Advanced UX Masterclass

The advanced UX landscape in government

A practical assessment of where UX capability is today and where it needs to go.

• What separates foundational UX from advanced practice in a government context
• How the Digital Experience Policy, Digital Service Standard and investment assurance processes are raising the bar
• Why delivery pressure, governance requirements and resource constraints are the real UX challenge
• Australia's OECD standing and what it actually demands of practitioners
• The shift from UX as a design discipline to UX as a service delivery capability
• Connecting user outcomes, policy intent and operational realities

Applied activity: In pairs or trios, complete a service decision scan on a short government scenario. Identify the assumption, the people affected, the intended service outcome and the evidence still missing. Participants write privately before a short round-robin.

Participant output: A one-sentence decision statement and a short list of evidence gaps.

Example: A short Robodebt story shows the human cost when automation, governance and accountable decision-making become disconnected from the people affected.

Move beyond awareness to practical AI integration in day-to-day UX work, including sense-checking ideas, catching issues earlier and shifting from rework to continuous refinement. Apply these tools within your agency's AI use policy.

• Using AI to bring alternative perspectives earlier in the design process, before anything goes to formal review
• AI for rapid UX ideation and pressure-testing concepts without losing design rigour
• AI-assisted prototyping: accelerating from an idea to a testable artefact
• AI for research synthesis: pattern recognition, gap identification and faster sense-making
• Assessing work against best practice, compliance and experience standards earlier
• Exploring AI use in design systems and existing interface standards
• AI governance, privacy, legal and policy considerations for public sector practitioners
• Knowing where AI can assist, where specialist expertise is needed and where accountable human judgement remains essential
• Using AI to free capacity for higher-value work, not as a workforce-reduction exercise

Applied activity: Using five simple questions, participants review an AI-generated summary of user research and compare it with the original research material. In pairs or trios, they look for anything inaccurate, unsupported or unsuitable under their agency's rules. Each group agrees one rule for using AI safely and decides what a person must check before the work can be used. The class then improves the five questions together.

Participant output: An improved five-question checklist for reviewing AI-assisted work, one rule for using AI safely and a clear statement of what a person must check before the work is used.

Practical techniques for getting UX taken seriously, facilitating the conversations that surface what matters and building a measurement approach that leadership and delivery teams will use.

• Why UX struggles to gain support unless it is linked to service priorities, budget constraints, workforce capacity and demand reduction
• Repositioning UX as improving service delivery and reducing avoidable operational workload, not just customer experience
• Translating UX evidence into language executives and budget holders respond to
• Navigating organisational complexity and competing priorities without losing user focus
• Building the business case by linking UX outcomes to error reduction, service performance and capacity
• Inclusive workshop facilitation so quieter participants contribute as much as the most active voices
• Moving from output measures to service, customer, trust, accessibility and operational outcome measures
• Designing a concise UX outcomes view for executives, governance reporting and investment assurance

Applied activity: Participants choose a realistic decision they would like stakeholders to make within the next 30 days and begin an outcome and influence worksheet. They explain what decision is needed, who will be affected, what evidence they have, why the decision matters and how they could tell whether it has made a difference. In groups of three, participants review one another's worksheets and identify the part that needs the most work.

Participant output: A first draft of an outcome and influence worksheet, with one part clearly identified for improvement.

The facilitator shares a weak UX value statement on screen and the group improves it in real time. Participants then use what they have just seen to improve their own worksheet. They clarify what they need stakeholders to decide, check what evidence would support that decision, choose one measure for users or the service and one for the organisation, and decide what simple supporting material, such as a short summary or prototype, would be most useful.
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Final participant output: A refined outcome and influence worksheet with a clearer value statement, two practical measures of success and one useful piece of supporting material.

Reflection and Day 2 preparation

Silent prompt: One thing I will try is... Participants post their sentence to chat or keep it in their notes. Invite participants to bring an anonymised, non-sensitive screenshot or short description of a service page, form, flow or process for the Day 2 live redesign.

