Meta Eyes Historic $10B+ Investment in Scale AI, Powers Future AI

Recent reports indicate Meta Platforms is in discussions for a substantial investment in Scale AI, a leading firm in data labeling and AI model evaluation.[1][2][3][4][5][6] The potential financing could exceed $10 billion, positioning it as one of the largest private funding events in history.[3][4][5][6] While the specific terms remain under negotiation and could change, this move signals Meta's aggressive push to bolster its artificial intelligence capabilities.[1][2][3][4][5][6] Scale AI, which provides critical services for training machine learning models, was last valued at nearly $14 billion in a 2024 funding round that included backing from Meta, Microsoft, and Nvidia.[1][7][8][3] This prospective major investment underscores the increasing importance of high-quality data in the development of advanced AI systems and Meta's determination to remain at the forefront of AI innovation.[9][3]

The rumored multibillion-dollar investment into Scale AI aligns with Meta's significantly increased capital expenditure on AI and infrastructure.[9][10][11] Meta's 2025 capital expenditure guidance is between $64 billion and $72 billion, a substantial jump from previous years, primarily directed towards building large-scale AI data centers and acquiring necessary hardware.[9][10] This massive spending is intended to support the training and deployment of advanced AI models, including the anticipated Llama 4.[9][10][11] An investment in Scale AI, known for its expertise in generating labeled training data, would complement Meta's infrastructure ambitions by providing the essential "fuel" for its powerful computing resources.[9] Such a partnership could create a more vertically integrated AI development ecosystem for Meta, from data provision and model training to deployment and iteration.[9] Meta has already been leveraging Scale AI's services; the two companies partnered on Defense Llama, a version of Meta's Llama large language model tailored for military use.[12][3][13] Furthermore, Scale AI's Data Engine contributed a significant amount of data for supervised fine-tuning (SFT) and reinforcement learning from human feedback (RLHF) to help develop Llama 3.1.[14]

Scale AI, founded in 2016 by Alexandr Wang and Lucy Guo, has established itself as a crucial player in the AI industry by providing data labeling, annotation, and model evaluation services.[12][15][16] Its offerings are vital for companies developing AI applications across various sectors, including autonomous vehicles, robotics, and generative AI.[12][15][17] Scale AI's customers include prominent tech companies like OpenAI, Microsoft, General Motors, and Toyota, in addition to Meta.[12][3][17] The company operates on a business-to-business model, transforming unstructured data into high-quality, structured training data through a combination of technology and human review.[16] Scale AI has seen rapid growth, with reported revenue of $870 million in 2024 and projections to more than double that to $2 billion in 2025.[15][3] In May 2024, Scale AI raised $1 billion in a funding round led by Accel, reaching a valuation of $13.8 billion.[7][15][8] Meta and Amazon were among the investors in that round.[7][8] There have also been reports earlier in 2025 that Scale AI was seeking a valuation as high as $25 billion in a potential tender offer.[12][15][3] The company outsources data labeling tasks through subsidiaries like Remotasks.[12]

A significant investment by Meta in Scale AI would have broad implications for the competitive AI landscape. It highlights the immense value being placed on high-quality, well-labeled data, which is foundational to building more capable and reliable AI models.[18][19][20] Meta's Llama family of large language models, including the recently released Llama 3 and the anticipated Llama 4, require vast amounts of diverse data for training.[21][22][23][24][25][26] Llama 3 was reportedly pre-trained on over 15 trillion tokens of data from publicly available sources, a sevenfold increase compared to Llama 2.[23] The upcoming Llama 4 is expected to be trained on over 30 trillion tokens, incorporating text, image, and video data.[24][26] Ensuring a steady supply of accurately labeled data is crucial for refining these models, improving their reasoning and instruction-following capabilities, and reducing biases.[22][25] While Meta has focused on an open development strategy for its AI models, a major external investment like the one rumored for Scale AI would be a notable, though not unprecedented, move, potentially signaling a strategy to secure critical components of the AI supply chain.[3][22][27] This comes as tech giants like Microsoft, Amazon, and Google are also making substantial investments in AI startups and infrastructure.[9][3]

In conclusion, Meta's reported plan to invest upwards of $10 billion in Scale AI underscores a strategic imperative to secure and enhance its data pipeline as it escalates its AI development efforts. This potential deal reflects the critical role of specialized data providers like Scale AI in the rapidly advancing field of artificial intelligence and points to an intensification of investment and competition among major technology players. As AI models become increasingly complex and integrated into various products and services, access to vast, high-quality, and meticulously labeled datasets will continue to be a key differentiator and a driver of significant strategic investments.[9][3][18][20] The outcome of these talks could significantly shape Meta's AI trajectory and influence the broader AI industry's focus on data infrastructure.