This white paper explains how AI and machine learning enhance access modeling, certification recommendations, and anomaly detection. It introduces ML-driven role discovery, dynamic access roles to reduce role sprawl, and identity outlier scoring to proactively identify risky access. By leveraging peer group analysis and collaborative filtering, organizations can automate low-risk decisions while focusing scrutiny on high-risk scenarios. The paper demonstrates how cohesive AI integration strengthens governance, reduces manual effort, and supports compliance in complex, hybrid environments.

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