Being laid off due to AI’s efficiency savings is a fear of many workers, with more than 40% saying they will face some form of AI-induced anxiety in 2026. according to a Mercer study. But AI may not be as big a cause of layoffs and layoffs as companies adopting them might claim, and even when they are, it could be too much and far too soon, according to several news sources. research collected by Sherwood.
Big layoffs, big claims
In all, Challenger data suggests more than 1.2 million employees have been laid off in 2025, representing the highest rate of job cuts since 2020. Many of these have been driven by government layoffs, particularly with regard to the short-lived DOGE initiative led by Elon Musk.
Of that larger total, companies specifically cited AI as the reason in about 55,000 cases, with Challenger reporting about 72,000 AI-related job losses since 2023. There was a more than 1,100% year-over-year increase in 2025, suggesting a huge shift in that direction and perhaps indeed a real trend of AI replacing workers.
But not so fast, as new reports suggest that some of these employers may be using AI as an excuse to cover up for underperforming companies. This “AI-washing” can be a convenient excuse to cut spending in a way that, to investors, appears to be a more positive development than it otherwise would have been.
False alarm?
This trend was first identified by an LSE study in the first half of 2025, which revealed that many companies in the agricultural sector claimed to be using AI, but were not doing so at all. Even those who did were often augmenting humans with AI rather than replacing them with it, and yet that didn’t stop them from talking about their use of AI to appear more innovative than they actually were.
CNBC made similar statements in November last yearciting pricing 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 these layoffs.
In January this year, Forrester published a report which suggests that, despite the grandiose claims of AI developers, he estimates that only 6% of jobs in the United States will be automated by 2030, suggesting that widespread replacement of jobs by AI is extremely unlikely. In fact, he even predicts that the majority of job losses attributed to AI so far and in the near future will likely be reversed as companies realize the challenges of effectively implementing AI.
As for those who left out purported AI improvements, this suggests that it is often more the financial situation of the company that determines the decision, rather than technical innovation. While this suggested that customer service, software developers, and junior technical positions were most under AI pressure, it was rare that companies announcing AI-related layoffs had a mature AI solution to effectively fill these roles.
It concludes that to realize the full potential of AI, businesses should invest in human employees and their training to get the most out of new technologies, rather than replacing them outright.
Oxford Economics found similar results in its January reportsuggesting that while AI was cited as a reason behind some layoffs, the majority were more often affected by traditional economic and business factors. This suggests that if AI were already replacing work on a large scale, we would see an increase in productivity to account for it, but there is little sign of this so far.
Further research on The budget laboratory suggests that economic and employment trends that predate the introduction of AI into the workplace are far more impactful. Its data so far suggests that “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 that there are few differences in employment patterns for the 20-24 and 25-34 age groups. If AI disrupted entry-level positions on the scale some have suggested, we would expect recent graduates to have more difficulty finding employment. But its data suggests that this is simply not the case and that the trends are largely similar to what they were a decade ago – although it suggests that its smaller sample size might be hiding broader trends.
“The picture of AI’s impact on the labor market that emerges from our data largely reflects stability, not a major economy-wide disruption,” he concludes.
Shoot for the future
Even when companies that have legitimately laid off employees or eliminated certain positions due to what they see as efficiency savings and AI performance improvements, the data often suggests they have taken the plunge. In a survey carried out in December 2025 by the Harvard Business Reviewwhere more than 1,000 executives from various global companies were surveyed, the results suggest that the vast majority of business changes driven by AI were due to expected future potential rather than existing evidence of improvement.
More than 600 of the executives surveyed said they made layoffs at their companies 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. 29% of respondents said they have reduced their hiring rates due to anticipation of what AI will be able to do in the future. Only two percent of respondents said they had made mass layoffs due to the effective implementation of AI.
This would certainly match previous research we’ve seen. MIT reported in August Last year, more than 95% of generative AI deployments in businesses failed to deliver any tangible improvement to profits or losses.
It’s not nothing, but it’s not much either
Despite data suggesting that layoffs in the AI sector are overstated or overestimated, and perhaps not realistic in hard numbers, they exist. I lost my job because the places I wrote for used AI to write their blog posts for them. Major publications let many journalists go because AI research summaries impacted traffic.
Large industries are having to pivot and change because of AI, and workers are being left behind. But not on the scale that AI companies have sold us on, and maybe we don’t need to be as nervous as we might otherwise be.
AI is changing things, but not as much as it seems.