Australia - Queensland - AI Risk Assessment (2024)

Foundational Artificial Intelligence Risk Assessment (FAIRA) guideline (Queensland Government)

Australia • Queensland

RAI-AU-QL-FAIRAXX-2024
Effective: 1 Sep 2024
In Force(In Force)As published at forgov.qld.gov.au · checked 10 Sep 2026

Australia - Queensland - AI Risk Assessment (2024) is In Force in Australia as of 10 Sep 2026, according to forgov.qld.gov.au.

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The Queensland Government's Foundational Artificial Intelligence Risk Assessment (FAIRA) guideline (v1.0.0) provides non-mandatory, best-practice guidance for public sector agencies to identify, assess and manage risks across the AI lifecycle. Issued as part of the Queensland Government Enterprise Architecture (QGEA) suite in September 2024, FAIRA complements the Queensland AI governance policy and aligns with ISO guidance and the National Framework for the Assurance of AI in Government.

Summary

The Foundational Artificial Intelligence Risk Assessment (FAIRA) guideline is a Queensland Government Enterprise Architecture (QGEA) guidance document released in September 2024 to support Queensland public sector agencies assess and manage risks associated with artificial intelligence (AI) across the AI lifecycle. FAIRA is intended as a foundational, practical instrument for describing AI solutions in terms of technical components, system design, human interaction, implementation context and impacts, so agencies can apply existing risk management and governance processes to AI initiatives. The guideline sets out a three-part FAIRA framework (component analysis/Part A; values assessment/Part B; common controls/Part C) and recommends stakeholder engagement, versioning and proportionate assessment commensurate with the complexity and potential consequences of AI use.

FAIRA is non-mandatory guidance (published within QGEA as “CurrentNon-mandated”) but is expressly designed to assist agencies to meet their obligations under the Queensland Artificial Intelligence governance policy and existing statutory and administrative obligations relating to risk management, privacy, procurement and security. The guideline points agencies to existing standards (e.g., ISO/IEC 42001, ISO 22989, ISO 38507) and national instruments such as the National Framework for the Assurance of AI in Government to improve consistency and comparability of assessments. Practical elements include templates (e.g., a ‘When is a FAIRA needed’ checklist in Appendix A), an AI component mapping approach, a values-driven risk identification process and a catalogue of common controls aimed at mitigation across technical, organisational, procurement and human-centred layers.

Key operational recommendations require agencies to initiate a FAIRA at the earliest feasible point in procurement, development or deployment; to involve multi-disciplinary stakeholders (business owners, legal, privacy, IT/security, procurement, risk managers); to document scopes and exclusions; to update the FAIRA whenever the system purpose, context or functionality changes; and to integrate FAIRA outcomes into agency ICT profiling, assurance reviews and wider risk registers. Reporting pathways include FAIRA registration in digital tools and resources, inclusion in Digital Investment Governance Framework submissions, and integration with privacy and cybersecurity reporting channels.

Although FAIRA itself does not create novel legal obligations or penalties, the guideline situates FAIRA within mandatory risk and governance duties that agencies already carry and highlights that failure to properly assess and manage AI risks could cause downstream governance, procurement or legal consequences under other instruments. FAIRA therefore functions as both a practical risk assessment methodology and a coordinating reference for Queensland public sector AI governance.

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Overview

The Foundational Artificial Intelligence Risk Assessment (FAIRA) guideline is published by the Queensland Government within the Queensland Government Enterprise Architecture (QGEA) directions and guidance. FAIRA (v1.0.0, effective September 2024) provides a structured, foundational approach for Queensland public sector agencies to identify, evaluate, communicate and treat risks across an AI lifecycle. The guideline is intended as practical, non-mandatory guidance that complements mandatory AI governance requirements; agencies are advised to use FAIRA (or an equivalent) in conjunction with the Queensland Artificial Intelligence governance policy and to align assessments with recognised international standards such as ISO/IEC 42001 and ISO 22989. FAIRA comprises three parts (component analysis, values assessment and control catalogue) designed to be proportionate and iteratively updated as systems evolve; it also provides templates to record decisions when an assessment is not required. The guideline is accessible on the QGEA website and FAIRA framework materials are available for agencies to download and adapt.

