Cracks Emerge in Meta’s $14.3 Billion Partnership with Scale AI Amid Executive Departures and Data Quality Concerns
Meta’s ambitious investment in Scale AI is facing significant challenges only months after the tech giant acquired a 49% stake valued at $14.3 billion. The partnership, intended to fuel Meta’s push into superintelligent AI through the Meta Superintelligence Labs (MSL), has encountered executive turnover, internal tensions, and questions about data quality and vendor loyalty.
High-Profile Departures Shake Meta’s AI Labs
Since June 2025, when Meta finalized its substantial investment, the initial optimism has been tempered by the rapid departure of key personnel. Notably, Ruben Mayer, former Senior Vice President of GenAI Product and Operations at Scale AI, left Meta after just two months. Mayer managed AI data operations teams and was directly reporting to Alexandr Wang, Scale AI’s CEO, who also joined Meta’s elite AI team.
However, Mayer’s absence from TBD Labs—a division within Meta focused on developing AI superintelligence and staffed with recruits from OpenAI—has highlighted organizational friction. Several insiders describe disjointed collaboration between Scale AI executives embedded at Meta and the core MSL researchers, suggesting challenges in the integration and alignment of teams.
Quality Concerns and Vendor Competition
Meta’s reliance on Scale AI as a primary data provider for training AI models is also under scrutiny within the company. Though Scale AI is renowned for its data-labeling and annotation infrastructure critical for machine learning, leading researchers at TBD Labs have reportedly criticized the quality of Scale AI’s datasets.
As a consequence, Meta’s AI team continues to engage other data vendors, including prominent Scale AI competitors like Surge and Mercor. Sources reveal that TBD Labs has been collaborating with these competitors since before the lab’s inception, leading to questions about the rationale behind Meta’s multi-billion-dollar stake in Scale AI if other vendors are preferred for critical data needs.
This strategy reflects a complex balancing act. While it’s common for AI labs to work with multiple data-labeling providers, the scale of Meta’s investment elevates expectations that Scale AI would be the exclusive or dominant partner. The divergence has sparked concerns inside and outside Meta about Scale AI’s ability to meet the demanding standards required for cutting-edge AI research.
Broader Industry Impact and Fallout
Meta’s investment has caused ripples across the AI ecosystem. Following the announcement, other leading tech companies like Google, OpenAI, and Microsoft distanced themselves from Scale AI, reportedly ending or reducing their partnerships. These developments, combined with recent layoffs affecting about 200 data-labeling employees at Scale AI, indicate the firm is navigating a challenging transitional period.
Industry analysts speculate that Meta’s acquisition of Scale AI is driven partly by the ambition to secure top AI talent—evidenced by Alexandr Wang’s dual role at Scale AI and Meta’s labs—and less by Scale AI’s current product offerings. This interpretation is supported by reports that many executives from Scale AI are not well integrated with principal teams developing the next generation of AI models at Meta.
Tensions Within Meta’s AI Workforce
Inside Meta, the rapid recruitment of elite AI researchers with lucrative compensation packages has created unease among legacy employees, some of whom feel undervalued. This disparity has resulted in threats of resignation and actual staff departures, further disrupting the Superintelligence Labs’ momentum. Despite heavy investments and high-profile hires, early AI model releases like Llama 4 have met with muted reception, criticized for underperforming in areas such as coding, reasoning, and instruction-following.
Looking Ahead
Meta’s giant bet on Scale AI and the superintelligence race remains a high-stakes gamble. The partnership’s future hinges on resolving internal discord, improving data quality, and delivering AI capabilities that can compete with the likes of OpenAI and Google DeepMind. Observers will be watching closely to see if Meta can leverage its investment to accelerate AI innovation or if the emerging fractures will hamper its leadership ambitions in the sector.