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Business
May 12, 2026
Analyzed by GPT OSS 120B

GM Cuts 600 IT Jobs to Accelerate AI‑First Workforce

AI Summary
General Motors eliminated roughly 600 IT positions—about 10% of its department—to replace them with talent skilled in AI development, data engineering, and cloud‑native workflows. The move signals a broader shift toward rebuilding enterprise tech teams around artificial‑intelligence capabilities rather than merely adding AI tools.

GM’s Strategic IT Workforce Reduction

General Motors announced a deliberate 10% cut to its IT organization, laying off around 600 salaried employees. The automaker frames the action as a preparation for a future driven by artificial intelligence.

Details of the 10% IT Layoff and Skill‑Swap

The layoffs, first reported by Bloomberg and confirmed to TechCrunch, are part of a skills‑swap strategy: removing roles that no longer align with the company’s AI roadmap and opening positions for professionals with AI‑native development, data engineering, cloud engineering, and prompt‑engineering expertise.

  • GM continues hiring for the same IT department, but only for AI‑focused skill sets.
  • Key capabilities sought include model training, pipeline engineering, agent development, and AI workflow design.

Numbers Behind the Restructuring

  • ~600 IT employees laid off (≈10% of the department).
  • In August 2024, GM cut about 1,000 software workers in a separate wave.
  • Recent AI‑centric hires: Behrad Toghi (AI lead, ex‑Apple) and Rashed Haq (VP of autonomous vehicles, former Cruise AI head).

Implications for the Automotive and Enterprise AI Landscape

The restructuring illustrates how large manufacturers are moving beyond superficial AI adoption. By rebuilding the workforce from the ground up, GM is positioning itself to develop proprietary AI models and pipelines, a trend likely to ripple across the automotive supply chain and other capital‑intensive industries.

What GM’s AI‑Centric Hiring Signals for the Future

Analysts expect more enterprises to follow GM’s playbook: systematic talent turnover aimed at embedding AI expertise across core engineering functions. As AI‑native roles become the new baseline, we may see a surge in demand for prompt engineers, model engineers, and cloud‑AI architects, reshaping hiring markets and university curricula alike.