AI Governance: Risk, Governance, and Portfolio Strategy in Artificial Intelligence (AI) Enabled Organizations (IS & AI STRATEGY)

Artificial Intelligence is reshaping how organizations decide, operate, and compete—but governance has not kept pace. As AI systems grow more autonomous, interconnected, and opaque, the central challenge is no longer whether organizations can deploy AI, but whether they can govern it responsibly, strategically, and sustainably. This book focuses on building the architecture of trust for AI-enabled organizations. It examines how risk management, governance, compliance, and portfolio strategy must work together to support innovation without creating ethical blind spots, regulatory exposure, or systemic fragility. Rather than treating governance as a constraint, the book reframes it as an enabling capability that allows organizations to scale AI with confidence and accountability. As the culminating volume in the AI and IS Strategy Series, the book integrates leading governance frameworks and regulatory standards—including COBIT, ITIL, ISO/IEC 38500, NIST AI Risk Management Framework, the EU AI Act, and OECD and UNESCO principles—into a coherent, operational approach. It moves beyond abstract principles to show how governance is enacted through decision rights, oversight mechanisms, lifecycle controls, risk instruments, and portfolio prioritization. Readers will learn how to design governance operating models suited to modern enterprises, manage AI and IS portfolios across incremental and disruptive initiatives, align compliance with strategic intent, and anticipate emerging challenges posed by agentic and multi-agent systems. The book also addresses governance in entrepreneurial and platform contexts, where speed, scaling, and ecosystem coordination introduce additional risks and responsibilities. Written for executives, strategists, architects, policymakers, and risk and compliance leaders, this book provides a practical, systems-level perspective on governing AI in organizations where intelligent systems are no longer experimental, but foundational.