryan, calling him “an absolute legend” in a note to staff from news director Justin Stevens. “Every day as you wake up and you think about what’s happening in the economy, if you only needed to listen to one voice to be sure that you got its essential elements, it would be Peter’s,” Chalmers said.
Stevens said Ryan has metastatic thyroid cancer and is moving to palliative care, and focusing on his wife, Mary Cotter, and daughter Charlotte.
Recognised with the Order of Australia medal in 2022, Ryan has reported for flagship radio programs AM, The World Today and PM and his roles have included Washington bureau chief, head of TV news and current affairs in Victoria, executive producer of Business Breakfast and founding editor of Lateline Business.
His advice to colleagues: “Show up to work early and prove that you’re ready to take on the big story of the day. Try to have a Plan B in your back pocket just in case your original brilliant idea doesn’t go anywhere and the EP comes walking your way. Finally: Be kind and caring to people who need it.”
skip past newsletter promotion Sign up to Weekly Beast Free weekly newsletter Amanda Meade's weekly diary on the latest in Australian media, free every Friday Enter your email address Sign up Privacy Notice: Newsletters may contain info about charities, online ads, and content funded by outside parties. For more information see our Newsletters may contain info about charities, online ads, and content funded by outside parties. For more information see our Privacy Policy . We use Google reCaptcha to protect our website and the Google Privacy Policy and Terms of Service apply. after newsletter promotion
Trump on mic
Murdoch’s New York Post launched a new podcast this month from the “legendary political columnist Miranda Devine”, an Australian journalist who relocated from Sydney’s Daily Telegraph to New York in 2019.
An unashamed right-wing cheerleader, Devine’s first guest was unsurprisingly Donald Trump. Videos of Devine laughing in a cosy chat with the president in the White House have been shared widely on social media.
View image in fullscreen Miranda Devine writing about her interview with Donald Trump. Composite: The Advertiser
Among the scoops she claimed from the debut Pod Force One was Trump saying all rioters found to be burning the US flag should earn an “automatic” one-year jail sentence.
The chat started off with the following exchange.
Devine: “Mr President, thank you so much for doing this, our very first podcast, especially, I mean, I know how much you have on your plate. I mean, how do you juggle it all?
Trump: “I’ve got wars. I’ve got war and peace, and I have you. And I heard it was your first, so this is your first [podcast]. It’s gonna, it’s an honour to be on your show.”
When Trump falsely claimed Joe Biden allowed immigrants to come in to the US “from jails and prisons all over the world … [and] from mental institutions” Devine replied: “Why did he do that, it’s so destructive?”
ABC’s got it made
The ABC put out a media release this week announcing it was “delighted” Kyle Hugall had been appointed “Head of Made”.
There was little in the release to explain what this role at Made might entail or indeed what Made was, although Hugall was described as a creative leader who had worked in advertising.
The title reminded us of a letter written by senior presenters to the board in 2016 that condemned new layers of “preposterously named executives” which would have been at home in an episode of the ABC satire on bureaucracy, Utopia. Titles included “Head, Spoken” (Radio National manager) and “Classical Lead” (manager of Classic FM).
Non-state actor
Despite the failure of her “official” endorsement of Peter Dutton before the last election, Sharri Markson has issued her own symbolic sanctions on Anthony Albanese and Penny Wong.
“I’m going to start tonight by issuing my own symbolic sanctions against the two most damaging figures in the Albanese government, the prime minister and the foreign minister,” the Sky News Australia host said.
“I sanction Wong and Albanese for their antagonistic and extreme rhetoric which, over the past 20 months has only inflamed anti-Israel sentiment and contributed to the dangerous rise in antisemitism in our country.”
Distress and harm
An apparent suicide of a young man at a public place in the Adelaide CBD on Sunday has been extensively reported by the Advertiser, much to the dismay of the South Australian Police and the man’s family.
A spokesperson for the police told Weekly Beast that despite the police advising all media outlets on Sunday 15 June that the incident was “a mental health matter, and we will not be reporting on it any further”, some members of the media went ahead anyway and the family was “extremely distraught”.
The Advertiser published several stories in the newspaper and online, as well as a video. The content included multiple photographs of the location, the manner of suicide and the man’s private photographs.
