As debates persist regarding AI’s actual influence on the labor force, OpenAI CEO Sam Altman stated that some companies are engaging in a practice where they falsely link workforce reductions to the technology’s impact during layoffs.
“I’m not sure of the exact percentage, but there’s what we call ‘AI washing’ where people blame AI for layoffs they would have made anyway, and then there’s actual displacement of various jobs by AI,” Altman said during the India AI Impact Summit on Thursday.
AI washing has become more prevalent as emerging data on the tech’s impact on the labor market paints a confused, inconclusive picture of whether the technology is already destroying human jobs or will do so in the future.
For example, a report published this month by the National Bureau of Economic Research found that among thousands of surveyed C-suite executives in the U.S., UK, Germany, and Australia, there was no significant change in workplace employment over the past three years since the release of ChatGPT in late 2022.
However, prominent tech leaders such as Anthropic CEO Dario Amodei have warned of a potential white-collar bloodbath due to AI. Klarna CEO Sebastian Siemiatkowski suggested this week that the buy-now, pay-later firm would reduce its workforce by 2030, in part because of the acceleration of AI. According to the 2025 survey, around 40% of employees expect to follow Siemiatkowski’s lead in reducing staff due to AI.
Altman clarified that he expects more job displacement due to AI, as well as the emergence of new roles that complement the technology.
“We’ll find new types of jobs, as we do with every technological revolution,” he stated. “But I expect the real impact of AI taking over jobs in the next few years will start to be noticeable.”
Signs of AI washing
Data from a recent study suggests that Altman and Amodei’s vision of mass worker displacement due to AI is not certain and has not yet occurred. Using data from the Bureau of Labor Statistics’ Current Population Survey, the research found no significant differences in the rate of change of occupation mix or length of unemployment for individuals in jobs highly exposed to AI from the release of ChatGPT through November 2025. The numbers indicated no significant AI-related labor changes at this point.
Martha Gimbel, executive director and co-founder of the Yale Budget Lab, said earlier this month.
Gimbel attributed the practice of AI washing to companies shifting diminished margins and revenue, which resulted from failing to effectively navigate cautious consumers and geopolitical tensions, onto AI. WebAI founder and CEO David Stout also wrote in an article that tech founders face increased pressure to justify exorbitant and ongoing investments in AI, which is why many have created narratives of AI disrupting labor and the economy through predictions of mass worker displacement.
This period of waiting for the effects of AI to materialize is similar to what chief economist Torsten Slok describes. Nearly 40 years ago, economist and Nobel laureate Robert Solow observed little productivity gains during the PC age despite predictions of a productivity boom, and Slok sees a similar pattern today.
“AI is everywhere except in the incoming macroeconomic data,” he wrote in an article last week.
Evidence of AI’s impact on jobs
Slok also said this lull in AI-driven economic impact could follow a J-curve, where initial slow performance is masked by early massive spending before a rapid surge in productivity and labor changes.
Economist and director of Stanford University’s Digital Economy Lab Erik Brynjolfsson said in a statement that recent labor data may be telling a new story of AI truly impacting productivity and labor. He noted a trend reflected in the latest revised job numbers: last week’s job report revised job gains down to just 181,000, despite fourth-quarter GDP tracking up 3.7%. Brynjolfsson’s own analysis showed a 2.7% year-over-year productivity increase last year, which he attributed to AI’s productivity benefits starting to become evident.
Brynjolfsson published a study last year showing a 13% relative decline in employment for early-career employees in jobs highly exposed to AI. Meanwhile, most experienced workers saw stable or growing employment levels.
“The updated 2025 U.S. data indicates that we are now moving from the investment phase to the harvest phase,” he wrote in the Financial Times, “where those earlier efforts start to show as measurable output.”