10% of GM’s IT Force Is Out. The New Hires Must Think Like AI Builders.

It wasn’t a cost-cutting measure. At least, not entirely.

On May 11, General Motors confirmed it had laid off more than 600 salaried IT employees - over 10% of its entire IT department. But the company isn’t shrinking by 600 heads. It plans to hire the same number back, just with radically different skills. The targeted layoffs, first reported by Bloomberg and confirmed by TechCrunch, represent a deliberate workforce “swap”: shedding IT workers whose expertise no longer aligns with the automaker’s new AI‑driven reality and recruiting engineers to build AI systems from the ground up.

The automaker officially described the move as “transforming its Information Technology organization to better position the company for the future,” but in practice, it means a hard pivot away from legacy IT and toward AI‑native development. The new IT department won’t be filled with people who simply use AI tools for productivity. Instead, GM is looking for those who can design, train, and deploy AI models from scratch.

This isn’t an isolated event. It is a signal of how enterprise AI adoption will unfold across the entire global economy. For the IT workforce - and particularly for India’s massive outsourcing industry - it raises urgent questions about which skills will survive the AI transition and which will become obsolete.

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Quick Facts Box

Not a Job Cut, but a Skill Swap

The distinction is crucial. Many layoff announcements are straightforward cost reductions - companies cut headcount and leave the holes unfilled. That’s not what is happening at GM.

A person familiar with the layoffs confirmed to TechCrunch that the company is still hiring for its IT department, but the open positions are for an entirely different set of capabilities. The most sought‑after roles now include AI‑native development, data engineering and analytics, cloud‑based engineering, agent and model development, prompt engineering, and new AI workflows. In practice, GM is looking for people who know how to build with AI from the ground up - designing systems, training models, and engineering pipelines - rather than professionals who only use AI as a productivity tool.

This is not a one‑time event. GM has been laying off white‑collar employees in waves over the past 18 months as it consolidates resources around high‑priority initiatives, including AI. Back in August 2024, the company cut about 1,000 software workers. In October 2025, it laid off hundreds more salaried employees alongside thousands of blue‑collar staff after its electric vehicle investments went sour.

But the current round is different. It is not a response to poor performance. It is a strategic redesign of the tech workforce itself. The company has also seen significant leadership changes: three top software executives left last November as Sterling Anderson, a former Aurora co‑founder, was brought in as Chief Product Officer, and pushed to consolidate GM’s technology businesses. In their place, GM hired Behrad Toghi from Apple as its AI lead and brought on Rashed Haq, formerly head of AI and robotics at its own shuttered self‑driving arm Cruise, as vice president of autonomous vehicles.

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What GM Is Building (and Why It Needs New Skills)

To understand the hire, you have to understand the destination. GM is not just tinkering with AI. It is betting that software will become the primary differentiator in vehicles.

The automaker is shifting investment toward a centralized computing platform scheduled for 2028, when an “eyes‑off” driving system is also expected to debut. Both initiatives require far more specialised AI and software talent than the corporate IT roles that support internal systems. In fact, Google Gemini AI is set to start rolling out in GM vehicles as early as 2027.

These are not projects where legacy skills translate directly. Building an AI‑native driving platform is a different discipline from maintaining internal computing systems. That’s why GM’s restructuring is not just about adding AI tools on top of existing teams. It’s about deliberately rebuilding the workforce from the foundation up. The specific capabilities GM is hiring for - agent development, model engineering, AI‑native workflows - point directly at where large‑enterprise demand is heading.

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From the perspective of the wider automotive industry, AI adoption is accelerating rapidly. According to Perforce’s 2026 Automotive Software Development Report, 71% of automotive development teams now use AI in product design, and 45% are incorporating it not just as an assistive tool but as part of the end product itself. However, the same report notes that organizations are facing fewer resources and leaner development teams, making the ability to recruit AI‑capable engineers a competitive necessity.

As vehicle functionality increasingly shifts from hardware to software, industrial giants across the board are finding that their talent mix no longer matches their technological aspirations. GM’s decision suggests that deeper, more specialised software and AI expertise will be required simply to stay competitive in the coming years. The broader pattern is unmistakable: automotive and other traditional industries are beginning to restructure their workforces in the same way that Silicon Valley firms have been doing for years. Routine development and testing roles are being phased out, while architect-level positions that involve AI integration, platform design, and safety-critical systems are prioritized.

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The India Angle: A Warning for IT Outsourcing

For India, GM’s decision is more than a distant corporate announcement. It is a concrete illustration of a larger shift that is already disrupting the country’s $250 billion IT services industry - and its 15 million middle‑class professionals.

The traditional model that powered India’s IT rise was labor arbitrage: executing routine coding, testing, and support tasks for global clients at a fraction of the cost of in‑house Western teams. That model is exactly what AI now threatens. Generative AI tools can draft applications, generate test scripts, and even maintain software systems - tasks that require large teams today but may soon require far fewer people.

