Accessibility remediation traditionally meant hours of research, consultant calls, and trial-and-error fixes. Now artificial intelligence transforms this time-consuming process into something remarkably efficient.
The game-changer isn’t just having AI available, it’s having AI that already knows your specific accessibility issues. Instead of manually feeding code into chatbots, imagine AI that’s pre-loaded with your audit data and ready with responses to your exact issue and pre-engineered prompt.
This shift from generic to specific AI assistance fundamentally changes how teams approach accessibility remediation.
| Benefit | What It Means | Real Impact |
|---|---|---|
| Faster Project Completion | Projects that used to take months now complete in weeks. AI eliminates research time and provides instant guidance, cutting project timelines significantly. | Meet compliance deadlines without stress. Move on to other important work sooner. Ship accessible products faster. |
| Reduced Consultant Dependency | AI handles the routine accessibility questions that typically require expensive expert consultations. Get instant answers without scheduling meetings or waiting for responses. | Your budget goes further. Complex issues still get expert attention while routine fixes happen immediately. No more bottlenecks waiting for consultant availability. |
| Team Learns While Working | Every AI-assisted fix teaches your developers accessibility principles. They understand why issues matter and how to prevent them in future code. | Your team builds lasting accessibility expertise. Future projects have fewer issues because developers code accessibly from the start. Knowledge stays in-house. |
| Instant Context-Aware Help | AI already knows your specific issues and audit data. Click “Analyze with AI” to get targeted solutions without explaining the problem or providing background. | Developers stay focused and productive. Fixes are done right the first time. No confusion from generic advice that doesn’t fit your situation. |
| Everything in One Place | No copying between tools, no manual data entry, no scattered documentation. Your audit data, AI assistance, and progress tracking all live in the same platform. | Teams work more efficiently. Everyone sees real-time updates. No information gets lost between spreadsheets, emails, and chat messages. |
Table of Contents
How Does AI Speed Up Accessibility Fixes?
AI accelerates remediation by eliminating the research phase. When developers encounter an unfamiliar WCAG issue, they typically spend minutes or hours understanding the requirement, researching implementation approaches, and determining the best fix for their specific context.
With AI integrated directly into the remediation workflow, that research time disappears. The AI already has your audit data. It knows your specific issue. It understands the WCAG context. It provides immediate, actionable guidance.
Consider the math: saving three minutes per issue on a 100-issue project equals five hours. But the real savings come from accuracy. When developers get the right answer immediately, they implement fixes correctly the first time. Fewer validation rounds. Less rework. Projects that took 10 weeks now complete in 4 weeks.
The financial impact is equally clear. Technical accessibility consultants charge $195 per hour. A typical project might need 20 hours of support. With AI handling routine questions, that drops to 8 hours. That’s $2,340 saved on a single project.
What’s the Actual Process for Using AI to Fix Issues?
The process starts when you upload your accessibility audit report. The platform automatically extracts all issue data, WCAG criteria, and recommendations. No manual data entry. No copying and pasting. Everything becomes immediately actionable.
From your dashboard, you see every accessibility issue in your project. Click any issue to view its complete details — location, WCAG criterion, description, applicable code, and suggested fix.
Here’s where AI becomes powerful. Click “Analyze with AI” to access five specialized tools:
- Simplify and Explain — Breaks down technical WCAG language into plain English
- Detailed Technical Answer — Provides comprehensive code examples and implementation guidance
- Alternative Approaches — Offers different remediation methods when standard fixes conflict with existing functionality
- WCAG Standards — Explains the success criterion in depth
- Custom Analysis — Handles specific questions that don’t fit other categories
Select the tool that matches your need. The AI generates its response using your pre-loaded audit data. No prompt engineering required. No context setting needed. Just instant, relevant guidance.
Implement the fix using the AI guidance. For code issues, you get specific examples. For content issues, you understand the principles. Copy relevant code snippets, adapt them to your implementation, and test the fix.
Update the issue status to “Completed” and add implementation notes. Team members see updates in real-time. When marked complete, issues move to validation. Auditors validate fixes directly in the platform with all context available.
Will My Team Actually Learn Accessibility This Way?
Yes, and this is perhaps the most valuable outcome. Each issue fixed with AI guidance builds permanent accessibility knowledge. After working through 50 issues, developers start recognizing patterns. They understand keyboard navigation requirements. They know what makes alt text effective. They spot accessibility issues before they reach production.
This experiential learning creates lasting expertise. Developers aren’t just copying fixes — they’re understanding why issues matter and how solutions work. The AI explains the user impact. It clarifies the technical requirements. It shows multiple approaches.
Future audits find fewer issues because your team implements accessible patterns from the start. The knowledge compounds with each project. Your organization develops internal accessibility competence instead of perpetual consultant dependence.
Teams report that after one project with AI assistance, developers handle similar issues independently. They’ve learned the patterns. They understand the principles. They code accessibly by default.
Key Takeaway
Fixing accessibility issues with AI can mean turning a 50-hour remediation project into a 20-hour project. It also means saving thousands in consultant fees while building internal expertise (as well as reducing the number of hours needed from your developers).
The technology exists today. AI can’t automate accessibility fixes, but it makes remediation dramatically more efficient. Upload your audit to Tracker, analyze with AI, implement fixes faster, and build lasting accessibility knowledge.
Your team gets answers instantly. Projects complete faster. Costs drop significantly. Most importantly, your organization develops the accessibility expertise to build inclusive products from the start.