Just because a startup fails doesn’t mean it can’t cash out big.  According to a report by Forbes , defunct companies are selling their digital footprints to AI companies as training data—and making real money from it. Shanna Johnson, the CEO of now-defunct software company Cielo24, told the publication that she was able to sell every Slack message, internal email, and Jira ticket as training data for “hundreds of thousands of dollars.” This isn’t a one-off scenario. SimpleClosure, a startup that helps companies like Cielo24 shut down, told Forbes that there’s been major interest from AI companies trying to get their hands on workplace data. Because of this, SimpleClosure launched a new tool that allows companies to sell their wealth of internal communications—from Slack archives to email chains—to AI labs. The company said it’s processed 100 such deals in the past year. Payouts ranged from $10,000 to $100,000. Naturally, there are real data privacy concerns here. Even if the data is anonymized, these communications can contain personally identifiable information, especially for an employee who built out a long career at the company.  “I think the privacy issues here are quite substantial,” Marc Rotenberg, founder of the Center for AI and Digital Policy, told Forbes . “Employee privacy remains a key concern, particularly because people have become so dependent on these new internal messaging tools like Slack. . . . It’s not generic data. It’s identifiable people.” AI has been at the heart of workplace tensions, especially as companies increasingly pressure workers to embrace AI tools.  A new Gallup poll revealed that ethical opposition and data privacy concerns are among the reasons some employees choose not to use AI on the job. Concerns about privacy in the workplace are not just bound to AI, either: A 2024 survey by Checkr , a background check platform, found that nearly half of the 3,000 respondents would consider taking a pay cut if it meant their employer wouldn’t track their online activity. Large language models have been trained on substantial amounts of publicly available data, like news articles, books, and social media posts. Advanced agentic models—AI systems that can make autonomous decisions—require more intricate datasets, including documents, emails, and FAQs that provide context, feedback, and real-time data. An uptick in demand for workplace data is creating entirely new business models. As Forbes reports, AfterQuery, a San Francisco-based research lab, develops digital office “worlds,” which AI labs purchase to train AI agents to navigate online workplaces and solve real-world problems. Everything from employee Slack channels planning team happy hours to emails troubleshooting website issues are valuable assets in the data training economy. Maybe one day, sooner than we expect, we’ll all have AI agents handling happy hour planning and drafting the emails we dread. And it’ll be thanks to a graveyard of startups that didn’t quite make it.