U.S. employers are increasingly citing artificial intelligence as the primary reason for cutting jobs across the corporate sector [1, 4].
This trend signals a disconnect between corporate narratives and technological reality. While firms use AI to justify workforce reductions, experts suggest these decisions are driven by executive fear and a misunderstanding of how large language models actually function.
In May 2026, U.S. employers announced 97,000 job cuts [1]. This figure represents the highest number of May job cuts since 2020 [1]. While reports indicate AI is now the leading reason given for these reductions [1], some analysts argue that the technology is not the actual cause.
Thomas Roulet, a professor at Cambridge, said a high level of uncertainty is driving firms away from making "any" HR decisions [2]. According to Roulet, the underlying drivers are uncertainty and the fear of making the wrong move rather than a genuine technological necessity [2].
Devavrat Shah, an MIT professor and Celonis chief scientist, said enterprises have been pointing language models at problems they were never built for [3]. This misapplication of AI reasoning leads companies to reach incorrect conclusions about operational efficiency, and staffing needs.
Scientific consensus on the ability of AI to truly reason remains elusive. Quanta Magazine said the idea that artificial intelligence can "reason" is more intuitive than ever, but intuitions can be wrong and the science is far from settled [5].
These contradictions suggest that AI has become a convenient corporate shield. By blaming a perceived technological shift, firms can execute layoffs while appearing to follow an inevitable industry trend, even if the AI tools they employ lack the reasoning capabilities to justify such cuts [2, 3].
“Enterprises have been pointing language models at problems they were never built for”
The gap between the reported cause of layoffs and the technical reality of AI suggests a period of corporate volatility. Companies are not necessarily replacing humans with superior AI reasoning, but are instead reacting to market pressure and the fear of falling behind. This creates a risk where firms may erode their human capital based on a flawed understanding of AI's current capabilities.
