Advances in technology, and the inevitable litigation that follows, often unfold against a backdrop of long-standing laws—and artificial intelligence (or AI) will not be an exception. For an example of AI-related disputes being litigated under an established legal framework, one only has to look to the application of copyright laws largely in place for over a century to generative AI lawsuits brought by Sarah Silverman and other artists and media companies. See, e.g., Peter Brown, “ChatGPT May Be Threatening Your Copyrights and Privacy,” New York Law Journal, Aug. 7, 2023. While perhaps not as attention grabbing as those copyright cases, trade secret law—developed over decades through common law decisions and state and federal statutes—will likely be one of the key areas of law where stakeholders work to protect, or in some cases protect against, evolving AI technology.

This article examines the core elements of traditional trade secret misappropriation claims and their likely application to AI technology that continues to advance at seemingly warp speeds. Section I takes a practical approach to thinking about the definition of AI. Section II discusses the definition and requirements for establishing an enforceable “trade secret,” and how those requirements are likely to be applied with respect to AI innovations. Section III then discusses how one type of trade secret known as a “combination trade secret” could play a critical role in future AI-related trade secret litigation.

An Overview of Artificial Intelligence

Definitions of “artificial intelligence” continue to vary (and be debated), but AI commonly refers to computer systems that are capable of performing tasks that mimic human intelligence. See “The Artificial Intelligence Glossary,” Sept. 30, 2024, https://www.law.com/legaltechnews/2024/09/30/the-artificial-intelligence-glossary/. The term “artificial intelligence” also serves as something of an umbrella label encompassing a variety of more specific technologies, including machine learning and deep learning. Id. Unsurprisingly, AI technology can be inherently valuable, and can also drive practical use cases, including the following examples (recently discussed by the U.S. Patent and Trademark Office):

• Anomaly detection whereby the use of a neural network can identify or detect anomalies (and can be used in various industries like cybersecurity) (PTO Example 47).
• Speech separation in which AI technology analyzes speech signals and can separate desired speech from extraneous or background speech capable (PTO Example 48).
• Fibrosis treatment in which an AI model has been designed to assist in personalizing individual patient medical treatment. (PTO Example 49)