AI Strategy & Governance Foundation And Practitioner (The Leaders) - United Kingdom

AI Strategy & Governance Foundation and Practitioner Course Outline

Module 1: AI Strategy Development

• The Strategic Case for AI at Executive Level
• AI Maturity Models and Competitive Positioning
• Aligning AI Ambition to Business Objectives
• Identifying Strategic AI Opportunities Across the Enterprise
• Activity: Mapping AI Opportunities to Strategic Priorities
• Competitive Advantage and Business Model Innovation Through AI
• Workshop: Drafting Your Enterprise AI Strategy

Module 2: Enterprise AI Vision and Operating Model

• Defining a Compelling Enterprise AI Vision
• AI Operating Model Design and Delivery Options
• Roles, Accountabilities and Decision Rights
• Integrating AI into Existing Operating Structures
• Case Exercise: Choosing the Right Operating Model
• AI Leadership Team Composition and Mandate

Module 3: AI Governance Frameworks

• What Effective AI Governance Looks Like
• Governance Architecture: Structures, Layers and Bodies
• Policies, Standards and Decision-Making Processes
• Governance Across the AI Lifecycle
• Linking Governance to Risk and Compliance Functions
• Workshop: Designing Your AI Governance Model
• Sustaining and Evolving Governance over Time

Module 4: Board and Executive Responsibilities

• Board-Level Oversight and Executive Accountability for AI
• Fiduciary Duties in an AI-Enabled Organisation
• Escalation Pathways and Board Reporting Mechanisms
• Activity: Structuring an AI Board Report
• Engaging the C-Suite in AI Governance

Module 5: Responsible AI and Ethics

• Core Principles of Responsible AI
• Fairness, Transparency and Explainability in Practice
• Human Dignity, Bias and Discrimination Risk
• Ethical Decision-Making Frameworks for Leaders
• Building an Ethical AI Culture Across the Organisation
• AI Policy Development: Scope, Content and Ownership
• Activity: Auditing an AI Initiative for Ethical Compliance

Module 6: AI Risk Management

• The AI Risk Landscape for Senior Leaders
• Categorising AI Risks: Strategic, Operational and Reputational
• Risk Appetite, Tolerance and Prioritisation Methods
• Third-Party and Supply Chain AI Risk
• Case Exercise: Managing a High-Profile AI Risk Event
• Embedding Risk Management into AI Governance

Module 7: Regulatory and Compliance Considerations

• Global AI Regulatory Landscape and Direction of Travel
• The EU AI Act: Executive Obligations and Implications
• Data Privacy, GDPR and AI Compliance Intersections
• Sector-Specific Regulatory Requirements
• Building a Compliance Monitoring and Reporting Function
• Activity: Compliance Gap Analysis for an AI Programme

Module 8: AI Portfolio and Investment Management

• Thinking in Portfolios: Strategic AI Investment Logic
• AI Initiative Classification and Prioritisation Criteria
• Business Case Development and ROI at a Strategic Level
• Balancing Innovation, Scaling and Run-the-Business Initiatives
• Vendor and Build-vs-Buy Decision Frameworks
• Executive KPIs and Success Metrics for AI
• Activity: Scoring and Prioritising an AI Initiative Portfolio

Module 9: AI Transformation Roadmaps

• What an Enterprise AI Roadmap Must Achieve
• Structuring Phases: Foundation, Scale and Optimise
• Dependencies, Sequencing and Critical Path Thinking
• Governance and Risk Milestones in the Roadmap
• Communicating the Roadmap to the Board and Stakeholders
• Workshop: Building a 12-Month Enterprise Implementation Roadmap

Module 10: Change Management and AI Adoption

• Organisational Readiness and Leadership for AI-Driven Change
• Overcoming Resistance and Building AI Confidence
• AI Adoption Strategies Across Business Functions
• Human-AI Collaboration: Redesigning Ways of Working
• Workforce Transformation and Strategic Skills Planning
• Activity: Designing an AI Adoption and Engagement Plan

Module 11: AI Centre of Excellence

• Purpose and Value of an AI Centre of Excellence
• CoE Operating Models, Governance and Staffing
• Measuring CoE Impact and Maturity
• Case Exercise: Designing a Fit-for-Purpose AI CoE

Who Should Attend this AI Strategy & Governance Foundation and Practitioner Course?

This AI Strategy & Governance Foundation and Practitioner Course equips delegates with the strategic insight and governance capability required to shape, approve, and implement responsible AI initiatives at an organisational level. This training can benefit a wide range of professionals, including:

• Senior Leaders
• Board Members
• Chief Technology Officers
• Chief Data Officers
• Risk and Compliance Professionals
• Digital Transformation Leaders
• Strategy Consultants

Prerequisites of the AI Strategy & Governance Foundation and Practitioner Course

There are no formal prerequisites for attending this AI Strategy & Governance Foundation and Practitioner Course. However, familiarity with business operations, digital technologies, or organisational strategy will help delegates engage more fully with the course content. Prior exposure to AI tools or productivity platforms is beneficial but not required.

AI Strategy & Governance Foundation and Practitioner Course Overview

The AI Strategy & Governance Foundation and Practitioner Course equips delegates with a structured approach to planning, governing, and scaling AI initiatives across an organisation. Rather than focusing on technical development, this course explores the strategic, financial, regulatory, and organisational factors that drive successful AI adoption.

This course helps delegates to gain practical knowledge of AI value mapping, ROI assessment, risk governance, regulatory considerations, and organisational change management. They will also understand how responsible AI governance supports better decision-making, stronger compliance, and more effective enterprise-wide AI adoption.

This 4-Day course by The Knowledge Academy enables delegates to develop practical strategies for leading AI transformation within their organisations. Upon completion, delegates will be able to assess AI opportunities, mitigate governance and compliance risks, and create a structured, board-ready AI roadmap for sustainable business adoption.

AI Strategy & Governance Foundation and Practitioner Course Objectives

• To understand core AI strategy and governance principles
• To align AI initiatives with organisational goals and risk frameworks
• To identify ethical, legal, and regulatory AI considerations
• To design responsible AI governance structures and policies
• To assess AI risks, controls, and compliance requirements
• To implement AI oversight and performance monitoring mechanisms
• To develop practical AI governance roadmaps for organisations

Upon completion of this AI Strategy and Governance Certification, delegates will have the strategic clarity and practical tools to lead AI initiatives responsibly. They will be equipped to engage confidently with boards, regulators, and teams on all matters relating to AI strategy, governance, and organisational readiness.

What's Included in this AI Strategy & Governance Foundation and Practitioner Course?

• World-Class Training Sessions from Experienced Instructors
• AI Strategy & Governance Foundation and Practitioner Examination
• AI Strategy & Governance Foundation and Practitioner Certificate
• Digital Delegate Pack

AI Strategy & Governance Foundation and Practitioner (The Leaders) Examination 

To achieve the AI Strategy & Governance Foundation and Practitioner Certification, candidates will need to sit for an examination that evaluates their understanding of AI adoption at an organisational level, including governance, risk management, compliance, and value realisation. The exam tests the ability to align AI initiatives with business strategy, establish responsible AI frameworks, and lead sustainable AI transformation. The exam format is as follows: 

• Question Type: Multiple Choice 
• Total Questions: 50 
• Total Marks: 50 Marks 
• Pass Mark: 74%, or 37/50 Marks 
• Duration: 60 Minutes 
• Open Book/ Closed Book: Open Book