As AI agents become increasingly integrated into applications ranging from small demos to enterprise-level solutions, managing secure data access poses significant challenges. These AI-driven applications require robust access control mechanisms to ensure that users with varying privilege levels only access data they are authorized to see. The discussion highlights scenarios where access is controlled at multiple levels, such as database queries, API calls, and AI-generated outputs. For instance, User A has unrestricted access to resources, while User B's access is limited by role-based constraints, ensuring they cannot retrieve sensitive data without proper authorization. Strategies like row-level security, API gateway policies, and data masking are employed to enforce these controls. The implementation of role-aware AI agents dynamically adjusts based on user permissions, ensuring compliance with data governance policies and protection of sensitive information. The article underscores the importance of combining authentication, API security, and database filtering with AI output moderation to build secure AI-driven applications.