As part of Seyfarth’s 2026 Trade Secrets Webinar Series, our panel presented From Prompt to Proof: Investigating and Litigating Trade-Secret Theft in the Age of AI, exploring how artificial intelligence is transforming the way organizations create, use, protect, investigate, and litigate trade secrets.
Jesse Coleman and Gio Perez of Seyfarth Shaw LLP, together with Jim Vaughn of iDiscovery Solutions, discussed the growing intersection of AI, trade secret protection, employee mobility, digital forensics, and cybersecurity. Drawing on their experience in litigation, investigations, and AI governance, the panel examined practical steps organizations can take to protect valuable confidential information while embracing new technologies.
View the Recording – CLE credit for this recording expires on September 8, 2027. Please refer to the program description for jurisdiction-specific details and deadlines.
Key Takeaways
AI-Related Trade Secrets Extend Beyond the Data Entered Into a Tool
Organizations often focus on the information employees input into AI systems, but protectable trade-secret value may exist throughout the broader AI ecosystem. Proprietary training and evaluation methods, AI-generated insights, unique workflows, prompts, datasets, model configurations, and human review processes can all contribute to a company’s competitive advantage. In many cases, the value lies not in a single component, but in the unique combination of technologies, data, and expertise that make up an organization’s AI stack.
Using AI Does Not Automatically Destroy Trade Secret Protection
The use of AI tools does not necessarily eliminate trade-secret protection, but the surrounding safeguards matter. Courts evaluating whether information remains protectable will likely examine the specific AI platform involved, the account used, applicable contractual terms, confidentiality and retention protections, employee authorization, and the company’s overall governance practices. Decisions made today regarding AI implementation and oversight may later become critical evidence in demonstrating that reasonable measures were taken to preserve secrecy.
AI Changes the Evidence, Not the Core Legal Inquiry
Traditional trade secret principles continue to apply, but AI can complicate the evidentiary picture. Because AI tools can summarize, transform, and synthesize information without reproducing source material verbatim, organizations must be prepared to trace the full lifecycle of confidential information from inputs to outputs and any resulting competitive use. Effective investigations should focus not only on source files, but also on prompts, outputs, derivatives, implementation efforts, and indicators of downstream use.
AI Controls Should Follow the Entire Employee Lifecycle
Managing AI-related risk requires more than a standalone policy. Organizations should address AI usage during onboarding, throughout employment, and during offboarding. This includes preventing the introduction of prior-employer confidential information, identifying approved tools and acceptable uses, restricting access to sensitive information, and reviewing personal AI accounts and AI-generated materials when employees depart. Consistent controls throughout the employment lifecycle can help reduce risk and strengthen legal protections.
Effective AI Governance Requires Practical Rules and Strong Vendor Management
Rather than attempting to prohibit AI outright, organizations should provide employees with clear, practical guidance regarding permitted uses. The panel discussed the value of developing usage frameworks that distinguish between permitted, controlled, approval-required, and prohibited activities. Organizations should also conduct diligence on AI providers, understand how company information is accessed, retained, and protected, and ensure contractual protections align with the organization’s expectations and risk tolerance.
Reasonable Measures Must Be Implemented and Provable
Written policies alone are rarely enough to establish trade-secret protection. Organizations should be prepared to demonstrate that they identified the information they intended to protect, trained employees on their obligations, restricted access appropriately, approved the use of specific tools, documented vendor diligence efforts, and responded promptly to potential disclosures. The same measures that help prevent misappropriation can also strengthen a company’s position if litigation becomes necessary.
Final Thought
While AI is changing how confidential information is created, used, and potentially misappropriated, the fundamental principles of trade-secret protection remain the same. Organizations that take proactive steps to implement governance frameworks, employee training, technical safeguards, and defensible investigative processes will be better positioned to leverage AI’s benefits while protecting their most valuable proprietary information.
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