“The launch of ChatGPT in 2022 ignited the artificial-intelligence boom — and elicited a chorus of warnings from AI bosses of an impending jobs apocalypse,” said The Economist in “Prepare for an AI jobs apocalypse,” the lead article in its May 16 issue. “Never mind that they have reason to talk up the disruptiveness of their products, or that rich-world employment is near all-time highs — the dark message has landed.”
Public anxiety about AI-driven unemployment has clearly been rising. Seven in ten Americans believe AI will make it harder to find work, while nearly one-third fear for their own jobs. The concerns have been amplified by a slowdown in hiring for recent college graduates, especially in technology-related occupations such as software development.
Yet, despite these fears, the historical record offers reasons for caution before concluding that AI will trigger mass unemployment.
“Labour markets constantly change,” noted The Economist. “Today’s offices would be unrecognisable to a worker from 50 years ago. Never in modern history has technological progress hurt the overall demand for human labour.”
The article points to the so-called Engels pause, the period from roughly 1790 to 1840 during the early Industrial Revolution when steam-powered mechanization transformed manufacturing. During those decades, British GDP expanded rapidly while working-class wages stagnated, fueling social unrest and movements like the Luddites, who destroyed textile machinery they believed threatened their livelihoods.
But more recent economic history suggests that technology itself was not the primary cause of stagnant living standards during that period. As The Economist noted in a related Money Talks newsletter, historians now attribute much of the hardship to high food prices driven by wars and trade policies rather than to automation directly reducing labor demand.
This historical perspective matters because it reminds us that technological change has repeatedly disrupted labor markets without causing permanent mass unemployment.
Americans are quite pesimistic about the impact of AI on jobs
“At no time in polling history have Americans been less optimistic about their long-term employment prospects,” wrote The Economist in a second article, “The jobs apocalypse: a (very) short history.” According to one survey, the average person believes there is a 22% chance of losing their job within five years — a higher level of anxiety than during the global financial crisis of 2007–09.
The fears are increasingly tied to AI. A 2025 Gallup survey found that nearly three-quarters of Americans expect A.I. to slash jobs. And, nearly one in five American workers recently told pollsters that AI or automation is “very” or “somewhat” likely to replace them.
Public anxiety has also been reinforced by statements from prominent AI executives. Anthropic CEO Dario Amodei has warned that AI could potentially drive unemployment rates to 10–20% within five years. Similarly, Sam Altman, CEO of OpenAI, has said that workers should expect significant changes in their roles as AI systems become more capable and widely adopted.
But economist are far less apocalyptic
Many economists reject the so-called “lump of labor fallacy” — the mistaken belief that there is a fixed amount of work in the economy. Throughout modern history, technological progress has simultaneously destroyed some jobs while creating new industries, occupations, and forms of work.
This question has long fascinated economists. If technology has been automating human labor for over two centuries, why hasn’t automation already eliminated most jobs?
MIT economist David Autor addressed this question in his influential 2015 paper, “Why Are There Still So Many Jobs? The History and Future of Workplace Automation.” The answer, Autor argued, reflects a fundamental economic reality: tasks that cannot be substituted by automation are often complemented by it.
Automation certainly replaces some human labor. But it also raises productivity, lowers costs, expands demand, and creates opportunities for new kinds of work. Discussions about automation often focus excessively on job substitution while underestimating the complementary relationship between technology and labor.
Most jobs consist of multiple tasks. Some tasks are relatively easy to automate, while others require judgment, creativity, interpersonal skills, or physical dexterity. Automating routine portions of a job does not necessarily eliminate the entire occupation. In many cases, automation increases the productivity and value of workers by allowing them to focus on the aspects of their jobs where human capabilities matter most.
Research on technology and employment has often emphasized the jobs lost to automation while paying less attention to the creation of entirely new occupations. To better understand this process, Autor and his collaborators — economists Caroline Chin, Anna Salomons, and Brian Seegmiller — analyzed the emergence of new work in the US economy over the past eight decades in their 2022 paper, “New Frontiers: The Origins and Content of New Work, 1940–2018.”
Their findings are striking. Roughly 60% of employment in 2018 consisted of occupations introduced since 1940. From 1940 to 1980, much of this new work emerged in mid-skill manufacturing, operations, administrative, and clerical occupations. But from 1980 to 2018, new job creation shifted increasingly toward high-skill managerial, professional, and technical occupations, alongside lower-paid service jobs involving physical and interpersonal tasks such as health aides, food services, and personal care.
So far, labor-market data does not show evidence of an AI-driven jobs collapse.
“The labour market certainly is not cracking yet,” said The Economist. Employment rates across OECD countries remain near record highs, unemployment is historically low, and the US continues to add jobs in many AI-exposed industries. The US Bureau of Labor Statistics projects that the economy will add more than five million jobs between 2024 and 2034.
But history is not always a reliable guide to the future. Today’s AI systems are improving at extraordinary speed. Advanced models can now perform coding, writing, research, and reasoning tasks that seemed out of reach only a few years ago. AI agents are proliferating rapidly, and business investment in AI infrastructure continues to surge.
There is little direct evidence in labor-market data that AI is destroying jobs at scale. But, given the pace of technological progress, The Economist cautions that it would also be unwise to dismiss the possibility of significant disruptions ahead. The more important question may not be whether AI eliminates work altogether, but how quickly labor markets, institutions, and political systems can adapt to large-scale economic reallocation.
What should governments do?
This raises difficult policy questions.
China, for example, has encouraged companies to deploy AI while discouraging layoffs. Other economists have proposed higher taxes on capital or levies on data centers.
Some proposals focus on slowing technological adoption. But attempts to significantly inhibit technological progress would likely prove counterproductive. AI has the potential to generate enormous benefits — not only economic growth and productivity gains, but also advances in healthcare, scientific discovery, climate research, and poverty reduction.
Had the Luddites succeeded in halting industrial automation two centuries ago, the world would almost certainly be far poorer today.
A more constructive approach would focus on helping workers adapt to economic transitions while ensuring that the gains from AI are more broadly shared. If AI substantially increases profits in sectors such as software, semiconductors, and cloud infrastructure, governments could explore tax reforms that capture a portion of these economic rents more effectively.
At the same time, stronger labor-market adjustment policies could help workers navigate disruptions. Wage insurance programs could cushion income losses during career transitions, while active labor-market policies — such as Denmark’s highly regarded retraining and job-placement programs — could help workers move into new occupations more quickly.
These policies would improve economic resilience and fairness regardless of AI’s ultimate impact on employment.
The jobs apocalypse may never arrive. But if governments wait for definitive evidence before strengthening social protections and workforce transition mechanisms, they may find themselves responding too late to potentially profound economic changes.
