Meta Cuts Roughly 600 Roles in AI Unit Amid Superintelligence Push

Meta Platforms is cutting about 600 jobs in its artificial intelligence division as part of a major restructuring of its AI operations. The move comes amid the company’s ambitious push toward creating “superintelligence” and follows a recent period of large-scale hiring for its elite AI labs.

What’s happening and who is impacted

The job cuts affect Meta’s legacy AI research unit, known as Facebook Artificial Intelligence Research (FAIR) (FAIR), along with its product-AI and AI infrastructure teams. These teams fall under the broader umbrella of what Meta refers to as its “Superintelligence Labs”. The newer division called the “TBD Lab” remains untouched, and Meta says it will continue hiring for that unit.

In the internal memo reviewed by several outlets, Meta’s Chief AI Officer, Alexandr Wang, explained that by shrinking the team size, fewer conversations would be required to make decisions, and each individual would have greater scope and impact. In short: the company wants to be leaner and faster.

Why Meta says it’s doing this

Meta insists the layoffs do not signal a pull-back from AI investment; rather, they reflect a shift in strategy. The company claims it is doubling down on high-impact AI efforts and moving away from internal overlap, redundancy and slower decision cycles. The legacy units being trimmed are seen as less aligned with the current aggressive strategy.

Some of the motivations behind these changes include:

• The need for smaller, talent-dense teams that can move quickly.
• Integration of research into product faster, rather than maintaining large siloed labs.
• Refocus of resources on the most strategic AI projects (such as large-language-models and next-gen systems) rather than broader research portfolios.

Context: a hiring surge followed by cuts

Just months ago, Meta was aggressively hiring for its AI capabilities. The company made several headline moves: hiring top AI talent from rivals like OpenAI, Google, Apple; investing billions of dollars into AI start-ups; and setting up the Superintelligence Labs as a marquee initiative. Many of the employees being cut came from that expansion wave.

Now the company appears to be retrenching parts of the business that grew fastest but may be delivering less value. Industry watchers say this pattern — hire big, then trim for agility — reflects broader tension in the AI arms race.

Reactions & implications

The layoffs have triggered significant reaction internally and externally:

• Within Meta, some employees see the move as unsettling, especially those who joined recently believing in long-term commitment.
• Outside Meta, commentators view this as proof that even high-profile AI teams are not immune to job insecurity when strategy shifts.
• For the AI ecosystem, the layoffs raise questions about how companies balance expansive research ambitions with operational discipline and efficiency.

What it means for Meta and the AI race

• Meta’s AI direction: The company is making clear that its current priority is focused AI systems, flagship products, and large-language-model leadership—not broad foundational research for its own sake.
• Talent strategy: Meta may increasingly prioritise fewer elite individuals doing high-impact work, rather than sprawling teams doing incremental research.
• Competitive signal: By trimming parts of its AI unit while continuing new hiring in others, Meta is sending a signal that it is pivoting from expansive growth to selective excellence in AI.
• Job market implications: For AI professionals, especially in research and infrastructure roles, this underscores that even marquee positions can be fragile in major tech companies.

Final thought

Meta’s decision to lay off 600 AI-division employees comes at a time when the company proclaims its most ambitious plans yet in AI. While the restructuring aims to align the workforce with strategic priorities, it also reveals the pressures and contradictions within the ongoing AI arms race: the push for rapid innovation, the need for agility, and the reality of cost, talent and organisational complexity.

In short, this isn’t just another layoff round in tech—it’s a signal that even companies betting big on AI are refining their map, recalibrating their teams, and shifting from expansion to execution.