Close

Recap the three Day 1 outputs and preview accessibility, discovery, lightweight UX and capability-building on Day 2.

The most persistent gaps in public sector digital products and why catching them at the end costs far more than building them in from the start.

• Accessibility as a first principle: designing for users with lower digital confidence, older devices or disability, not just meeting compliance checklists
• Why accessibility issues caught at acceptance testing can require expensive redesign or rearchitecture
• Low and no connectivity as a design constraint in rural and non-metro usage scenarios
• Designing for offline, degraded and intermittent connectivity from the beginning of service design and journey mapping
• Fallback and contingency planning when there is an outage or service interruption
• Service resilience and continuity planning as a UX and service design responsibility
• What New Zealand's Web Accessibility Standard 1.2 and the emerging Digital Accessibility Standard signal for Australian practice
• Testing for inclusion by reaching users often excluded from research panels

Applied activity: In pairs or trios, participants imagine how to make a service as difficult as possible to understand, access and use, particularly for people with disability, low digital confidence or unreliable internet. Everyone writes ideas silently before taking turns to share. Each group then turns the problems into practical checks, identifies what users could do if the service was unavailable and chooses the most important improvement.

Participant output: A short list of accessibility and service reliability checks, an alternative for when the service cannot be used and one priority improvement.

Example: The ABS 2026 Census shows why public services should offer more than one way to take part and consider people's access needs early.

Build stronger discovery practices that surface real problems, then choose UX methods that work within the practical constraints of government delivery.

• Why limited access to users is one of the most common blockers to good UX in government
• Advanced discovery techniques that work within government constraints
• Problem definition frameworks that distinguish technology problems from people, process and data problems
• Design thinking applied to complex, multi-stakeholder public sector challenges
• Customer-centred decision-making and keeping user needs visible throughout delivery
• Using AI to accelerate desk research, secondary synthesis and gap analysis, with verification
• Why delivery speed and resource shortages make heavyweight UX methods impractical in many agencies
• A practical toolkit of lightweight research, prototyping and testing approaches
• Fitting UX into agile and hybrid delivery models, project governance, intake and change management
• Templates and reusable artefacts that save time without compromising quality

Applied activity: In pairs, participants have 10 minutes to review a real public-sector webpage. They identify anything that may confuse users, make them unsure what to do next or leave them stuck if something goes wrong. The facilitator then improves part of the page live using the issues the group found. Participants write a clear description of the user problem and choose a simple way to investigate or test it, such as a short usability test or a few user interviews.

Participant output: A clear description of the user problem, the three most important issues and a practical way to investigate or test it.

Embed UX practice beyond the specialist designer so the whole team can contribute, without pretending specialist expertise is unnecessary.

• Why UX is becoming a shared team responsibility, not just the responsibility of designers
• Building UX maturity across organisations: from ad hoc activity to embedded practice
• Helping product managers, analysts, developers and delivery managers apply core UX thinking
• Clear guardrails for when a lightweight method is appropriate and when risk or complexity requires a specialist
• AI-assisted UX as a capability multiplier for teams with limited design resources, with review and accountability built in
• Strategic workforce planning through literacy, training, reusable artefacts, communities of practice and responsible adoption
• Prioritising methods and improvements against user need, organisational goals, governance and service outcomes
• Learning from practical government case comparisons and other participants

Applied activity: Choose one practical change that would strengthen how your team uses UX over the next 30 days. Create a first-draft plan covering what you will trial, why it matters, who will own it, the first action, how progress will be recognised and when specialist help may be needed.

Participant output: A first-draft 30-day capability plan ready for peer review.

In pairs or trios, participants test each other’s plans for focus, feasibility and risk. They check that the first action is realistic, ownership is clear, progress can be observed and the point for seeking specialist advice has been identified. Participants then revise their plans. Two volunteers, and a third if time permits, briefly explain one useful course principle in their own words and describe how it influenced their plan. The other participants add examples or anything important they think is missing in the chat.
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Final participant output: A refined 30-day capability plan with an owner, first step, measure of progress and a clear point for specialist advice.