Definitions

FAIRA adopts working definitions tailored for government use. Key terms include "AI solution" (any product, service or system that performs functions commonly described as AI or that stakeholders reasonably regard as AI), "AI lifecycle" (conception, design, procurement, development, deployment, operation, monitoring and decommissioning), "component analysis" (technical and integration mapping of system parts and data flows), and "values assessment" (systematic mapping of stakeholder and public values to potential harms, such as privacy, fairness and human rights). FAIRA emphasises pragmatic classification over rigid definitional thresholds: when in doubt, teams are encouraged to complete a basic record or ‘‘When is a FAIRA needed’’ template to demonstrate decision-making. FAIRA also references types of AI functions in international guidance (e.g., ISO 22989) to assist risk proportionality judgments.

Governance and Institutional Framework

FAIRA sits within the broader QGEA and is administered as guidance by the Department of Customer Services, Open Data and Small and Family Business. The guideline advises agencies to embed FAIRA outcomes into existing governance structures—ICT governance, audit and risk committees, investment assurance and procurement approvals—and to establish clear responsibilities for FAIRA delivery and sign-off (e.g., project sponsors, business owners, CIOs and risk managers). Agencies must consider FAIRA outputs when preparing submissions to the Digital Investment Governance Framework and in ICT profiling. FAIRA recommends multi-disciplinary AI assessment teams that include legal, privacy, security, business continuity and subject-matter experts. The guideline also maps reporting channels and suggests agency-level escalation pathways for unresolved high risks. For additional governance context, see the QGEA AI governance policy page and the Department of Customer Services’ guidance for digital and data governance on the QLD government site (Department of Customer Services, Open Data and Small and Family Business).

Key Focus Areas

FAIRA identifies recurring domains of risk to be analysed and recorded. These include: (1) Purpose and context risk—ensuring AI use aligns with legitimate government functions and intended benefits; (2) Data risk—data quality, provenance, bias, privacy and lawful basis for processing; (3) Model risk—training methods, validation, drift, explainability and robustness; (4) Human–machine interface—clarity of roles, oversight, escalation and human-in-the-loop mechanisms; (5) Operational risk—system dependencies, third-party hosting and procurement arrangements; (6) Security and resilience—cybersecurity posture, supply chain risk and continuity planning; (7) Societal and rights impacts—discrimination, access to services, civic freedoms and public trust; (8) Accountability and transparency—records, documentation, decision logs and explainability measures; and (9) Regulatory and legal alignment—privacy principles, administrative law, procurement law and sector-specific obligations (health, social services, corrections, etc.). Each focus area includes suggested indicators and sample controls drawn from the FAIRA control catalogue: governance controls, technical measures (e.g., testing and validation), contractual protections with vendors, privacy-by-design, and user-facing transparency measures. FAIRA encourages agencies to rate the potential consequence and likelihood within their existing risk frameworks and escalate material risks for cross-agency review where appropriate.

Implementation Framework

FAIRA provides a phased implementation approach: Establish Context (scope, stakeholders, regulatory constraints); Component Analysis (map system architecture, data flows, integration points and third-party dependencies); Values Assessment (map affected values to potential harms and stakeholders); Risk Analysis and Evaluation (assess likelihood and consequence within agency risk matrices); Risk Treatment (document controls, residual risk and monitoring plans); and Reporting/Assurance (record FAIRA outputs in assurance submissions and ICT profiling). The guideline supplies templates and a controls catalogue to ensure repeatability. Implementation emphasizes proportionate assessment: simple AI components warrant concise FAIRA records, while high-impact systems require detailed analysis, external assurance and independent testing. Agencies are encouraged to maintain version control, re-assess on significant model or context changes, and link FAIRA outputs to procurement contracts and SLAs for ongoing compliance and vendor management.

