Programme overview
Introduction
Artificial intelligence initiatives frequently reach the boardroom embedded within strategic capital requests, transformation programmes, and enterprise risk reports. However, governing bodies often encounter difficulty evaluating where these technologies generate measurable value versus unmitigated liability. Without formal oversight mechanisms, directors risk either granting passive assent to speculative proposals or imposing broad restrictions that stall operational progress. This five-day course on AI for boards and executives equips non-executive directors, board chairs, and senior executives with systematic frameworks to interrogate management assumptions, establish technical risk thresholds, and maintain institutional accountability. Participants develop practical competencies in evaluating business cases, reviewing algorithmic incident scenarios, and establishing a Board AI Oversight Charter with Core Concept.
Course Objectives
- Evaluate how predictive, generative, and agentic artificial intelligence alter competitive structures and corporate operating models.
- Define distinct board and executive governance responsibilities using international frameworks including ISO/IEC 38507 and ISO/IEC 42001.
- Scrutinise management investment proposals through structured board enquiry protocols and value verification frameworks.
- Set an AI risk appetite statement and oversee impact assessments, operational incidents, and third-party dependencies.
- Monitor algorithmic performance and compliance using the Three Lines Model and dedicated board reporting dashboards.
- Construct a Board AI Oversight Charter specifying oversight mandates, committee duties, and management escalation triggers.
Target Audience
- Board chairs and non-executive directors seeking structured oversight methodologies for emerging technologies
- Members of board audit, risk, governance, and technology oversight committees
- Chief executive officers and managing directors accountable for enterprise strategy and organizational governance
- Executive committee members spanning finance, operations, technology, risk, and corporate governance functions
- Company secretaries and governance advisers guiding board deliberations on technology stewardship
Course Outline
Day 1: AI and the Strategic Context
- Distinctions Between Predictive, Generative, and Agentic AI Systems for Executive Oversight
- Competitive Disruption Analysis Across Industry Sectors Using Porter's Five Forces
- Board AI Literacy Diagnostic and Capability Baseline Assessment
- Enterprise AI Maturity Review Across Strategy, Data Assets, Talent, and Governance
- Cross-Sector Value Realisation Evidence Across Productivity, Revenue Generation, and Service Delivery
Day 2: Governance Standards and Principles for AI
- ISO/IEC 38507 Governance Implications of AI for Governing Bodies and Executive Leadership
- OECD AI Principles as a Policy Baseline for Corporate Technology Stewardship
- ISO/IEC 42001 AI Management System Requirements and Board Verification Protocols
- NIST AI RMF Govern Function Core Outcomes and Governing Body Accountabilities
- Three Lines Model Implementation for Algorithmic Risk and Compliance Supervision
Day 3: Setting Ambition and Directing Investment
- Strategic AI Ambition Formulation Structured by the Three Horizons Model
- AI Capital Allocation and Portfolio Scrutiny Using Value at Stake and Real Options Valuation
- Structured Board Enquiry Protocols for Evaluating Management Business Cases
- Enterprise Operating Architecture Review: Centralised, Hub-and-Spoke, and Federated Models
- Workforce Transition and Organizational Impact Using Task-Based Exposure Metrics
Day 4: AI Risk Appetite, Incidents and Exposure
- Board AI Risk Appetite Formulation Aligned with ISO 31000 and COSO ERM Frameworks
- ISO/IEC 42005 AI System Impact Assessment Review and Management Scrutiny
- Incident Stress-Testing: Enterprise Data Leakage, Algorithmic Hallucination, and Synthetic Media Fraud
- Third-Party Dependencies, Supply Chain Vulnerability, and Foundation Model Concentration Risk
- Comparative Governance Analysis: Risk-Based, Principles-Based, and Sector-Specific Regimes
Day 5: Board Case Work and the Oversight Charter
- Board Room Case Evaluation: Authorising a Direct Customer-Facing Generative AI Deployment
- Crisis Governance Case Analysis: Remediation and Disclosure of Algorithmic Bias Incidents
- Board AI Dashboard Architecture: Value Realisation, Risk Metrics, and Ethical Conduct Indicators
- Drafting the Formal Board AI Oversight Charter for Enterprise Adoption
- Simulated Board Deliberation and Executive Committee Peer Challenge
Skills You Will Gain
- AI Governance
- Risk Oversight
- AI Strategic Oversight
- AI Business Case Scrutiny
- Algorithmic Risk Supervision
- Operating Model Evaluation
- Board Dashboard Design
Why Attend This Course
- Establish an actionable Board AI Oversight Charter refined through simulated boardroom deliberation.
- Equip directors with structured enquiry protocols to separate viable proposals from ungrounded projections.
- Validate that enterprise algorithmic deployments remain strictly within approved institutional risk thresholds.
- Benchmark organizational oversight mechanisms against international governance standards and executive peer practices.
Conclusion
Executive leadership and governing boards cannot delegate artificial intelligence oversight entirely to technical departments, nor can they govern effectively without disciplined supervisory structures. By progressing from strategic positioning and international governance standards to capital allocation scrutiny, risk appetite calibration, and incident oversight, this course provides directors with structured control over technology adoption. Participants conclude the programme with an operational Board AI Oversight Charter, ensuring a consistent and defensible foundation for institutional decision-making.