The consequences are already visible. According to a Bernstein analysis of AI‑vulnerable jobs, global capability centres and the IT sector in India employ up to 15 million people who anchor the middle class. A potential reduction of 30% of this workforce over the next two years could shrink the country’s top consuming class by about 5 million people, endangering the private consumption that accounts for 60% of India’s GDP.

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Oracle laid off about 10,000 workers in India earlier in 2026. Tata Consultancy Services posted its first annual revenue decline since its IPO. Amazon cut 500 jobs within the country earlier this year. AUMOVIO, a German automotive tech firm, announced it would cut up to 1,000 engineering jobs in India - roughly 17% of its local workforce - as part of a global shift toward software-defined vehicle platforms and AI‑based safety systems.

A study from Zinnov found that 55% of GCC portfolios in India are now under displacement pressure, mainly in execution-heavy roles. The pivot will need to be toward owning AI‑led products and higher‑value decisions, not just completing repetitive tasks for overseas clients. Kapil Joshi, CEO of staffing firm Quess Corp, noted that demand for coders has fallen about 16%, while hiring has increasingly shifted toward mid‑management roles with little fresh intake at the entry level.

The structural message is consistent: India can no longer rely on the labor‑arbitrage advantage that made its IT sector world‑famous. The future will belong to professionals who can design AI systems, orchestrate agent workflows, and embed domain expertise - not just execute instructions.

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The New Technical Stack

What does a “new stack” candidate look like? The job listings GM has posted offer a vivid picture.

A search of GM’s careers website revealed 82 open IT roles spanning AI, autonomous vehicles, and even motorsports. The common thread is not comfort with a specific programming language, but rather the ability to work with AI as a foundational layer of the technology architecture. That means understanding how to train and evaluate models, how to manage inference pipelines, and especially how to integrate agentic workflows into production systems - capabilities that were not part of standard IT curricula just a few years ago.

The shift mirrors what is happening across the enterprise software landscape. Companies are no longer satisfied with plug‑in AI features. They want teams that can build proprietary models tailored to their market, product, and operational data. That requires a depth of AI literacy that goes far beyond calling an API.

For professionals in India, the implication is clear: generic “coding” skills are no longer a durable career asset. What will be rewarded instead are abilities in data engineering, model deployment, agent orchestration, and the architecture of AI systems - complemented by a strong understanding of the industry domain in which those systems will operate.

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The Bottom Line

GM’s layoffs are not a sign of financial distress. They are a sign of strategic foresight. The automaker is not waiting for a crisis to remake its workforce. It is shedding legacy IT roles today to make room for the AI competencies it knows it will need tomorrow.

For IT professionals, the message is uncomfortable but unambiguous. The same AI tools that companies are racing to deploy will also reshape the labor market, compressing demand for routine coding and expanding the premium on AI‑native skills. The workforce of the future will be smaller in some respects, but far more specialised in others.

The companies that thrive will be those that treat workforce restructuring not as a reactive cost‑cutting exercise, but as a deliberate strategic shift. GM’s layoffs are a case study in how that shift looks in practice: eliminating roles that no longer fit, recruiting for the stack of tomorrow, and preparing for a world in which artificial intelligence is not an add‑on but a core capability. The only question left is how quickly the rest of the industry will follow suit.

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If you work in IT or software development, have you started retooling for AI‑native skills? What’s been your biggest challenge in making the shift from traditional development to AI‑driven engineering? Share your thoughts in the comments below.

If you found this article useful, share it with a colleague in tech or a student just entering the workforce. The skills that keep you employed are changing - and they’re changing faster than most people realise.

FAQ

Q1: Did GM lay off 600 people to cut costs? 

A: Not entirely. GM is hiring back the same number of employees, but for roles with different skill requirements - AI‑native development, data engineering, model training, and prompt engineering. It’s a “skill swap,” not a net headcount reduction.

Q2: What kinds of skills is GM looking for? 

A: AI‑native development, data engineering, cloud‑based engineering, agent and model development, and prompt engineering - essentially, people who can build and deploy AI systems, not just use AI tools for productivity.

Q3: How does this affect India’s IT industry? 

A: GM’s shift mirrors a global trend: companies are moving away from routine coding and testing toward AI‑native, higher‑value roles. Indian GCCs and IT firms are already cutting routine engineering jobs and hiring more AI specialists. The labor‑arbitrage model is under pressure.

Q4: Should I still pursue a career in coding? 

A: Yes, but with a different focus. Generic “typing code” skills are becoming commoditised. The value is shifting to system design, data engineering, AI integration, and the ability to orchestrate AI agents - not just writing functions.

Q5: What’s the “eyes‑off” driving platform GM is working on? 

A: A system that would allow drivers to take their eyes off the road (Level 3 automation) targeted for 2028. It requires specialized AI and software talent, which is a key reason GM is restructuring its IT workforce now.

 Tags: GM Layoffs, AI Skills, IT Workforce, Artificial Intelligence, Automotive Tech, Future of Work