GM just laid off hundreds of IT workers to hire those with stronger AI skills

General Motors has laid off approximately 600 IT employees, over 10% of its IT workforce, in a strategic move to prioritize AI-focused skills. The company confirmed the layoffs to TechCrunch, first reported by Bloomberg, and stated they are part of a broader effort to transform its technology organization to better prepare for the future.

GM’s layoffs targeted staff whose expertise no longer aligns with the company’s evolving technological priorities. The company is actively hiring for roles requiring skills in AI-native development, data engineering, cloud-based engineering, and model training, emphasizing building AI systems from the ground up rather than merely using AI tools.

Sources familiar with the layoffs told TechCrunch that the company is still hiring for different roles within its IT department, indicating a skills shift rather than a pure headcount reduction. GM’s focus on AI has intensified over the past 18 months, including the departure of several top software executives and the hiring of new AI specialists such as Behrad Toghi from Apple and Rashed Haq from Cruise.

Why It Matters

This development signals a significant shift in enterprise technology strategies, with GM exemplifying how major companies are restructuring their workforce to integrate AI more deeply. It highlights the growing demand for specialized AI skills in the automotive and tech industries, and underscores a broader trend of companies rebuilding their teams around AI-native capabilities rather than traditional IT roles.

Background

Over the past 18 months, GM has been restructuring its software and technology divisions, including the departure of senior executives and the consolidation of its AI efforts under new leadership. The company’s hiring of AI experts and recent layoffs reflect a strategic pivot from traditional IT functions toward AI and autonomous vehicle development. Notably, GM’s move follows broader industry trends of increased enterprise AI adoption, driven by the need for more sophisticated data and model engineering.

“GM is transforming its Information Technology organization to better position the company for the future.”

— GM spokesperson

“The company is still hiring people for roles in its IT department, but for different skills, primarily in AI-native development and data engineering.”

— Source familiar with the layoffs

“GM’s restructuring is a signal of what enterprise AI adoption looks like in practice—building the workforce from the ground up for AI-native systems.”

— Kirsten Korosec, TechCrunch transportation editor

What Remains Unclear

It is not yet clear how long the layoffs will continue, whether GM plans further staff reductions, or how quickly the new AI-focused hires will ramp up the company’s AI initiatives. Details on the long-term impact on GM’s overall workforce and operational efficiency remain to be seen.

What’s Next

GM is expected to continue hiring specialists in AI, data engineering, and cloud systems to fill its newly prioritized roles. Monitoring the company’s AI development projects and organizational restructuring over the coming months will clarify how this shift impacts its technological capabilities and competitive position.

Key Questions

Why did GM lay off so many IT workers?

GM laid off over 600 IT employees to replace skills that no longer align with its strategic focus on AI development, data engineering, and cloud-based systems, as part of a broader organizational transformation.

Are these layoffs permanent?

It is unclear whether the layoffs are permanent or temporary. GM is still hiring for new roles, suggesting a skills-based realignment rather than a total workforce reduction.

What kind of AI skills is GM seeking?

GM is seeking expertise in AI-native development, data engineering, cloud-based engineering, model training, prompt engineering, and AI workflow design—skills necessary to build AI systems from the ground up.

How does this move compare to industry trends?

GM’s restructuring reflects a broader industry trend where large enterprises are rebuilding their workforce around AI capabilities, integrating AI deeply into core operations rather than using it as a supplementary tool.