U.S. employers announced more than 150,000 job cuts in October 2025, marking the highest number of layoffs for the month in over two decades, according to a new report from global outplacement firm Challenger, Gray & Christmas. The surge reflects growing economic uncertainty as companies turn to AI-powered automation and aggressive cost-cutting measures.

Tech Sector Leads Layoffs as AI Disruption Grows

The technology industry recorded the largest number of layoffs, followed by retail and services. The report indicates that businesses across sectors are strategically downsizing as they adopt artificial intelligence and adjust to weakening consumer and corporate spending.

Key Drivers: Cost-Cutting, AI, and “DOGE Impact”

Cost-cutting was the primary reason cited for October’s job cuts, while artificial intelligence implementation ranked second. Notably, “DOGE Impact” emerged as a leading factor for layoffs in 2025, hinting at the ongoing influence of cryptocurrency market volatility on employment decisions.

Layoffs Skyrocket 175% Year-Over-Year

Layoffs in October jumped 175% from the same period last year, reaching 153,074. From January through October 2025, employers have announced over 1.09 million job cuts, up 65% compared to the same timeframe in 2024. This marks the highest total cuts since the pandemic year of 2020, when over 2.3 million layoffs were announced by the end of October.

Andy Challenger, Chief Revenue Officer at Challenger, Gray & Christmas, commented:

“Some industries are correcting after the hiring boom of the pandemic. But as AI adoption accelerates and spending weakens, companies are tightening their belts, resulting in hiring freezes and significant layoffs.”

Government Shutdown and Broader Economic Concerns

Layoff data from private agencies like Challenger’s is drawing greater attention as the ongoing U.S. government shutdown delays official labor statistics. Meanwhile, a federal judge this week upheld a block on former President Donald Trump’s proposed buyout plan for federal workers, further contributing to economic uncertainty.