A Wall Street Journal survey of 16 economists, including Nobel laureate Daron Acemoglu, found a significant divergence in opinions regarding AI's net impact on the job market. While 15 of the 16 economists agreed that AI will meaningfully increase labor productivity, they were sharply divided on the question of whether AI will eliminate more jobs than it creates. Eight economists expect no net change in employment, five anticipate net job losses, and two foresee net job growth. This contrasts with data from Challenger, Gray & Christmas, which reported 38,579 AI-attributed job cuts in May, representing 40% of all announced cuts, while the Bureau of Labor Statistics simultaneously reported a gain of 172,000 payroll jobs in the same month.
Several economists offered differing perspectives. Jed Kolko, a Peterson Institute senior fellow, suggested that companies might be using AI as an excuse for layoffs due to prior over-hiring rather than actual AI-driven displacement. Conversely, Daron Acemoglu, who voted for net job losses, pointed to historical precedents like imports from China and robot adoption, which had negative, long-lasting displacement effects. Justin Wolfers of the University of Michigan echoed this, noting that AI specifically targets cognitive work, potentially impacting white-collar workers similarly to how blue-collar workers were affected in the 1970s. However, Torsten Slok, Chief Economist at Apollo, found "zero evidence" of AI-related job losses in weekly ADP employment data, arguing that the AI boom is creating demand for labor and driving up wages in key sectors.
The consensus among the surveyed economists and other experts was the critical need for better measurement and data regarding AI's impact. Erika McEntarfer, former BLS commissioner, noted that fewer than one in five U.S. firms use AI in any business function, suggesting limited current disruption. Stanford's Erik Brynjolfsson highlighted that while hundreds of billions of dollars are invested in AI deployment, less than 1% is spent on understanding its transition effects. Additionally, research by the Stanford Digital Economy Lab, using ADP payroll data, showed a 16% relative employment decline for workers aged 22 to 25 in AI-exposed occupations, while older workers in the same fields saw growth. Unemployment among recent college graduates currently stands around 5.6%, well above the rate for all workers, with early-career job postings down 12% from pre-pandemic levels.
