Meta Announces 10% Workforce Reduction as Tech Giants Restructure Operations
Meta plans to lay off 8,000 employees and cancel 6,000 open positions, while Microsoft offers voluntary buyouts to 7% of U.S. staff.

Meta announced plans to reduce its workforce by 10 percent, affecting approximately 8,000 employees, according to an internal memo. The social media giant will also cancel plans to fill 6,000 open positions as part of what the company described as efforts to run more efficiently and offset other investments.
The layoffs represent Meta's continued focus on artificial intelligence initiatives and operational efficiency. Company leadership indicated the workforce reduction is necessary to reallocate resources toward AI development and other strategic priorities. The cuts are scheduled to take effect in May.
Meanwhile, Microsoft is implementing its first voluntary employee buyout program, offering departure packages to approximately 7 percent of its U.S. workforce. The software giant's move represents a different approach to workforce optimization compared to Meta's direct layoffs.
The technology sector has experienced significant restructuring over the past year as companies adjust to changing market conditions and increased focus on AI capabilities. Both Meta and Microsoft have been investing heavily in artificial intelligence development while simultaneously seeking to improve operational efficiency.
The White House separately accused China of "industrial-scale" theft of AI technology, highlighting growing tensions around artificial intelligence development and intellectual property protection in the tech sector. This accusation comes as companies across the industry navigate increasing geopolitical concerns while pursuing AI advancement.
Other developments in the AI sector include Anthropic partnering with law firm Freshfields to create legal AI tools, and Applied Digital signing a $7.5 billion lease agreement for AI data center infrastructure with an unnamed hyperscaler, demonstrating continued investment in AI infrastructure despite workforce adjustments at major tech companies.