The Australian Press Council has specific guidelines for the reporting of an individual suicide, which say it should only be done if it is in the public interest and the journalist has the consent of the family. The manner of suicide should not be disclosed. This individual was not a public figure.
Late on Thursday, with another article published in the Advertiser, the South Australian police took the unusual step “on behalf of [the] family” of asking the media to remove all the content.
We “formally request all media remove any articles, social media or any media relating to his death”, SA police said. “The reporting and media articles are causing further unnecessary distress and harm to the family and friends of [the deceased]. We trust that all media will adhere to this request on behalf of the family and actions its requests immediately.”
The editor of the Advertiser, Gemma Jones, and the editor of the Daily Mail, Felicity Hetherington, did not respond to requests for comment and the stories remain online at the time of publication.
| 2025-06-20T00:00:00 |
2025/06/20
|
https://www.theguardian.com/media/2025/jun/20/news-corp-bets-big-on-ai-tools-but-journalists-voice-concerns
|
[
{
"date": "2025/06/19",
"position": 25,
"query": "artificial intelligence journalism"
}
] |
Public Service Media and Generative AI
|
Public Service Media and Generative AI
|
https://www.publicmediaalliance.org
|
[] |
This page is a live resource, with the latest policies, guidelines, strategies and approaches being adopted by public service media – both PMA members and non- ...
|
As Generative AI becomes more prevalent and more integrated into media organisations, public service media carry a special responsibility to be transparent and responsible over how they manage the use of it. As multilateral efforts are underway to regulate AI, public broadcasters are already recognising its potential to improve their own processes and output. But PSM are also tempering such opportunism with caution about the potential ramifications of AI and how it might impact their own journalism and public trust in their journalism, as well as the information sphere more broadly.
As outlined below, many of the same concerns and hopes have been made by multiple broadcasters. Yet each organisation might demonstrate a different priority, or a different approach. Swedish Radio has established an AI Council, for example. Yle said it will only use Gen AI technology developed in Finland.
Read more: How public media is adopting AI
| 2025-06-19T00:00:00 |
https://www.publicmediaalliance.org/resources/public-service-media-and-generative-ai/
|
[
{
"date": "2025/06/19",
"position": 33,
"query": "artificial intelligence journalism"
}
] |
|
AI in Media and Entertainment: Top Use Cases You Need ...
|
AI in Media and Entertainment: Top Use Cases You Need To Know
|
https://smartdev.com
|
[
"Uyen Chu"
] |
In media and entertainment, AI technologies automate complex tasks like video editing, dubbing, and content curation. They also power innovations such as ...
|
Introduction
Media and entertainment face pressure to deliver high-quality, personalized content at scale, under tight budgets and compressing production timelines. Artificial Intelligence (AI) is rapidly emerging as the game-changing force – automating creative workflows, enhancing monetization, and unlocking new storytelling possibilities. This guide explores how AI is transforming the industry and what it means for decision-makers and content professionals.
As AI continues to redefine content creation, personalization, and production in media and entertainment, the real value emerges when these innovations are seamlessly integrated into scalable, real-world solutions. For organizations looking to accelerate digital transformation and creative agility, discover how AI-assisted software development can help turn cutting-edge ideas into impactful business results.
What is AI and Why Does It Matter in Media and Entertainment ?
Definition of AI and Its Core Technologies
Artificial Intelligence (AI) refers to computer systems capable of tasks that normally require human intelligence – learning, reasoning, generating content, and decision‑making – using methods like machine learning, natural language processing (NLP), and computer vision.
In media and entertainment, AI technologies automate complex tasks like video editing, dubbing, and content curation. They also power innovations such as personalized recommendations, synthetic media generation, and real-time translation to enhance both production efficiency and viewer engagement.
The Growing Role of AI in Transforming Media and Entertainment
AI is rapidly becoming foundational across the media and entertainment ecosystem. From pre-production to post-release, it is transforming how content is conceived, created, and consumed. Whether through script generation, automated editing, or audience targeting, AI is deeply integrated into daily workflows across studios, broadcasters, and digital platforms.
Streaming services like Netflix and Disney+ use machine learning to drive hyper-personalized content recommendations, directly influencing viewer retention and engagement. At the same time, sports broadcasters are embracing AI to generate real-time highlights and even revive iconic voices using synthetic voice technology. These tools not only enhance the viewer experience but also reduce turnaround time for content delivery.
