Businesses have begun to make money from internal data: employee correspondence, tasks, and documents are sold as material for training artificial intelligence models.
Businesses have begun to make money from internal data: employee correspondence, tasks, and documents are sold as material for training artificial intelligence models.
According to Forbes, interest in such data has skyrocketed due to the shortage of high-quality content for training AI. Open sources are no longer enough, so companies are looking for real-world examples with context, errors, and a full history of decisions.
A case in point is the shutdown of cielo24. Its former CEO, Shanna Johnson, sold 13 years of its archive, which included internal correspondence, tasks, and operational data. The deal, she says, brought in hundreds of thousands of dollars and allowed the company to be liquidated debt-free.
In parallel, the infrastructure for such deals is being formed. Startup SimpleClosure, which helps close businesses, has conducted about 100 sales of corporate archives in a year and returned more than $1 million to the founders. Typical payments for one data set range from $10,000 to $100,000.
The cost depends on the quality and structure. The most expensive data is the one that shows the full workflow: how the task is formulated, how it is discussed, and what result is reached. Such connections allow the model to be trained to perform real business tasks, not just to generate text.
Separately, demand for workplace simulations is growing. In such systems, AI is trained on real company processes and learns to act like an employee. According to Forbes, major players are already investing in this area, and Anthropic may invest up to $1 billion in such solutions.
At the same time, experts warn of risks. Even after data is anonymized, there is still a chance that people or companies can be re-identified. In addition, research shows that language models are able to reproduce fragments of the data on which they were trained.
The reason for the emergence of this market is the lack of quality data for AI development. Real-world workflows have proven to be much more valuable than texts from the open Internet, because they contain decision-making logic. As a result, corporate archives are transformed into a separate asset that can be monetized even after the company is closed.
Previously, dev.ua wrote about how much people who sell their videos and phone conversations for AI training earn .
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