Autonomous Policy Enforcement: AI Agent-Based Access Control Systems for Dynamic Resource Management

This chapter presents an approach to organizational data governance through autonomous Artificial Intelligence agent-based policy enforcement systems, specifically leveraging Data Security Platform technology capabilities. Traditional access control mechanisms often fail to adequately address the dynamic and complex nature of modern enterprise data environments, leading to significant governance gaps that compromise data quality, security, and compliance across distributed organizational infrastructures. The Intelligent Policy Agent Network (IPAN) architecture is introduced as a comprehensive solution where Large Language Model-powered agents operate as autonomous policy enforcers, performing real-time database discovery, enabling conversational access control, implementing dynamic data masking, and ensuring cross-database policy enforcement. Through empirical evaluation across diverse industry sectors including finance, insurance, and healthcare, the framework demonstrates substantial improvements in policy compliance rates, significant reductions in unauthorized access incidents, and dramatic decreases in manual governance overhead.