As debate continues over AI’s true impact on the labor force, OpenAI CEO Sam Altman said some companies are engaging in “AI washing” when it comes to layoffs, or falsely attributing workforce reductions to the technology’s impact.
“I don’t know what the exact percentage is, but there’s some AI washing where people are blaming AI for layoffs that they would otherwise do, and then there’s some real displacement by AI of different kinds of jobs,” Altman told CNBC-TV18 at the India AI Impact Summit on Thursday.
AI washing has gained traction as emerging data on the tech’s impact on the labor market tells a muddied, inconclusive story about how the technology is destroying human jobs—or if it has yet to touch them.
A study published this month by the National Bureau of Economic Research, for example, found that of thousands of surveyed C-suite executives across the U.S., the U.K., Germany, and Australia, nearly 90% said AI had no impact on workplace employment over the past three years following the late-2022 release of ChatGPT.
However, prominent tech leaders like Anthropic CEO Dario Amodei have warned of a white-collar bloodbath, with AI potentially wiping out 50% of entry-level office jobs. Klarna CEO Sebastian Siemiatkowski suggested this week the buy-now, pay-later firm would reduce its 3,000-person workforce by one-third by 2030 in part because of the acceleration of AI. Around 40% of employers expect to follow Siemiatkowski’s lead in culling staff down the line as a result of AI, according to the 2025 World Economic Forum Future of Jobs Report.
Altman clarified he anticipates more job displacement as a result of AI, as well as the emergence of new roles complementing the technology.
“We’ll find new kinds of jobs, as we do with every tech revolution,” he said. “But I would expect that the real impact of AI doing jobs in the next few years will begin to be palpable.”
Signs of AI washing
Data from a recent Yale Budget Lab report suggests Altman and Amodei’s vision of mass worker displacement from AI is not certain and is not yet here. Using data from the Bureau of Labor Statistics’ Current Population Survey, the research found no significant differences in the rate of change of occupations’ mix or length of unemployment for individuals with jobs that have high exposure to AI from the release of ChatGPT through November 2025. The numbers suggested no significant AI-related labor changes at this juncture.
“No matter which way you look at the data, at this exact moment, it just doesn’t seem like there’s major macroeconomic effects here,” Martha Gimbel, executive director and cofounder of the Yale Budget Lab, told Fortune earlier this month.
Gimbel attributed the practice of AI washing to companies passing off diminished margins and revenue from a failure to effectively navigate cautious consumers and geopolitical tensions to AI. WebAI cofounder and CEO David Stout also wrote in a commentary piece for Fortune that tech founders are facing increased pressure to justify exorbitant and continued investment in AI, which is the reason why many have created narratives of AI disrupting labor and the economy through predictions of mass worker displacement.
This era of toe-tapping in wait for the effects of AI to take hold rhymes with the 1980s IT boom, according to Apollo Global Management chief economist Torsten Slok. Nearly 40 years ago, economist and Nobel laureate Robert Solow observed little productivity gains in the PC age, despite prognostications of a productivity surge, and Slok sees a similar pattern today.
“AI is everywhere except in the incoming macroeconomic data,” he wrote in a blog post last week.
Evidence of AI’s impact on jobs
Slok also said this lull in AI-driven economic impact could follow a J-curve of an initial slowdown in performance obscured by early mass spending before an exponential surge in productivity and labor changes.
Economist and Stanford University’s Digital Economy Lab director Erik Brynjolfsson said in a Financial Times op-ed recent labor data may be telling a new story of AI indeed impacting productivity and labor. He noted a decoupling of job growth and GDP growth reflected in the latest revised job numbers: Last week’s jobs report revised down job gains to just 181,000, despite fourth-quarter GDP tracking up 3.7%. Brynjolfsson’s own analysis revealed a 2.7% year-over-year productivity jump last year, which he attributed to AI’s productivity benefits beginning to peek through.
Brynjolfsson published a landmark study last year showing a 13% relative decline in employment for early-career employees with jobs with high levels of AI exposure. Most experienced workers, meanwhile, saw employment levels that remained stable or grew.
“The updated 2025 U.S. data suggests we are now transitioning out of this investment phase into a harvest phase,” he wrote in the FT, “where those earlier efforts begin to manifest as measurable output.”
