Enterprise AI governance requires a robust operating model beyond just policy, focusing on architecture, telemetry, and runtime enforcement. Generative AI, especially agentic systems, blurs traditional security boundaries of identity, data, and system control. Organizations must adapt by addressing how agents act, their authorization, and auditability to manage risks effectively. AI
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IMPACT Provides a framework for organizations to implement effective AI governance, addressing operational challenges beyond policy.
RANK_REASON The article discusses best practices and challenges in enterprise AI governance, offering an opinionated perspective rather than announcing a new product, research, or funding.