AI skills – General Motors laid off about 600 salaried IT workers, saying it is reshaping its IT team for AI-focused roles while continuing selective hiring.
General Motors’ latest IT shake-up is a clear signal that “AI adoption” is starting to look like something much more concrete than adding new tools.
The automaker confirmed it laid off more than 10% of its IT department—about 600 salaried employees—framing the moves as a deliberate skills swap. The layoffs were initially reported by Bloomberg, and GM later confirmed the action to TechCrunch.
In an emailed statement, GM said it is “transforming its Information Technology organization” to better position the company for the future, but it did not provide specific details on the scope of the restructuring or which roles were affected beyond the overall reduction in headcount.
Importantly, the changes are not described as a simple cut-and-freeze.. A person familiar with the layoffs told TechCrunch that GM is still hiring in its IT organization. but for different skill sets.. The most in-demand capabilities include AI-native development. data engineering and analytics. cloud-based engineering. and work tied to agent and model development. along with prompt engineering and the creation of new AI workflows.
What GM appears to be seeking in practice is not just employees who can use AI to improve everyday productivity. but people who can build AI systems from the ground up.. That includes designing those systems, training models, and engineering the pipelines that connect data to models and deliver usable outputs.
The broader hiring shift also fits into a longer arc of restructuring inside the company’s white-collar ranks.. Over roughly the past 18 months. GM has laid off employees in several departments as it reallocated resources toward higher-priority initiatives. with AI positioned as one of those priorities.
Earlier in this process, the company cut about 1,000 software workers in August 2024. That step underscored that the company’s talent changes are not isolated to IT alone, but part of a larger push to reorganize how software and AI capabilities are staffed.
GM’s software and product direction has also been shaped by leadership changes tied to autonomous and AI expertise. In May 2025, Sterling Anderson—co-founder of autonomous trucking startup Aurora and a veteran from the autonomous vehicle industry—was hired as chief product officer.
Since Anderson’s arrival, three top executives left the company’s software team, according to the report.. They were Baris Cetinok. senior vice president of software and services product management; Dave Richardson. senior vice president of software and services engineering; and Barak Turovsky. a former VP at Cisco who served as GM’s chief AI officer for only nine months.
Those departures came as Anderson pushed to consolidate GM’s disparate technology businesses into a single organization.. The reorganization helps explain why GM could pair layoffs with targeted hiring: when teams and business units are consolidated. roles often change. and some responsibilities get redefined or redistributed.
GM has moved to fill parts of that gap with new hires specifically aligned with AI.. In October, it brought in Behrad Toghi, previously at Apple, as AI lead.. The company also hired Rashed Haq as vice president of autonomous vehicles. and Haq previously spent five years at Cruise—where he worked as head of AI and robotics until the self-driving company was acquired and later shuttered by GM.
For the wider tech industry. GM’s restructuring illustrates what enterprise AI adoption can mean when executives treat AI as a core capability rather than a bolt-on feature.. Instead of simply distributing AI tools across existing teams. the company is rebuilding staffing around skills that map directly to building models. agents. data systems. and AI-driven workflows.
The specific capabilities GM highlights—agent development. model engineering. and AI-native workflows—also point to where demand is increasingly converging in large organizations.. As those systems move from experiments into production. companies tend to need engineers who can manage the full chain: data preparation. model development and training. system integration. and operational pipelines that keep AI services reliable.
At the same time. the statement that GM is still hiring for IT roles suggests the impact is likely less about shrinking the company’s total ambition and more about reshaping the composition of its workforce.. For employees watching these changes. it also indicates that “AI skills” in the enterprise are being defined less by using AI and more by building AI capabilities end-to-end.
General Motors IT layoffs AI-native development enterprise AI hiring data engineering analytics agent and model development cloud engineering prompt engineering