Voluntary AI Safety Standard (10 Guardrails)¶

Australia’s Voluntary AI Safety Standard provides ten practical guardrails organisations can adopt now to deploy and use AI safely and responsibly.

The standard was developed by the Department of Industry, Science and Resources (DISR) and first published in November 2023. In 2024, the guardrails were updated following consultation to align more closely with the Government’s proposed mandatory guardrails for high-risk AI applications.

The standard is voluntary and complements existing Australian law. It provides a practical framework for organisations to manage AI safely while future regulation is considered.

Importantly, the 10 guardrails are consistent with leading international standards and frameworks, including:

Status update (October 2025): In October 2025 the National AI Centre released the Guidance for AI Adoption, which sets out 6 essential practices (AI6) for responsible AI governance and adoption. This guidance is described as the first update of the Voluntary AI Safety Standard (VAISS) and is now the primary reference for organisations using AI in Australia.

The 10 guardrails on this page remain fully integrated into the new guidance and are best used as a detailed control set and historical reference, especially where contracts, risk registers or external frameworks still refer to the original VAISS guardrails.

Why this matters¶

Adopting the guardrails early helps organisations build trust, resilience, and regulatory readiness. By embedding these practices now, businesses can:

Reduce risks from bias, errors, and misuse of AI
Strengthen transparency and customer confidence
Position themselves ahead of future mandatory compliance requirements
Demonstrate leadership in responsible AI adoption

The 10 Guardrails¶

Establish accountability
Implement risk management
Protect data
Ensure transparency
Enable human control
Test reliability
Monitor impacts
Ensure accountability in the supply chain
Maintain records
Support human autonomy

What the guardrails do¶

Encourage transparency and accountability for AI systems.
Require risk assessment, testing, and human oversight before and after deployment.
Promote record-keeping and supplier due-diligence across the AI supply chain.
Emphasise stakeholder engagement and ongoing monitoring as systems evolve.

How this maps to the 6 essential practices (AI6)¶

The Guidance for AI Adoption condenses the 10 VAISS guardrails into 6 essential practices. At a high level:

AI6 practice	Closest VAISS guardrails and themes
Decide who is accountable	1. Establish accountability; 9. Maintain records
Understand impacts and plan accordingly	2. Implement risk management; 7. Monitor impacts; 10. Support human autonomy
Measure and manage risks	2. Implement risk management; 3. Protect data
Share essential information	4. Ensure transparency; 8. Ensure accountability in the supply chain; elements of 7 and 10
Test and monitor	6. Test reliability; 7. Monitor impacts
Maintain human control	5. Enable human control; 10. Support human autonomy

How to use this mapping

Use AI6 as your top-level framework when explaining AI governance to boards, executives and regulators.
Use the 10 guardrails in this page as a control library when:
building or updating AI policies and standards
designing AI risk assessments and risk registers
writing contractual clauses and supplier questionnaires.
Where you see references to the "Voluntary AI Safety Standard" or "guardrails" in external documents, you can confidently interpret them through this AI6 lens.

How to use this in your business¶

Adopt the 10 guardrails as acceptance criteria for any AI initiative.
Update policies and procurement to reflect supplier alignment with the guardrails.
Integrate testing, documentation, and oversight into your normal change-management.
Review systems at least annually or on material change.

SME-Scaled Implementation Approach¶

While the 10 guardrails apply to all organisations, SMEs can adopt them at different maturity levels:

Guardrail 1: Establish accountability

Minimum: Designate an AI responsible person
Better: Create simple AI governance policy
Best: Regular board/leadership AI updates

Guardrail 2: Implement risk management

Minimum: Use SAAM risk assessment tool
Better: Quarterly risk reviews
Best: Integrated risk management system

Guardrail 3: Protect data

Minimum: Follow existing cybersecurity practices
Better: AI-specific data controls
Best: Enhanced encryption and access controls

Guardrail 4: Ensure transparency

Minimum: "Powered by AI" labels
Better: Explain AI role in decisions
Best: Full algorithmic transparency

Guardrail 5: Enable human control

Minimum: Override capability for all AI decisions
Better: Human review of significant decisions
Best: Human-in-the-loop for all critical processes