AI’s impact is especially clear in editing and production speed. Tools like Moments Lab’s MXT‑2 can index and clip video content up to seven times faster than manual methods, supporting media giants like Warner Bros, Discovery and Hearst. As demand for rapid, high-volume content grows, AI is redefining what’s possible in terms of scale, efficiency, and creative agility.
Key Statistics and Trends Highlighting AI Adoption in Media and Entertainment
AI adoption in media and entertainment is accelerating rapidly, with the global market expected to grow from $19.8 billion in 2024 to $123.5 billion by 2033, at a CAGR of 22.6%. North America currently leads the sector with a 38% market share, while Asia-Pacific is the fastest-growing region. This growth is driven by AI’s role in automating workflows, enhancing personalization, and reducing production costs.
Generative AI has seen sharp adoption, rising from 33% to 71% usage among organizations between 2022 and 2024. Meanwhile, AI already influences around 69% of global ad revenue, with projections hitting 94% by 2029. These trends highlight a deepening reliance on AI to scale content production and monetization strategies.
Business Benefits of AI in Media and Entertainment
AI is solving some of the most pressing challenges in media and entertainment – streamlining operations, cutting costs, and enabling more dynamic audience engagement. Below are five core benefits driving adoption across the industry.
1. Streamlined Content Production
AI automates time-intensive tasks such as editing, tagging, and scene recognition, allowing teams to produce content faster with fewer resources. This significantly shortens production timelines, especially for high-volume or fast-turnaround formats.
By handling repetitive functions, AI frees creative professionals to focus on high-value work, enhancing both productivity and content quality. It also reduces dependency on large production crews or extended post-production phases.
2. Enhanced Personalization
Machine learning algorithms analyze user behavior to deliver highly personalized content recommendations. This improves user retention by keeping audiences engaged with relevant content tailored to their preferences.
Personalization also extends to marketing and advertising, enabling platforms to present users with promotions or messages that align with their viewing habits. The result is improved engagement and higher conversion rates.
3. Automated Localization and Accessibility
AI-driven translation and dubbing tools enable rapid localization of content for global audiences. This allows platforms to scale international distribution without the cost and time associated with manual processes.
Accessibility features such as automatic captioning and voice-to-text improve compliance and expand reach to underserved audiences. These tools make content more inclusive while supporting legal and regional standards.
4. Intelligent Metadata and Content Discovery
AI automatically generates metadata such as keywords, scene descriptions, and content summaries, improving content searchability and discoverability. This allows platforms to organize large libraries more efficiently and connect users with relevant material.
Improved metadata also supports internal analytics, making it easier to track performance trends and inform programming decisions. In turn, this enhances content strategy and overall catalog value.
Dive into our case study on AI-Driven Engagement Platform for a Journalism Marketplace to see how AI solutions can enhance content discovery and engagement through smart tagging and NLP.
5. Cost Efficiency and Operational Optimization
AI reduces operational costs by automating workflows that would traditionally require manual labor. These efficiencies are especially valuable in areas like editing, asset management, and quality control.
Over time, AI tools can scale operations without proportionally increasing headcount or infrastructure costs. This makes it easier for organizations to adapt to market demand while maintaining profitability.
Challenges Facing AI Adoption in Media and Entertainment
While AI offers powerful benefits, its implementation is far from seamless. Below are five key challenges that companies must navigate to adopt AI effectively and responsibly.
1. Intellectual Property and Copyright Risk
Training AI models often involves using copyrighted materials – scripts, audio, and footage – raising legal and ethical concerns. Without explicit permissions or licensing frameworks, companies risk litigation and reputational damage.
This creates uncertainty around how AI-generated content can be commercialized or distributed, slowing adoption across production environments. Organizations must balance innovation with legal compliance.
2. Quality Control and Content Integrity
AI-generated outputs, especially in visual and narrative formats, can suffer from inconsistencies or inaccuracies. Whether it’s disjointed dialogue or unnatural visuals, quality lapses can compromise viewer trust.
Maintaining a human-in-the-loop approach is essential to ensure creative standards and brand integrity are upheld. AI can support, but not fully replace, human judgment in content creation.
3. Ethical and Audience Trust Concerns
Synthetic media, such as deepfake voices or avatars, can blur the line between tribute and manipulation. Without transparent usage disclosures, audiences may feel misled or uncomfortable.
