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Course Overview
Artificial Intelligence is transforming every aspect of modern business, making effective governance essential for ensuring responsible, ethical, and sustainable AI adoption.
In this three-day instructor-led course, you'll learn how to establish governance structures that enable organizations to confidently adopt and scale AI while balancing innovation, compliance, risk management, and human oversight. Using the ITIL® AI Governance framework, you'll explore practical approaches for governing AI-enabled products and services, assessing AI risks, implementing governance controls, and continually improving AI governance capabilities.
Throughout the course, you'll apply governance concepts to realistic business scenarios while learning how AI governance integrates with existing ITIL practices, organizational strategy, and digital transformation initiatives.
Who Should Attend
- IT Leaders and Managers
- AI Governance Officers
- CIOs and CTOs
- Digital Transformation Leaders
- Product and Service Managers
- Enterprise Architects
- Risk, Compliance, and Security Professionals
- Data and AI Professionals
- IT Service Management Professionals
- Business Leaders responsible for AI adoption
Course Objectives
- Explain AI governance principles and their role within the ITIL framework.
- Differentiate governance from management in AI-enabled organizations.
- Understand AI capabilities, risks, ethical considerations, and governance requirements.
- Assess AI governance maturity and organizational readiness.
- Apply the ITIL AI Governance Model and Improvement Model.
- Design governance requirements for AI-enabled systems.
- Implement governance controls that support responsible AI adoption.
- Monitor, assure, and continually improve AI governance.
- Align AI governance with regulatory, ethical, and sustainability requirements.
- Apply governance principles to real-world AI scenarios.
- Prepare for the ITIL AI Governance (Version 5) certification exam.
Course Outline
Module 1: AI Governance Foundations
- Introduction to AI Governance
- AI Governance versus IT Governance
- Governance versus Management
- ITIL Guiding Principles
- ITIL Value System
- Product and Service Lifecycle
- Four Dimensions of Service Management
- ITIL Maturity Model
- Continual Improvement
- Transformation Model
- Governance responsibilities and organizational value
Module 2: AI Fundamentals
- AI concepts and terminology
- Generative AI
- Agentic AI
- Narrow AI
- AI characteristics and behaviors
- AI opportunities and business value
- AI across industries
- AI-enabled digital transformation
- Sustainability considerations
- The ITIL AI Capability (6C) Model
Module 3: AI Risks, Ethics, and Strategy
- AI risk categories
- Ethical principles
- Fairness
- Transparency
- Accountability
- Human oversight
- AI risk profiling
- Bias and hallucinations
- Data governance
- Shadow AI
- Strategic AI adoption
- AI governance challenges
Module 4: ITIL AI Governance Framework
- AI Governance perspectives
- Governance lifecycle
- AI Governance Model
- AI Governance Improvement Model
- Governance patterns
- Governance maturity
- Governance readiness assessment
- Governance characteristics
- Stress-testing governance
Module 5: Designing and Implementing AI Governance
- Governance requirements
- Decision authority
- Human oversight
- Governance controls
- Preventive, detective, and corrective controls
- Governance for Shadow AI
- Supplier governance
- Sustainability requirements
- AI governance implementation
- Governance roles and responsibilities
Module 6: Maintaining AI Governance
- Governance assurance
- Governance maturity indicators
- Auditability
- Traceability
- Documentation
- Monitoring AI governance
- Metrics and observability
- Continual improvement
- Governance stewardship
- Stakeholder feedback
- Regulatory compliance
- Third-party AI governance
Module 7: Practical Application of AI Governance
- Governance scenario analysis
- Governance maturity assessment
- AI capability assessment
- Governance gap analysis
- Risk assessment
- Governance design
- Governance implementation
- Monitoring governance effectiveness
- End-to-end governance scenarios
- Governance trade-off analysis
- Practical exam-style exercises