Guardrail 6: Test reliability

Minimum: Pre-deployment testing
Better: Monthly performance monitoring
Best: Continuous testing and validation

Guardrail 7: Monitor impacts

Minimum: Track errors and complaints
Better: Proactive impact assessment
Best: Real-time monitoring dashboard

Guardrail 8: Ensure accountability in supply chain

Minimum: Vendor compliance check
Better: Contractual AI requirements
Best: Regular vendor audits

Guardrail 9: Maintain records

Minimum: Keep AI decision logs
Better: Comprehensive documentation
Best: Automated compliance reporting

Guardrail 10: Support human autonomy

Minimum: Opt-out options
Better: User control preferences
Best: Full user agency over AI interactions

Summary Table¶

Guardrail	Minimum Requirement	Better Practice	Best Practice
1. Establish accountability	Designate responsible person	Simple governance policy	Regular board/leadership AI updates
2. Risk management	Use SAAM risk tool	Quarterly reviews	Integrated risk management system
3. Protect data	Follow cybersecurity basics	AI-specific controls	Enhanced encryption & access controls
4. Transparency	“Powered by AI” labels	Explain role in decisions	Full algorithmic transparency
5. Human control	Override capability	Human review of major decisions	Human-in-the-loop for critical processes
6. Reliability testing	Pre-deployment testing	Monthly monitoring	Continuous testing & validation
7. Monitor impacts	Track errors & complaints	Proactive assessments	Real-time monitoring dashboards
8. Supply chain accountability	Vendor compliance check	Contractual AI requirements	Regular vendor audits
9. Maintain records	Keep decision logs	Comprehensive documentation	Automated compliance reporting
10. Human autonomy	Opt-out options	User control preferences	Full user agency over interactions

Regulatory outlook and the future of the guardrails¶

As at December 2025, the position on AI-specific regulation in Australia has shifted.

The National AI Plan confirms that the Government will, for now, rely on existing technology-neutral laws and sector regulators (for example, privacy, consumer law, financial services, safety, anti-discrimination) to manage AI-related harms. Earlier proposals to introduce standalone mandatory guardrails and a dedicated AI Act for high-risk AI applications have been paused.

Instead:

the Guidance for AI Adoption (AI6) provides voluntary but strongly endorsed governance expectations
a new AI Safety Institute will be established from 2026 to monitor, test and advise on emerging AI capabilities, risks and harms
regulators will continue to apply and, where necessary, adapt existing frameworks to AI use cases.

The 2024 consultation on mandatory guardrails and high-risk AI remains an important signal of how future regulation might be framed if the Government decides that existing laws are not sufficient. The principles-based definition of "high-risk AI" and the examples of sensitive domains (healthcare, employment, financial services, critical infrastructure, government decision-making, etc.) remain useful reference points for organisations when they assess and prioritise their own AI risk.

In practical terms, organisations should:

treat the 10 guardrails + AI6 as best-practice voluntary standards rather than imminent hard law
focus on integrating these controls into existing privacy, risk, safety, security and compliance processes
monitor future updates from the AI Safety Institute, NAIC and sector regulators, which may influence how strongly certain guardrails are expected in particular industries.

Government's principles-based definition of "high-risk AI"¶

In its earlier consultation on mandatory guardrails for high-risk settings, the Australian Government proposed a principles-based definition of "high-risk AI".

An AI application may be considered high-risk if it has a high likelihood of causing material harm in one or more of the following areas:

human rights or freedoms
health and safety
legal rights or obligations
democratic processes
environmental outcomes
broader societal impacts.

Risk was to be assessed based on context, severity and scale, rather than a static list of application types.

Illustrative examples from public commentary¶

The following examples are not part of any official legal definition. They are drawn from media, legal analyses, and the 2024 Senate inquiry into AI, which suggested that some systems and general-purpose models might warrant stronger oversight:

healthcare diagnosis or treatment
employment decisions (hiring, firing, promotion)
financial services (loans, insurance, credit scoring)
government service delivery and eligibility assessments
critical infrastructure operation and security
legal or quasi-legal decisions.

By contrast, many common "everyday" uses of AI (marketing automation, customer service chatbots, internal productivity tools, content generation and basic analytics) are generally treated as lower-risk, but must still comply with existing law and good-practice governance.