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Indemnification in AI data deals: who covers a rights claim
Indemnity decides who pays when a rights claim lands. Here is what it promises, and why it is only as good as the rights behind it.
Published 2026-07-22 · 6 min read
Key takeaways
- Indemnification shifts the cost of a rights claim from the buyer to the supplier.
- The promise is only as strong as the supplier and the rights beneath it.
- Signed per-asset licences and inspectable provenance make an indemnity credible.
- AI copyright law is unsettled, which raises the value of clean, licensed data.
- Verify sourcing as well as the clause; the best indemnity is one you never use.
Picture the claim that keeps a model builder up at night. A dataset you trained on turns out to contain material someone did not consent to license. A rights holder comes calling. Who pays?
That is the question indemnification answers. It is one of the most negotiated clauses in a data deal, and for buyers it is one of the most important. But an indemnity is a promise, and a promise is only worth the party and the rights behind it.
What an indemnity actually promises
Indemnification is a contractual promise to cover certain losses. In a data deal, the licensor typically agrees to defend and compensate the buyer if a third party brings a rights claim tied to the licensed material.
It shifts a defined risk from the buyer to the supplier. If the data infringes someone’s rights, the cost of that problem is meant to land on the party that supplied it, not the party that trained on it. That is the point of the clause.
Why the promise depends on the rights behind it
An indemnity from a supplier with no assets, or no real rights, is thin comfort. If a claim arrives and the supplier cannot pay, or was never entitled to license the data, the buyer is exposed anyway.
This is why signed, documented rights make an indemnity credible. When each asset carries a real licence, voice and likeness consent where a person is identifiable, and provenance a buyer can inspect, the supplier is standing behind something solid. The indemnity stops being a hopeful sentence and becomes a backstop with substance under it.
Why buyers should care right now
The legal ground under AI training is unsettled. In Thomson Reuters v. Ross, a US court rejected a fair-use defence — though that case concerned non-generative AI, a legal-research tool, not a generative model. In the United Kingdom, Getty Images largely lost its case against Stability AI: it abandoned its main copyright and database-right claims, and the court rejected the secondary copyright claim, leaving only narrow trademark findings.
Neither case settles the law, and that is the point. When outcomes are uncertain, the value of clean, licensed, consented data rises, because it keeps the disputes that are testing these questions away from your door. Indemnity is the contractual half of that protection; provenance is the factual half.
What buyers should ask for
Ask who gives the indemnity and whether they can honour it. A licensor standing behind their own rights is stronger than a broker passing through material they never controlled.
Ask what it covers. Rights and consent claims tied to the data are the core. Check for carve-outs and caps that would hollow it out. Ask how it connects to the warranties, since an indemnity usually backs a breach of those promises.
Then verify the foundation. Ask to see provenance. Confirm consent was captured per asset and that voice or likeness consent exists where people are identifiable. An indemnity you never need is the best kind, and sound sourcing is how you get there.
Sources
Frequently asked questions
Is an indemnity clause enough on its own to protect a buyer?
No. It is a promise to cover losses, and it depends on the supplier being able to honour it and having held real rights. Pair it with verified provenance and per-asset consent.
What should an indemnity in a data deal cover?
At minimum, third-party rights and consent claims tied to the licensed material. Check the scope, any carve-outs, any cap, and how it links to the supplier’s warranties.
Does Getty v. Stability mean training data is safe to use?
No. Getty largely lost that case, but on specific grounds, including abandoned claims and where the training took place. It does not clear AI training generally, which is exactly why licensed, consented sourcing matters.
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