Meta reportedly weighs layoffs affecting 20% of staff

According to a report by Reuters, Meta is considering layoffs that could affect 20% or more of its workforce. These potential cuts are reportedly intended to help the Facebook parent company offset its heavy spending on AI infrastructure, as well as AI-related acquisitions and hiring. The potential scale of these workforce reductions is significant when compared to the company’s total headcount; a recent regulatory filing shows that Meta employed nearly 79,000 people as of December 31.

Meta has contested the report, pushing back against the assertion that major cuts are imminent. A Meta spokesperson dismissed the report, stating that it refers to theoretical approaches. “This is speculative reporting about theoretical approaches,” the spokesperson said in a statement. Despite this response, the report has intensified discussions about how technology firms manage their operational costs while spending heavily on artificial intelligence.

The report arrives amid a broader industry debate over the motivations behind recent tech sector staff reductions. While companies like Block have recently announced layoffs—attributing them to the necessity of restructuring as AI automates more work—some pundits and executives have raised doubts about these explanations. OpenAI’s Sam Altman and other industry observers have suggested that some of these layoffs constitute “AI-washing.” This is the practice of using AI as a pretext or cover for other corporate issues, such as over-hiring during the pandemic, rather than reflecting genuine operational automation.

If Meta moves forward with these cuts, it would follow previous workforce reduction trends at the company. The last time Meta announced layoffs of this scale was in November 2022, when it cut 11,000 jobs, followed by another 10,000 in March 2023. The potential new round of cuts suggests that the pressure to balance heavy spending on AI with lean operations remains a key factor for the company.

Why it matters

Meta’s potential move highlights the tension between aggressive AI investment and operational efficiency, suggesting that even tech giants are feeling the pressure to justify heavy spending on AI infrastructure.