GM laid off IT specialists to hire AI engineers: what's behind it

When an auto giant with a hundred thousand employees lays off hundreds of IT specialists and immediately hires engineers with AI skills, it looks like another "digital transformation." But behind this news is a more pragmatic story: the company is shifting focus from supporting legacy systems to building new AI-based products. And this isn't about "replacing people with robots" — it's about changing the team's architecture.

According to TechCrunch, GM is looking for specialists in AI-native development, data engineering, cloud engineering, and prompt engineering. So it's not that "AI writes code itself" — rather, the task profile is changing: less support, more building from scratch. And that's normal for any company that wants to stay competitive.

AI skills aren't a silver bullet, but a new tool

In our experience, AI engineers are indeed needed where you have to integrate LLMs into product logic, build RAG pipelines, or set up agentic systems. But for 80% of typical enterprise tasks — automating reporting, data migration, ERP support — good backend developers familiar with classical algorithms are still sufficient. GM, apparently, decided that its IT department is overloaded with legacy support and wants to reassemble the team around product development with an AI component. That's reasonable, but risky: if you lay off too many experienced engineers who know "how the factory works," you can lose critical expertise.

Who benefits and who is at risk

For GM, this is a way to speed up AI adoption in production and customer-facing processes. For those laid off, it's an unpleasant but expected signal: the job market is shifting toward specialists who can work with data and models. For us, as a team that hires engineers ourselves, it's confirmation: demand for AI engineers is growing, but it doesn't cancel the need for classical engineering. Without the ability to design architecture, understand network protocols, and write clean code, an AI engineer remains just an "API user."

What IT specialists should do

If you work in a large corporation and see your role reduced to "keeping things running" — it's worth thinking about developing AI competencies. You don't have to become a prompt engineer: it's enough to understand how models work, how to fine-tune them, and how to integrate them into existing systems. GM isn't the only one making this swap — it's a trend we're also seeing among our clients from the CIS. But no need to panic: AI tools don't replace engineers yet — they change their toolkit.

Ultimately, GM's decision isn't a revolution, but an evolution: the company is reallocating resources between support and development. And if you're building an IT team too, you should ask yourself: how many of your people are busy supporting legacy and how many are creating something new? The answer might tell you who to hire next.