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Resources

Everything you need to plan, assess, govern, and deliver AI projects in the Australian Public Service.

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Templates

Ready-to-use documents for your AI projects. Copy, customise, and use.

Planning & Stakeholders

Start here when initiating a new AI project. These templates help you identify who needs to be involved and how.

Stakeholder Register
Identify, categorise, and track all stakeholders in your AI project. Includes influence/interest mapping.
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Engagement Plan
Plan communications and engagement activities across all project phases.
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RACI Matrix
Define who is Responsible, Accountable, Consulted, and Informed for each activity.
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Assessments

Evaluate readiness, risks, and quality before and during your AI project.

AI Readiness Assessment
Evaluate organisational capability across strategy, data, technical, people, and process dimensions.
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Security Assessment
Identify AI-specific security risks including data poisoning, model attacks, and infrastructure threats.
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Risk Register
Track and manage AI project risks with pre-populated common risk categories.
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Data Quality Assessment
Evaluate training data across completeness, accuracy, consistency, and representativeness.
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Use Cases & Business Cases

Document opportunities and build investment cases.

Use Case Identification
Systematically evaluate whether AI is appropriate for your problem. Includes suitability checklist.
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Business Case
Comprehensive investment case covering benefits, costs, risks, and implementation approach.
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Governance & Operations

Establish governance structures and prepare for operations.

Data Governance
Framework for data ownership, quality standards, and lifecycle management for AI projects.
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Incident Response Plan
Procedures for detecting, containing, and recovering from AI system incidents.
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Persona Planning
Define user personas to ensure AI solutions meet diverse needs.
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Guidance

Practical how-to guides, FAQs, and fact sheets to help you navigate specific challenges.

How-To Guides

Guide What You'll Learn
Bias Testing Identify, measure, and mitigate systematic unfairness in AI systems
Explainability Make AI decisions interpretable for different audiences
Model Cards Create standardised documentation for ML models
Monitoring Track system health, model performance, and business impact
Guide What You'll Learn
Ethical AI Apply Australia's AI Ethics Principles in practice
Vendor Evaluation Assess AI vendors and solutions for government procurement

FAQs & Fact Sheets

Resource Description
Privacy Impact Assessment FAQ Common PIA questions answered with government context
Synthetic Data Fact Sheet When, why, and how to use synthetic data for AI projects

Playbooks

End-to-end frameworks for major workstreams. Comprehensive guides that tie together templates and guidance.

AI Project Delivery
Full project lifecycle from discovery through deployment and monitoring. Covers all phases with checklists and decision points.
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Governance Framework
Establish AI governance structures, policies, and oversight mechanisms for your organisation.
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MLOps
Operationalise machine learning with CI/CD, monitoring, retraining, and production best practices.
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Change Management
Manage organisational change for AI adoption. Build buy-in, train staff, and sustain adoption.
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Quick Reference

I need to... Start here
Evaluate if AI is right for my problem Use Case Identification
Get funding approval for AI Business Case Template
Assess our team's AI capability AI Readiness Assessment
Test my model for bias Bias Testing Guide
Document a model properly Model Cards Guide
Set up monitoring Monitoring Guide
Prepare for an incident Incident Response Plan
Evaluate vendors Vendor Evaluation Guide
Deliver an AI project end-to-end Delivery Playbook