ITIL AI Governance White Paper

Evolving Governance to Enable Responsible AI

Artificial Intelligence (AI) is transforming the way organizations operate, make decisions, and deliver value. Yet, without effective governance, its adoption can create significant risks, from biased decisions and data misuse to compliance failures and reputational damage. This paper provides a practical playbook for embedding effective AI governance into corporate structures, enabling organizations to capture the benefits of AI responsibly and sustainably.

The core message is that traditional IT governance is insufficient for AI. AI introduces unique challenges: autonomy in decision-making, lack of transparency, evolving ethical dilemmas, and fast-changing regulatory requirements. To address these, organizations must extend governance across four perspectives: Decision Authority & Risk Management, Ethical Principles & Responsible AI, Data Governance & Performance Management, and Regulatory Compliance & Operational Standards.

The paper applies the PeopleCert 6C model to classify AI capabilities (Creation, Curation, Clarification, Cognition, Communication, Coordination) and map them against AI-specific risks. It outlines a structured, four-step approach for adapting governance: stress-testing current frameworks, defining AI-specific requirements, designing governance adjustments, and operating governance dynamically.

Who Should Read This Paper

Executives and Board Members – to understand why AI governance must evolve from control to stewardship, ensuring AI use aligns with corporate purpose, ethics, and regulatory expectations.

Chief Information Officers (CIOs) and Chief Digital Officers (CDOs) – to find a structured, four-step roadmap for embedding AI oversight into existing technology governance without rebuilding it from scratch.

IT and Service Management Leaders – to discover how traditional IT governance (including ITIL) can be stress-tested and adapted for AI-driven operations, ensuring resilience and accountability.

Practitioners and Consultants in ITSM, DevOps, and Governance – to gain practical assessment tools (governance patterns, risk heatmaps, maturity indicators) for implementing AI governance frameworks in client or internal environments.