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Scan for outdated or missing drivers - takes under a minuteDriver Scan →Repair Windows errors before they cause bigger problemsFix Now →For Australian organisations, AI governance is not one new, universal AI law. Your risk register should distinguish existing legal duties that depend on your organisation and use case, voluntary government guidance, and a specific privacy-policy obligation scheduled to start on 10 December 2026 for certain automated decisions. The voluntary AI Safety Standard can help structure your controls, but adopting it does not itself create new legal duties or replace legal advice.
Which Australian AI rules belong in the register?
Keep legal obligations, voluntary guidance and historical proposals separate. They have different legal force and apply in different circumstances.
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| Source | Status and scope | Risk-register treatment |
|---|---|---|
| Existing laws | Applicable duties depend on the organisation, data, decision and activity. Relevant areas can include directors’ duties, privacy laws and additional sector- or use-specific laws. | Record the responsible entity, relevant regime, why it applies, the obligation owner and the next review date. Do not assume a general AI checklist covers every applicable law. |
| Voluntary AI Safety Standard | The Department of Industry, Science and Resources describes its ten guardrails as voluntary. The Department says the standard does not create new legal duties about AI systems or their use. | Use the guardrails as a practical governance structure for assessment, controls, monitoring and accountability—not as a substitute for identifying legal duties. |
| Proposals for mandatory high-risk guardrails | Government material cited for these measures describes proposals and consultation, not a general mandatory regime in force. | Do not register a proposal as a current obligation. Recheck legislation and official announcements when reviewing the legal mapping. |
| Automated decision-making (ADM) privacy-policy obligation | From 10 December 2026, APP entities using personal information in ADM that has the potential to affect rights or interests must describe in their privacy policies the kinds of personal information used and the kinds of decisions made using ADM. | Identify whether the organisation and decision fall within scope, inventory the relevant information and decision types, and assign an owner and completion date before commencement. |
The Department also says the voluntary guardrails align with ISO/IEC 42001:2023 and NIST AI Risk Management Framework 1.0. That is an alignment reference, not evidence that Australian organisations must adopt either framework or obtain certification.
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What should an AI risk-register entry contain?
The fields below are practical recommendations drawn from the guardrails and privacy guidance; they are not a claim that every field is independently required by statute. Use one entry per system and material use, rather than treating “AI” as a single organisation-wide risk.
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| Register area | Record | Review or escalation trigger |
|---|---|---|
| System and use | System and supplier, version, intended purpose, users, decision context, capabilities, limitations and prohibited uses. | New version, new purpose, changed users or materially different deployment conditions. |
| Accountability | System owner and accountable executive; operational, privacy, security and legal roles; escalation route; staff capability and training needs. | Ownership changes, unresolved control gaps or an incident requiring escalation. |
| People and impacts | Affected groups, how people interact with the system or their data is processed, potential harms, accessibility, bias and discrimination risks, and engagement undertaken. | A newly affected group, changed decision context or evidence of unexpected harm. |
| Risk and treatment | Likelihood and impact of harms to people, groups, the organisation and environment; risk tolerance; acceptance criteria; inherent and residual risk; control, owner and due date. | Changed circumstances, a missed treatment deadline or residual risk beyond the organisation’s tolerance. |
| Data and privacy | Data sources, quality, provenance, permitted use and rights; personal or sensitive information; retention and minimisation; privacy-by-design review; privacy notices; confidentiality and cybersecurity controls. | New data sources, a change in data use or retention, or a privacy or security incident. |
| Performance and change | Acceptance criteria, pre-deployment test evidence, monitoring approach, behaviour or performance changes, incident handling, change control and review schedule. | Failed testing, drift or other unexpected behaviour, an incident or a material system change. |
| Human oversight and recourse | Who can intervene, when human review is needed, how a person can challenge an outcome, complaint handling and remediation ownership. | A challenge, complaint or outcome that suggests the control or review path is not working. |
| Transparency and evidence | What users or affected people are told, relevant explanations, supplier disclosures, and records of assessments, testing, decisions, incidents and mitigations. | A change in what people need to know, or a decision or incident that requires updated records. |
| Supplier and supply chain | Supplier-identified risks, relevant data and model information, test results, limitations, responsibilities, contract commitments, incident notification, audit evidence and review cadence. | Supplier changes, missing information needed to assess risk, a contractual change or a supplier incident. |
| Legal mapping and ADM milestone | Jurisdiction, relevant entity and legal regime, applicability rationale, sector, counsel or compliance review, obligation owner and next review date. Separately flag potentially in-scope ADM, the personal-information categories and decision types involved, and ownership of the privacy-policy update. | Changed use, data or legal status; and, for an in-scope ADM use, the 10 December 2026 commencement date. |
How to build and maintain the register
- Inventory systems and uses. Record what each system does, who uses it, whose information or interests may be affected, and whether it is used to support or make decisions. Include material system versions and deployments.
