* Section - ONE: Foundations of holistic AI governance; ** Chapter - 01: The AI governance imperative; ** Chapter - 02: Understanding the AI governance ecosystem; ** Chapter - 03: Data governance - the bedrock of AI governance; ** Chapter - 04: Governance as a cultural framework; ** Chapter - 05: AI foundations for governance: models, capabilities and trade-offs; * Section - TWO: Strategic foundations - core building blocks for AI governance; ** Chapter - 06: The structural foundations of AI governance; ** Chapter - 07: Proactive engagement - ensuring AI governance reflects operational reality; ** Chapter - 08: Centralized intelligence - tracking AI and AI governance issues in one system; ** Chapter - 09: Adaptive governance - ensuring oversights evolves as AI expands; ** Chapter - 10: Continuous monitoring - tracking AI governance effectiveness at the program level; * Section - THREE: Strategic oversights: PRISM as mechanism for building and evaluating AI governance; ** Chapter - 11: PRISM - a structured approach to building and evaluating AI governance; * Section - FOUR: Operationalizing AI governance - structures, tools, and oversights mechanisms; ** Chapter - 12: Anchoring AI governance in organizational structures; ** Chapter - 13: Assessing data risks to govern AI use, development and deployment; ** Chapter - 14: Aligning AI governance with business strategy and risk appetite; * Section - 15: Tracking AI-enabled tools, systems and vendor deployments; ** Chapter - 16: Implementing the AI intake process - governing AI from the start; ** Chapter - 17: AI governance policies, guidelines and enforcement mechanisms; ** Chapter - 18: Upskilling leadership and key staff for AI governance responsibilities; ** Chapter - 19: Incident response: structuring oversight for AI failures; ** Chapter - 20: Systems level continuing monitoring and adaptive AI governance; * Section - FIVE: Scaling and future-proofing AI governance; ** Chapter - 21: Scaling AI governance across business units and global operations; ** Chapter - 22: Measuring AI governance effectiveness and maturity; ** Chapter - 23: Preparing for regulatory evolution and multi-jurisdictional compliance; ** Chapter - 24: Integrating AI governance with enterprise risk and cybersecurity programs; ** Chapter - 25: Future-proofing AI governance against emerging technologies and risks.