What company data do AI companies buy?

Why do AI companies want internal business records?

AI labs first trained their models on the public internet. Forbes reports that former OpenAI chief scientist Ilya Sutskever said that supply was used up by late 2024, and that public text is of limited help for building AI agents that do office work. An agent learns a job from examples of the job being done, and most of those examples sit inside companies.

Buyers say so in their own words. OpenAI's Data Partnerships page asks for large datasets that are "not already easily accessible online to the public today", and for data that "expresses human intention", such as long-form writing or conversations. Business Insider reports that OpenAI, Anthropic and Meta are building AI agents for businesses, and that Gartner expects annual spending on data for AI to grow from under $1 billion in 2025 to almost $6.5 billion in 2027.

A tidy table of figures teaches a model little. A record that shows a problem, the people who worked on it, the decision they made and what happened next teaches it a lot.

What data do AI companies want from a business?

The company data AI companies buy falls into seven groups, and most companies hold several at once. The table sums up what each shows an AI company and what usually has to come out before anything is licensed.

Can you sell Slack and email data to AI companies?

Yes, if your company owns the records. Chat often holds the reasoning other systems leave out: threads where people explain why they chose something, not only what they did. That is what makes it worth checking if you want to sell Slack data to AI companies, and the same goes for Microsoft Teams.

Email adds the outside world: customers, suppliers, approvals and the people copied in. Anyone looking to sell email data to AI buyers should know the records are already in demand. Reuters reported in August 2026 that Google agreed to buy Spirit Airlines' internal data in its bankruptcy, including employee emails, Microsoft Teams messages, spreadsheets and calendars, to train its AI models. MIT Technology Review put it at 100 million emails and 500 million Teams messages. The sale still needed court approval when reported.

Chat and email also carry the most personal detail. Google told Business Insider it was not looking to buy any personal information from Spirit, and that any such data would be excluded or de-identified by an independent third party.

Can you sell CRM and support ticket data to AI?

Both are among the clearest examples of work with a result attached, which is why we look at them early. A CRM follows a deal from first touch to closed or lost, and every step in between. A help desk captures a customer's problem end to end, from complaint to resolution. Closed deals and resolved tickets let a model connect a decision to its result.

To sell CRM data to AI buyers, or sell support ticket data to AI, the value sits in the work history, not in the contact list. Both record types are full of customer details, so they usually need the most care before anything is shared.

What do project tools, documents, meetings and finance records add?

An issue in Jira, Linear or GitHub holds the description, each status change, the comments and links to related work, often including the code change that fixed it. That is one reason software and SaaS companies often hold deep records. Private codebases can be licensed on their own, separately from the rest of your data.

Documents and wikis show how a company says work should be done. In our view they count most when they sit beside the chat and tickets that show the work actually being done. Meetings and calls add spoken reasoning: OpenAI says it can work with audio and video as well as text, and can transcribe spoken words.

Finance and operations systems hold invoices, reconciliations, approvals and orders. Paid invoices are outcomes, and month-end close with every adjustment explained is the kind of specialist work buyers name often. Finance and accounting firms tend to hold a lot of it.

What makes company records more valuable for AI training?

Size alone doesn't decide what records are worth. AI labs pay for depth in data for AI training. When we review a company's data, these are the things we look at first. The factors that set the price of company data are covered in a separate guide.

• Years of history: a long-running record shows how decisions played out over time, not just a single moment.
• Outcomes attached: closed deals, resolved tickets and paid invoices let a model connect a decision to its result.
• Reasoning written down: threads where people explain why they chose something, not only what they did.
• Specialist work: decisions from finance, legal and engineering teams are among the records buyers name most often. Business Insider reports especially high demand in fields AI companies are trying hardest to automate, such as law and accounting.
• Linked records: in our view, chat, tickets, email and code that refer to each other are worth more, because a buyer can follow one piece of work from start to finish.

What usually has to come out before company data is licensed?

Buyers want the work, not people's private lives. Data you hold on behalf of clients is out of scope, as is anything the company doesn't have the rights to. OpenAI says it is not seeking sensitive or personal information, or information that belongs to a third party. Reuters reported that the Spirit data was to contain no customer information or personally identifiable information, and MIT Technology Review reports that sellers' archives are scrubbed of personal details and HR records are left out.

Roles, timing and the work itself are what carry the value, so removing personal details rarely costs much. Whether a given record can be licensed at all depends on your contracts and the privacy law where you operate. These records tend to stay out:

• HR, payroll and medical records about staff
• Customer contact details and account numbers
• Client material you are not free to share
• Anything the company doesn't have the rights to
• Passwords, keys and other credentials

How do you list the data your company holds?

You don't need to export or clean anything to find out where you stand. Start with a short list: which tools your team works in, roughly how long it has used each, how far back the records go, and whether the company owns them or holds them for clients. Add your industry, country and head count.

Those are the questions our free check asks. We look at what you have and tell you whether it could qualify and what affects its value, even if the answer is no. For the wider picture, including who pays and how licences work, read how to sell company data to AI companies, or our guide to who buys company data for AI.