AI and Jobs: Young Workers Face 16% Employment Drop as Automation Wave Targets Cognitive Work

AI and job losses: How the next automation wave will impact the workforce

AI is moving up the career ladder and targeting cognitive, analytical and creative tasks. The jobs most at risk now are no longer on factory floors, but in offices, campuses and the innovation hubs that were once thought to be insulated from any tech disruption. A study earlier this year from the Digital Planet initiative at Tufts University shows how the wave of anticipated job losses in the next three to five years will look different from the past. The study's American AI Jobs Risk Index ranks 784 U.S. occupations in 20 industry sectors across metropolitan areas and states, assessing their vulnerability "based on the most current understanding of AI's evolving impact." The study shows why AI's advancement is not just about the speed of adoption, but its reach. Professor Bhaskar Chakravorti, dean of global business at Tufts' Fletcher School and one of the researchers behind the study, told CNBC that the findings reflect a labor market paradox. Most expendable The more AI helps you do your job, the more expendable you become. "The parts of the country or the jobs that are most helped by the technology are also the ones that are most hurt by it," Chakravorti said. "If you're in high tech, you are also doing exactly the kind of work that AI is getting better and better at doing," he said. "Many of those roles will be displaced. But then the people who remain in the jobs, including writers and authors, are going to become more productive, because technology is going to be a very powerful assistant." The Tufts study argues that AI risk to particular jobs doesn't mean such jobs are less valuable. Instead, the risk derives from AI becoming increasingly good at performing such core tasks as writing, coding, summarizing, researching, analyzing and even generating first drafts. Over the next two to five years, the study found that some of the most vulnerable occupations include writers and authors (57%), computer programmers (55%) and web and digital interface designers (55%). The largest total income loss is borne by software developers, management analysts, market research analysts and marketing specialists, reflecting their high salaries and the number of workers. Younger workers first Research performed at the Stanford Digital Economy Lab suggests the earliest labor-market effects may already be appearing among younger workers. Using ADP payroll data on millions of workers, the study late last year examined the employment effects of AI. "The clearest signal in our data: young workers who are in AI-exposed occupations" are the most vulnerable, Erik Brynjolfsson, director of the Stanford lab and co-author of the report, entitled " Canaries in the Coal Mine " told CNBC in an email. "It's the overlap, not one or the other." The study found that employment for early-career workers ages 22 to 25 in the most AI-exposed occupations had fallen 16% relative to their peers. "Older workers in those same occupations are largely holding steady," Brynjolfsson said. One possible reason is that AI can replace the kind of formal knowledge younger workers often bring to a job, while helping experienced workers apply judgment built over time. "AI is a substitute for book knowledge, which a new grad brings," Brynjolfsson said. "It's a complement to tacit knowledge, what experience builds." The declines, according to Brynjolfsson, are more concentrated where AI automates work or substitutes for what junior employees do. In jobs where AI assists workers, entry-level employment has held up and in some cases even grown. In a study of customer service agents published last year in The Quarterly Journal of Economics, Brynjolfsson and others found that the least experienced workers gained the most from AI assistance, improving productivity by 34%, compared to a wider average of 14%. Disruption not replacement The current wave of automation differs from previous eras because generative AI targets cognitive work. "Steam engines hit muscle work and earlier software hit routine clerical work," Brynjolfsson said. "But generative AI helps with many cognitive tasks -- writing, coding, analysis -- the bread and butter of well-paid knowledge work. That's new." Still, he warns against thinking that whole job categories will disappear. "No job is a single task," Brynjolfsson said. "Even the most exposed occupations have plenty of tasks that AI can't do. The key to understanding the changes is to focus on the task-based approach, not whole jobs." Neither the Tufts nor the Stanford study predicts millions of jobs will evaporate overnight. Instead, they identify where AI is most likely to reshape daily work. Health care is one example. The Tufts study shows that physicians, including cardiologists and psychiatrists, appear less exposed despite their higher salaries. "As far as healthcare professionals are concerned, there is a degree of augmentation of their work that is going to happen because of AI, as opposed to displacement," Chakravorti, the Tufts professor, said. "What you will see is that technology is potentially freeing up time for many healthcare professionals, and they can continue to basically serve more patients and do more work in the same time period," he said. Less demand, more productivity Overall, the research suggests AI will reduce demand for workers in some cases, while making employees more productive in others. Brynjolfsson said the lesson from history is not that labor-market disruption should be dismissed, but that outcomes are shaped by choices. "In the long run, industrialization made us vastly richer and created far more jobs than it destroyed," he said. "But the transition took decades, and for a generation ordinary workers' wages moved only slowly while output soared. This wave is moving much faster than the earlier waves did." "The key lesson from history isn't 'don't worry,'" Brynjolfsson said. "It's that outcomes depend on choices -- by companies, policymakers, and workers. That's why we should think of the effects of technology on work as a design problem, not a prediction problem." For now, the full effects are still in their early stages. Brynjolfsson said most workers have not yet fully adopted generative AI at work. "Most workers still barely use these tools," he said. "The labor market effects we're measuring now are the leading edge, not the full wave."

