Meta begins 8,000 layoffs, notifies Singapore staff

Meta has started a global reduction of roughly 8,000 jobs, with initial layoff notices sent to employees in Singapore in the early morning and notifications to U.S. and European staff following later that day. Engineering and product teams are expected to be among the most affected, and the company may announce further reductions later in the year as it completes a reorganization.

Janelle Gale, Meta’s head of people, outlined the changes in an internal memo that described a move to a “flatter structure” and “smaller teams” intended to speed decision-making. The memo states, “We believe this will make us more productive and make the work more rewarding.” The company has said the reorganization will align resources to priorities tied to AI development.

Meta has increased spending on AI research, hardware and data centers. The company has invested more than $100 billion in AI initiatives and has reported plans for a large AI campus in Louisiana that has been described with a potential value of about $200 billion. Prior corporate investments included roughly $80 billion in metaverse-related projects, including work on the Horizon Worlds virtual platform.

Some employees have raised concerns about an internal program to collect data from employee devices for AI training. The initiative would gather keystrokes, mouse movements and screen content, and it has prompted criticism inside the company over privacy and workplace surveillance implications.

Other technology firms have also reduced staff amid shifts toward AI and cost cutting. Recent reductions in the broader tech and crypto sectors have included large workforce changes at several companies.

Meta informed affected employees directly and said remaining staff will move into smaller, more cross-functional teams focused on delivering AI-related products and services. Investors have questioned whether the scale of AI spending will produce matching returns, increasing scrutiny of the company’s long-term profitability and the pace at which new AI products will reach the market and generate revenue.