AI Controls and Assurance

• 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.

Section A – Governance Principles

• AI system lifecycle and governance obligations – five governance touchpoints explained - procurement, configuration, deployment and integration, ongoing monitoring, update and decommissioning.
• Core principles and their application to AI - the application and extension of established governance principles and frameworks to AI, the limitations of this, embedding AI across the three interconnected dimensions of frameworks, structures, and tools.
• Data governance in AI systems: architecture, quality and controls – training data as the foundational risk, what data quality means for AI, data lineage and provenance, access controls and data minimisation.
• AI risk categories and the governance professional’s role in the risk framework – mapping AI risk categories to the risk register, escalation and what it means in practice, the breakdown of human review processes: automation bias and informed judgement.

Section B – Professional Practices

• Procurement, vendor governance and third-party Ai risk – what makes procurement different, contract controls for AI vendors, assessing AI vendor transparency claims, ongoing vendor governance.
• Monitoring, incident response and controls assurance – what AI monitoring must detect, threshold design and escalation logic, incident response for AI-specific failure modes, controls assurance.
• Agentic AI: operational governance of autonomous systems – why conventional controls are inadequate, scope limitations, tiered autonomy design, audit trail requirements, monitoring agentic systems.

Section C – Personal Thinking

• Examine the case of Mobley v Workday, Inc. (N.D. Cal., Case No. 23-cv-00770-RFL), the most significant live test of AI vendor liability in employment discrimination in the common law world, and the one with the most direct operational implications for Australian governance professionals who procure, configure or are responsible for AI-powered HR tools.

  The case is directly relevant to governance professionals because the failures it exposes are not policy failures or board failures. They are operational controls failures made by the people who built, configured and deployed the system.

  For governance professionals in Australian organisations, the governance questions this case raises are not hypothetical.

  Case study: Mobley v Workday and the liability gap in algorithmic hiring.

Download course outline

A short course is assessed as follows:

• A final quiz (multiple choice, achieve 75% to pass, unlimited attempts).
• A short case study written response (suggested answers are revealed for reflection).
• Knowledge checks are included as you progress through the course material (these are not assessed).
• See the Assessment Rules for further information.

We provide specialised in-house training to organisations who want to train large groups of staff.

What are the benefits on in-house training?

• Train large numbers of staff.
• Participate in customised training that caters to the needs of your staff and your organisation’s business objectives.
• Invite and engage with your key clients, suppliers and contractors to ensure you’re working together with the same knowledge.

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