General Motors cut roughly 600 IT staff this week, more than one in ten people in its technology department, and confirmed it is rehiring for entirely different roles. The people leaving worked in traditional IT. The people coming in will build AI systems, manage data pipelines, and design what are called agents: software that can complete multi-step tasks on its own, like processing an invoice, filing a report, or flagging a procurement anomaly, without a human clicking through each step.
This is the part worth paying attention to if you run or manage any kind of operation. GM is not a software company. It makes cars in factories. When a company that size decides its internal IT needs to look like a Silicon Valley AI team, that decision will ripple outward to its suppliers, its consultants, its insurers, and every other organisation that wants to stay in the same room as it commercially.
The pattern behind this move goes back further than this week. GM shut down Cruise, its self-driving taxi unit, in December 2024 after spending over 10 billion dollars and generating less than 500 million in revenue. That was a painful and public failure. What followed was a quiet but systematic rebuild of the company's entire technology leadership. A new chief product officer was brought in from Aurora, a self-driving truck company. An AI lead was hired from Apple. A new head of autonomous vehicles came from inside Cruise itself, the one part of that project that actually learned something. Three senior software executives left. The message from leadership was consistent: we are not adding AI on top of what we have. We are starting the technology function over with different people.
The layoffs hit workers based in Austin and Warren, Michigan. These are not manufacturing towns. These are white-collar IT hubs. The jobs being cut are the kind that exist at every company of a certain size: systems maintenance, internal tech support, legacy software management. The jobs being created are for people who know how to build, train, and run AI systems.
None of this is unique to GM. A survey of 1,000 US business leaders found that 39% conducted layoffs in 2025, with AI listed alongside economic uncertainty as a primary reason. By the end of 2026, 37% of companies surveyed expect to have replaced roles with AI. Notably, it is not entry-level workers being cut first. High-salary employees without AI skills are being identified as the priority targets, because eliminating them saves more money immediately while the company can point to AI investment as the strategic rationale.
What makes GM's version of this story different is the specificity. They are not just saying they want people who know how to use AI tools. They are hiring for agent development, meaning people who build autonomous software systems that take actions without human prompting. That is a meaningfully harder and rarer skill than knowing how to use a chatbot. And the fact that a 116-year-old car company is chasing it tells you something about where enterprise demand is heading across every sector.
For managers and directors in non-tech industries, the honest question this raises is not whether AI will affect your team. It is whether your organisation is currently paying for the maintenance of yesterday's operations while your competitors are quietly rebuilding for the next five years. GM was bleeding cash on Cruise, failed publicly, and then used that failure to justify a clean rebuild. Most organisations will not get that kind of forcing event. The pressure will come more gradually, through a competitor who moves faster, a client who expects AI-enabled service, or a board that starts asking why the IT budget looks the same as it did in 2019.
The risk of getting this wrong is real. One auto industry analyst noted that cutting operational staff and replacing them with AI often creates hidden costs: the AI does not always work as expected, and you end up needing people to check its work anyway. GM spent a decade learning that lesson with Cruise. The companies that do this well will treat it as a skills transition, not a cost-cutting exercise. The ones that do it badly will cut the wrong people, hire the right-sounding titles, and wonder why nothing actually improved.