Meta cuts 10% of jobs as AI spending rises

Meta said it will cut 10% of its workforce, or about 8,000 jobs, from May 20 and drop plans to fill 6,000 open roles as it keeps investing heavily in AI.

Meta said the restructuring is aimed at aligning costs with its growing investment in AI infrastructure.

The company has been ramping up spending on AI development, including computing capacity and data centers, as it competes with other tech giants in building advanced AI systems.

Meta shares were down about 2.4% at US$658.40 in midday trading after the announcement.

🔗 Source: CNBC

🧠 Food for thought

Implications, context, and why it matters.

Meta is trading salaries for servers at a major scale

Meta expects capital spending of US$115 billion to US$135 billion this fiscal year as it puts more money into Meta Superintelligence Labs, its AI research and product group, along with the core business 1.
The buildout includes a US$27 billion deal with Blue Owl Capital, an investment firm, to fund and develop Meta’s Hyperion data center in rural Louisiana 2.
Meta set a goal for 65% of its software engineers to use AI tools for more than 75% of their committed code in the first half of this year 3.
Projects that once needed large teams can now be handled by one talented person with AI tools, said Mark Zuckerberg, CEO of Meta 4.

AI can also be a convenient narrative for corporate restructuring

Meta has described the planned cuts as a way to save money for other investments, while a wider pattern suggests some companies use AI as a cleaner public reason for layoffs tied to other financial strain 5 3.
In a recent survey, 44% of U.S. companies named AI as a reason for planned layoffs, while six in ten said they present layoffs or slower hiring through an AI lens to make those moves easier to accept 3.
The pattern reaches beyond Meta. Microsoft offered voluntary retirement to about 8,750 employees, or 7% of its U.S. workforce, while Dell cut headcount by about 10% in fiscal year 2026 as it grew its AI server business 5 3.
That approach may help a company look better from the outside, though it can hurt morale and trust inside if AI does not actually ease workloads 3.