Being laid off due to AI efficiency savings is a fear held by many workers, with over 40% claiming to be dealing with some form of AI-induced anxiety in 2026, according to Mercer research. But it may be that AI isn’t as big a cause of layoffs and redundancies as the companies enacting them might claim, and even when they are, it might be too much and far too soon, according to multiple sources of research collated by Sherwood.
Big layoffs, big claims
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In total, Challenger data suggests over 1.2 million employees were let go in 2025, marking the highest rate of job cuts since 2020. Many of these were led by government redundancies, particularly with regards to the short-lived DOGE initiative headed by Elon Musk.
Of that larger total, firms specifically cited AI as the reason for them in around 55,000 cases, with Challenger reporting around 72,000 AI-related job losses since 2023. There was over a 1,100% increase year-on-year in 2025, which suggests an enormous swing in that direction and perhaps indeed, a genuine trend that AI is replacing workers.
But not so fast, because new reports suggest some of these employers may be using AI as an excuse to cover for underperforming businesses. This “AI-washing” may be a convenient excuse to cut expenses in a way that, to investors, sounds like more of a positive development than it might otherwise be.
False alarm?
This trend was first called out by research from LSE in the first-half of 2025, which found that many companies within the agriculture industry were claiming to use AI, but weren’t at all. Even the ones that did were often augmenting humans with AI rather than replacing them with it, and yet it didn’t stop them from talking up their AI use to seem more innovative than it actually was.
CNBC made similar claims in November last yearciting tariff and trade uncertainties, as well as a turbulent economy overall, as more likely reasons for layoffs than the AI-inspired layoff claims made by many of the companies behind them.
In January this year, Forrester put out a report suggesting that, despite the grandiose claims by AI developers, it estimates only 6% of US jobs will be automated by 2030, suggesting that widespread AI job replacement is extremely unlikely. Indeed, it even projects that the majority of job layoffs attributed to AI so far and in the near future are likely to be reversed as companies realise the challenges of effectively implementing AI.
As for those let go over claimed AI improvements, it suggests that often it’s more the case of company financials driving the decision, rather than technical innovation. Although it did suggest that customer service, software developers, and junior technical positions were under the most pressure from AI, it was rare that companies announcing AI-related layoffs had any kind of mature AI solution to fill those roles effectively.
It concluded that to fully realise the potential of AI, companies would need to invest in human employees and their training to help make the best use of the new technologies, rather than replacing workers with it outright.
Oxford Economics found similar results in its report from Januarysuggesting that although AI was being cited as a reason behind some layoffs, the majority were more commonly affected by traditional economic and business factors. It suggests that if AI were already replacing labor at a grand scale, we’d be seeing an increase in productivity to account for it, but there’s little sign of that so far.
Other research out of The Budget Lab suggests that economic and employment trends that predate the introduction of AI into the workplace are much more impactful. Its data so far suggests, “there is no substantial acceleration in the rate of change in the composition of the labor market since the introduction of ChatGPT.”
It even highlights how there is little difference in employment patterns for age groups 20 to 24 and 25 to 34. If AI were disrupting entry-level positions on the scale some suggest, it would be expected to see recent graduates struggling more for employment. But its data suggests that just isn’t the case and that patterns are largely similar to how they were a decade ago – though it does suggest that its smaller sample size may be hiding larger trends.
“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,” it concludes.
Firing for the future
Even when companies that did legitimately let people go or make certain positions redundant because of what they see as AI efficiency savings and performance improvements, often the data suggests they’ve jumped the gun. In a survey conducted in December 2025 by the Harvard Business Reviewwhere over 1,000 executives were polled at various global companies, the results suggested the vast majority of changes made to businesses because of AI were because of expected future potential rather than existing evidence of improvement.
Over 600 of the polled executives claimed to have made layoffs at their businesses in anticipation of what AI will be able to do in the future, rather than because of anything it can do, or has done recently. Another 29% of those polled said that they had reduced their hiring rates because of the anticipation of what AI will be capable of down the line. Only two percent of those polled said they had made large layoffs because of actual AI implementation.
This would certainly track with previous research we’ve seen. MIT reported in August last year that over 95% of generative AI deployments at businesses fail to make any kind of tangible improvement to profit or loss.
It’s not nothing, but it’s not a lot either
Despite the data suggesting that AI-layoffs are overstated, or over-reported, and maybe not realistic in any tangible numbers, they do exist. I have lost work because places I wrote for now use AI to write their blog posts for them. Major publications have let go of many reporters because AI search summaries have impacted traffic.
Major industries are having to pivot and change because of AI, and workers are missing out. But not on the grand scale that AI companies sold us on, and maybe we don’t need to be quite as nervous as we otherwise might be.
AI is changing things, but not as much as it may seem.
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