Tools & Frameworks¶

Purpose: Curated directory of practical AI tools, frameworks and resources for safe and responsible implementation Audience: Technical teams, governance professionals and implementation leads | Time: 20-30 minutes

A curated list of practical tools, frameworks and resources to help Australian businesses implement AI safely and responsibly.

🏛️ DTA AI Impact Assessment Tool (Commonwealth)¶

In December 2025, the Digital Transformation Agency (DTA) overhauled its Policy for the Responsible Use of AI in Government (effective 15 December 2025). Alongside the updated policy, the DTA published two key resources:

• AI Impact Assessment Tool – a 12-section fillable template aligned with the Australian Government's AI Ethics Principles. Designed for Commonwealth agencies but useful for any organisation wanting a structured impact assessment. (digital.gov.au)
• AI Procurement Guidance – practical guidance for procuring AI products and services responsibly. (dta.gov.au)

Key dates for Commonwealth agencies:

• 15 June 2026 – first mandatory requirements take effect
• December 2026 – all remaining requirements take effect

🤖 GovAI Chat (APS AI Plan)¶

As part of the APS AI Plan 2025, the Australian Government's GovAI Chat — an AI assistant for Australian Public Service (APS) staff — entered alpha trial in April 2026, delivered through GovTEAMS by the Department of Finance. User inputs and documents are not retained by AI model providers for training. The beta trial is expected in July 2026. This is not a tool organisations outside the APS can access directly, but it signals concrete implementation of the APS AI Plan and the DTA responsible use policy at the tooling level — and a worked example of public sector GenAI with embedded safeguards (govai.gov.au; digital.gov.au).

🎯 AI Risk & Ethics Frameworks¶

• Australian Government AI Ethics Principles – 8 principles guiding ethical AI use. (industry.gov.au)
• Voluntary AI Safety Standard (10 Guardrails) – published 2024, aligns with ISO/IEC 42001 and NIST AI RMF. (industry.gov.au)
  • Note: The Guardrails explicitly align with ISO/IEC 42001:2023 and the NIST AI Risk Management Framework 1.0.
• National framework for the assurance of AI in government (DTA) – how agencies assure AI systems. (dta.gov.au)
• NIST AI Risk Management Framework (AI RMF 1.0) – comprehensive, sector-agnostic guidance. (nist.gov)
• NIST Generative AI Risk Management Profile – profile for GenAI use cases. (nist.gov)
• ISO/IEC 23894 – AI risk management guidance. (iso.org)
• ISO/IEC 42001 – AI management system (AIMS) requirements. (iso.org)
• OECD AI Principles – intergovernmental principles for trustworthy AI. (oecd.ai)
• Singapore Model AI Governance Framework – practical implementation guidance. (pdpc.gov.sg)

📋 Governance & Policy Tools¶

• Privacy Impact Assessments (PIAs) – OAIC guidance on conducting PIAs. (oaic.gov.au)
• NSW Artificial Intelligence Assessment Framework – Structured risk-based assessment framework for AI systems; updated to address generative AI. (digital.nsw.gov.au)
• ASD Essential Eight – baseline mitigation strategies. (cyber.gov.au)
• Notifiable Data Breaches (NDB) Scheme – reporting obligations. (oaic.gov.au)
• Australian Privacy Principles (APPs) – core privacy obligations. (oaic.gov.au)

🔬 Technical Testing & Monitoring¶

• Model Cards – documentation standard for AI models. (arXiv)
• Datasheets for Datasets – dataset transparency and quality control. (arXiv)
• Aequitas – open-source bias/fairness audit toolkit. (github.com)
• Fairlearn – open-source fairness assessment and mitigation. (fairlearn.org)
• NIST AI RMF Playbook (TEVV) – testing, evaluation, verification and validation resources. (airc.nist.gov)

🔒 Privacy & Security¶

• Differential Privacy – OpenDP, OpenMined community resources. (opendp.org, OpenMined)
• Homomorphic Encryption – OpenFHE library and docs. (openfhe.org)
• Confidential Computing – architecture patterns and use cases (Consortium). (confidentialcomputing.io)
• Data anonymisation – ARX, Amnesia, sdcMicro (open-source). (arx.deidentifier.org, amnesia.openaire.eu, github.com/sdcTools/sdcMicro)

💡 Explainability & Transparency¶

• LIME – local interpretable model-agnostic explanations. (github.com)
• SHAP – Shapley value–based feature importance. (github.com)
• DALEX – model exploration and explanations. (github.com)

📊 Continuous Monitoring & Ops¶

• MLflow – experiment tracking and model registry. (mlflow.org)
• Prometheus – metrics collection for model/service health. (prometheus.io)
• Kubeflow – open-source MLOps on Kubernetes. (kubeflow.org)

🛡️ LLM Application Safety & Secure Development¶

• OWASP Top 10 for LLM Applications – common risks and mitigations. (owasp.org)
• OWASP AI Security & Privacy Guide – secure AI development guidance. (owasp.org)
• MITRE ATLAS – adversary tactics/techniques/mitigations for ML systems. (atlas.mitre.org)
• Guidelines for Secure AI System Development – joint guidance (UK NCSC, CISA and partners). (ncsc.gov.uk)

🔍 RAG Evaluation & QA (Open-source)¶

• ragas – evaluation for retrieval-augmented generation. (github.com)

🚀 Serving & Data Infrastructure (Open-source)¶

• KServe – model serving on Kubernetes. (kserve.github.io)
• Feast – feature store. (docs.feast.dev)

✅ Procurement & Vendor Risk (Checklist)¶

Further Reading¶

• Voluntary AI Safety Standard – 10 Guardrails
• Australian AI Ethics Principles
• OAIC – AI and Privacy guidance
• NIST AI Risk Management Framework
• NIST SP 1270 – Identifying and Managing Bias in AI
• OECD AI Principles
• OWASP Top 10 for LLM Applications
• ASD Essential Eight