GM, Ford and Stellantis cut 20,000 office jobs — AI to accelerate the wave

Three major American automakers—General Motors, Ford, and Stellantis—collectively laid off more than 20,000 office employees over the past decade. According to CNBC's analysis, this represents a 19-percent reduction in their combined white-collar workforce. This week, GM announced the layoff of 500–600 IT specialists, evidence of an accelerating trend that, according to analysts, artificial intelligence will only exacerbate.

Scale of Layoffs in Numbers

According to CNBC, the combined reduction of white-collar staff across the three companies began in the 2010s but has accumulated impressive volumes. This reflects a systematic restructuring that affected management, information technology, engineering, and other office functions. Key figures in the layoffs:

• General Motors—the largest cuts in corporate apparatus and management divisions
• Ford—wave-like layoffs in engineering, management, and administrative structures
• Stellantis—integration following the Fiat Chrysler and PSA merger led to massive elimination of redundant functions

Artificial Intelligence as a Catalyst

This week, General Motors laid off between 500 and 600 IT workers. The company called the layoffs part of its automation and optimization strategy. According to analysts, the implementation of artificial intelligence in corporate processes—from accounting to engineering design—will only accelerate such waves. Experts point to dual pressure: margins are shrinking due to costly transition to electric vehicles, while AI allows companies to do more with fewer people.

"Automakers face dual pressure: margins are shrinking due to the

transition to electric vehicles, while AI allows companies to do more with fewer people."

Prospects and Risks for the Industry

The wave of layoffs that began in the early 2020s comes as a replacement for a period of workforce expansion in the previous decade. Now AI is becoming a permanent catalyst, allowing companies to avoid rehiring office personnel when operations recover. The main risk is knowledge loss. When experienced engineers and managers with twenty years of experience leave, with them goes an understanding of manufacturing nuances and unwritten rules. AI can inherit documented knowledge, but not the collective experience of professionals.

What It Means for the Economy

Automakers are becoming pilots for a wave of AI-driven layoffs in traditional industry. If GM, Ford, and Stellantis prove that one can reduce office staff by 20–30% and remain profitable, other industries will follow suit. For white-collar workers, this means growing competition with automation; for investors, the potential for margin growth; for the economy, the risk of imbalance between the pace of workforce displacement and the ability to retrain.