Altman stated during the India AI Impact Summit that a phenomenon known as “AI washing” exists – meaning companies blame layoffs on technology even when workforce reductions were planned independently of it. He added that real displacement of some roles by AI is already occurring, but the scale of both trends is difficult to measure.
His remarks come as a National Bureau of Economic Research study indicates that nearly 90 percent of surveyed senior executives in the United States, United Kingdom, Germany, and Australia reported no noticeable impact of AI on employment in their companies during the three years since ChatGPT’s launch in late 2022. The findings align with economists’ observations suggesting that macroeconomic effects of the technology are not yet visible.
Some industry leaders, however, present far more alarmist forecasts. Dario Amodei of Anthropic previously warned of the potential elimination of up to half of entry-level white-collar jobs, while Sebastian Siemiatkowski announced that Klarna plans to reduce its workforce by one third by 2030 partly due to accelerating automation. A 2025 World Economic Forum report, meanwhile, found that about 40 percent of employers expect staff reductions in the future because of AI.
Data from the Yale Budget Lab, based on labor market statistics, has not shown significant changes in employment structure or unemployment duration in occupations most exposed to automation since the debut of generative AI. The institute’s director, Martha Gimbel, said there is currently no clear evidence of large macroeconomic effects tied to the technology.
Some analysts attribute the layoff narrative to investor pressure and the costs of implementing AI. David Stout argued that tech founders face growing pressure to justify massive spending on the technology, which encourages messaging about its supposedly immediate impact on the labor market.
Economists see a historical parallel. Apollo Global Management chief economist Torsten Slok noted that the current situation resembles Nobel laureate Robert Solow’s observation from the 1980s, when computers were widespread but productivity gains were not visible in statistics. Slok said that today “AI is everywhere except in the macroeconomic data.”
Other researchers see early signs of a shift. Erik Brynjolfsson, in an analysis published in the Financial Times, pointed to a divergence between GDP growth and employment trends as well as a 2.7 percent year-over-year productivity increase that he attributed to AI’s influence. In his earlier research, he also recorded a 13 percent relative decline in employment among entry-level workers in highly automatable occupations, while employment levels among more experienced workers remained stable.
Altman concluded that in the coming years AI’s impact on the labor market will become more noticeable, but – as with previous technological revolutions – new professions and roles supporting AI systems will also emerge.