🏛️ AI and Governance: Foundations for Oversight and Decision-Making

AI is increasingly shaping how organisations operate, manage information, assess risk and make decisions. For boards, company secretariats and governance professionals, the challenge is not understanding how AI works at an engineering level. It is ensuring that AI is used within clear boundaries, with appropriate accountability, human oversight and organisational control.

This course provides a detailed, governance focused examination of AI in organisational settings. It explains why AI is no longer solely an IT matter and explores how it affects responsibility, risk appetite, decision authority, assurance and stakeholder trust. Learners develop the confidence to discuss AI clearly, challenge unsupported claims and translate technical information into practical governance questions.

The course examines major areas of exposure, including data protection, confidentiality, intellectual property, automated decisions, third party providers and informal AI use. It also demonstrates how AI can support governance functions such as board paper preparation, policy comparison, meeting administration, research, action tracking and reporting without replacing professional judgement.

Regulation receives particular attention. Learners explore the different approaches developing across major jurisdictions and receive a practical explanation of the EU AI Act, including its risk based structure, prohibited practices, transparency requirements, general purpose AI obligations, AI literacy and the responsibilities of providers and deployers.

The course then moves from principles to operational practice. It explains how organisations can create AI inventories, assess proposed uses, assign ownership, approve systems, monitor performance, manage incidents and respond to provider or model changes. It also examines how boards can provide meaningful oversight without micromanaging and how board level AI literacy can be developed through relevant use cases, scenario exercises and continuing education.

Designed as a substantial reference course, it supports governance professionals throughout the AI lifecycle, from early adoption and policy development to mature oversight, assurance, adaptation and eventual system retirement. By the end, learners will be better prepared to govern AI proportionately, challenge it confidently and maintain accountability as its organisational role continues to expand.