- Map the applicable law. Identify the organisation and activity involved, the relevant data and decision, and any sector-specific context. Assign someone to confirm applicability; do not infer that a voluntary standard settles the legal question.
- Assess risks across the lifecycle. Consider harms to individuals and groups as well as organisational and environmental impacts. Assess during planning and procurement, before deployment, and when circumstances change. Document acceptance criteria, controls, residual risk and who can approve it.
- Set controls and evidence. Specify the test, monitoring, privacy, security, oversight and recourse controls that address each material risk. Name the owner and record evidence that the controls operate, rather than recording only that a policy exists.
- Review when something changes. Reassess after a change in purpose, data, supplier, system behaviour or affected people, and after incidents or complaints. Set a review cadence as well as event-based triggers.
- Track the ADM policy work. For a potentially in-scope decision, assign ownership to establish whether the organisation is an APP entity and whether the decision meets the obligation’s scope, then prepare the required policy descriptions before 10 December 2026.
Privacy, personal information and automated decisions
The Office of the Australian Information Commissioner (OAIC) recommends considering privacy risks during generative-AI planning and design through a privacy-by-design approach. It describes a privacy impact assessment (PIA) as a systematic way to identify effects on people’s privacy and recommend ways to manage, minimise or eliminate those effects. A PIA can inform the register; the OAIC’s guidance should not be confused with the precise wording of statutory obligations.
The ADM obligation is narrower than a blanket requirement to publish details of every automated tool. The stated trigger is an APP entity using personal information in ADM with potential to affect rights or interests. The policy must describe the kinds of personal information used and kinds of decisions made using ADM. The OAIC’s May 2026 consultation page said it was seeking views to inform guidance, including on scope; that consultation does not resolve every borderline case. If a system may be in scope, record the issue for legal or privacy review rather than assuming either that the obligation applies to every automated output or that a human is involved enough to exclude it.
Suppliers, affected people and First Nations data
Do not treat a supplier’s assurances as your risk assessment. The guardrails call for enough supplier information to assess risk and document system capabilities, limitations, testing and control arrangements. Where information is missing, record the gap, its effect on your assessment, the person responsible for obtaining it and whether the system can safely be used while the gap remains.
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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11Register how affected people can learn about relevant AI use and challenge its use or outcomes. Define who receives a challenge, when a human reviews it, how complaints are handled and who is responsible for remediation. The process should be usable by the people affected, including where accessibility needs arise.
If a system uses data from or about First Nations communities, the Department says organisations should respect Indigenous Data Sovereignty Principles and secure free, prior and informed consent from relevant communities before beginning AI projects that engage First Nations data or affect First Nations communities. Record which communities may be affected, how engagement and consent are addressed, and who is accountable for that work.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the register can—and cannot—show
A well-maintained register can show that an organisation has identified its AI uses, assessed impacts, assigned accountable owners, selected controls and reviewed changes. It is an operational record, not proof by itself that the organisation has met every legal duty. The applicable duties depend on the organisation and use case, and voluntary adoption of the guardrails does not automatically satisfy them.
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