Overview
As AI becomes a priority across Queensland’s public sector, leaders are increasingly grappling with the same practical questions: What’s allowed? Who approves it? What controls are required? What risks need to be managed? And how do we ensure AI delivers real operational value rather than becoming another pilot that never scales?
It’s easy to try something small — it’s harder to make it safe, approved, and useful across an agency.
Queensland is moving from ‘interest’ to clearer expectations. The Queensland Government Artificial Intelligence Governance Policy (QGEA) is now current and mandated (effective September 2024–current), supported by whole-of-government guidance on the use of generative AI in Queensland Government (effective August 2023–current). Together, these signals make the shift clear that AI is no longer just an innovation conversation, it’s a leadership, governance, and accountability issue.
The opportunity is significant. Queensland has committed to a $1 billion Queensland Government Digital Fund to drive a whole-of-government approach to investing in critical digital and ICT systems, strengthening oversight, efficiency, and value-for-money in delivery. For leaders, this means AI success must be measured in operational outcomes, safer adoption, clearer decision rights, and demonstrable improvements in service delivery and internal performance, not pilots for their own sake.
The challenge is no longer understanding what AI can do. The challenge is understanding how to adopt it responsibly.
Get out of the pilot trap — and into governed, defensible delivery.
This one-day course is designed specifically for Queensland public sector leaders who need to set direction, govern adoption and make informed decisions.
The course focuses on the issues leaders consistently identified as their biggest priorities:
- Understanding what is permitted, what requires approval, and how to establish appropriate guardrails
- Building governance, decision-making frameworks and accountability structures that support safe adoption
- Managing privacy, confidentiality, supplier and data risks in complex public sector environments
- Assessing organisational readiness, including data quality, business process maturity and trusted information controls
- Identifying practical, high-value use cases that improve service delivery and internal operations
- Evaluating AI proposals and vendor claims with confidence
- Moving beyond isolated pilots towards governed, scalable implementation
Participants will leave with a practical and defensible AI action plan tailored to their agency, including priority opportunities, governance considerations, decision points, risk controls and next steps for responsible adoption. Throughout the program, participants will work through practical examples drawn from Queensland Government contexts, exploring how AI can improve service delivery, internal operations and decision-making while maintaining appropriate governance, privacy protections and public trust.
Move beyond experimentation. Build the confidence, governance and practical foundations needed to adopt AI safely, effectively and at scale.
Who Should Attend?
Senior leaders across QLD Government, including:
Executives, directors, and senior managers
Policy and program leaders shaping digital and AI strategy
CIOs, CDOs, and digital and data leaders
HR, workforce, and organisational transformation leaders
Learning Outcomes
By the end of this course, you will be able to:
Understand modern AI (LLMs, RAG, agentic AI and emerging AI capabilities) at a practical level to lead decisions
Make confident calls on risk vs reward, with practical mitigations that work in public sector context
Establish governance + enablement: approvals, access controls, allowed tool pathways, and guardrails
Evaluate AI proposals and vendor claims using structured leadership questions and decision tools
Identify high-value operational use cases across service delivery and internal operations (and avoid hype-driven dead ends).
Assess readiness realistically (process maturity, data quality, trusted data controls)
In-person Training
AI for QLD Public Sector Leaders: Strategy, Governance & Practical Application
Session details
- Gain clarity on what AI means for leadership decision-making in Queensland Government
- Make better decisions about where to invest, prioritise, pause or stop AI initiatives
- Strengthen confidence in engaging with vendors and internal teams and in challenging claims appropriately
- Learn practical governance and enablement patterns: allowed tools, approvals, access controls, policies, procedures and safe operating models.
- Work through real public sector scenarios not generic or vendor-led examples.
- Walk away with a clear plan aligned to Queensland policy, privacy expectations and operating constraints
- Leave with a practical, governed AI action plan for your agency/department
Some familiarity with topic is recommended
Key Sessions
Welcome & Context
- Program objectives and outcomes
- The Queensland Government AI landscape
- Why AI is becoming a leadership and accountability issue
- Queensland Government AI governance expectations
- Overview of the day
- What AI means for Queensland Government
- Opportunities across service delivery and internal operations
- The evolving role of leaders in AI adoption
Activity: AI Opportunities & Challenges Mapping
- Plain-language explanation of LLMs, RAG and emerging AI capabilities
- Hallucinations, bias, explainability and human oversight
- Understanding AI risks without becoming a technical specialist
Activity: Which AI Proposal Would You Approve?
- Why AI won't fix broken processes or poor-quality data
- Assessing business process maturity and operational readiness
- Data quality, trusted information and governance foundations
- Determining organisational readiness for AI adoption
- Identifying where AI is likely to create genuine value
Activity: AI Readiness Assessment & Capability Gap Analysis
- Queensland Government Artificial Intelligence Governance Policy
- Information Privacy Act 2009 (Qld) considerations
- Privacy, confidentiality and trusted information handling Supplier risk, model risk and accountability obligations
- Public trust and responsible adoption
- Queensland Government and public sector case examples: governance approaches, controls and lessons learned
Activity: Approve, Reject or Escalate? Assessing AI Use Cases in a Queensland Government Context
- Understanding approvals, access controls and decision rights
- Establishing guardrails for responsible AI use
- Approved pathways for experimentation and adoption
- Policies, procedures and assurance mechanisms
- Creating governance that enables innovation rather than blocks it
- Examples of governance and enablement models being applied across government
Activity: Design Your Governance & Enablement Blueprint
- Asking the right leadership questions before investing
- Assessing value, feasibility and risk
- Distinguishing meaningful solutions from vendor hype
- Determining what evidence is needed before approval
- Making confident investment and implementation decisions
Activity: Vendor Pitch Challenge – Invest, Pilot, Pause or Reject?
- Identifying practical opportunities across service delivery and internal operations
- Prioritising high-value, low-risk initiatives
- Matching AI opportunities to organisational capability and readiness
- Building a realistic service delivery and operational improvement pipeline
Activity: Process-to-AI Mapping Workshop
Participants map a real process from their organisation and identify pain points, AI opportunities, risks, controls and expected benefits
- Why pilots fail to scale
- Embedding AI into workflows, governance and decision-making
- Workforce readiness and adoption considerations
- Building a practical roadmap for implementation
- Creating momentum while managing risk
- Lessons from successful and unsuccessful public sector AI implementations
Activity: 90-Day Action Planning Workshop
Closing & Next Steps
- Complete 6–12-month AI roadmap & 90-day action plan
- Key governance checkpoints and implementation priorities
- Summary: leading AI-enabled departments in QLD
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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