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ITIL v5 AI Governance

Last Update:

November 6, 2026

Accredited by:

Course Overview

AI is moving faster than most governance structures can absorb. Shadow AI, unclear accountability, and inconsistent decision-making have become the default risk profile for
organizations without a structured governance model. ITIL AI Governance (Version 5) closes that gap, giving professionals a PeopleCert-accredited, ITIL-aligned framework to assess, design,
implement, and maintain AI governance across the organizational lifecycle.

Built around the ITIL AI Governance Improvement Model, the course is a practical, repeatable method for stress-testing governance, defining requirements, and maintaining assurance as AI
capability matures. Participants apply the ITIL AI Capability Model (6C model) to evaluate AI suitability, risk, and controls against real scenarios, and work through the four governance
perspectives: autonomy, ethics, data, and compliance, understanding why none can stand alone.

By the final module, participants can run the full model end-to-end: assessing readiness, designing adjustments, implementing controls, and maintaining governance across structures,
culture, and supplier relationships. The result is a credible, applied certification that holds up under regulatory scrutiny.

Learning Objectives

Following the completion of the course, you will be able to:

  • Understand the fundamentals of AI, governance, and AI governance, and how they relate to corporate governance, IT governance, and leadership
  • Define key AI concepts and apply the ITIL AI Capability Model to assess AI behaviour, use cases, risks, and governance needs
  • Explain how AI creates value and introduces risk and trade-offs across strategy, transformation, and sustainability
  • Describe AI risks, ethical principles, and countermeasures, and how they shape governance requirements and controls
  • Apply the ITIL AI Governance Improvement Model to assess, design, implement, and maintain governance
  • Apply AI governance across practical scenarios, complementary frameworks, regulation, and third-party or supplier relationships

Target Audience

Ideally for:

  • IT service management and ITSM leaders extending their practice into AI oversight
  • Transformation, digital adoption, and change management professionals
  • Product and service managers responsible for AI-enabled products or services
  • Risk, compliance, and governance officers evaluating AI-related exposure
  • AI adoption leads and organizational functions introducing AI into operations

Prerequisites

None.

Examination/Certification

  • 90 minutes duration
  • 40 multiple-choice questions
  • 70% (28/40) required to pass
  • Open book*

 

Training Content

DAY 1
9.00am – 11.00am

1. The AI World and the Need for AI Governance

  • What AI offers, and where it puts organizations and professionals at risk
  • AI’s progression from tool to assistant, co-worker, and AI-enabled workforce, and the governance question at each stage
  • Why growing AI adoption raises the stakes for governance
  • Characteristics of good AI governance: fit-for-purpose, adaptive, integrated, holistic, ethical, sustainable

11.00am – 11.15am – Short Break

11.15am – 12.30pm

2. What Is Governance?

  • Governance, AI governance, management, and leadership, defined and distinguished
  • Corporate, IT, and AI governance versus regulation
  • How governance and management interact to create value
  • Benefits of good governance versus risks of poor governance

12.30pm – 1.30pm – Lunch

1.30pm – 3.30m

3. What Is AI and What Can Be Governed?

  • The ITIL AI Capability Model (6C model)
  • AI risks, challenges, and strategic impact
  • The four AI governance perspectives: autonomy and decision-making, ethical and responsible AI, data quality and security, regulatory compliance
  • Why the four perspectives are interdependent

4. When AI Governance Fails: Capabilities, Risks, and Controls

  • GenAI, Agentic AI, and Narrow AI: when to use each
  • Key AI characteristics: learning, autonomy, opacity
  • AI risks: bias, privacy, hallucination

3.30pm – 3.45pm – Short Break

3.45pm – 5.00pm

5. ITIL as a Governance Toolkit

  • ITIL fundamentals applied to AI governance
  • How AI supports ITIL product and service lifecycle management
  • How AI enables automation across value chain activities

DAY 2

9.00am – 11.00am

6. ITIL AI Governance Improvement Model: Assess, Stress-Test, Define, Design

  • The AI governance lifecycle and ethical principles for trustworthy AI
  • Why IT governance alone is insufficient for AI initiatives
  • How Shadow AI creates governance risk: visibility gaps, data leakage, compliance exposure
  • The ITIL AI Governance Improvement Model: purpose and steps
  • Using the 6C model to assess suitability, risk, and controls
  • Assessing governance readiness and designing requirement adjustments
  • Evaluating trade-offs between ethics, business objectives, delivery, and trust

11.00am – 11.15am – Short Break

11.15am – 12.30pm

7. ITIL AI Governance Improvement Model: Implement and Maintain

  • Implementing AI governance adjustments
  • Maintaining, assuring, and improving AI governance
  • Governance stewardship and continual improvement
  • Compliance, regulation, and external alignment
  • Applying the full model end-to-end, from assessment to monitoring

12.30pm – 1.30pm – Lunch

1.30pm – 3.30pm

7. ITIL AI Governance Improvement Model: Implement and Maintain (continued)

8. AI in Your World: Unlocking AI in Your Role, Industry, and Function

  • AI value across industries and organizational functions
  • Establishing scenario context and a governance baseline

3.30pm – 3.45pm – Short Break

3.45pm – 5.00pm

9. Connecting AI Governance With Frameworks, Regulations, and Standards

  • Integrating the ITIL AI Governance Improvement Model with other frameworks
  • Applying a holistic governance lens across structure, culture, skills, technology, data, suppliers, and stakeholder trust each other in managing the product and service lifecycle

Price From:

RM5,800.00

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