Top Highlights
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AI labs are hungry for real-world data: Companies are offering hundreds of thousands—sometimes millions—of dollars for work records, emails, documents, and call transcripts.
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The market is expanding fast: Startups such as Handshake, Micro1, and Mercor are sourcing professional records, student work, and other materials for AI training.
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Real workflows are the prize: Labs want the complexity and messiness of actual business work, not just expert-generated simulations.
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Data is AI’s other big bottleneck: Alongside massive spending on computing power, the industry is racing to secure more high-quality training data—raising questions about privacy, consent, and workers’ contributions.
The New Data Gold Rush
AI companies need more than public websites and books. They also want the records businesses create every day: emails, reports, support tickets, call transcripts and chat logs.
Data brokers now offer companies money to license these files. Some pitches cite one-time payments from $350,000 to $1.8 million. One offered as much as $2 million. Those figures come from sales pitches, however, and may not reflect typical deals. Still, offers to individual writers and students show that buyers want specialized work, too.
Why Work Files Matter
Public information rarely captures how a workplace operates. Real records can show how people solve problems, handle exceptions and make decisions under pressure. That detail may help AI systems perform useful tasks, not just produce fluent answers.
Some brokers say they remove names and other identifying details before they sell data. That step can reduce privacy risks. Yet it cannot guarantee safety: a message may reveal someone through its context, or include confidential business information.
A Trade-Off for Workers and Companies
For a company facing closure, a data deal could bring in revenue. For workers, it may offer payment for work they already produced. But a check does not settle every question. Who owns the files? Did employees, clients or freelancers agree to their use? And will the people who created the work share in future gains?
Therefore, companies should review contracts, privacy rules and staff agreements before they sell. Buyers should explain how they will use the data and protect it. AI needs better examples of real work. At the same time, workers and businesses deserve a clear choice about whether their records become training material.
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