1. Programme Overview

This executive-level programme equips board members and senior executives with the governance, oversight, and decision-making capabilities required to responsibly adopt and oversee AI-enabled systems in complex, regulated environments. The programme focuses on strategic accountability, risk ownership, and board-level judgement rather than technical AI implementation.

2. Target Audience

• Board Directors (Executive and Non-Executive)

• C-suite and ExCo members

• Senior Risk, Compliance, Audit, and Governance leaders

• Chairs of Risk, Audit, or Technology Committees

3. Total Learning Time

6 CPD Hours (Delivered as a full-day executive workshop or modular equivalent)

4. Learning Objectives

By the end of this programme, participants will be able to:

1. Define and apply board-level governance responsibilities for AI-enabled systems, including oversight, challenge, and accountability.

1. Evaluate AI-enabled initiatives using a structured governance lens (purpose, risk appetite, controls, assurance, and accountability).

1. Identify and prioritise key categories of risk arising from AI-enabled systems (strategic, operational, legal/regulatory, ethical, and systemic).

1. Assess the adequacy of management assurance, reporting, and controls for AI-enabled systems, including escalation triggers and residual risk.

1. Determine appropriate decision rights, committee oversight, and governance cadence across the AI lifecycle (design, deployment, monitoring, change).

1. Formulate a board-level action plan to strengthen AI oversight aligned to organisational context and regulatory expectations.

5. Programme Structure (High-Level Agenda)

• Module 1: AI as a Governance Challenge, Not a Technology Issue

• Module 2: Board Accountability, Oversight, and Decision Rights in AI Contexts

• Module 3: Risk, Ethics, and Systemic Failure Modes of AI-Enabled Systems

• Module 4: Regulatory Expectations and Supervisory Perspectives

• Module 5: Board-Level Scenarios and Decision Simulations

• Module 6: Governance Maturity and Next-Step Actions

6. Learning Methods

• Expert-led executive briefing

• Facilitated board-level discussion

• Case-based analysis of real-world AI governance failures and near-misses

• Scenario-based decision exercises

• Structured executive reflection and peer dialogue

7. Assessment / Engagement

Participant engagement is demonstrated through:

• Active participation in facilitated discussions

• Scenario-based judgement exercises

• Structured reflection on governance implications for their own organisation

No formal examinations; assessment is reflective and applied, appropriate for senior executives.

8. Quality Assurance

• Delivered by senior practitioners and researchers with expertise in AI governance, risk, and executive decision-making

• Content reviewed regularly to reflect evolving regulatory, ethical, and systemic risk developments

• Participant feedback captured and used for continuous programme refinement