Scale AI’s Rise to Power

Founded by Alexandr Wang in 2016, Scale AI began as a startup to streamline data labeling for machine learning. Today, it is a linchpin in the AI supply chain, offering data annotation services to giants like OpenAI, Microsoft, and Meta. The company specializes in curating vast, high-quality datasets required to train and fine-tune large language models (LLMs) and computer vision systems.

Meta's Dependence on Scale AI

In Meta’s quest to develop cutting-edge AI tools and chatbots, it has relied heavily on data prepared by Scale AI. From labeling images and text to refining nuanced datasets for model accuracy, Scale AI has served as Meta’s behind-the-scenes workhorse. This close partnership allowed Meta to accelerate model development without building massive in-house data labeling infrastructure.

A Strategic Shift Amidst Competition

However, recent reports indicate a shift. As Meta secures more in-house capabilities and strikes new data partnerships, its reliance on Scale AI may be reducing. Scale AI’s role, while still critical, faces challenges as big tech companies seek greater data sovereignty. At the same time, competition from other data providers and geopolitical concerns about AI data sourcing are reshaping industry dynamics.

Wang’s Broader Influence on the AI Landscape

Despite changing tides, Alexandr Wang’s influence is growing. Scale AI is central not only to Meta’s AI ambitions but also to the broader U.S. push to maintain leadership in artificial intelligence. Wang, often compared to Sam Altman and Elon Musk in tech circles, has positioned his company as a key strategic asset — quietly powering the AI revolution with one labeled dataset at a time.