AI Essentials for Governance Professionals – Foundations of Informed Oversight

The aim of this course is to establish the foundational understanding of artificial intelligence that governance professionals need to engage with AI as a governance matter: what AI is, how it works at the level relevant to oversight and accountability, the core concepts of bias, data, transparency and opacity that are central to governance risk, and why the distinctive characteristics of AI create challenges for conventional governance frameworks in Australian organisations.

Learning objectives

• Explain what artificial intelligence is and the distinction between AI and conventional software. Understand the difference between narrow AI, general-purpose AI and agentic AI, at the level of understanding required to evaluate information presented to the board.
• Describe how AI systems are built and how they produce outputs, including the role of training data, how models learn patterns, why outputs cannot always be explained by their developers, and why the character of training data directly affects the reliability and fairness of outputs.
• Identify the five key risks AI introduces — hallucination, bias, overconfidence, data privacy and the regulatory gap — explain the theoretical basis for each, and recognise the signals that indicate one or more of these risks may be present in an AI system operating within the organisation.
• Apply understanding of how AI works and what can go wrong to the practical situations directors encounter: recognising how AI is used across sectors and inside organisations, identifying when organisational use of AI is creating risk exposure, and engaging critically with primary material on AI-related failures to identify what better AI literacy at board level would have changed.

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AI Governance, Risk and Oversight – Strengthening Accountability and Risk Oversight

The aim of this course is to examine how established governance principles, directors’ duties, and risk oversight frameworks apply to artificial intelligence, and to develop the capability of governance professionals to support informed, accountable, and defensible board-level oversight of AI where automated systems influence organisational decisions, risk, and stakeholder outcomes within Australian organisations.

Learning objectives

• Examine the board’s role and accountability in relation to artificial intelligence, including how directors’ duties of care, diligence and good faith apply when AI systems materially affect organisational decisions, risk exposure or stakeholder outcomes.
• Identify the categories of risk introduced by AI at a governance level, including strategic, ethical, operational, regulatory and reputational risks, and apply existing risk governance frameworks to assess how AI-specific characteristics should be captured, documented and escalated within the organisation’s risk management processes.
• Apply governance principles of accountability, transparency and integrity to the oversight of AI, including identifying the governance structures, policy instruments and reporting mechanisms that support defensible board oversight, and document and report findings in a form suitable for the governance professional’s report to the board.
• Identify the indicators of AI bias and governance accountability failure and examine the structures boards need to have in place to satisfy themselves that AI systems operating within their organisations are performing fairly, within sanctioned parameters and consistently with the organisation’s stated values.

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AI Controls and Assurance – Designing Operational Governance for Senior Professionals

The aim of this course is to develop the capability of governance professionals to identify governance obligations across the AI system lifecycle, apply data governance and risk controls to AI systems, and recognise when those controls are absent or failing so that issues can be escalated appropriately within Australian organisations.

Learning objectives

• Identify the governance obligations that apply across the AI system lifecycle, from procurement through to decommissioning, and recognise where the absence of controls creates risk exposure and what documentation is required to demonstrate a system is operating within approved parameters.
• Apply data governance principles to AI systems at an operational level, including data quality, lineage, access controls and training data obligations, and identify where data decisions create risk that requires escalation.
• Assess monitoring frameworks and incident response protocols for AI systems, including the controls that detect performance drift, bias amplification and system failure, and the escalation mechanisms that translate operational signals into assurance for organisational leadership.
• Examine the governance implications of agentic and autonomous AI systems, including the specific control challenges they create, and develop well-reasoned recommendations for operational governance arrangements that are proportionate to the risks and legally defensible in an Australian context.

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Certificate in AI Governance

This Certificate does not assume prior AI governance training. The starting point is not what participants already know about governance, but where AI creates new obligations.

AI governance is the application of established governance principles and accountability frameworks to the acquisition, deployment and oversight of AI systems within an organisation. Artificial intelligence is influencing decisions, risk and stakeholder outcomes in organisations internationally, therefore boards and governance professionals need to approach AI with genuine confidence.

This Certificate is for governance professionals who need to apply their expertise to AI with confidence.

The decisions that determine whether an AI system is trustworthy, fair and legally defensible are made by the governance professionals who have oversight, procure them, configure them, connect them to organisational data, define their operating parameters, monitor their outputs and respond when they fail. This Certificate provides a structured approach to navigating those responsibilities.

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