- Scale AI cuts 14% of its workforce, including 200 full-time staff and 500 contractors, following a rapid generative AI expansion after Meta’s large investment.
- The restructuring aims to consolidate GenAI teams, but comes amidst partner pullbacks and uncertainty over the company’s ability to pivot and restore client confidence.
What happened: Scale AI cuts 14% of workforce after Meta investment, hiring of founder Wang
Scale AI has laid off around 200 full-time employees—which is about 14% of its staff—and 500 contractors following a major restructuring plan, as revealed in an internal memo from interim CEO Jason Droege. The cuts came shortly after Meta’s investment, reportedly $14.3 billion for a 49% stake, and the departure of co-founder Alexandr Wang to join Meta’s new Superintelligence Labs. Droege acknowledged that the firm had expanded its Generative AI division too rapidly, creating inefficiencies, bureaucracy, and unclear responsibilities.
Scale AI is consolidating its GenAI division from 16 teams into five focused pods—covering code, language, expert systems, experimental projects, and audio development—and merging the go-to-market teams into a single “demand generation” unit. Affected staff will receive severance, with full-time salaries continuing into mid-September.
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Why it’s important
The workforce reduction follows Meta’s substantial investment—part of its effort to build up AI capabilities and recruit top talent, including Wang. It reflects growing pains commonly seen in fast-scaling AI startups, where rapid expansion can outpace operational discipline. Beyond internal restructuring, Scale AI is grappling with shifting relationships: partners such as Google and OpenAI have reportedly pulled back from new projects, citing concerns over the company’s Deepening ties with Meta.
Despite the cuts, Scale AI remains well-funded and plans to redirect investment into enterprise, public-sector, and government-focused AI operations later in the year. However, questions remain about whether the company can rebuild trust with former clients and regain momentum in its core data-labelling services.
