Tech giants cut thousands as AI spending surge reshapes industry

LEXINGTON, Ky. — Meta is laying off approximately 8,000 workers, or about 10% of its workforce, as major technology companies restructure operations amid massive investments in artificial intelligence infrastructure, according to reporting from LEX 18 News.

The Facebook parent company announced Thursday it would cut the positions to improve efficiency and redirect resources toward high-priority business areas. The company also plans to leave approximately 6,000 positions unfilled, further reducing its headcount as it pivots toward AI-focused spending.

Meta has signaled to investors that its 2024 operating expenses will grow significantly, reaching between $162 billion and $169 billion, driven primarily by infrastructure costs and employee compensation for artificial intelligence specialists commanding premium salaries.

Microsoft announced similar workforce reductions Thursday, offering voluntary buyouts to approximately 8,750 U.S. employees, representing roughly 7% of its domestic workforce. The software giant plans to make the buyout offers in early May as an alternative to sudden layoffs being implemented by competitors. The Redmond, Washington-based company has invested billions in expanding its global data center network to support cloud computing services, AI systems and its productivity suite, including the AI assistant Copilot.

The restructuring reflects a broader industry trend where technology companies are using artificial intelligence to automate tasks previously requiring large teams, enabling leaner operations while maintaining productivity. Wedbush analyst Dan Ives characterized Meta's cuts as strategic, allowing the company to streamline operations and reduce costs while leveraging AI tools for efficiency gains.

The workforce reductions come as major technology companies, including Amazon and Block, grapple with similar restructuring efforts. Industry observers view the cuts as necessary adjustments to balance the enormous capital expenditures required for artificial intelligence infrastructure with operational efficiency demands in an increasingly competitive AI marketplace.