AI for Interaction Design: A Guide for Australian UX Designers (2026)

Interaction design is the discipline of defining how users interact with digital products — the flows, the feedback, the transitions, and the patterns that make an interface feel intuitive or frustrating. AI tools are changing how UX designers approach this work, making it faster to explore the design space and easier to identify problems before they reach users.

AI for Information Architecture

Information architecture — how content and functionality are organised and labelled — is foundational to good UX. Poor information architecture makes everything else harder: navigation is confusing, users can't find what they need, and the mental model of the product doesn't match users' expectations.

Card sorting analysis

Card sorting — asking users to organise content into groups — is a standard technique for developing information architecture. AI can analyse card sorting results, identifying common groupings and patterns across participants. "Here are the results from a card sorting exercise with twenty participants. What groupings are most consistent and what does this suggest about how to organise the navigation?"

Tree testing analysis

Tree testing — asking users to find items in a proposed navigation structure — validates information architecture before it's built. AI can analyse tree testing results, identifying where users get lost and what the results suggest about the navigation structure.

Navigation pattern recommendations

AI can recommend navigation patterns based on the content type, user goals, and device context. "We have a content-heavy website with five main sections and dozens of sub-pages. What navigation patterns would work best for desktop and mobile?" AI can explain the trade-offs between different navigation approaches — mega menus, hamburger menus, tab bars, and sidebar navigation.

Label testing

AI can help evaluate navigation labels — whether the words used in menus and buttons match users' mental models. "Here are the navigation labels we're considering. What might users expect to find under each label? Are there any labels that might be confusing?" AI can draw on its knowledge of common UX patterns to identify potentially confusing labels.

Designing Interaction Flows

Interaction flows — the sequences of screens and states that users move through to complete tasks — are the core deliverable of interaction design. AI tools are making flow design faster and more thorough.

Flow generation

AI can generate interaction flows from task descriptions. "A user wants to reset their password on a mobile app. What are the steps in this flow and what screens are needed?" AI can generate a starting point for the flow that you then refine based on your specific context and constraints.

Edge case identification

AI is particularly useful for identifying edge cases in interaction flows — the unusual situations that are easy to miss in the main flow design. "Here is the main flow for our checkout process. What edge cases should we design for?" AI can identify error states, empty states, loading states, and other edge cases that need to be designed.

Flow critique

AI can critique interaction flows — identifying potential usability issues, unnecessary steps, and opportunities to simplify. Describe your flow and ask AI to evaluate it from a usability perspective.

Micro-Interaction Design

Micro-interactions — the small animations, transitions, and feedback mechanisms that make interfaces feel responsive and polished — are often the difference between a product that feels good and one that feels clunky. AI tools are making micro-interaction design more accessible.

Animation parameters

AI can suggest animation parameters for micro-interactions — duration, easing curves, and timing. "I'm designing a button that changes state when clicked. What animation parameters would make this feel responsive and satisfying?" AI can draw on established principles of animation and motion design to suggest appropriate parameters.

Feedback design

AI can help design feedback mechanisms — how the interface communicates the result of user actions. "A user submits a form. What feedback should the interface provide and how?" AI can suggest appropriate feedback patterns for different contexts and outcomes.

Loading state design

Loading states — what users see while waiting for content to load — are often neglected but significantly affect perceived performance. AI can help design loading states that set appropriate expectations and keep users engaged.

Accessibility in Interaction Design

Accessibility is a legal requirement for many Australian organisations under the Disability Discrimination Act 1992, and a user experience imperative for all. AI tools are making it easier to design accessible interactions.

WCAG compliance

AI can evaluate interaction designs against WCAG 2.1 AA criteria — the standard required by most Australian government and large enterprise websites. Share your design and ask AI to identify potential accessibility issues.

Keyboard navigation design

Many users navigate interfaces using keyboards rather than mice — including users with motor disabilities and power users who prefer keyboard shortcuts. AI can help design keyboard navigation — tab order, keyboard shortcuts, and focus management.

Screen reader compatibility

AI can help design interactions that work well with screen readers — the assistive technology used by users with visual impairments. This includes appropriate ARIA labels, semantic HTML structure, and focus management.

Cognitive accessibility

Cognitive accessibility — designing for users with cognitive disabilities, including dyslexia, ADHD, and memory impairments — is often overlooked. AI can help identify design patterns that may be challenging for users with cognitive disabilities and suggest more accessible alternatives.

Design Systems

Design systems — collections of reusable components, patterns, and guidelines — are essential for maintaining consistency across large products and teams. AI tools are making design systems faster to build and easier to maintain.

Component documentation

AI can help write component documentation — descriptions of when to use a component, how to use it, and what variations are available. Good documentation is essential for a design system to be adopted and used consistently.

Pattern library development

AI can help identify patterns in existing designs and suggest how to systematise them. "Here are screenshots of our current product. What patterns are repeated across the product that should be systematised in a design system?"

Design token generation

Design tokens — the named values for colours, typography, spacing, and other design properties — are the foundation of a design system. AI can help generate a comprehensive set of design tokens from a brand guide or existing design.

Consistency checking

AI can help check designs for consistency with the design system — identifying components that deviate from the system and suggesting how to bring them into alignment.

Designing for Australian Contexts

Australian UX designers often work on products used by Australian users with specific needs and contexts.

Digital literacy diversity

Australia has significant diversity in digital literacy levels — from highly tech-savvy urban professionals to older Australians and people in regional areas who may be less comfortable with digital interfaces. AI can help design for this diversity — identifying patterns that may be challenging for less digitally literate users.

Indigenous Australian users

Designing for Indigenous Australian users requires cultural sensitivity and understanding of specific needs — including language diversity, different relationships with technology, and specific privacy considerations. AI can help identify design considerations for Indigenous Australian users, though community consultation is essential.

Government service design

Many Australian UX designers work on government digital services, which have specific requirements around accessibility, plain language, and compliance with the Digital Service Standard. AI can help ensure designs meet these requirements.

Building Better Interactions

The Australian UX designers who are most effective in 2026 are those who use AI to explore the interaction design space more thoroughly — generating more options, identifying more edge cases, and evaluating designs more rigorously — while applying their own judgement to make the decisions that matter. AI makes the craft of interaction design faster and more thorough; the design thinking that makes interactions genuinely good remains human.