The ongoing dialogue regarding the ever-imminent displacement of white-collar workers by AI is predicated on the assumption that the technology will become as skilled as the very workers it threatens to displace, thereby cutting labor costs. But a new study found that’s not quite what’s playing out in many companies that have carried out AI-related layoffs.
A survey of 350 global business executives with an annual revenue of at least $1 billion by the research and advisory firm Gartner found that many have reduced their workforce irrespective of AI adoption. While 80% of those surveyed who have piloted an AI or autonomous technology have reported workforce reductions, the businesses cut jobs due to automation regardless of whether the technology was actually generating returns.
“Looking only at layoffs is shortsighted in terms of getting value from AI,” Helen Poitevin, VP analyst at Gartner and a key researcher of the study, told Fortune. “Chasing value only through headcount reduction is likely to lead most organizations down a path of limited returns.”
Similar data from a broader range of perspectives supports the conclusion that there;s a gap between AI adoption and successful implementation. Great Place to Work surveyed nearly 4,000 workers across 25 countries and found that while 82% of executives said that their company provides AI tools to help them do their job better, only 48% of frontline managers and just 38% of individual contributors said the same. At typical workplaces, only 15% of employees were change enthusiasts and 35% were open to change.
The looming threat of AI automation has many employees fearing for their jobs. But a growing number of business leaders and economists are skeptical that the technology will actually spur layoffs. Apollo chief economist Torsten Slok recently argued the Jevons paradox: a 19th century theory that explained why the demand for coal increased even as steam engines became more efficient and coal became cheaper. The paradox also applies to the AI age, Slok argued, and it predicts the technology will lead to more jobs, not less.
Poitevin said the companies reporting high ROI were not the same ones reporting AI-related workforce reductions. In fact, workforce reduction rates were nearly equal for those reporting higher ROI and those with smaller returns or even worsened outcomes from autonomous operations.
“That’s not where the value is,” she said of layoffs. “That’s not where the productivity gains are going to be.”
Instead, the study found companies with the highest gains were those using AI as a form of “people amplification,” implementing the technology to make workers more productive rather than outright replacing them.
There’s a growing divide today in how global business leaders are approaching AI adoption. In a separate Gartner survey of CEOs and other business executives, about one-third said they expect autonomous AI to help humans make decisions, but stop short of making those decisions independently. But another 27% said they expect AI to do exactly that, with minimal or no human involvement.
Anthropic CEO Dario Amodei recently walked back his controversial claim from last year that AI would wipe out half of white-collar entry-level roles. He instead said AI could augment work, referring to the Jevons paradox, though cautioning that AI is evolving at a faster rate than previous technologies and could consequently lead to different outcomes.
“When you strain a system more than, you know, than it’s usually strained, it’s possible you get these weird behaviors and this big disruption,” he said.
Layoffs attributed to AI have become a common practice, at least across Silicon Valley. Outplacement services company Challenger, Gray and Christmas found that AI was the leading reason for layoffs in March and April, and the total number of layoffs attributed to AI hit 49,135 for the full year. That’s nearly as much as the total for all AI-related layoffs the firm reported in 2025.
However, AI innovation isn’t the sole reason for layoffs in this category; layoffs attributed to heightened AI spending has become a trend across hyperscalers allocating a high percentage of their budgets on the AI infrastructure buildout. As a result, companies like Microsoft and Meta have said they needed to cut headcount to free up cash. There’s also the possibility that many of these layoffs are attributed to AI but are in reality inspired by other underlying motivations in a stunt known as “AI washing.” That’s what Sam Altman said in an interview earlier from February.
“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,” he said.
But Poitevin said the data shows these layoffs, even if related to AI, appear to be a way companies are testing the waters with AI rather than initiating a structural reset.
“It seems to us to be a kind of one-time exercise by many in small amounts,” she said, “but not what translates to getting full ROI from their AI investment.”
[This report has been updated to include Great Place to Work survey data.]
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