AI Is changing work faster than the data can keep up | Fortune

Recent studies have shown AI having a positive impact on job growth and opportunities, yet large groups of economists, as well as labor activists, warn that the emerging technology threatens to quickly transform the financial system, and that action must be taken now. Tech companies, especially large ones, have continued to cull jobs during the AI boom. Microsoft laid off nearly 5,000 people in early July as it continues to pour billions into AI data centers. The layoffs added to earlier downsizing by the software giant and moves by companies that include Amazon and Oracle to shed thousands of people in the last two years. But whether AI is directly leading to job cuts has been difficult to measure, and the picture is blurred by corporate whiplash: CEOs blame AI for layoffs one month, then hail it as an engine for new job creation the next. Even recently, some of the largest companies, such as Google parent Alphabet, have reportedly told investors they plan to increase headcount. "There's been discretion out there as to what extent the layoffs we have been observing are really driven by AI," Till Von Wachter, a professor of economics at the University of California, Los Angeles, told Fortune. "It's been notoriously hard to pin that down." The latest U.S. jobs report, which revealed that employers unexpectedly cut 23,000 jobs in July, has only added to the confusion. Some economists, such as Ben Zipperer from the Economic Policy Institute, said AI's impact on jobs has so far been more limited than what some doomsday scenarios initially predicted. The latest U.S. jobs report, which revealed that employers unexpectedly cut 23,000 jobs in July, as only added to the confusion. And some recent data has shown a bullish picture. A recent study by financial services firm Ramp of more than 21,000 U.S. firms found that companies that invested in AI grew their headcount. Ramp categorized its heaviest AI spenders as "high-intensity" adopters. Over two years, these top spenders expanded their overall staff by 10% and boosted entry-level hiring by 12%, defying other reports that college graduates face a barren job market. By contrast, the bottom two-thirds of adopters saw no headcount growth at all. Though the study found general AI adopters tended to be larger firms, the most intense adopters were smaller companies which might already be growing regardless of AI and are more open to experimentation. High-intensity companies were utilizing more advanced tools like coding agents or APIs (protocols that allow various applications to communicate). The Ramp study has parallels to a recent report by researchers at Google that found AI so far is mostly being used as a collaborative tool rather than an outright job-replacer. Meanwhile, a June California Policy Lab study found no statewide spike in unemployment insurance claims among AI-exposed roles like software developers and customer service reps since ChatGPT's release in late 2022, but it did find elevated UI claims specifically for college-educated workers in highly-exposed roles, as well as a significant increase in claims from high-exposed roles in the San Francisco area. The Big Tech companies "definitely overhired during the pandemic and are now making the decisions to correct that overhiring," Ara Kharazian, lead economist at Ramp, told Fortune. Some are "blaming it on AI. But what we're seeing from firms that are using AI that didn't have that overhiring problem is that they're continuing to grow." He added that although many firms in his study were fast-growing to begin with, they grew even faster following AI adoption. AI washing or AI cloaking? Untangling AI's true impact could take years, stymied by a phenomenon researchers call "AI washing," where companies attribute layoffs to AI to seem forward-thinking, or the opposite trend, where companies avoid mentioning AI for fear of public outcry. Much existing research has had to rely on estimating which tasks could potentially be accomplished by AI, or indirect surveys rather than actual spending or usage records. Some companies may also be hiring at the same time others are displacing workers, according to UCLA's Wachter. Yet despite some positive results, both economists and on-the-ground workers are calling attention to the negative impact AI is already having on the labor market. In July, nearly 200 economists and researchers published a statement warning that AI could cause large-scale