SUMMARY
Purpose: Ensure inclusive, WCAG-compliant experiences through continuous accessibility quality assurance during product delivery and iteration.
Design Thinking Phase: Implement
Time: Ongoing (part of each sprint QA cycle)
Difficulty: ⭐⭐
When to use:When shipping new product features or flows requiring accessibility validationWhen receiving or acting on live customer accessibility feedbackDuring regression, smoke, or exploratory QA — especially for at-risk components
What it is
Accessibility QA (Delivery & Continuous Feedback) is an embedded UX practice that verifies digital accessibility compliance during development and after launch. It combines structured QA checks, user feedback, and AI-assisted reviews to continuously validate inclusive access across devices, platforms, and user contexts.
📺 Video by devnexus. Embedded for educational reference.
Why it matters
Accessibility isn't a checkbox—it's a continuous commitment. Left unchecked, minor regressions can block entire user segments from completing core tasks. Accessibility QA ensures product inclusivity doesn’t degrade through iterations. It empowers teams to interpret standards (like WCAG 2.2) in practical, user-centred ways while catching issues before user complaints arise or legal risk surfaces.
When to use
- Before each code merge during delivery to catch semantic errors, colour violations, or keyboard traps
- After release to evaluate newly shipped features from multiple user ability levels
- When customer voices, support tickets, or usability studies raise accessibility difficulties
Benefits
- Rich Insights: Surfaces nuanced barriers that are invisible through UI-only QA
- Flexibility: Adapts to fast-moving sprints and real-time feedback from actual users
- User Empathy: Builds understanding by auditing from screen reader, motor, and cognitive access perspectives
How to use it
- Define accessibility criteria for each feature based on WCAG, design system specs, and critical user flows.
- Use AI to generate audit checklists and simulate common barriers (e.g. keyboard-only use, high contrast).
- Pair automated checks with manual testing—ideally using screen readers and voice control flows.
- Store results in an accessibility backlog and triage issues into sprints or bug cycles.
- Set up auto-detection in dev environments (e.g. axe-core) and conduct monthly in-production scans.
- Actively incorporate end-user feedback loops into accessibility reporting and QA coverage expansion.
Example Output
Accessibility QA Snapshot for “Checkout – Step 2 (Shipping Method)”
- Automated audit tools triggered: axe DevTools, Lighthouse (score: 90)
- Manual test (screen reader – NVDA): Radio buttons labelled incorrectly, hard to navigate by arrow keys
- Keyboard-only test: Focus order jumps unpredictably after step indicator
- Customer feedback: “Can’t complete shipping form on Safari using VoiceOver”
- Fix priority: P1 accessibility regression → added to sprint backlog
Common Pitfalls
- Over-reliance on tools: Automated scanners miss up to 70% of real-world issues. Manual testing is critical.
- Lack of user context: Accessibility barriers vary by ability, device, and task—not just WCAG violations. Pair audits with real user scenarios.
- Bolted-on QA: If teams delay accessibility QA to the end, regressions slip through. Embed it into definition of done and code reviews.
10 Design-Ready AI Prompts for Accessibility QA – UX/UI Edition
How These Prompts Work (C.S.I.R. Framework)
Each of the templates below follows the C.S.I.R. method — a proven structure for writing clear, effective prompts that get better results from ChatGPT, Claude, Copilot, or any other LLM.
C.S.I.R. stands for:
- Context: Who you are and the UX situation you're working in
- Specific Info: Key design inputs, tasks, or constraints the AI should consider
- Intent: What you want the AI to help you achieve
- Response Format: The structure or format you want the AI to return (e.g. checklist, table, journey map)
Level up your career with smarter AI prompts.Get templates used by UX leaders — no guesswork, just results.Design faster, research smarter, and ship with confidence.First one’s free. Unlock all 10 by becoming a member.
Prompt Template 1: “Audit an End-to-End User Flow for Accessibility Risks”
Audit an End-to-End User Flow for Accessibility Risks
Context: You are a UX designer reviewing a [key journey] in a [multi-device product].
Specific Info: The flow includes [5 sequential steps], with known challenges on [mobile] and [spoke feedback from screen reader users].
Intent: Identify accessibility gaps across screen reader support, keyboard navigation, contrast, and aria-labels.
Response Format: Return a step-by-step flow audit with callouts for WCAG criteria, severity level, and quick-impact fixes.
Ask clarifying questions if any steps or assistive needs are missing.
Then, suggest one proactive design adjustment that would prevent future accessibility debt.
Prompt Template 2: “Generate a VoiceOver Test Script for Critical Path”
Generate a VoiceOver Test Script for Critical Path
Context: You are conducting a manual accessibility QA test on macOS using VoiceOver for a [checkout flow].