This raises broader ethical questions around consent, representation, and emotional authenticity. Clear guidelines and communication are necessary to retain viewer trust and respect audience sensitivities.
4. Talent Displacement and Labor Disputes
As AI automates roles in editing, localization, and writing, fears of job loss are intensifying across creative sectors. These concerns have already fueled pushback from industry unions and professionals.
Tensions around fair credit, compensation, and control over AI outputs are creating friction during adoption. Companies must address these concerns to ensure sustainable integration.
5. Technical Infrastructure and Integration Barriers
Deploying AI at scale requires robust data infrastructure, cloud computing capabilities, and seamless system integration. Many legacy production environments lack the technical foundation for AI implementation.
This creates significant upfront investment needs – both in technology and workforce training – which can be a barrier for small to mid-sized studios. Strategic planning and phased rollouts are critical to managing costs and complexity.
Specific Applications of AI in Media and Entertainment
1. Personalized Cont ent Recommendations
AI-powered recommendation systems help streaming platforms and media services cut through content overload by tailoring suggestions to each user’s behavior. They analyze vast datasets – viewing habits, ratings, search history, session times, and metadata – using collaborative filtering and deep learning to predict what users will enjoy.
These systems integrate seamlessly within user interfaces, updating recommendations in real time as users interact. They require robust data pipelines, model retraining, and privacy safeguards to adhere to data regulations. Strategically, they reduce churn and personalize experiences at scale, but they must manage bias and avoid creating echo chambers.
Despite privacy concerns, transparent opt-ins and anonymized data help strike a balance. Bias mitigation (e.g., on regional content) and continuous model tuning are critical. Ultimately, these systems offer efficiency, personalization, and significant ROI.
Real-World Example: Netflix employs its AI recommendation engine – analyzing user watch history, searches, and engagement – to personalize home screens. Powered by deep learning models built on member data, it’s credited with saving Netflix around $1 billion annually. This personalization contributed to Netflix reaching 260 million paid subscribers by Q4 2024.
Explore how AI shapes personalized customer experiences in our article on AI-powered virtual assistants.
2. AI-Powered Video Editing & Highlight Generation
Automated editing tools index raw footage using computer vision, audio analysis, and transcript data to identify key moments. By applying scene detection, audio sentiment, and keyword tagging, these systems generate highlight reels, trailers, and clips without manual effort. This speeds up production workflows, enabling media teams to produce highlights seven times faster and double social media revenue.
Integration into editing suites (e.g., Adobe Premiere) allows editors to refine AI-generated suggestions, ensuring creative control and final polish. However, these tools require quality metadata, robust training data, and scalable architectures to avoid biases and misidentifying important moments. Ethically, AI aids editors but need checks to prevent overreliance and preserve creative judgment.
Operationally, it slashes labor costs and supports rapid content repurposing across platforms. It also raises questions about IP, licensing, and the role of human oversight. The value lies in speed, consistency, and extended content reach.
Real-World Example: Moments Lab’s MXT‑2 uses multimodal AI to index footage and produce highlight reels up to 7x faster, helping clients like Warner Bros Discovery and Hearst increase social media revenue two-fold. The tool ingests video, audio, and metadata, generating clips ready for manual refinement. This drastically reduces editing time and accelerates content distribution.
3. Generative AI for Advertising & Creative Production
Generative AI transforms ad creation by drafting visuals, copy, and storyboards from text prompts. Leveraging GANs, transformers, and multimodal models, it helps marketers ideate and iterate quickly. The system digs into brand assets and trend data to maintain consistency across channels.
It integrates with ad platforms and design tools to auto-generate variants for A/B testing, reducing time and cost in campaign development. Key considerations include training data quality, brand alignment, and compliance with copyright standards. Organizations must balance creative freedom with content authenticity.
This drives strategic value through faster iteration cycles, enhanced targeting, and greater return on ad spend. Ethical concerns include creative homogenization and AI dependency, requiring human oversight. Despite this, the ROI appears compelling enough to spur fast adoption.
Real-World Example: WPP leveraged AI to produce a Super Bowl commercial in-house, using its WPP Open platform and acquired AI startups to automate creative tasks. The project slashed production costs and expedited timelines considerably. It illustrates generative AI’s ability to deliver high-profile, brand-safe advertising content at scale.
