Updated
Updated · sociallifemagazine.com · May 26
Scale AI Founders Amass $5 Billion in Equity After 2018 Split
Updated
Updated · sociallifemagazine.com · May 26

Scale AI Founders Amass $5 Billion in Equity After 2018 Split

1 articles · Updated · sociallifemagazine.com · May 26
  • About $5 billion in combined Scale AI equity now belongs to co-founders Alexandr Wang and Lucy Guo, years after Guo was fired in 2018 and the pair became estranged business associates.
  • The rupture centered on how Scale handled more than 240,000 contract workers: Guo has said she pushed for timely payments, while Wang prioritized rapid growth.
  • Scale’s rise turned both stakes into fortunes. The company was valued at $29 billion after Meta bought 49% for $14.3 billion in June 2025, and revenue had reached $870 million by 2024.
  • Wang stayed to build Scale, later leaving as CEO to become Meta’s Chief AI Officer, with a net worth estimated at $3.2 billion to $3.6 billion.
  • Guo kept roughly 5% of Scale after her exit, a stake now worth about $1.3 billion, underscoring how early ownership and patience can create AI-era wealth even after a founder departs.
Why did Meta abandon its open-source AI strategy after hiring Scale AI's CEO?
As Meta's AI chief, will Wang solve the same labor issues that fractured his first company?
Fired with 5% equity, she became a billionaire. What does this reveal about true value in a startup?

Inside Scale AI’s $29 Billion Rise: Meta’s Game-Changing Stake, Founder Fallout, and the New Faces of AI Wealth

Overview

Between 2025 and 2026, Scale AI underwent major changes as Meta Platforms Inc. invested in the company and hired its co-founder, Alexandr Wang, to lead Meta’s AI strategy. This move was driven by Meta’s urgent need to catch up with AI leaders like Google and OpenAI, especially after its Llama 4 models underperformed. By acquiring a stake in Scale AI, Meta aimed to access specialized datasets crucial for training advanced language models. Wang’s transition to Meta marked a strategic shift, highlighting the growing importance of high-quality data and leadership in the competitive AI landscape.

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