This guide challenges the belief that AI speed and security are mutually exclusive. It explains that traditional governance methods—manual approvals, static policies, and delayed security reviews—fail in AI-driven environments, often leading to shadow AI and weak enforcement. The guide emphasizes that AI systems evolve continuously, making static controls ineffective. It advocates for treating security policies like code—continuously applied, tested, and updated. Key recommendations include aligning with global standards, enforcing code-level policies early, and using system-level intelligence to correlate behavior with governance intent. The outcome is a shift from reactive risk management to a scalable, automated system of record for AI governance that enables innovation without sacrific

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