AI Isn’t Causing Most Layoffs—But It’s Getting the Blame

AI-driven layoffs are increasingly used as a cost-cutting strategy, as illustrated by the graphic depicting the human impact and financial motives.

AI is increasingly being used as a convenient excuse for layoffs. A noticeable trend is emerging in the job market, with companies blaming job cuts on artificial intelligence, even when the technology isn’t the primary driver. This practice—often called “AI washing”—lets executives frame layoffs as innovation rather than acknowledge more common issues such as over-hiring, declining demand, or cost-cutting pressures.

Recent labor statistics highlight this shift. Challenger, Gray & Christmas reported more than 1.17 million U.S. layoffs in 2025, with nearly 55,000 explicitly attributed to AI. While that number has risen sharply, it doesn’t mean AI is replacing tens of thousands of workers. Most companies still lack the advanced, production-ready AI systems needed for large-scale automation. In many cases, the AI narrative is moving faster than the underlying technology.

This gap is creating unease among employees. Mercer’s Global Talent Trends research shows a significant rise in concerns about AI-driven job loss, even though actual displacement remains limited. When companies use AI as a blanket explanation for layoffs, it undermines trust and obscures the underlying business factors behind their decisions.

As a consultant, I see this disconnect firsthand. Many organizations are experimenting with AI, but few have implemented it at a level that justifies workforce reductions. The real challenge is aligning strategy, capability, and communication—ensuring AI is used responsibly and transparently, not as a convenient storyline.

How to Spot AI Washing in Layoff Announcements

Vague references to “future efficiencies.”

Vague references to “future efficiencies.”

If a company discusses AI’s potential without pointing to specific, deployed systems, the motivation is likely financial rather than technological.

Layoffs followed by rehiring.

When organizations cut roles citing automation but later hire similar positions—sometimes offshore or at lower wages—it indicates that AI wasn’t the true cause.

There is considerable hype surrounding AI that doesn't align with operational reality. While tech companies are often cited for AI-related layoffs, broader research indicates that there isn't significant displacement across the economy due to AI. The narrative frequently outpaces the actual evidence.

Another issue is the lack of investment in training and reskilling. Genuine AI transformation requires upskilling and process redesign. When companies overlook these crucial steps, "AI disruption" becomes a buzzword rather than a solid strategy.

A More Responsible Path Forward

In my consulting work, I help organizations distinguish genuine AI capabilities from hype. When leaders base decisions on evidence rather than buzzwords, they foster stronger teams, clearer communication, and more resilient operations.

In my upcoming post, I’ll outline what AI can realistically achieve by 2026 and where its limitations remain. The aim is straightforward: to cut through the noise and help leaders confidently navigate the future of work rather than feel apprehensive.