Nearly three years ago, shortly after OpenAI released ChatGPT-4, Sam Altman, the company’s C.E.O., suggested that the artificial-intelligence revolution could eliminate up to half of all existing jobs. “I think that’s good,” Altman said, at a Wall Street Journal conference. “I think that’s the way of progress. And we’ll find new and better jobs.” In May of last year, Dario Amodei, the C.E.O. of Anthropic, said that A.I. could destroy up to half of all entry-level positions and send the unemployment rate up to between ten and twenty per cent by 2030. So far, though, there’s little sign of job displacement on the scale that the two tech barons predicted. And Altman, for one, is backtracking. Speaking on a podcast last month, he admitted that the A.I. transformation was proceeding slower than he had expected, adding, “The economy just has so much inertia.”

Like everyone else, Altman can read economic statistics. The August job figures, which were released last Friday, showed that the economy created a hundred and sixty-two thousand jobs last month, more than Wall Street had expected, and that the nationwide unemployment rate stayed at 4.1 per cent—a low figure in historical terms. During the past couple of years, the rate has risen a bit, but many economists attribute this to slower economic growth and lower immigration, rather than A.I. destroying jobs. Since August, 2023, according to another government survey, layoffs and discharges have averaged about 1.7 million a month. That’s little changed from the average figure during the decade from 2010 to 2019.

To be sure, the impact of A.I. could be more concentrated, and one area many people believe it is showing up is in job prospects for recent college graduates. Between June of 2022 and June of 2026, joblessness in this group rose from 4.2 per cent to 5.7 per cent, pushing it above the over-all unemployment rate for the first time in decades. Some observers have linked this rise to businesses, such as tech giants and Wall Street banks, limiting their hiring and investing heavily in A.I. tools. But recent research suggests that A.I. isn’t the only factor affecting corporate-recruitment policies. A study from the Federal Reserve Bank of New York highlighted the spread of remote work, saying it has made some employers reluctant to add new workers to positions in which they won’t interact regularly with their colleagues. Another complicating factor is that whatever is impacting recent college graduates also seems to be affecting young people who don’t have a degree. In recent years, the jobless rate has risen for all Americans in the twenty-two to twenty-seven age group.

Something we know for sure is that A.I. use spreading is still spreading, and not just in the U.S. Earlier this year, the consulting firm McKinsey surveyed big businesses around the world and found that forty per cent of them are deploying A.I. agents, up from twenty-seven per cent last year. But the McKinsey study also confirmed that the impact on employment has been smaller than expected. In its 2025 survey, thirty-two per cent of respondents from organizations using A.I. said that they expected to see A.I.-related job cuts this year. In the latest survey, just fourteen per cent of respondents reported seeing actual A.I.-related job reductions. These findings jibe with the results of statistical analyses carried out by economists at the Yale Budget Lab using data on individual occupations. “The occupational mix is not yet changing in ways that clearly align with the introduction of AI into the workforce,” the Lab reported in a recent update.

How can these findings be explained? One possibility is that many professions may be more A.I.-resistant than first thought. In a new book, “Messy Jobs,” the economists Luis Garicano, of the London School of Economics, and Jin Li and Yanhui Wu, both of the University of Hong Kong, discuss jobs that are hard for A.I. models to displace because they involve a broader range of tasks than might appear at first glance. They cite radiologists as an example. When A.I. first came in, many observers thought they would be displaced en masse. That hasn’t happened, and that may be because, in addition to reading scans, radiologists also do things like talk to patients, coördinate with surgeons, and reach judgments on tricky cases—things that A.I. models may struggle with. Another factor to consider is that, for now, anyway, many professions that involve manual labor seem happily oblivious to A.I. Data from Anthropic shows that cleaners, carpenters, electricians, and plumbers account for virtually none of the usage of Claude, its A.I. system.

From an employment perspective, that’s good news. But A.I. and robotics are progressing by the month. Perhaps the hammer is still hanging over America’s knowledge workers; it just hasn’t fallen yet. Take the legal profession. In theory, generative-A.I. models can carry out some of the tasks that lawyers have traditionally undertaken, such as drawing up and checking documents, researching past cases, and even making legal arguments. (One recent blind test found that law professors preferred A.I.-generated answers to legal questions over those written by their fellow-professors.) And yet, according to the Bureau of Labor Statistics, the number of lawyers is stable, or even rising slightly. Last month, there were 1,245,900 people providing legal services in the U.S. That figure is up about half a per cent from a year ago, and it’s at roughly the same level as it was a decade ago.

But how long can this situation persist? Ultimately, client fees pay the salaries of all these lawyers, and, thanks to A.I., the fee structure is being challenged on at least two fronts. The legal world is awash with A.I. startups promising to transform the industry’s economics. And now Wall Street banks, which spend enormous sums on legal services, are demanding fee reductions from their lawyers. “If the number of hours they’re working on a matter has come down because of A.I. . . . our expectation is for costs to come down significantly per transaction,” Adam Meshel, Citigroup’s global head of legal, told the Financial Times. It seems likely that some law firms, to preserve their profit margins, will further automate their operations and reduce their head count, particularly at junior levels.

Law is merely one area where competition and the profit motive could make A.I. bite workers. Given the rapid development of cheaper open-weight models from China and elsewhere, it’s easy to imagine similar scenarios playing out in many other industries where cognitive tasks are central, such as consulting, finance, and publishing, not to mention coding, accounting, and data processing. Ever since the rollout of ChatGPT, there have been two scenarios for the impact of A.I. on workers: the technology could complement people’s skills and boost their productivity and wages, or it could render lots of skills obsolete and end up substituting for many workers entirely. Recently, concerns about the negative possibilities of A.I. prompted more than two hundred economists and researchers to sign a public letter calling on policymakers and tech leaders to “build the incentives, guardrails, and institutions needed to steer AI in a direction that complements humans and benefits society.”

One upside of many people in Silicon Valley overstating the speed of the A.I. revolution is that we may have a bit more time to introduce reforms that elevate the interests of workers, encourage firms to deploy A.I. in a positive manner, and make sure that the profits A.I. generates are widely shared. (On the existential question of safety, OpenAI’s Hugging Face saga suggests that time may be in considerably shorter supply.) Although there is no magic solution to the economic challenges that A.I. pose, economists have suggested a number of policies, including changing the corporate tax laws to favor investments in people over machines; exploiting the government’s procurement powers in areas where it’s a big spender on technology, such as health care and education; establishing federal jobs subsidies; and even a federal jobs guarantee. (In the political realm, of course, there is a growing movement to block or delay the development of data centers.)

But it’s not just a matter of preserving jobs in the age of A.I.: wage trends are also alarming. Twenty-five years ago, more than sixty per cent of all income that was created in the economy accrued to labor in the form of wages and other compensation. Now, even before the full effects of A.I. are felt, official figures show that the labor share has fallen to a historic low of 52.8 per cent. To be sure, some of this drop—perhaps a third—can be attributed to technical factors, including shifts in tax policy that have encouraged businesses to reclassify some labor income as capital income. But much of the fall reflects a genuine shift from wages to profits, which agentic models could accentuate. An A.I. apocalypse in the labor market doesn’t appear to be arriving on the schedule advertised by the likes of Altman and Amodei. But having a bit of breathing space is no excuse for inaction. ♦