The article explores the challenges of managing AI agent data access securely, particularly in multi-user environments where different privilege levels exist. It discusses various implementation approaches to ensure users only see data they are authorized to access, including base scenarios, role-based access control, middleware enforcement, row-level security, proxy database access, API gateway policies, token-based access control, and data masking. The article emphasizes the importance of proper authentication, API security, database-level filtering, and AI output moderation to build secure AI-driven applications that comply with data governance policies and protect sensitive information from unauthorized access.