Meta’s Investment in Scale AI Falters as CEO Departs and Quality Concerns Arise

Meta’s investment of $14.3 billion in data-labeling vendor Scale AI, made in June and involving CEO Alexandr Wang and several top executives joining Meta Superintelligence Labs (MSL), is reportedly experiencing some strain. One executive, Ruben Mayer, former Senior Vice President of GenAI Product and Operations at Scale AI, has left Meta after just two months with the company, according to sources familiar with the matter.

Mayer was tasked with overseeing AI data operations teams at Meta but did not work in TBD Labs, the core unit within Meta dedicated to building AI superintelligence. However, Mayer contests some details about his role, stating that he was there to help set up the lab and was part of TBD Labs from day one, rather than being excluded from the core AI unit. Mayer also clarified that he did not report directly to Wang and expressed satisfaction with his Meta experience.

Beyond personnel changes, Meta’s relationship with Scale AI appears to be evolving. Sources indicate that TBD Labs is now working with third-party data labeling vendors such as Mercor and Surge, two of Scale AI’s main competitors, for training upcoming AI models. Although it’s common for AI labs to work with several data labeling vendors, the fact that Meta invested heavily in one vendor while preferring to work with competing providers is notable.

Scale AI initially relied on a crowdsourcing model using a large, low-cost workforce for simple data labeling but has transitioned towards attracting subject matter experts like doctors, lawyers, and scientists with its Outlier platform. Competitors like Surge and Mercor have built their businesses around high-paid talent from the outset and are growing rapidly.

Meta declined to comment on the quality issues with Scale AI’s product, while Surge and Mercor did not respond to requests for comment. Asked about Meta’s increasing reliance on competing data providers, a spokesperson for Scale AI pointed to the startup’s initial announcement of Meta’s investment, which mentions an expansion of their commercial relationship.

Meta’s partnership with third-party data vendors may indicate that it is not putting all its eggs in Scale AI, despite the massive investment. However, the situation is different for Scale AI, as it recently lost clients like OpenAI and Google and laid off 200 employees in its data labeling business in July, with new CEO Jason Droege citing shifts in market demand as a factor.

Some speculate that Meta’s investment in Scale AI was primarily to attract Wang, a founder who has been active in the AI space since Scale AI was founded in 2016 and seems to be helping Meta attract top AI talent. However, the question remains about how valuable Scale is to Meta.

One current MSL employee indicates that several of the Scale executives brought over to Meta are not working on the core TBD Labs team. Meanwhile, tensions have reportedly been rising within Meta’s AI unit since bringing in Wang and a wave of top researchers, according to two former employees and one current MSL employee. New talent from OpenAI and Scale AI have expressed frustration with navigating the bureaucracy of a large company, while Meta’s previous GenAI team has seen its scope limited.

The tensions suggest that Meta’s largest AI investment to date may be off to a rocky start, despite being intended to address the company’s AI development challenges. After a lackluster launch of Llama 4 in April, Meta CEO Mark Zuckerberg reportedly grew frustrated with the company’s AI team and has since been making aggressive efforts to recruit top AI talent, strike deals, and build massive data centers across the U.S., such as the $50 billion Hyperion facility in Louisiana.

Wang, who lacks a background in AI research, was an unconventional choice to lead an AI lab. Zuckerberg attempted to bring in more traditional candidates like OpenAI’s chief research officer, Mark Chen, and tried to acquire the startups of Ilya Sutskever and Mira Murati but was declined by all parties.

Recently, some of the new AI researchers brought in from OpenAI have left Meta, while many longtime members of Meta’s GenAI unit have departed due to changes. Among the latest to leave is MSL AI researcher Rishabh Agarwal, who posted on X that he would be leaving the company. When asked about his time at Meta and what drove his decision to leave, Agarwal declined to comment.

Director of product management for generative AI, Chaya Nayak, and research engineer, Rohan Varma, have also announced their departure from Meta in recent weeks. The question now is whether Meta can stabilize its AI operations and retain the talent it needs for future success. MSL has already begun working on its next-generation AI model, with reports suggesting that it aims to launch it by the end of this year.