As the debate over AI’s true influence on the labor force continues, OpenAI CEO Sam Altman stated that some organizations are engaged in “AI washing” when it comes to layoffs, which is the practice of erroneously attributing staff cutbacks to the technology’s impact.
At the India AI Impact Summit on Thursday, Altman told CNBC-TV18, “I don’t know what exactly the 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.”
AI washing has become more popular since new information concerning the technology’s effects on the labor market presents a hazy, conflicting picture of whether or not human employment are being destroyed by the technology.
For instance, according to a study released this month by the National Bureau of Economic Research, nearly 90% of the thousands of C-suite executives polled in the U.S., the U.K., Germany, and Australia stated that AI had no effect on workplace employment during the three years after ChatGPT was released in late 2022.
However, well-known tech executives, such as Dario Amodei, CEO of Anthropic, have warned of a white-collar carnage, with AI perhaps eliminating 50% of entry-level office positions. This week, Sebastian Siemiatkowski, CEO of Klarna, proposed that the buy-now, pay-later company would cut its 3,000 employees by one-third by 2030, partly due to the rapid advancement of artificial intelligence. According to the 2025 World Economic Forum Future of Jobs Report, almost 40% of companies anticipate that they will eventually follow Siemiatkowski’s example of laying off employees due to AI.
Altman clarified that he expects AI will result in significant employment displacement as well as the creation of new positions that complement the technology.
“As with every tech revolution, we’ll find new kinds of jobs,” he declared. “However, I anticipate that in the coming years, the actual effects of AI performing jobs will start to become noticeable.”
AI washing indicators
Altman and Amodei’s prediction of widespread job displacement from AI is uncertain and has not yet materialized, according to data from a recent Yale Budget Lab paper. From the launch of ChatGPT until November 2025, the study used data from the Bureau of Labor Statistics’ Current Population Survey and found no discernible variations in the length of unemployment or the pace of change in the mix of vocations for people with high exposure to AI. The data indicated that there are now no appreciable labor changes connected to AI.
Martha Gimbel, executive director and creator of the Yale Budget Lab, told this month that regardless of how you interpret the data, there don’t appear to be any significant macroeconomic repercussions at this time.
Gimbel ascribed the practice of AI washing to businesses using AI to cover up lower profits and revenue from their inability to successfully handle wary customers and geopolitical concerns. WebAI cofounder and CEO David Stout also stated that tech founders are under more pressure to defend high and ongoing investments in AI. As a result, many have constructed stories about AI upending labor and the economy by predicting the mass displacement of workers.
According to Torsten Slok, chief economist of Apollo Global Management, this period of waiting for the effects of AI to become apparent is comparable to the IT boom of the 1980s. Slok observes a similar trend now to economist and Nobel laureate Robert Solow, who over 40 years ago noted that despite predictions of a productivity boom, productivity gains in the PC era were little.
Last week, he stated on his blog that “AI is everywhere except in the incoming macroeconomic data.”
Proof of AI’s effect on employment
This gap in AI-driven economic impact, according to Slok, may follow a J-curve, which shows an initial performance slowdown masked by early mass spending followed by an exponential increase in productivity and labor changes.
Economist Erik Brynjolfsson, director of Stanford University’s Digital Economy Lab, suggested that fresh labor data might be revealing a different story about how AI indeed affecting labor and productivity. He saw a decoupling of job growth and GDP growth shown in the most recent corrected job numbers: Last week’s jobs report lowered job increases to 181,000, despite a 3.7% increase in fourth-quarter GDP. Brynjolfsson’s own investigation indicated a 2.7% year-over-year productivity increase last year, which he attributed to AI’s productivity gains starting to show.
Last year, Brynjolfsson released a groundbreaking study that revealed a 13% relative drop in employment for early-career workers in positions with heavy exposure to AI. In contrast, the majority of seasoned workers saw either stable or increasing employment levels.
He commented in that “the updated 2025 U.S. data suggests we are now transitioning out of this investment phase into a harvest phase where those earlier efforts begin to manifest as measurable output.”
