Meta has invested $14.8 billion in San Francisco–based Scale AI, acquiring a 49% non-voting stake and appointing its CEO, Alexandr Wang, to lead Meta’s newly formed Superintelligence Lab. The Meta Scale AI investment values Scale AI at $29 billion and marks Meta’s second-largest investment, following its $19 billion acquisition of WhatsApp in 2014. The transaction grants Meta privileged access to high-quality data pipelines, which are essential for training large language models (LLMs), while Scale AI remains operationally independent.
Meta Scale AI investment: Shift from LLMs to Infrastructure
The New York Times reports that Meta made a $14.3 billion strategic investment in Scale AI, purchasing a 49% non-controlling stake in the data infrastructure business, which is now worth more than $29 billion. This is the tech giant’s second-largest transaction after it acquired WhatsApp in 2014, and it reflects a strong push to revive its artificial intelligence initiatives in the face of increasing competition.
As part of the agreement, Scale AI CEO and co-founder Alexandr Wang will depart his executive role to join Meta, where he will lead a newly established division known as the “Superintelligence Lab.” Wang, who will remain on Scale’s board, is bringing a small team of Scale employees with him to spearhead Meta’s initiative to build next-generation AI systems with capabilities that surpass human intelligence.
Additionally, this agreement strengthens the two businesses’ current commercial relationships, particularly in the areas of data annotation and model evaluation, which are important components for training sophisticated AI systems. Jason Droege, Scale’s former Chief Strategy Officer, has been named temporary CEO. Meta’s investment structure ensures that Scale stays operationally autonomous, a strategy designed to reduce regulatory friction.
The Meta Scale AI investment underscores Meta CEO Mark Zuckerberg’s determination to revitalize the company’s AI efforts. Frustrated with Llama 4’s performance, Zuckerberg is personally leading efforts to revive the company’s AI push, recruiting top talent with generous offers to build systems surpassing human intelligence.
Regulatory & Competitive Implications
The structure of the Scale deal has been carefully designed to avoid regulatory entanglements. Meta will acquire a 49% nonvoting stake, ensuring Scale AI retains operational independence. This approach mirrors recent strategies used by Microsoft with Inflection AI and Amazon with Anthropic, major partnerships that sidestep full acquisitions and their associated antitrust scrutiny.
The deal has drawn concern from regulators and lawmakers like Senator Elizabeth Warren, who warn it could still harm competition. While the FTC hasn’t commented on the Meta-Scale transaction, it is investigating similar AI partnerships. Experts say Meta’s non-controlling stake offers some protection, but scrutiny remains likely.
Potential Fallout and Industry Implications
Potential Fallout and Industry Implications
Following news of Meta’s involvement, some of Scale’s major clients, such as Google, have reportedly reconsidered their relationship with the startup. Scale maintains that it remains committed to safeguarding client data and preserving its independence. The startup continues to support a broad customer base across tech, government, and defense sectors.
Founded in 2016, Scale AI began by supplying annotated data for autonomous vehicles and later expanded to supporting large language models for clients like OpenAI, Microsoft, and Meta, offering a tailored alternative to Amazon’s Mechanical Turk.
Wang’s connections to the government and national defense also provide strategic value to the transaction. Under his leadership, Scale earned AI contracts with the Pentagon and maintained tight ties with federal agencies. Meta, too, has just begun providing AI capabilities to US government clients.
Additionally, Meta’s chief AI scientist, Yann LeCun, plays a central role in shaping the company’s superintelligence ambitions. A critic of current large language models, he advocates for AI that can reason, plan, and perceive the physical world—capabilities he sees as crucial to exceeding human-level intelligence.
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