job displacement in the next decade. "This could drive an unprecedented transformation of our economy, larger than the Industrial Revolution, but unfolding over a vastly shorter time frame," the statement says. Its signatories include Anthropic co-founder Jack Clark and Eric Schmidt, Google's former chief executive. The statement calls on policymakers to "act now" to better understand how AI is transforming the economy and to create legislation that will "steer A.I. in a direction that complements humans and benefits society." A 2025 report co-authored by Stanford economist Erik Brynjolfsson, one of the organizers of the recent statement from economists and researchers, analyzed ADP workforce data and found that workers aged 22-25 in AI-exposed roles such as software engineering suffered a 16% relative employment drop compared to less-exposed peers. Responding to the Ramp study, Brynjolfsson in June wrote on X that firms that adopt AI "may grow by gaining market share from non-adopters, so employment can rise among adopters even as exposed occupations shrink economy-wide." Kharazian, the Ramp economist, said when looking outside the high-intensity, high-growth part of Ramp's study, the company didn't find job gains, but it also didn't find broad job loss. Rank-and-file employees remain worried about the impact of AI, a spokesperson for Amazon Employees for Climate Justice, an advocacy group of current and former Amazon employees, told Fortune. Amazon Chief Executive Andy Jassy said about a year ago that AI would lead to a leaner workforce, but in February said that AI could ultimately fuel job creation, and he has framed Amazon's layoffs as an attempt to flatten its organizational structure. The company cut about 30,000 jobs between the end of 2025 and the start of this year. Far from making work easier, employees are feeling a "huge increased pressure" from Amazon executives to finish tasks faster using AI, the ACJ spokesperson said. AI tools have also made the demand for output higher. An Amazon spokesperson said the company expects employees "to use all available resources -- including AI tools -- to help them be even more effective and have an even bigger positive impact on our customers' lives" but said AI has not been the reason behind the majority of its layoffs, that AI adoption isn't a factor in deciding layoffs, and that while some roles may be reduced, entirely new categories of jobs will emerge. Amazon, Microsoft, and Oracle have all laid off thousands of workers as they spend billions on AI infrastructure. In a June filing, Oracle said its layoffs of thousands during the past year were tied to AI. Changing their tunes In addition to Amazon's Jassy altering his messaging on AI killing jobs, other high-profile CEOs have softened previous comments. OpenAI Chief Executive Sam Altman had long predicted that AI would lead to huge changes in the workforce, but in May said the company had been wrong about how much "people would continue to be at the center of everything." Anthropic Chief Executive Dario Amodei in June wrote that his earlier comments about AI eliminating jobs were not meant to be a "prophet of doom," but rather a call for policymakers to plan and adapt. Mustafa Suleyman, the head of Microsoft's AI lab, earlier this year predicted that most tasks that involve "sitting down at a computer" would be fully automated by AI within the next year or 18 months, though he later tempered his stance. Industries may handle their workforces differently based on a variety of factors. Some companies have taken aim at middle managers as the companies seek to be more nimble. Dave Clark, founder of AI logistics startup Auger and a former senior Amazon executive, said with the help of AI, his team of roughly 80 engineers now performs with the velocity of 800 engineers. While some data highlights risks for early-career workers, Clark said he's observed senior staff who can dive deep on specific tasks and curious new graduates who "sand off the edges" of AI output showing the clearest value during the AI age. But mid-level engineers may have the toughest time because they may be less inclined to experiment with new AI-driven workflows, he said. "The future state is less about your ability to be a precise expert on transportation or warehousing or something else, and more about your ability to understand how systems connect and work together," Clark said. "That makes me hopeful about it because I think that's much more enjoyable human work."

