Multiple reports this week revealed that General Motors is cutting hundreds of jobs in its IT department—but not with the intent to replace them outright with AI. The layoffs are reportedly impacting about 600 employees, or about 10% of the IT team, and the job cuts are partly designed to allow the company to bring on new employees with specific AI skills.
General Motors has confirmed the layoffs and suggested they were part of a broader change to its IT operations. “GM is transforming its Information Technology organization to better position the company for the future,” a company spokesperson said in a statement. “As part of that work, we have made the difficult decision to eliminate certain roles globally. We are grateful for the contributions of the employees affected and are committed to supporting them through this transition.”
According to a TechCrunch report, General Motors is still hiring IT employees, but only those with the type of skills that would allow them to actually build AI systems rather than simply having the ability to use AI to be more productive.
These layoffs are not exactly unprecedented: Over 200 salaried employees at General Motors were laid off in the fall, along with about a thousand cuts to software jobs back in 2024. (A round of sweeping job cuts last year also affected thousands of factory workers.) Each week, yet another company justifies layoffs by citing AI, as tech companies sink endless resources into shoring up their AI investments. Coinbase, Cloudflare, and PayPal all just announced job cuts and at least partly attributed them to AI.
General Motors, for its part, has said little about why these layoffs were necessary, unlike the myriad employers who now explicitly reference AI. In a CNBC report, General Motors employees claimed they were notified about the job losses through a scripted video meeting with HR and were not given the opportunity to ask questions. But this round of layoffs appears to be another example of what AI-related job cuts may look like going forward: not simply slashing headcount due to productivity gains with AI, but also dismissing workers in favor of “AI natives” or employees with a particular skill set—and offering little explanation as that kind of disruption become increasingly common.