The AI Paradox: Using Public AI Without Exposing Enterprise Data

About this session

Public AI is powerful, but many enterprises hesitate to use it because of the risk of exposing private or sensitive data. This talk will explore how organizations can benefit from tools such as ChatGPT, Gemini, and other AI agents without sacrificing data privacy. It will introduce a U.S. patent-pending operating model that combines prompt management, privacy guardrails, and controlled AI-agent execution. Attendees will learn how this model can help reduce data leakage risk while enabling safer and more practical enterprise AI adoption. The talk will provide a clear view of how companies can unlock public AI capabilities while keeping enterprise data protected.