Specific Info: The flow includes [3 screens], beginning with [cart review] and ending at [confirmation page].
Intent: Help QA testers simulate realistic screen reader interactions to catch non-obvious access issues.
Response Format: Return a narrated test script with navigation commands, expected label output, and user confirmation cues.
Suggest one additional step to validate edge case accessibility behaviour.
Prompt Template 3: “Create a Developer Handoff Checklist for WCAG 2.2”
Create a Developer Handoff Checklist for WCAG 2.2
Context: You are delivering final hi-fidelity designs for a new [payment component].
Specific Info: The implementation will happen using [React and Tailwind], with handoff through Figma annotations.
Intent: Ensure developers have clear, actionable WCAG guidance for implementing inclusively.
Response Format: Return a checklist grouped by relevant WCAG success criteria, including ARIA best practices.
Note any gaps that may require design clarification or developer pairing.
Prompt Template 4: “Map Accessibility Feedback into Actionable Backlog Items”
Map Accessibility Feedback into Actionable Backlog Items
Context: You’re a design lead triaging accessibility bugs logged post-release for a [search interface].
Specific Info: Users have reported [focus order issues and screen magnifier clipping].
Intent: Convert feedback into well-scoped, developer-friendly Jira tickets.
Response Format: Return 3–5 sample ticket drafts labelled by sprint priority and issue severity.
Recommend how to involve QA and PMs to validate these before pushing to sprint.
Prompt Template 5: “Review UI Component Tokens for Accessibility Gaps”
Review UI Component Tokens for Accessibility Gaps
Context: You are reviewing design system tokens for button components across themes.
Specific Info: Each token includes [background, border, hover, focus-visible states].
Intent: Identify tokens that may pose colour contrast issues or lack focus visibility.
Response Format: Create a table categorising risky tokens by theme, component, and WCAG guideline at risk.
Ask if any platform-specific overrides (e.g. dark mode behaviour) should also be considered.
Prompt Template 6: “Compare Two Design Variants for Accessible Interactions”
Compare Two Design Variants for Accessible Interactions
Context: You’re testing two modal designs for a new [notification subscription flow].
Specific Info: One uses inline toggle switches, the other uses labelled buttons.
Intent: Determine which design provides better accessibility outcomes for keyboard and screen reader users.
Response Format: Return an annotated comparison table with pros, cons, and potential usability blockers per variation.
Suggest how we might A/B test these designs with an inclusive user research cohort.
Prompt Template 7: “Write Alt Text and ARIA Descriptions for Key Screens”
Write Alt Text and ARIA Descriptions for Key Screens
Context: You are finalising alt text and ARIA labels for a new [analytics dashboard feature].
Specific Info: The dashboard includes charts, loading states, and dynamic table updates.
Intent: Generate meaningful descriptive text that supports screen reader comprehension without overwhelming the user.
Response Format: Return alt text and ARIA annotations grouped by component type.
Ask for examples if visual context is needed to improve label accuracy.
Prompt Template 8: “Develop a Test Plan for Multimodal Accessibility”
Develop a Test Plan for Multimodal Accessibility
Context: You are leading QA for an onboarding experience targeting users with diverse access modes.
Specific Info: Flows will be used via [voice control, touch, keyboard, and magnification].
Intent: Validate usability across multiple input and assistive tech combinations.
Response Format: Outline a test matrix with devices, inputs, user archetypes, and likely pain points to probe.
Suggest a recurring cadence to revisit this test planning during product scaling.
Prompt Template 9: “Score a Feature’s Accessibility Maturity”
Score a Feature’s Accessibility Maturity
Context: You are conducting a self-assessment on the accessibility state of a newly launched [profile editor].
Specific Info: The feature includes form validation, tooltip behaviour, and dynamic dropdowns.
Intent: Provide a maturity rating across compliance, usability, and error recovery dimensions.
Response Format: Return a 0–3 scale with justifications per dimension and suggestions to reach next level.
Offer one upstream design decision that could have improved this maturity score.
Prompt Template 10: “Translate User Personas into Accessibility Testing Personas”
Translate User Personas into Accessibility Testing Personas
Context: You have traditional personas designed around marketing and behaviour traits for a [travel app].
Specific Info: Existing personas do not currently consider ability-based use cases.
Intent: Expand them into accessibility testing personas for more inclusive QA scenarios.
Response Format: Provide 3 enriched personas with situational impairments, assistive tools used, and prioritised needs.
Prompt how we might pilot these expanded personas during upcoming usability tests.
Recommended Tools
- axe DevTools
- WAVE Evaluation Tool
- ChromeVox (Chrome Screen Reader)
- semantic-dom-diff for DOM-level accessibility regression testing
- Accessibility Insights from Microsoft
