Programme overview
Technical depth: Conceptual · Practical mode: Case study
Introduction
Many organisations are running dozens of AI pilots without a shared view of where AI should change the business, what it must not be used for, or who decides. The result is duplicated spend, uneven risk control and pilots that never reach scale. This Core Concept course equips executives to set a deliberate corporate AI strategy: defining the ambition, choosing where AI creates advantage, designing the operating model and governance, and sequencing the work into a realistic roadmap. Participants leave with a Corporate AI Strategy and three-horizon AI Roadmap for their own organisation.
Course Objectives
- Assess the organisation's AI maturity and strategic position using a structured maturity model and value-chain analysis
- Set an AI ambition and guiding principles that align with corporate strategy and risk appetite
- Prioritise AI use cases into a portfolio balanced across value, feasibility and risk
- Design an AI operating model, including a Centre of Excellence, decision rights and funding approach
- Establish AI governance and capability-building arrangements based on ISO/IEC 42001 and ISO/IEC 38507
- Sequence AI initiatives into a three-horizon roadmap with OKRs that the board can approve and monitor
Target Audience
- Executives accountable for corporate strategy and enterprise transformation
- Chief digital, data and technology executives responsible for AI platforms and capability
- Business unit heads who must decide where AI will change their operations and services
- Strategy, planning and portfolio executives who allocate investment across initiatives
- Risk, legal and compliance executives who shape the organisation's AI risk appetite and principles
Course Outline
Day 1: The Strategic Case for AI and Current Position
- AI Capability Landscape Under ISO/IEC 22989 Concepts and Terminology
- Industry Disruption Scan Using Porter's Value Chain
- Enterprise AI Maturity Assessment With the MITRE AI Maturity Model
- Current AI Initiative Inventory and Duplication Review
- Competitor and Peer AI Positioning Benchmark
Day 2: Strategy Frameworks and Governance Standards
- AI Ambition Statement and Strategic Choice Cascade
- Wardley Mapping for AI Capability Build and Partner Choices
- OECD AI Principles as the Basis for Corporate AI Principles
- ISO/IEC 38507 Board Responsibilities for AI Direction and Oversight
- ISO/IEC 42001 AI Management System Scope and Policy Setting
Day 3: Designing the AI Strategy
- AI Canvas for Use-Case Definition and Prediction Value
- Use-Case Prioritisation Matrix: Value, Feasibility and Risk
- AI Operating Model Options: Centralised, Federated and Hub-and-Spoke
- AI Centre of Excellence Mandate, Roles and Decision Rights
- Data, Platform and Talent Capability Plan
Day 4: Strategic Risk, Scale and Adoption
- NIST AI RMF Profile for Enterprise AI Risk Appetite
- Scaling Barriers: Pilot Purgatory, Technical Debt and Fragmented Platforms
- Workforce Impact Assessment and Reskilling Strategy
- Comparative Review of Emerging AI Regulation Across Jurisdictions
- Scenario Planning for Generative and Agentic AI Developments
Day 5: Case Work and the Corporate AI Strategy
- Telecommunications Operator Case Study: Rebuilding a Stalled AI Programme
- Public Utility Case Study: AI Operating Model Choice
- Three-Horizon AI Roadmap Build With OKRs and Funding Gates
- Corporate AI Strategy Drafting for an Own Organisation
- Board Review Panel and Strategy Defence
Skills You Will Gain
- AI Maturity Assessment
- Strategic Choice Framing
- Use-Case Portfolio Prioritisation
- AI Operating Model Design
- AI Principles and Policy Setting
- Capability Gap Planning
- Strategic Scenario Planning
- Roadmap Sequencing
Why Attend This Course
- Return to work with a Corporate AI Strategy and three-horizon AI Roadmap, already challenged by a board-style panel
- Replace scattered pilots with a single portfolio that the executive team has agreed to fund and govern
- Decide which AI capabilities to own and which to source, based on where they create advantage
- Test your strategic thinking against executives from telecommunications, utilities, finance and government
Conclusion
AI changes an organisation's strategy only when leaders decide deliberately where it should be used, how it will be governed and in what order the work will happen. This course moves from assessing AI maturity and strategic position, through strategy frameworks and governance standards, to use-case prioritisation, operating model design and the risks of scaling. The final day produces a Corporate AI Strategy and three-horizon AI Roadmap that executives take back to their board as the basis for coordinated investment.