AI layoffs are looking more and more like corporate fiction that’s masking a darker reality, Oxford Economics suggests
Despite headlines warning of robots taking over the workforce, a new research briefing from Oxford Economics casts doubt on the narrative that artificial intelligence is currently causing mass unemployment. According to the company’s analysis, “companies do not appear to be replacing workers with AI on a large scale,” suggesting instead that companies may be using the technology as a cover for routine headcount reductions.
In a report released on January 7, the research firm claimed that although there is anecdotal evidence of job displacement, macroeconomic data do not support the idea of a structural shift in employment due to automation. Instead, he points to a more pessimistic corporate strategy: “We think some companies are trying to dress up layoffs as a good news story rather than bad news, like over-hiring in the past.”
Rotate the narrative
The primary motivation for recasting job cuts appears to be investor relations. The report notes that attributing headcount reductions to the adoption of AI “conveys a more positive message to investors” than acknowledging traditional business failures, such as weak consumer demand or “past overemployment.” By framing layoffs as a technology pivot, companies can present themselves as forward-thinking innovators rather than companies that struggle with cyclical downturns.
In a recent interview, Wharton management professor Peter Cappelli said: luck He’s seen research on how companies, because markets typically celebrate news of job cuts, announce “fake layoffs” that never actually happen. Companies were judging the stock market’s positive reaction to news of potential layoffs, but “a few decades ago, the market stopped rising because… [investors] I began to realize that companies weren’t actually doing the layoffs they said they were going to do.
When asked about the supposed connection between AI and layoffs, Cappelli urged people to look closely at the ads. “The headline is: ‘It’s because of AI,’ but if you read what they actually say, they say: ‘We expect AI to cover this business.’ I didn’t do that. They just hope. And they say it because that’s what they think investors want to hear.”
The data behind the hype
The Oxford report highlighted data from Challenger, Gray & Christmas, the recruitment firm that is one of the leading providers of layoffs data, to illustrate the disparity between perception and reality. While AI has been cited as the reason behind nearly 55,000 job cuts in the United States in the first 11 months of 2025 — representing more than 75% of all AI-related cuts reported since 2023 — that number represents only 4.5% of the total job losses reported.
By comparison, job losses attributable to record “market and economic conditions” were four times greater, totaling 245,000 jobs. When viewed against the broader backdrop of the US labor market, where between 1.5 million and 1.8 million workers lose their jobs in any given month, “AI-related job losses remain relatively limited.”
The productivity puzzle
Oxford posits a simple economic test for the AI revolution: If machines are truly replacing humans on a large scale, output per remaining worker should rise dramatically. “If AI is indeed replacing labor on a large scale, productivity growth should accelerate. But that is generally not the case.”
The report notes that recent productivity growth has actually slowed, a trend that is consistent with cyclical economic behaviors rather than an AI-led boom. While the company acknowledges that productivity gains from new technologies often take years to materialize, current data suggests that the use of AI remains “experimental in nature and has not yet replaced workers at scale.”
At the same time, recent data from the Bureau of Labor Statistics confirms that the “low-employment and fire” labor market is turning into a “no-jobs expansion,” Diane Swonk, chief economist at KPMG, previously said. luckEva Roitberg.
This is consistent with what Savita Subramanian, Head of Equity Research and Quantitative Strategy at Bank of America, said. luck In August about how companies in the 2020s learned how to replace people with processes in general. At the same time, she agreed that productivity measures “haven’t really improved much since 2001,” recalling the famous “productivity paradox” identified by Nobel Prize-winning economist Robert Solow: “You can see the computer age everywhere except in productivity statistics.”
The briefing also addresses concerns that artificial intelligence is eroding entry-level white-collar jobs. While US graduate unemployment rose to a peak of 5.5% in March 2025, Oxford Economics argued that this was likely to be “cyclical rather than structural”, citing an “oversupply” of degree holders as the most likely reason. The share of college-educated 22- to 27-year-olds in the United States rose to 35% by 2019, with steeper increases observed in the eurozone.
Ultimately, Oxford Economics concludes, labor market transformations are likely to be “evolutionary rather than revolutionary.”
This story originally appeared on Fortune.com
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2026-01-07 21:09:00
