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ARTICLE · 26 JUNE 2026

Considerations And Strategies For Patenting AI

Gesmer Updegrove LLP
Gesmer Updegrove LLP
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Gesmer Updegrove LLP

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Artificial intelligence and machine learning inventions present unique patenting challenges that require careful strategic choices between patent and trade secret protection. This guide examines how to frame AI/ML innovations as concrete technical improvements, structure claims around specific architectural features and processing steps, and draft specifications that satisfy eligibility and disclosure requirements.

United StatesIntellectual Property
Todd Gerety
Todd Gerety

Key Takeaways:

  • The patent-versus-trade-secret choice turns on detectability. Patent what is observable in products, publications, or standards, and consider trade secret for contributions hidden in non-observable model internals. The two can be layered.
  • Subject-matter eligibility under 35 U.S.C. § 101 depends on framing the invention as a concrete technical improvement or practical application, not a desired result or business outcome.
  • Recite specific technical features (model architecture, processing steps, data handling, and special-purpose hardware) as an ordered combination of input, processing, and output limitations.
  • Draft for enforcement. Keep each independent claim performable by a single actor and tied to observable activity, and separate training claims from inference claims.

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The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.

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