Meta Cuts 8,000 Jobs as AI Spending Surges to $135 Billion

Meta confirmed Thursday it will eliminate approximately 8,000 positions, representing roughly 10% of its global workforce, as the company pivots resources toward artificial intelligence development. The cuts take effect May 20, 2026, according to internal communications first reported by BBC News.

Janelle Gale, Meta's chief people officer, outlined the reductions in a memo that also revealed the company is closing around 6,000 open roles it had previously been hiring for. The dual approach—cutting existing staff while freezing new hires—signals a structural shift rather than a temporary cost-cutting measure. Employees received the news via email, the kind of notification that arrives with the same mundane ping as a calendar reminder, except this one rewrites career trajectories.

Capital expenditures tell the real story here. Meta spent $72.2 billion on data centers and AI infrastructure in 2025 alone. That figure is projected to climb to at least $115 billion in 2026, per the company's January earnings report. Some sources cite total AI spending closer to $135 billion for the current year—roughly equal to what Meta invested in AI over the previous three years combined. The math is brutal: fewer humans, more servers.

Mark Zuckerberg essentially telegraphed this move months ago. During Meta's January earnings call, he called 2026 "the year that AI starts to dramatically change the way that we work." He noted projects that previously required large teams could now be accomplished by a single talented person. (A problem that has plagued users for years, frankly—though not the one most employees are worried about right now.)

The company is simultaneously acquiring AI startups like Moltbook and Manus while building out its superintelligence lab. This isn't just about efficiency; it's about competitive positioning against OpenAI and other rivals in the generative AI space. The physical reality of this shift means more engineers staring at GPU clusters, fewer product managers coordinating cross-functional teams, and a lot of empty desks in Menlo Park.

Affected U.S. employees will receive 16 weeks of base pay plus two additional weeks for every year of employment. International packages will be similar, though specific terms vary by region. Meta has already conducted two smaller layoff rounds this year, cutting around 2,000 workers. This announcement represents the company's largest reduction since 2023.

Industry context matters. Amazon laid off 16,000 workers in January, its second major reduction in three months. Block eliminated 40% of its workforce—more than 4,000 people—in February. Oracle cut over 10,000 jobs. Microsoft offered voluntary buyouts to thousands of long-tenure employees on the same day as Meta's announcement. The pattern is unmistakable: AI investment correlates with workforce contraction across the sector.

One employee told BBC News the company has become "obsessed with AI," particularly after Meta began tracking and logging employee computer interactions to train its models. The timing feels dystopian to some—layoffs announced alongside increased surveillance of remaining staff. Whether this creates a more efficient organization or a more anxious one remains to be seen.

Meta shares dropped more than 2% on Thursday afternoon following the announcement. Investors appear to be weighing the long-term AI bets against short-term disruption. The company eliminated tens of thousands of jobs in 2022 and 2023 during post-pandemic right-sizing. Last year, it cut about 5% of what it called its "lowest performers," though it planned to backfill many of those roles.

The question isn't whether AI can do more work. The question is whether the people left to manage it can handle the pressure of doing more with less. Whether users actually pay for the resulting products remains the real question.

Artūras Malašauskas is an AI Systems Integrator with 20+ years of production-grade web engineering experience. He has designed, shipped, and scaled enterprise Python/PHP systems for logistics, SaaS, and public-sector clients. For the past year, he has focused exclusively on AI integrations: deploying open-source LLMs, building generative media pipelines (image, audio, video), and engineering multi-agent workflows for real production environments. His standard: reproducibility, security, cost-efficient inference—no vaporware. He documents and evaluates emerging AI tooling, separating verified capabilities from marketing noise. Technical editor at: muza-ai.eu, ai-verslas.lt, ai-naujinos.lt Connect on LinkedIn