AI training data is becoming a billion-dollar business as labs buy workflow data and RL environments

创业邦 · wechat · 2026-07-25

This long WeChat article argues that AI training data has become one of the most underestimated businesses in the current AI wave.

Why the market is exploding

Deedy’s map of 28 training-data companies reportedly shows about $8.5B in annual revenue and nearly $100B in total valuation.
The piece says the market is growing fast because data is no longer a one-off input; it is now a recurring fuel for faster model iteration.
As models improve, labs need more targeted, high-value data more frequently, especially for coding and agentic workflows.

From labeling to deeper services

Early text labeling paid around $0.02 per item; expert labeling now commands much higher hourly rates.
Companies like Scale AI are described as moving from pure labor outsourcing toward evaluation, task design, and engineering services.
The article says this shift lifts margins and gives data companies more pricing power.

Two new trends

Type1 data: real-world workflow data is becoming more valuable than hand-designed tasks.
RL environments: interactive training environments are replacing static datasets as a key purchasing target.

Four major players diverge

Scale AI is moving downstream into enterprise AI applications.
Surge stays boutique and focuses on high-end RLHF and safety work.
Mercor is expanding an expert network and bought Deeptune to enter RL environments.
Handshake is positioning itself as a data pipeline between workers, companies, and AI labs.

The article’s conclusion: simple data labeling is being compressed into the thinnest part of the value chain, while the real money moves to workflow capture, expert production, and environment infrastructure.

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AI training data is becoming a billion-dollar business as labs buy workflow data and RL environments

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