ITIL & Service Management
ITIL® (Version 5) AI Governance
Govern AI within the ITIL framework.
3 daysIntermediate7 modules
About this course
Govern AI within the ITIL framework. Over three days you will learn AI fundamentals, risks, ethics and strategy, the ITIL AI governance framework, and how to design, implement and maintain AI governance in practice.
What you'll learn
- 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.
Curriculum
7 modules
- 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
- 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
- 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
- AI Governance perspectives
- Governance lifecycle
- AI Governance Model
- AI Governance Improvement Model
- Governance patterns
- Governance maturity
- Governance readiness assessment
- Governance characteristics
- Stress-testing 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
- 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
- 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
Who it's for
IT service leaders, governance and risk professionals.
Before you start
- There are no formal prerequisites for this course. However, familiarity with IT service management concepts, digital transformation, or AI technologies is beneficial.
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