Who Owns AI-Generated Work Product? A Cross-Jurisdictional Snapshot
Authorship, originality and the contractual fixes available while the case law settles in the UK, EU and US.
Embeddings are derived data, but they are still derived from something confidential. What reasonable steps look like now.
Trade secret protection depends on reasonable steps to keep information secret. Embedding that information into a vector index creates a derived copy that most confidentiality programmes were not written to cover.
A numerical representation of a passage, generated so that similar meanings sit close together in a high-dimensional space. It is not the text, and it is not readable by a person. It is also not a one-way function in any strong sense: inversion research has repeatedly shown that substantial portions of source text can be reconstructed from embeddings, particularly with knowledge of the embedding model.
The practical conclusion: treat an embedding of confidential material as confidential material. The alternative — treating it as anonymised derived data — is a position that has not been tested and would be uncomfortable to argue.
Access controls that apply to retrieval results, not only to documents: if a user cannot open the document, retrieval must not return its passages. Deletion that cascades to the index. Encryption of the vector store with keys under your control. Contractual terms with embedding providers covering retention, training use and deletion. And an inventory that records where confidential material has been embedded, which most organisations do not have.
Definitions of Confidential Information should expressly cover derivatives, representations and other machine-readable transformations. Return-and-destroy obligations should reference derived artefacts explicitly. Neither is difficult to draft; both are absent from the majority of NDAs currently in circulation.
This article is general information about legal technology and practice, not legal advice, and it does not create a lawyer–client relationship. JuriPro is a technology company, not a law firm. Take advice from a qualified lawyer admitted in the relevant jurisdiction before acting on anything here.
Chief Technology Officer, JuriPro
Machine-learning engineer who has spent a decade building retrieval and document-understanding systems for regulated industries.
Authorship, originality and the contractual fixes available while the case law settles in the UK, EU and US.
A plain-English account of how a language model reads an agreement, where its judgement is genuinely useful, and the four failure modes every reviewing lawyer should know about.
Uncapped indemnities, silent auto-renewals, unilateral change rights: the provisions that rarely make the negotiation summary but decide who pays when something goes wrong.
Start a 14-day trial, or book a 30-minute walkthrough with someone who has practised.