Meta cuts 10% of workforce as Microsoft offers buyouts

Meta and Microsoft are using different tools to reshape payrolls around artificial intelligence. Meta said it will cut about 8,000 jobs, or roughly 10% of its workforce, and drop plans to fill about 6,000 open roles as it pours more money into AI infrastructure and highly paid technical hires. The first wave is scheduled to begin May 20, 2026.

With about 78,000 employees at the end of 2025, Meta’s cuts amount to roughly one in 10 workers. Reuters reporting indicated more layoffs could follow later in 2026, extending a reset that has become one of the clearest signs that Big Tech is thinning parts of its white-collar workforce while preserving spending for compute, model training and the talent race under Mark Zuckerberg.

Microsoft is taking a quieter but equally notable route. The company has begun offering voluntary buyouts to some U.S. employees, in its first buyout program of this scale. Eligible workers are at the senior director level and below, and they must have years of service plus age totaling 70 or more. Based on reported eligibility, about 7% of Microsoft’s U.S. workforce, roughly 8,750 employees, could qualify.

The contrast points to a broader labor-market shift that reaches well beyond Silicon Valley. Meta’s reported 2026 artificial intelligence spending has been pegged at about $135 billion, up from about $72 billion in 2025, a surge that suggests the company is redirecting cash from headcount toward chips, servers and AI teams. Microsoft’s buyouts, by comparison, signal a preference for managed departures over abrupt firings, but the goal is similar: reduce payroll growth while keeping the company positioned for the AI buildout.

For workers, the message is sharp. Security is weakening even at the biggest platforms, and the pressure is no longer limited to new hires or junior staff. Meta’s layoffs and Microsoft’s buyouts both show companies holding back on hiring, eliminating open roles and encouraging departures as they reorganize for a smaller, more automated workforce. That model is likely to spread as other employers look to cut costs, improve efficiency and fund their own AI spending without adding as many people.