Google’s $10MN bid for the corporate data of bankrupt Spirit Airlines initially appeared to be an unusual consequence of a company collapse. The deal now looks more like the emergence of a developing market where AI companies are increasingly willing to pay large sums for the data generated by businesses and their employees.
Google won the bankruptcy auction for Spirit’s internal business data over AI training company Mercor. AI models can be trained on enormous quantities of publicly available information, but internal business data captures information that AI developers increasingly struggle to obtain fresh sources for—the messy reality of how humans work and interact. Operational records are particularly valuable for developing AI agents designed to perform real workplace tasks.
Micro1, an AI data company that subsequent to the auction offered $12.5MN for Spirit's data, has made this opportunity part of its business model. The company says it helps businesses monetize their operational data through licensing arrangements and is seeking information such as standard operating procedures, knowledge bases, CRM data, project histories, QA processes and decision-making patterns.
Micro1's interest in Spirit also illustrates the growing competition for this information. The company’s founder and CEO, Ali Ansari, stated in a post on X on August 18 that “in the last 11 days, we've committed more than $20,000,000 to license real operational data to seed our RL environments. scaling on the realism dimension is just beginning.”
This week, on August 24, Ansari added:
“[M]ore than 1,000 companies have signed up to get paid for their anonymized data to train models just in the last few weeks. [A] massive TAM opportunity for the entire economy has emerged almost overnight.”
The claim provides a striking indication of how quickly the market may be developing.
Ansari has been making a broader argument about the commercial value of human-generated data. In a January post, Ansari claimed that “human data will be a $1 trillion/year market,” its value rising as AI systems become capable of automating more economic activity.
Micro1 is actively recruiting businesses into its data partnership program, with compensation based on the quality, uniqueness and value of the data provided. Its published examples include customer-support documentation, ticket workflows, QA processes, customer operations and knowledge management, indicating that the information generated by a contact center or customer-service operation can contain precisely the kind of real-world operational knowledge AI developers want to replicate.
Such context can be far more useful than another tranche of public web content.
Micro1 is far from the only company aiming to claim a share of that market. Scale AI is inviting submissions of non-public datasets to its Dataset Collection Initiative to help train models to analyze data, seeking material such as marketing performance, social media advertising campaigns, system logs, investing and scientific research. It offers contributors payments depending on the quality and use case of the dataset.
Trust Will Become Part of the Data Deal
The growing demand for non-public datasets could turn years of accumulated enterprise data into a potentially valuable asset.
CX teams are sitting on particularly rich datasets. Contact center transcripts, call recordings, agent notes, CRM histories, support tickets, quality-assurance records, workforce-management data and internal knowledge bases can collectively provide a detailed map of how an organization responds to large volumes of real customer situations.
Until recently, much of that information was valuable primarily because it helped the business operate. But AI’s insatiable need for data changes the calculation.
The Spirit case is different from conventional licensing deals involving media archives, stock photography or video libraries. And it is being sold through bankruptcy, meaning information created for one commercial purpose is potentially being repurposed in another.
“The consequences of this acquisition are chilling,” privacy expert Ron Zayas, Chief Executive Officer of Ironwall by Incogni, told CX Today.
“Understand that while it is customary for companies buying assets out of bankruptcy to get the data that they need to utilize those assets, in this case Google is buying the data. They claim they will use it only in aggregate to train AI engines, but that is a voluntary commitment. They are likely under no legal agreement to do so.”
The Association of Flight Attendants-CWA (AFA), representing Spirit’s former flight attendants, pointed out in objecting to the sale that Google could make inferences about employees from the anonymized data. The company could also potentially monetize customer behavior around travel, Zayas noted, adding “this is how Google makes money.”
There is also a reason some observers are skeptical of Google’s involvement in particular.
Google has faced significant privacy scrutiny before. In 2024, it agreed to delete billions of records of private browsing activity as part of a settlement of a class action over the Chrome browser’s Incognito mode, following allegations that the company had continued collecting users’ browsing data despite the privacy expectations associated with the setting.
And in 2025, Google agreed to a $1.375BN settlement with Texas Attorney General Ken Paxton over allegations that it unlawfully tracked and collected sensitive user data, including geolocation, Incognito searches and biometric information. Paxton described it as the largest recovery against Google by a state attorney general enforcing state privacy laws.
Those cases do not establish that Google will misuse Spirit’s data, but they explain why skeptics are likely to scrutinize its assurances around data handling closely.
For enterprises considering similar deals, a data buyer’s track record may become as important as the price it offers.
