Advancing Enterprise Security: A Framework for AI-Powered Privileged Access Posture Management

Abstract

The evolution of privileged access management (PAM) toward AI-driven Privileged Access Posture Management (PAPM) represents a significant advancement in enterprise security architecture. This article examines how traditional PAM systems, limited by static provisioning and manual discovery processes, are being transformed through artificial intelligence and machine learning capabilities. This article explores the core components of AI-driven PAPM, including continuous discovery, real-time risk assessment, and automated remediation workflows, demonstrating how these technologies address critical challenges such as over-provisioning, shadow accounts, and compliance monitoring. Through analysis of implementation strategies and real-world applications, this article illustrates how PAPM's dynamic approach to access control and security posture management is enabling organizations to maintain robust security while adapting to increasingly complex IT environments. The findings suggest that AI-driven PAPM not only enhances security operations through automated threat detection and response but also significantly improves compliance readiness and audit efficiency, marking a crucial evolution in privileged access security.