The CEO of Turing, a $2.2 billion AI training company, says the data-labeling boom that once powered early artificial intelligence models is officially over. Speaking on the 20VC podcast, Jonathan Siddharth declared, “The era of data-labeling companies is over.”
He explained that early AI systems depended on armies of human annotators tagging photos or classifying text. Now, advanced models like GPT-style agentic systems and reinforcement-learning architectures need complex, dynamic data that reflects real human problem-solving.
“Data needs have significantly changed,” Siddharth said. “Today’s AI needs data that mirrors how people actually think, work, and make decisions. It’s more real-world data — not simple labeling tasks.”
He added that modern AI labs no longer want vendors; they want research partners who can create simulated training environments, or “mini-worlds,” that help AI agents learn from lifelike situations. “It’s now the era of research accelerators,” Siddharth said, suggesting the next generation of AI training firms will rely on domain experts from diverse industries to model human workflows.
Turing, backed by $111 million in Series E funding at a $2.2 billion valuation, reported an annual revenue run rate of $300 million in 2024, nearly triple the prior year.
The New Face of AI Training
Turing’s message comes as the AI training sector enters a new phase. Giants like Scale AI, Mercor, and CloudFactory have seen massive valuations amid rising demand for data curation.
- Scale AI (private, recently valued at over $29 billion after Meta Platforms (NASDAQ: META) acquired a 49% stake).
- Mercor (private, valued near $10 billion in its October funding round).
- CloudFactory (private, among the older annotation firms now pivoting toward automation).
- Appen Limited (ASX: APX), one of the few publicly traded labeling firms, has seen its stock slide over 90% from its 2021 highs, reflecting the changing landscape.
The shift highlights an investment theme: while older labelling companies like $INOD and $TASK may struggle, AI infrastructure leaders such as Nvidia (NASDAQ: NVDA), Oracle (NYSE: ORCL), and Microsoft (NASDAQ: MSFT) are positioned to benefit from the new wave of data-intensive AI development.
Siddharth summed it up bluntly: “Simple tagging is done. The future belongs to those building the environments where AI learns to think.”
Disclosure: This article does not represent investment advice. The content and materials featured on this page are for educational purposes only.
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