Yale Budget Lab Report: Data Doesn’t Show AI Is Disrupting the Job Market, Raising Questions About ‘AI-Washing’ to Justify Mass Layoffs
Anxieties about AI costing people their jobs are growing intense: A from August 2025 found 71% of Americans feared permanent job loss due to AI. Last week, announced , bringing the total to more than 30,000 job cuts since October 2025. The action aligned with Amazon’s push toward AI development, though the tech giant attributed the reductions to an effort to slash bureaucracy, not the technology.
A recent from the Yale Budget Lab supports Amazon’s claim that these mass cuts—even at tech companies—aren’t the result of AI displacing workers.
“While anxiety over the effects of AI on today’s labor market is widespread, our data suggests it remains largely speculative,” the report said. “The picture of AI’s impact on the labor market that emerges from our data is one that largely reflects stability, not major disruption at an economy-wide level.”
To gauge AI’s effect on the labor force, the Yale Budget Lab tracked occupational mix—shifts in the types of jobs U.S. workers hold—as well as unemployment duration for roles with high exposure to AI.
Though there have been changes in occupational mix since ChatGPT’s 2022 release, the rate of change hasn’t been high enough to signal a massive shift, the report noted. In addition, the length of unemployment for individuals in AI-exposed jobs stayed consistent over time. Both metrics showed no evidence of large-scale labor disruption, from AI or any other factor.
“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 .
‘AI washing’ in action
The Yale Budget Lab’s claim contrasts with other data some have interpreted as a sign of massive labor upheaval. An released in November 2025 found current AI systems can already handle tasks for nearly 12% of the workforce. Goldman Sachs predicted could be displaced if AI technologies become widely adopted.
These forecasts don’t reflect today’s reality, despite growing concern over AI-related job losses. The gap between AI anxiety about job displacement and data showing the opposite has raised concerns about “,” or falsely blaming AI for company layoffs.
An last month backed this idea, citing data from outplacement firm Challenger, Gray & Christmas: While 55,000 U.S. job cuts in the first 11 months of 2025 were attributed to AI, they made up just 4.5% of total reported cuts. By contrast, job losses from standard “market and economic conditions” totaled 245,000.
“We suspect some firms are trying to dress up layoffs as a good news story rather than bad news, such as past over-hiring,” the Oxford report said.
According to Yale Budget Lab’s Gimbel, one reason companies blame AI for layoffs is to avoid telling investors they struggled with declining immigration, tariffs, and other policy uncertainties that inevitably disrupt the labor force. AI-related anxiety has made the technology a convenient scapegoat for CEOs facing skeptical investors.
“If you’re a CEO, what are you going to say? ‘Hi, I’m a really bad CEO. I totally mismanaged the macroeconomic situation for the last couple of years, so now a bunch of you are going to have to lose your jobs, but shareholders should keep trusting me moving forward?’” Gimbel said. “No, you’re not going to say that. You’re going to say, ‘The world is changing quickly, and we’re going to rightsize the company and make investments moving forward so we can be the most productive version of ourselves to win the future.’”
What’s really happening with the labor market?
She noted it’s far more realistic to link the low-hire, low-fire labor market conditions to the myriad political factors shaking up the economy, as well as the aftereffects of the and the that naturally slowed the job market.
To be clear, economic constraints could impact how quickly new technologies are implemented—providing a blueprint for when AI might begin to heavily affect labor, Gimbel suggested. During the first Industrial Revolution, for example, led mill owners to rush to invest in technologies like the power loom and spinning jenny that automated weaving and displaced workers.
“Technological change does not happen in a vacuum,” she said.
AI’s next big test in the labor market will be a recession, Gimbel said—something that would force changes incentivizing mass AI adoption. According to PwC data, AI adoption and productivity gains , with 56% of companies reporting they get “nothing out of” AI yet.
If AI causes major changes to the job market, Gimbel said, it will show up in massive shifts in the mix of jobs people hold and longer unemployment for those with high exposure to AI in their previous roles. Until then, she noted, it’s not time to sound the alarm.
“If you think the AI apocalypse for the labor market is coming, it’s not helpful to declare that it’s here before it’s here,” she said. “Any of this can change. That’s why we’re tracking it … Just because a technology can do something doesn’t mean that everyone loses their jobs tomorrow. It doesn’t mean they won’t lose their jobs in five years, though.”