Monitoring and Evaluation

FAIRA recommends continuous monitoring and periodic re-evaluation. Monitoring metrics include model performance drift, incident and complaints reporting, user feedback, privacy impact metrics, security incident rates and audit outcomes. Agencies should define trigger conditions for re-running FAIRA assessments (e.g., new purpose, different population, new data sources, substantial model retraining or shift to new vendor). The guideline suggests integration with existing assurance cycles (assurance reviews, audit programs, ICT profiling) and storing FAIRA records in accessible digital repositories to support oversight and transparency. Where relevant, agencies should use external or third-party assurance (independent testing, red-teaming, external audits) for high-consequence AI. FAIRA also highlights the importance of documenting monitoring plans, KPIs and responsibilities for remedial actions in the event of harm or performance degradation.

Penalties, Liability, and Appeals

FAIRA itself is guidance and does not prescribe statutory penalties. However, the guideline makes clear that inadequate risk assessment and control may lead to administrative or legal consequences through other legal instruments—e.g., breaches of privacy principles, procurement rules, sector-specific regulation or obligations to maintain appropriate systems of internal control. Potential consequences for agencies include failed assurance submissions, procurement approval delays, internal audit findings, mandatory remediation directives and, where governed by other laws, regulatory enforcement or civil liability. FAIRA also recommends establishing internal appeal and escalation pathways for contested risk findings and maintaining records of decisions (including the ‘‘When is a FAIRA needed’’ template) to provide an evidentiary trail for oversight bodies and, if necessary, external review.

Relationship to Other Instruments

FAIRA is designed to be complementary to a suite of instruments: the Queensland AI governance policy (which sets governance obligations), the Digital Investment Governance Framework (assurance process), privacy frameworks (Queensland privacy principles and agency privacy management), cybersecurity policies, procurement rules and national and international standards (ISO/IEC 42001, ISO 22989, ISO 38507). FAIRA references the National Framework for the Assurance of AI in Government and is intended to support agencies in meeting obligations under those frameworks. Agencies are advised to map FAIRA outputs to these instruments when preparing business cases, procurement documentation and assurance reviews to ensure consistent compliance and to avoid duplication of effort.

International Alignment

FAIRA explicitly references international standards and frameworks to promote interoperability and comparability of assessments across jurisdictions. The guideline aligns its structure with ISO guidance (notably ISO/IEC 42001 management-system concepts and ISO 22989 technical function categories) and draws on the National Framework for the Assurance of AI in Government to reflect national coordination. This alignment facilitates adoption of FAIRA outputs in multi-jurisdictional procurement, cross-jurisdiction assurance and for benchmarking against international good practice, and supports vendor engagement where suppliers need to demonstrate compliance with both Queensland public-sector expectations and internationally recognised standards.

Implementation Timeline

MilestoneDateNotes
FAIRA guideline published (QGEA)2024-09-01Guideline v1.0.0 published as Current (Non-mandated)
AI governance policy issued (QGEA)2024-09-01Policy sets governance obligations; cross-references FAIRA
FAIRA framework update (docx) timestamp2025-08-06Framework document metadata shows update (agencies should check for later updates)
Recommended: agency adoption planningOngoingAgencies to integrate FAIRA into procurement and assurance cycle

Sources and References

SourceType
Foundational artificial intelligence risk assessment guidelinePrimary Source
FAIRA framework (QGEA framework document)Primary Source
Artificial intelligence governance policy (QGEA)Primary Source

Requirements for a company

What an organisation has to do under Australia - Queensland - AI Risk Assessment (2024), at a glance. Not legal advice — the table below gives the provision and deadline for each item.

Must do

7
  • Consider FAIRA outputs when preparing submissions to the Digital Investment Governance Framework and in ICT profiling.Queensland public sector agencies
  • Use the Foundational Artificial Intelligence Risk Assessment (FAIRA) guideline or an equivalent framework.Queensland public sector agencies
  • Complete an AI component analysis, including architecture, data flows, and integrations.Queensland public sector agencies using FAIRA
  • Perform a values assessment and log identified risks.Queensland public sector agencies using FAIRA
  • Document and assign mitigation controls for identified risks.Queensland public sector agencies using FAIRA
  • Integrate the FAIRA into procurement and assurance submissions.Queensland public sector agencies using FAIRA
  • +1 more in the table below

Must not do

0

Nothing in this category.

