Artificial intelligence is supposed to transform the labor market. Depending on whom you ask, AI is either about to eliminate millions of jobs or usher in a new era of productivity and prosperity. I am reviewing the evidence before I teach an “unemployment” chapter…
I want to give a signal boost to economist Noah Smith, who has been following the emerging evidence about AI and employment at his blog, Noahpinion. His answer, so far, is that the evidence for widespread displacement is weak.
In his September 7 post, “AI keeps stubbornly refusing to take our jobs,” Smith points out a contrast. Many technology executives expect AI to make human workers obsolete, and public opinion surveys from Pew Research Center indicate that Americans share these concerns. Yet employment has held up remarkably well, especially among prime-age workers. AI might still take our jobs soon, but we have not seen widespread displacement yet. Economists have been saying for a long time that automating tasks is not the same thing as eliminating jobs.
In “Automation and New Tasks: How Technology Displaces and Reinstates Labor,” Daron Acemoglu and Pascual Restrepo explain that automation can reduce demand for labor performing particular tasks while also increasing productivity and creating new tasks for workers.
Consider software developers. AI can now write substantial amounts of code. One might conclude that fewer programmers will be needed. But programmers also design systems and decide what software should do. Making code less expensive could expand the amount of software that firms want to produce. Greater productivity may increase rather than decrease the demand for skilled programmers. (my old paper on who wants these jobs is “Willingness to be Paid: Who Trains for Tech Jobs?“)
Smith points readers to Guy Berger’s analysis of software developer employment and reporting on firms that have reconsidered replacing programmers with AI. These examples challenge the assumption that better coding tools necessarily mean fewer coding jobs.
One piece of evidence comes from the U.S. Census Bureau’s Business Trends and Outlook Survey, highlighted by Alex Tabarrok at Marginal Revolution and discussed by Smith. Among firms using AI, 44 percent reported that it supplemented or enhanced existing employee tasks. Ten percent reported that AI performed tasks previously done by employees, while 11 percent reported that AI introduced tasks nobody had previously performed. Most firms reported no employment change attributable to AI.
Smith also highlights research by Ara Kharazian, Jonathon Simon, and David Stevens who find that firms adopting AI tend to expand their employment, including entry-level employment. These findings contrast with the popular narrative that businesses are replacing junior employees with chatbots.
What about young workers?
Perhaps the strongest evidence for AI-related displacement comes from Erik Brynjolfsson, Bharat Chandar, and Ruyu Chen in “Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence.”
Their research finds that workers ages 22–25 in occupations highly exposed to AI have experienced weaker employment outcomes than older workers in those same occupations. Entry-level positions are where young people acquire experience and begin building their careers.
Smith examined the paper in his August 2025 post, “AI and jobs, again.” He asks: Why should AI reduce demand for young workers while employment among older workers in the same exposed occupations continues growing?
One explanation is that experienced employees have knowledge that complements AI, while younger workers perform tasks that AI can more easily substitute for. Smith subsequently points readers to Joshua Gans’s discussion of this possibility.
The newest evidence
In his October 1 roundup, Smith discusses new research by Robert Fairlie and Yuting Wu using Current Population Survey data. They find no statistically significant increase in unemployment among recent college graduates during the summer of 2026, whether compared with previous summers or with other demographic groups.
He also points to wage data from Indeed suggesting that workers in more AI-exposed occupations have recently experienced stronger wage growth than workers in less-exposed occupations. That result is difficult to reconcile with the simplest story of a large negative shock to labor demand, although differences across occupations and changing labor supply complicate the interpretation.
In contrast to the relatively stable employment patterns in several occupations widely predicted to disappear, digital media and creative employment have experienced serious declines. So, there is probably at least one group of workers who will experience sudden and severe consequences from AI adoption.
Thanks, Noah.
