Tech industry cuts 80,000 jobs in Q1 2026, with half of the layoffs attributed to AI

According to a new report from Nikkei Asia, citing an analysis from RationalFX, there have been approximately 78,557 layoffs in the tech industry so far this year. This covers the period running from January 1 to April 1, with the report also stating that nearly half, or around 37,638, of these job losses were directly linked to "AI implementation and workflow automation."

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However, one additional stat adds a new layer to these figures: 76.7% of these cuts occurred in the United States, meaning roughly 60,000 of the 80,000 tech industry layoffs were U.S.-based. And when it comes to jobs being lost to AI for productivity gains and roles that are seemingly becoming redundant, it's believed that a large portion of these cuts could be driven by the expectation that AI will improve productivity, rather than by actual data reflecting this.

"I don't know if they are directly related to actual productivity gains," said Babak Hodjat, chief AI officer at Cognizant, of the job cuts. "Sometimes, you know, AI becomes the scapegoat from a financial perspective, like when a company hired too many, or they want to resize, and it gets blamed on AI." And with that, it would still take up to a year before companies start seeing notable productivity gains from AI.

Of course, these figures reflect what we've been seeing and hearing in recent months, including tech giant Oracle cutting 10,000 or so jobs and statements from industry leaders like Anthropic CEO Dario Amodei, who says AI technology will eliminate half of the entry-level white-collar jobs in the U.S.

That said, the human touch is still required, according to Babak Hodjat. "The expectation is, AI will do everything, and so we really don't need a service company," Hodjat added. "It turns out, you do need that last mile to make all these systems work for an enterprise. There's going to be a ton of people that are coming out of school that can't find a job and don't have the domain expertise. You have to bring them in. You have to have them learn on the job, on how to use AI within the various different domains."