Should do

5
  • Embed FAIRA outcomes into existing governance structures, including ICT governance and audit committees.Queensland public sector agencies
  • Establish clear responsibilities for FAIRA delivery and sign-off.Queensland public sector agencies
  • Maintain version control for FAIRA records and re-assess on significant model or context changes.Queensland public sector agencies using FAIRA
  • Store FAIRA records in accessible digital repositories.Queensland public sector agencies using FAIRA
  • Use external or third-party assurance for high-consequence AI systems where relevant.Queensland public sector agencies deploying high-consequence AI

Should not do

0

Nothing in this category.

Who must do what

The obligations under Australia - Queensland - AI Risk Assessment (2024), most serious first. Not legal advice — verify against the official text before relying on it.

#WhoRequirementBy whenWhereSeverity
1Queensland public sector agenciesConsider FAIRA outputs when preparing submissions to the Digital Investment Governance Framework and in ICT profiling.
“Agencies must consider FAIRA outputs when preparing submissions to the Digital Investment Governance Framework and in ICT profiling.”
Before preparing submissionsGovernance and Institutional FrameworkImportant
2Queensland public sector agenciesUse the Foundational Artificial Intelligence Risk Assessment (FAIRA) guideline or an equivalent framework.
“agencies are advised to use FAIRA (or an equivalent) in conjunction with the Queensland Artificial Intelligence governance policy”
Before placing AI solutions on marketOverviewImportant
3Queensland public sector agencies using FAIRAComplete an AI component analysis, including architecture, data flows, and integrations.
“Is the AI component analysis complete (architecture, data flows, integrations)?”
Before deploying AI solutionsCompliance ChecklistImportant
4Queensland public sector agencies using FAIRAPerform a values assessment and log identified risks.
“Has a values assessment been performed and risks logged?”
Before deploying AI solutionsCompliance ChecklistImportant
5Queensland public sector agencies using FAIRADocument and assign mitigation controls for identified risks.
“Are mitigation controls documented and assigned?”
Before deploying AI solutionsCompliance ChecklistImportant
6Queensland public sector agencies using FAIRAIntegrate the FAIRA into procurement and assurance submissions.
“Has the FAIRA been integrated into procurement/assurance submissions?”
Before submitting procurement or assurance documentsCompliance ChecklistImportant
7Queensland public sector agencies using FAIRADefine a monitoring plan and trigger conditions for re-assessment of AI solutions.
“Is a monitoring plan and trigger set for re-assessment?”
Before deploying AI solutionsCompliance ChecklistImportant
8Queensland public sector agenciesEmbed FAIRA outcomes into existing governance structures, including ICT governance and audit committees.
“The guideline advises agencies to embed FAIRA outcomes into existing governance structures”
OngoingGovernance and Institutional FrameworkRecommended
9Queensland public sector agenciesEstablish clear responsibilities for FAIRA delivery and sign-off.
“establish clear responsibilities for FAIRA delivery and sign-off”
OngoingGovernance and Institutional FrameworkRecommended
10Queensland public sector agencies using FAIRAMaintain version control for FAIRA records and re-assess on significant model or context changes.
“Agencies are encouraged to maintain version control, re-assess on significant model or context changes”
OngoingImplementation FrameworkRecommended
11Queensland public sector agencies using FAIRAStore FAIRA records in accessible digital repositories.
“storing FAIRA records in accessible digital repositories to support oversight and transparency.”
OngoingMonitoring and EvaluationRecommended
12Queensland public sector agencies deploying high-consequence AIUse external or third-party assurance for high-consequence AI systems where relevant.
“Where relevant, agencies should use external or third-party assurance (independent testing, red-teaming, external audits) for high-consequence AI.”
Before deploying high-consequence AIMonitoring and EvaluationRecommended

© Regulations.AI · updated on 20 Sep 2026 · reviewed against official sources on 10 Sep 2026