New AI-Native Talent Is Replacing Legacy IT Roles at GM

General Motors has laid off more than 10% of its IT department, roughly 600 salaried employees, but this is not the typical “AI is taking jobs” story that has dominated headlines over the last two years. GM is not broadly replacing workers with chatbots or using AI primarily as a cost-cutting mechanism. The company is removing roles tied to older enterprise IT structures while aggressively hiring for entirely different capabilities tied to AI-native development, cloud engineering, autonomous systems, data infrastructure, and model development.

The distinction is important because it shows how enterprise AI adoption is beginning to move beyond productivity software and automation tools.

Companies like GM are starting to reorganize themselves around AI-first technical architectures, building teams designed specifically for AI systems, agents, and machine-learning workflows rather than retrofitting older organizations to accommodate them.

Instead of simply asking employees to use AI, companies are searching for workers who know how to build with it from the ground up.

Why It Matters: GM’s restructuring may be one of the clearest examples yet of how enterprise AI adoption is changing workforce strategy in real time. Rather than layering AI tools onto existing organizations, companies are rebuilding portions of their workforce around entirely new technical competencies. The move shows where enterprise hiring demand appears to be heading: AI engineering, autonomous systems, cloud-native infrastructure, data orchestration, and agentic workflows.

• A Strategic Skills Swap: Sources familiar with the restructuring say the automaker is replacing workers whose expertise no longer aligns with its long-term strategy. Traditional enterprise IT and software management roles are increasingly being replaced by AI engineering, cloud-native development, model operations, and autonomous systems capabilities.

• AI Builders Wanted: GM’s hiring focus centers on engineers capable of architecting AI infrastructure from the ground up, including designing autonomous agents, building models, engineering data pipelines, and deploying AI-native workflows across the enterprise. The shift points to a growing divide between AI-assisted productivity work and AI-native engineering roles.

• Leadership Overhaul Continues: Since Sterling Anderson joined GM as chief product officer in 2025, the company has consolidated several technology divisions and reshaped leadership across software and AI. Multiple senior executives overseeing software engineering, services, and AI strategy departed during the transition, while GM simultaneously recruited AI-focused talent from companies including Apple and Cruise.

• Part of a Larger Trend: Oracle recently announced thousands of layoffs while continuing to expand AI infrastructure and data center spending, while Amazon eliminated thousands of jobs as it committed roughly $100 billion toward long-term AI infrastructure and machine learning expansion through AWS. Companies including Microsoft, IBM, Salesforce, CrowdStrike, and Workday have also announced workforce reductions tied to AI-driven operational changes and automation initiatives. Challenger, Gray & Christmas reported that AI-related restructuring contributed to more than 54,000 layoffs across major U.S. technology firms in 2025.

• ROI Questions Remain: Gartner recently found that while nearly 80% of organizations deploying autonomous technologies reported workforce reductions, those cuts did not consistently correlate with stronger ROI. According to the firm, the organizations seeing the best outcomes were typically those investing in reskilling, workflow redesign, governance, and human oversight alongside AI deployment, suggesting long-term success may depend less on replacing workers and more on redesigning how humans and AI systems operate together.

Go Deeper -> GM just laid off hundreds of IT workers to hire those with stronger AI skills – TechCrunch