Skip to main content

In-person Training

AI for Federal Public Sector Leaders: Strategy, Governance & Practical Application

Move from AI uncertainty to clear priorities, practical safeguards, and decisions you can defend

Next Intake 2 December 2026 | 10:00 AM – 5:00 PM AEDT
Next Intake 2 December 2026 | 10:00 AM – 5:00 PM AEDT

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
View course modules
Intermediate

No technical background required — ideal for those responsible for strategy, risk, services or people.

Key Sessions

​• Evolution: chatbots → copilots → retrieval-augmented generation → agentic AI
​• Implications for policy, HR, ICT, procurement, assurance, risk and service delivery
​• Productivity, fiscal sustainability and public value: where AI can genuinely help

Activity: Pain Points & Opportunities Mapping using an agency or functional lens

  • Plain-language explanation of LLMs, RAG, copilots and agentic AI
  • What AI can do well, where it fails and why leaders should be cautious
  • AI risks: hallucination, bias, over-reliance, model error and poor-quality inputs

Activity: “Which Answer Would You Approve?” — assessing AI outputs from a leadership, assurance and public trust perspective

​• Assessing AI use cases using risk, impact, readiness, complexity and public value criteria
​• Federal expectations: accountability, transparency, AI impact assessment, internal AI registers and oversight
​• Leadership decision points: proceed, pause, redesign or reject

Activity: Evaluate a use case using a practical Responsible AI decision framework

​• Key AI risks: data leakage, supplier risk, model risk, fraud, cyber exposure and privacy breaches
​• Alignment with privacy, cyber, assurance, procurement and compliance obligations
​• Control uplift: strengthening existing governance rather than creating unnecessary complexity

Activity: Threat → Control Mapping for one AI use case

​• Balancing innovation with accountability, fairness, transparency and public value
​• Explainability, human oversight and when not to use AI
​• Public sector examples from Australia, the UK, Singapore, Estonia and South Korea

Activity: Public Value Check using a mini-case review

  • AI oversight models, roles, approvals and lifecycle governance
  • Embedding AI into existing governance, risk, assurance, cyber, privacy and procurement structures
  • Internal registers, monitoring, escalation and evidence requirements

Activity: Design Your Governance Loop for safe AI deployment

  • Identifying high-value, low-risk opportunities
  • Avoiding hype-driven or vendor-led decisions
  • Activity: Use Case Canvas & Impact vs Risk prioritisation

​• Why pilots fail to scale and what leaders need to decide before implementation
​• Embedding AI into workflows, teams, approvals, assurance and change management
​• Measuring benefits, ROI, productivity improvement and workforce readiness

Activity: 90-Day Action Plan and 6–12-Month AI Roadmap

Meet Your Facilitator

Waqas Khan

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.

What your peers had to say

The course was excellent. The content was pitched at the right level and the table group sessions in the afternoon also helped to summarise the learnings.

The trainer was very knowledgeable and the course was very interesting, making me understand how AI came into being and helping me determine the next steps I should consider.

The content was extensive, insightful and relevant to the Government context.

The course was excellent. The content was pitched at the right level and the table group sessions in the afternoon also helped to summarise the learnings.

Register Today

Join this training for professionals working within the Public Sector

Extra Early Bird

Ends 18 Sep

$A 995

per person + tax $400 saving

Early Bird

Ends 16 Oct

$A 1195

per person + tax $200 saving

Regular

Ends 1 Dec

$A 1395

per person + tax

For group or payment enquiries or custom training solutions, please contact [email protected]

Customised in-house options available for teams

Interested in any of our online trainings?

You can also choose to have them delivered in house. We will work closely with our inspiring session facilitators to tailor the content around the key development areas your team are prioritising, shape the learning outcomes around your core departmental challenges and make the most of your L&D and upskilling budget.

Can't see what you need?

Download our training catalogue to review all available topics