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General Motors has laid off approximately 600 IT employees, representing over 10% of its IT workforce, to replace roles with workers skilled in AI development and engineering. The company aims to build an AI-native workforce to support its future initiatives.
General Motors has laid off more than 600 salaried IT employees, roughly 10% of its IT workforce, as part of a strategic shift toward AI-focused skills, confirmed by GM and first reported by Bloomberg News.
GM stated that the layoffs are part of a broader effort to transform its Information Technology organization to better position the company for future technological demands. The company emphasized that these layoffs are not all permanent reductions, as it continues to hire for new roles requiring advanced AI expertise.
Sources familiar with the matter told TechCrunch that GM is actively recruiting specialists in AI-native development, data engineering, cloud-based systems, and AI workflow engineering. The company seeks employees capable of designing AI systems, training models, and developing pipelines, rather than solely using AI as a productivity tool.
Over the past 18 months, GM has conducted multiple layoffs across various departments, including a recent cut of about 1,000 software workers in August 2024. The company has also made strategic hires, such as Behrad Toghi, an AI lead previously at Apple, and Rashed Haq, VP of autonomous vehicles with experience at Cruise, GM’s autonomous vehicle subsidiary.
Why It Matters
This development signals a significant shift in enterprise AI adoption, illustrating how large companies are not just adding AI tools but actively rebuilding their workforce to develop and deploy AI from the ground up. GM’s focus on AI-native skills highlights where industry demand is heading and underscores the importance of specialized expertise for future technological leadership.
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Background
GM’s restructuring follows a series of strategic moves over the past year, including leadership changes and consolidations within its software and AI divisions. The company’s efforts to integrate AI more deeply into its operations are part of a broader industry trend, where automakers and tech firms alike are prioritizing AI development to stay competitive in autonomous driving, data analytics, and smart manufacturing.
“GM is transforming its Information Technology organization to better position the company for the future.”
— GM spokesperson
“GM’s restructuring underscores a broader industry move toward rebuilding enterprise workforces around AI-native capabilities, not just adding AI tools on top of existing teams.”
— Kirsten Korosec, TechCrunch transportation editor
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What Remains Unclear
It is not yet clear how many of the laid-off employees will be replaced by new hires, or whether GM plans further layoffs. The specific timeline for the full transition to an AI-centric workforce remains uncertain, as does the impact on ongoing projects and overall company strategy.
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What’s Next
Next steps include GM continuing to hire specialists in AI and related fields to fill new roles, with future announcements likely to detail how these skills will be integrated into ongoing and new projects. Monitoring GM’s hiring trends and project developments will be key to understanding the full impact of this shift.
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Key Questions
Why did GM lay off so many IT workers?
GM laid off over 600 IT employees to replace roles with workers skilled in AI development, data engineering, and related fields, aiming to build an AI-native workforce for future technological needs.
Are the layoffs permanent?
GM stated that not all layoffs are permanent, as the company continues to hire for new roles requiring advanced AI skills, indicating a strategic workforce realignment rather than a simple reduction.
What kind of AI skills is GM seeking?
GM is looking for expertise in AI-native development, data engineering, cloud-based engineering, agent and model development, prompt engineering, and AI workflow engineering.
How does this reflect industry trends?
This move reflects a broader industry trend where large enterprises are actively rebuilding their workforce around AI capabilities, emphasizing the importance of developing AI systems from the ground up rather than just adopting AI tools.
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