Dive deeper into AI-powered marketing with our article on redefining campaign performance with AI.
4. Virtual Influencers & AI-Generated Characters
Virtual influencers are synthetic personas powered by AI – visual generation, voice synthesis, and scripted interaction. They appear on social platforms, modeling brands and engaging fans around the clock. These digital avatars offer brands total control over content, brand safety, and availability.
They rely on CGI, generative models, and AI-driven responses to mimic human behavior. Key technical needs include lifelike visuals, scalable dialogue systems, and persona management. Ethically, transparency is vital users must know if they’re interacting with an AI.
This opens new marketing channels and revenue streams, enhancing brand storytelling. Virtual influencers deliver cost-efficient engagement but raise concerns about authenticity, consent, and job displacement. Firms using them must establish ethical guardrails.
Real-World Example: Aitana López, created by The Clueless, is a virtual influencer with over 250k Instagram followers, earning approximately €10k monthly. Built using CGI and AI persona tools, she partners with major brands and blurs the line between digital and human influencers. Her popularity showcases the commercial potential of virtual personas.
5. AI in Scriptwriting and Storytelling
Generative AI aids writers by producing outlines, character arcs, dialogue snippets, and scene descriptions. Models like GPT‑4 or Claude analyze story structures and genre conventions, offering ideas to overcome creative blocks. This accelerates the ideation phase and supports writer collaboration.
These tools ingest training data – scripts, story bibles, character sheets – and produce drafts for human refinement. Writers integrate prompts into their workflows to jumpstart plots or test dialogue options. They must manage quality control, originality, and potential copyright concerns.
Strategically, AI boosts productivity and supports diverse creative voices. Yet ethical considerations around authorship, bias, and de-skilling require careful oversight. When used responsibly, AI enriches, not replaces, the writing process.
Real-World Example: Studios use tools like ScriptBook and ChatGPT to predict script success and generate drafts. ScriptBook analyzes plot structure and character dynamics to estimate box office potential. Meanwhile, ChatGPT and Jasper help writers iterate faster, reducing draft time and enhancing creativity.
Learn about different AI model types and how to choose the right one for creative tasks in our detailed guide about AI model.
6. Real-Time AI in Live Gaming & Sports Broadcasting
AI enhances live events by providing real-time commentary, dynamic NPC interactions, and immersive analytics. Tools analyze live data feeds – stats, events, audio, video – to generate contextual insights, commentary, and game adjustments. This enriches viewer/player engagement with personalized, data-driven content.
In gaming, conversational agents (like NPCs) respond intelligently, driven by voice models and real-time data. In broadcasting, AI delivers fast analytics and narrative overlays. Challenges involve ensuring accuracy, maintaining tone, and avoiding disruptive errors live.
Operational advantages include scalable, engaging experiences and new monetization paths. However, oversight and error-checking remain essential. Effectiveness hinges on balancing real-time insight with creative quality.
Real-World Example: Warner Bros Discovery partnered with AWS to launch “Cycling Central Intelligence,” an AI platform that generates live insights during mountain bike races. Built on AWS Bedrock with Claude 3.5, it delivers real-time stats and narrative to fans. Meanwhile, Fortnite features AI-powered Darth Vader NPCs using voice synthesis, boosting player immersion.
| 2025-06-19T00:00:00 |
2025/06/19
|
https://smartdev.com/ai-in-media-and-entertainment-top-use-cases-you-need-to-know/
|
[
{
"date": "2025/06/19",
"position": 61,
"query": "artificial intelligence journalism"
}
] |
Redefining the workforce landscape in the future of work
|
Redefining the workforce landscape in the future of work
|
https://www.peoplematters.in
|
[
"People Matters Pte. Ltd."
] |
Today, every discussion of the world of work must cover Artificial Intelligence (AI) to be complete. AI is revolutionising the way we live and work. To get the ...
|
This web-site uses cookies to ensure you get the best experience on our web-site. By continuing you're agreeing our Terms & Conditions & Privacy Policy
| 2025-06-19T00:00:00 |
https://www.peoplematters.in/article/ai-and-emerging-tech/your-identity-as-a-worker-in-the-future-of-work-44173
|
[
{
"date": "2025/06/19",
"position": 71,
"query": "future of work AI"
}
] |
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