Vanguard Chief Economist: AI and jobs, still in an ATM phase | Fortune

Every wave of technological change seems to arrive with a familiar prediction: This time, jobs are going away for good. The effect of automated teller machines (ATMs) on the bank teller profession reveals a more nuanced reality. When ATMs became widespread in the 1980s, many people assumed bank tellers would soon become obsolete. They were only partially correct. The number of tellers needed at individual branches did decline to some degree as ATMs automated routine tasks. Yet the broader employment outcome was less stark than feared. By lowering operating costs, ATMs made it economical for banks to open more branches. As a result, total U.S. bank teller employment remained broadly stable from 1980 through 2010. For a mid-career teller in the 1980s, the ATM posed far less of a threat to employment than many forecasts suggested. New demand for more occupations In fact, just as we expect artificial intelligence to transform the labor market, the expansion of retail banking created demand for a wider range of occupations. Banks hired more loan officers, credit analysts, personal bankers, and fraud and risk specialists. The work performed inside a branch moved up the skill-value chain. Branches became less about processing transactions and more about managing customer relationships. The real disruption came later. Beginning around 2010, mobile banking changed the equation. Unlike the ATM, which automated a task, mobile banking largely automated the entire trip to a bank. Customers no longer needed to visit a branch for many everyday banking activities. By 2025, only 9% of bank customers said branches were their primary banking channel, compared with 36% in 2007. Bank teller employment fell accordingly. Importantly, this transformation was not driven by technology alone. The Electronic Signatures in Global and National Commerce Act of 2000 gave electronic signatures the same legal standing as ink signatures, helping to enable fully digital banking experiences and accelerate the shift away from in-person transactions. The lesson is that isolated task automation rarely results in large-scale job losses, except in occupations built around a very narrow set of activities. (There aren't many switchboard operators left.) More often, meaningful disruption occurs when technologies are combined with new workflows, business models, and institutional changes that fundamentally alter how work is organized. The disruption caused by mobile banking included the creation of entirely new forms of employment: cybersecurity analysts, digital product managers, payment-platform engineers, and data-platform operators. This history offers a useful lens for understanding today's debate around AI. If AI becomes a general-purpose technology like electricity and the personal computer before it -- as developments increasingly suggest -- it will enable products, services, and industries that we have not yet envisioned. In short, fears of widespread job loss are likely overblown. The myth of large-scale white-collar job loss Since ChatGPT's arrival in late 2022, many people have argued that AI will quickly eliminate large numbers of white-collar jobs. Nearly four years later, the labor market tells a different story. Occupations with the greatest exposure to AI have not experienced widespread employment declines. Employment growth in highly exposed occupations has generally kept pace with -- or exceeded -- that of less exposed occupations. Layoff rates remain low, and although hiring has slowed, the slowdown has been broad-based rather than concentrated in AI-intensive fields. Today's large language models may be reminiscent of the ATMs of the 1980s -- powerful tools that automate certain tasks but augment many more, making workers more productive and leaving the broader structure of work largely intact. More significant labor market disruption may require something closer to the shift from ATMs to mobile banking: a deeper reconfiguration of business processes, organizational structures, and customer interactions that reshapes the role of workers rather than removing them from the equation. The history of technological change suggests capabilities alone rarely determine employment outcomes. What matters more is how organizations redesign work around those capabilities. AI may ultimately transform the labor market, just as mobile banking transformed retail banking. But the evidence today suggests we remain closer to the ATM phase than the mobile banking phase. The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.