WCAG Compliance with AI

From Rules to Remediation

🔄 Quick Recall: In the previous lesson, you mapped the AI assistive technology landscape across visual, auditory, motor, and cognitive disabilities. Now you’ll learn to use AI to ensure your digital products work with those assistive technologies — auditing for WCAG compliance and generating actionable remediation plans.

WCAG (Web Content Accessibility Guidelines) can feel overwhelming: WCAG 2.1 Level AA alone has 50 success criteria across 13 guidelines. Checking all of them manually across an entire website would take weeks. AI-powered auditing tools can scan your site in minutes — but understanding what they find (and what they miss) is the real skill.

The WCAG Audit Workflow

Step 1: Automated Scan

Help me plan a comprehensive WCAG accessibility audit.

My website:
- URL: [your site]
- Number of pages: approximately [X]
- Technology: [HTML/React/WordPress/etc.]
- Known issues: [any you're aware of]

Design the audit workflow:

AUTOMATED SCANNING (catches ~30% of issues):
- Which tools to use: axe DevTools, WAVE, Lighthouse
- How to scan: full-site crawl vs. representative pages
- What automated scans catch:
  • Missing alt attributes on images
  • Color contrast below 4.5:1 (text) or 3:1 (large text)
  • Missing form labels and associations
  • Empty headings or broken heading hierarchy
  • Missing page language attribute
  • Duplicate element IDs
  • Broken ARIA references

MANUAL TESTING (catches remaining ~70%):
- Keyboard navigation: can every function be reached and
  operated with keyboard alone?
- Screen reader testing: does the experience make sense
  audibly? (test with NVDA, VoiceOver, or JAWS)
- Cognitive review: is content clear, structured, predictable?
- Motion: do animations respect prefers-reduced-motion?

USER TESTING (real-world validation):
- Test with 3-5 users who use assistive technology
- Include different disability types
- Observe, don't just ask — watch how they navigate

Step 2: AI-Assisted Issue Analysis

Once you have a list of issues, use AI to make sense of them:

I've run an accessibility audit and found these issues:
[paste the list of issues from your audit tool]

For each issue:
1. Explain what it means in plain language
2. Who is affected and how severely
3. Rate priority: Critical / High / Medium / Low
4. Provide the specific code fix
5. Estimate time to fix

Group issues by:
- Type (images, forms, navigation, content, ARIA)
- Priority (Critical first)
- Page/component (batch similar fixes)

Then create a remediation schedule:
- Week 1: Critical issues
- Week 2-3: High priority
- Month 2: Medium priority
- Ongoing: Low priority

✅ Quick Check: Why should accessibility audits include both automated scanning AND manual testing? Because automated tools catch structural issues (missing attributes, contrast ratios, heading hierarchy) — approximately 30% of WCAG success criteria. But they can’t evaluate whether alt text is meaningful, whether tab order is logical, whether content is cognitively clear, or whether screen reader announcements make sense. The 70% that requires human judgment includes the most impactful usability issues.

Common WCAG Issues and AI Fixes

Images Without Alt Text

I have [X] images on my website that are missing alt text.
Help me categorize them and write appropriate alt text.

For each image, I'll describe what it shows.
You help me determine:

1. Is it INFORMATIVE (conveys meaning → needs descriptive alt)?
   Example: product photo, chart, infographic
   Alt text: describe what the image communicates

2. Is it DECORATIVE (purely visual → needs empty alt="")?
   Example: background patterns, dividers, ornamental icons
   Fix: alt="" (empty alt, not missing alt)

3. Is it FUNCTIONAL (part of a link or button → describe function)?
   Example: logo that links to homepage, icon button
   Alt text: describe what happens when clicked

4. Is it COMPLEX (chart/graph → needs extended description)?
   Example: data visualization, process diagram
   Fix: short alt + longer description nearby

Image descriptions:
[describe each image]

Color Contrast Failures

My accessibility scan found [X] color contrast failures.
Here are the color pairs that failed:

[paste color pairs with their contrast ratios]

For each pair:
1. What's the current contrast ratio?
2. What's the minimum required? (4.5:1 for normal text,
   3:1 for large text, 3:1 for UI components)
3. Suggest an adjusted color that meets the requirement
   while staying close to the original brand color
4. Show the hex code for the corrected color

ARIA Patterns

Help me implement ARIA correctly for these interactive
components on my website:

1. DROPDOWN MENU:
   Current: <div onclick="toggleMenu()">Menu</div>
   Needed: proper role, state, keyboard interaction

2. TAB PANEL:
   Current: <div class="tabs"> with click handlers
   Needed: role="tablist", role="tab", aria-selected,
   keyboard arrow navigation

3. MODAL DIALOG:
   Current: <div class="popup"> with close button
   Needed: role="dialog", aria-modal, focus trap,
   escape key to close, focus return on close

4. ACCORDION:
   Current: <div class="accordion"> with toggle
   Needed: proper headings, aria-expanded, aria-controls

For each: provide the corrected HTML with ARIA attributes
and explain the keyboard interaction pattern required.

CI/CD Integration

The most effective accessibility strategy catches issues before they ship:

Help me add accessibility testing to our CI/CD pipeline.

Our stack:
- Framework: [React/Vue/Angular/plain HTML]
- CI system: [GitHub Actions/GitLab CI/Jenkins]
- Test framework: [Jest/Cypress/Playwright]

Design an accessibility testing pipeline:

PULL REQUEST CHECKS (automated, every PR):
- axe-core integration in unit tests
- Color contrast validation
- HTML validation (proper semantics)
- Heading hierarchy check
- Image alt attribute presence

STAGING DEPLOYMENT (automated + manual):
- Full-site accessibility scan with axe
- Keyboard navigation smoke test (automated)
- Flag new pages for manual review

QUARTERLY AUDIT:
- Manual screen reader testing
- User testing with assistive technology users
- WCAG compliance report generation

Provide example configuration for [their CI system].

✅ Quick Check: Why are accessibility overlays (widgets that add font controls and contrast toggles to your site) controversial in the disability community? Because they don’t fix the underlying code — screen reader users already have their own tools configured to their preferences, overlays can conflict with assistive technology, courts haven’t accepted them as compliance evidence, and they give teams a false sense of security that stops investment in real fixes.

Key Takeaways

AI-powered accessibility auditing catches structural issues in minutes (missing alt attributes, contrast failures, ARIA errors) — but covers only ~30% of WCAG criteria
Prioritize remediation by user impact: missing form labels and keyboard traps block users entirely, while minor contrast violations are inconvenient but usable
Avoid accessibility overlays — they don’t fix underlying code, can interfere with assistive technology, and don’t satisfy legal requirements
Integrate automated accessibility testing into CI/CD pipelines to catch issues before they ship, with quarterly manual audits for the 70% that automation misses
ARIA is a powerful tool but must be implemented correctly — incorrect ARIA is worse than no ARIA, as it actively misleads screen readers

Up Next: You’ll learn to create accessible content at scale — using AI to generate alt text, captions, transcripts, and properly structured documents that meet accessibility standards.