General Motors has laid off more than 10% of its IT department, affecting nearly 600 salaried employees, as the company shifts its focus toward AI-driven technology roles.
The automaker confirmed the layoffs and said the move is part of efforts to prepare its Information Technology division for the future. “GM is transforming its Information Technology organization to better position the company for the future,” the company said in a statement.
According to reports, the layoffs are part of a broader restructuring strategy aimed at replacing outdated skill sets with AI-focused expertise. While some employees were removed, the company is reportedly continuing to hire for new technology roles.
GM is now prioritising professionals with experience in AI-native development, data engineering, analytics, cloud-based engineering, model and agent development, prompt engineering and AI workflows.
The company is reportedly seeking workers who can build AI systems from the ground up, including designing infrastructure, training models and developing AI pipelines, instead of simply using AI tools for productivity.
Over the past 18 months, General Motors has carried out multiple rounds of white-collar layoffs as it increases investments in AI and other strategic areas. In August 2024, the company cut nearly 1,000 software jobs.
The restructuring accelerated after Sterling Anderson, co-founder of autonomous trucking startup Aurora, joined GM as Chief Product Officer in May 2025. Anderson reportedly led efforts to merge the company’s separate technology divisions into a single organisation.
Last November, several senior software executives exited the company, including Baris Cetinok, Dave Richardson and former Chief AI Officer Barak Turovsky.
General Motors has since added new AI-focused leadership hires. The company appointed former Apple executive Behrad Toghi as AI lead in October and hired Rashed Haq, previously associated with Cruise, as Vice President of Autonomous Vehicles.
Industry observers say GM’s restructuring reflects a wider shift in enterprise AI adoption, where companies are redesigning teams and hiring structures around AI-first operations and advanced automation capabilities.
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