AI is rewriting how legal departments protect trade secrets — but courts are expected to apply existing law rather than create novel AI-specific doctrine, senior IP lawyers warn
Generative AI is transforming how companies create, share, and inadvertently expose confidential information — but senior intellectual property lawyers are counselling legal departments not to expect courts to develop new trade secret doctrine to accommodate it. Peter Toren, an IP and computer crime attorney and former federal prosecutor with the US Department of Justice, has stated that courts will apply established, widely accepted trade secret principles to AI-related disputes rather than adopting novel approaches, at least initially. The practical implication is that legal departments must use existing legal frameworks — trade secret law as it stands — to address the new risk landscape that AI creates, rather than waiting for bespoke AI-specific rules. The Thomson Reuters Future of Professionals Report (released 22 June 2026) adds a related dimension: a significant gap exists between what in-house clients want from their law firms on AI and what they are actually receiving, with 66% of those in firms with a clear AI strategy reporting that AI is meeting or exceeding expectations for creating value — suggesting the firms that communicate a clear AI programme to clients are significantly outperforming those that do not. Together, these developments point to a legal market where AI governance — both as a subject of legal advice and as a tool reshaping how advice is delivered — is rapidly becoming a core competency for in-house and external legal teams alike.
Why this matters
The trade secret–AI intersection is generating immediate client demand for legal departments to audit what information their AI systems are ingesting, how confidentiality obligations interact with AI training and output, and what contractual protections are needed in AI procurement and deployment agreements. The judicial conservatism signalled by senior IP lawyers — applying existing law rather than building new doctrine — actually raises the stakes for legal departments: they cannot rely on courts to create new protections and must structure their trade secret programmes robustly under current frameworks. The EU AI Act and diverging US state AI laws (with Colorado, Connecticut, and the federal government all taking different approaches in a three-week window in May–June 2026, per Law360 reporting) add a compliance dimension that will require external counsel to map obligations across multiple jurisdictions. The Thomson Reuters engagement gap finding suggests firms that invest in communicating their AI strategy to clients will capture a disproportionate share of in-house mandates.
On the Ground
On an AI governance matter for a legal department, a trainee would assist with drafting a vendor due diligence questionnaire probing how an AI tool handles confidential client data, review and mark up a data processing agreement to ensure it addresses trade secret and confidentiality obligations, and help prepare a regulatory impact assessment memo mapping the client's AI deployment against applicable state and EU rules.
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Question you might get
“A client's AI system has ingested documents that may contain a competitor's trade secrets. How would you advise the client's legal team on their exposure and what immediate steps should they take?”
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