General Motors recently announced it is laying off hundreds of employees from its technology team. According to a CNBC report, affected workers claim the company ended their employment through unexpected 15-minute virtual meetings, a pre-written message from human resources, and an abrupt disconnection. Employees described receiving calendar invites for unusual times, only to find themselves on short calls where their roles were terminated with minimal interaction.
Employee Reactions to the Layoff Process
A data analyst who worked for over a decade at GM told CNBC, “No appreciation or empathy. No questions. Nothing.” Two employees familiar with the process said the meetings followed a consistent pattern: a brief introduction, a scripted statement from HR, and immediate termination of access. Workers reported no opportunity to ask questions or seek clarification.
The layoffs come as GM reshapes its teams around artificial intelligence (AI) capabilities. The company is cutting between 500 and 600 salaried employees, primarily from its information technology division across locations including Austin, Texas, and Warren, Michigan. These cuts represent more than 10% of GM’s IT workforce.
Shift Toward AI
Several employees noted their teams had undergone recent changes, and they had been encouraged in recent months to incorporate AI tools into their daily workflows. A veteran programmer and data scientist at GM told CNBC, “They’re going to push AI for everyday work and everything else. I’ve seen it firsthand. It can make you much more productive as a programmer. It can really help you get more work done, but AI isn’t going to do you any good if you don’t know the business.”
While the job cuts may appear cost-driven, they align with a broader shift in hiring strategy. GM is actively recruiting talent focused on AI-native development, data engineering, and cloud-based infrastructure, indicating a transition away from traditional IT roles. In a statement, the company said, “GM is transforming its Information Technology organisation to better position the company for the future.”
Industry watchers refer to this as a “skills swap,” as companies fill roles tied to legacy systems with those who build and deploy AI systems in-house. Businesses are looking for employees who can build models, manage data pipelines, and design AI-driven workflows, rather than relying on third-party tools.
