GM Cuts 600 IT Jobs to Hire AI-Specialized Workers: What It Means for the Future of Work

General Motors (GM) is cutting approximately 600 jobs in its IT department, representing about 10% of its IT workforce, according to multiple reports this week. The layoffs are not intended to replace these roles outright with AI but are part of a strategic shift to bring in employees with specialized AI skills.

The company has confirmed the job cuts, framing them as part of a broader transformation of its IT operations. “GM is transforming its Information Technology organization to better position the company for the future,” a company spokesperson stated. “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, GM is still hiring IT employees, but only those with the expertise to build AI systems rather than merely using AI tools for productivity. This approach reflects a growing trend among companies prioritizing AI-native talent over general IT roles.

These layoffs follow a pattern of job cuts at GM. In the fall, over 200 salaried employees were laid off, and in 2024, the company cut about 1,000 software jobs. Last year, thousands of factory workers were also affected by sweeping job cuts. The trend is not unique to GM: companies like Coinbase, Cloudflare, and PayPal have recently announced job cuts, often citing AI as a factor.

Unlike many employers who explicitly reference AI as the reason for layoffs, GM has provided little clarity on the necessity of these cuts. According to a CNBC report, affected employees were notified of the job losses through a scripted video meeting with HR and were not given the opportunity to ask questions.

This round of layoffs highlights a potential shift in how AI-related job cuts may unfold in the future. Rather than simply reducing headcount due to productivity gains from AI, companies may increasingly dismiss workers in favor of hiring employees with specialized AI skills—often with minimal explanation as such disruptions become more common.