Overview
The pressure is no longer to “try AI” — it is to make confident, defensible decisions about where it belongs in government.
Federal agencies are under growing pressure to understand, adopt and govern AI in ways that improve service delivery, strengthen decision-making, and reduce manual effort while protecting public trust. The challenge is finding the right balance between innovation and control: using AI where it genuinely adds value without increasing risk, complexity, or compliance exposure.
The opportunity is significant, but so is the responsibility.
The APS AI Plan states that meaningful productivity gains depend on uplifting AI maturity. It cites Productivity Commission analysis that broader AI adoption could drive up to 4.3% labour productivity growth over the next decade in the market sector, equivalent to around AUD $116 billion in GDP. For the public sector, AI adoption could lift public sector gross value added by 13% by 2030, delivering an estimated AUD $19 billion in annual value.
But productivity gains will not come from pilots alone. They will come from leaders who can choose the right problems, ask the right questions, and put the right controls in place before AI is scaled.
Australia’s policy settings are also moving from encouragement to expectation. The updated Policy for the Responsible Use of AI in Government requires stronger governance, clear accountability for AI use cases, AI impact assessment, internal registers, transparency and mandatory foundational AI training for APS staff.
This program is designed to help federal public sector leaders move from AI awareness to confident, defensible decision-making about where AI adds value, what to avoid, and how to implement it safely. It provides practical tools to assess opportunities, manage risk and governance expectations, and build a clear action plan for safe, practical AI implementation.
Who Should Attend?
Federal Government professionals and teams involved in policy, programs, services, operations, digital transformation, workforce change, risk or governance, including:
Policy, program and service delivery professionals Managers, team leads and project leads Digital, data and transformation practitioners Strategy, innovation and improvement teams HR, workforce and organisational change professionals Risk, governance and compliance staff
Learning Outcomes
By the end of this course, you will be able to:
Understand modern AI, including LLMs, retrieval-augmented generation, copilots and agentic AI, well enough to lead credible conversations and investment decisions
Recognise and manage the ethical, regulatory, workforce, privacy, cyber, fraud and public trust risks unique to government AI use
Apply a practical responsible AI assessment approach to evaluate use cases before implementation, including risk, impact, readiness, complexity and public value
Identify the right AI use cases and avoid hype-driven, vendor-led or high-risk initiatives that are unlikely to deliver measurable public value
Collaborate more effectively with CIOs, data teams, risk, assurance, cyber, procurement and vendors using shared language and concrete decision tools
Assess whether current or proposed AI initiatives are safe, compliant, defensible and worth scaling within federal governance expectations
Leave with a practical, governed AI action plan and roadmap tailored to an agency, division or function
In-person Training
AI for Federal Public Sector Leaders: Strategy, Governance & Practical Application
Session details
- Gain clarity on how AI applies to federal public sector leadership, service delivery, assurance, transformation and organisational performance
- Make more informed decisions on where to invest, prioritise, pause, redesign, or avoid AI
- Strengthen your ability to lead AI initiatives with confidence, credibility, and defensible judgement
- Navigate federal responsible AI, privacy, cyber, procurement, assurance and policy expectations without adding unnecessary complexity
- Learn from practical public sector scenarios and comparable government examples, not generic or vendor-led AI content
- Build practical tools you can take back to your agency, including a decision framework, use-case canvas, risk-control checklist, maturity snapshot and roadmap
- Walk away with practical direction aligned to federal AI policy expectations that can be immediately adapted for your agency or function
No technical background required — ideal for those responsible for strategy, risk, services or people.
Registration for this course is not open yet. To register your interest, please email [email protected].
Meet Your Facilitator
Waqas Khan
Data & AI Leader Driving Organisational Transformation | Expert in AI Governance, LLMs, Agentic AI, RAG, Data Engineering & Scalable Advanced Analytics
Waqas Khan is a data and AI leader with strong expertise in Large Language Models, agentic systems and Retrieval-Augmented Generation. Currently completing a PhD in Artificial Intelligence at RMIT University, he focuses on trustworthy and explainable AI, bringing cutting-edge research into real-world government and industry applications. He has led major analytics and modernisation initiatives, including a cloud-native procurement platform for the Department of Government Services that significantly improved visibility, governance and decision-making.
With a solid foundation in cloud data platforms, AI-enabled systems and data governance, he delivers scalable architectures that uplift operational performance and support strategic decision-making. He is known for building high-performing teams, advising senior executives on data and AI strategy and driving capability uplift across organisations. Passionate about responsible and future-focused AI, he is committed to helping organisations navigate an increasingly intelligent landscape.
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