Trade Secrets in the Age of AI: How Generative and Agentic Systems are Changing Insider Risk

Artificial intelligence is transforming the trade secret threat landscape. As companies deploy internal AI tools, enterprise search, co-pilots, and agentic systems, the risks posed are increasingly subtle, scalable, and harder-to-detect. Employees can extract and synthesise sensitive information without direct access to underlying repositories, and at a speed and scale that outpaces many legacy legal technical and compliance controls.  This session will examine the risks posed by internal use of artificial intelligence, consider how AI is changing the mechanics of trade secret misappropriation, and question how legal, technical, and governance frameworks must evolve in response.

• Examine how AI changes the mechanics of trade secret misappropriation, internal access, intent monitoring and proof.
• Explore how agentic AI may enable the collection summarisation and external extra-filtration of sensitive information.
• Address the growing tension between productivity and protection - how can companies embrace AI tools without unintentionally creating a machine assisted insider threat environment?
• Discuss emerging legal, technical, investigative and governance challenges, such as: When does an AI query constitute misappropriation? How should practitioners design reasonable measures, considering the risks posed by internal AI use?