We’ve connected AI with your accessibility audit report. This means AI tells your team how to fix each issue inside a streamlined dashboard.
Your developers, designers, and content managers can now fix accessibility issues correctly — even if they have no accessibility experience.
That’s powerful.
And that’s a lot of time and money saved.
| Key Point | What It Means for You |
|---|---|
| Audit Data Integration | AI has your specific audit report data pre-loaded, eliminating generic responses and providing fixes tailored to your exact issues |
| No Experience Required | Developers, designers, and content managers without accessibility training can make correct fixes using AI guidance specific to each issue |
| Five Pre-Prompted Tools | Each issue comes with specialized AI tools that already know what questions to ask and how to guide fixes |
| Real Issues, Not Scans | Working from manual audit reports means AI assists with actual accessibility barriers, not automated scan false positives |
| Immediate ROI | Teams fix issues correctly the first time, reducing validation rounds and technical support hours at $195 per hour |
Table of Contents
The Simple Change That Makes Everything Different
AI excels at providing guidance when it has specific context. That’s the breakthrough with Accessibility Tracker: we connected AI directly to your audit report data.
When your developer hits an ARIA implementation they don’t understand, the AI already knows the specific issue context, the WCAG requirement, and can provide code examples tailored to the actual problem.
When your designer encounters a color contrast issue, they don’t need accessibility training. They click “Analyze with AI” and get specific guidance about their exact issue, including the applicable code from the audit and alternative approaches that work with their design system.
When your content manager needs to write alt text, the AI explains exactly what makes descriptions effective for screen reader users — with examples based on your actual images.
This isn’t generic AI assistance. This is AI that knows your exact issues, your specific code, and your audit recommendations.
Why This Changes Everything
For years, accessibility remediation has been bottlenecked by expertise. You either trained your entire team (expensive and time-consuming) or relied on specialists (creating workflow bottlenecks) or hired consultants at $195 per hour (unsustainable for most projects).
Now your entire team contributes effectively. Right away. Without training.
The AI doesn’t automate fixes — that’s impossible. Instead, it guides each team member through their specific fixes with precision. Like having an accessibility expert sitting next to every person on your team, available instantly, pre-loaded with knowledge about each exact issue.
Why Audit-Based AI Works vs. Automated Tools
Most accessibility platforms start with automated scans that only flag about 25% of WCAG issues. Even if you add AI to help fix those issues, you’re working with incomplete and often incorrect data.
Accessibility Tracker is audit-based which means everything starts with an actual audit report that identifies all accessibility issues. Now AI has the complete, accurate information about each issue:
- The specific location and URL
- The applicable code snippet
- The auditor’s recommendation
- The WCAG success criterion
- The users affected
This context transforms AI from a generic helper into a specialized accessibility consultant for each issue.
Five Tools That Really Help
Your team doesn’t need to craft prompts or understand WCAG. For each issue, they choose from five pre-configured tools:
Custom Analysis: Allows specific questions about unique situations that don’t fit the other categories.
Simplify and Explain: Translates technical WCAG language into plain English. Perfect for content managers who need to understand why their video needs captions or designers learning about color contrast requirements.
Detailed Technical Answer: Provides specific code examples and implementation guidance. Developers get model code they can adapt, not generic documentation.
Alternative Approaches: Offers different remediation methods when the standard fix conflicts with existing functionality. Sometimes there are multiple ways to meet a WCAG requirement.
WCAG Standards: Explains the success criterion in depth, helping teams understand not just how to fix issues, but why they matter for users with disabilities.
Real Results From Real Projects
Consider a typical scenario: Your audit report shows 150 issues across your website. Your development team has minimal accessibility experience. Your designer has never worked with WCAG requirements. Your content team doesn’t understand screen reader requirements.
Traditional approach: Schedule training sessions. Hire consultants at $195 per hour. Deal with multiple validation rounds as fixes aren’t implemented correctly. Watch the project stretch from two months to five.
With audit-based AI: Each team member starts fixing issues immediately. The designer handles color contrast with AI explaining specific requirements. Developers fix keyboard navigation with code examples tailored to their implementation. Content managers add proper alt text with AI explaining what makes descriptions effective.
The project finishes in six weeks instead of five months.
How Teams Without Accessibility Experience Succeed
The magic happens because the AI eliminates the knowledge gap without requiring training. Your team learns by doing, with perfect guidance at every step.
A developer working on their first keyboard trap issue doesn’t need to research WCAG 2.1.2. They view the issue in Tracker, click “Analyze with AI,” and select “Detailed Technical Answer.” The AI provides:
- Analysis of their current implementation
- Specific problems identified
- Step-by-step fix instructions
- Code examples ready to implement
- Testing methods to verify the fix
After fixing ten keyboard navigation issues with AI guidance, that developer intuitively understands keyboard accessibility. They’ve learned through practical application, not abstract training.
The Efficiency Multiplier
When every team member can contribute effectively, projects accelerate. Instead of one accessibility specialist becoming a bottleneck, work distributes across your entire team:
- Designers fix visual issues independently
- Developers handle code problems without waiting for guidance
- Content editors remediate text issues immediately
- Project managers understand progress without technical translation
This parallel workflow, enabled by AI assistance, creates the 2.5x efficiency gain we see with Tracker projects.
Building Permanent Capability
Here’s what most companies miss: every issue fixed with AI assistance builds lasting knowledge. Your team isn’t just completing a project; they’re developing accessibility expertise.
After your first project with Tracker, your organization has team members who understand accessibility principles, can identify issues proactively, and implement accessible patterns from the start. Your next audit finds fewer issues because your team now builds with accessibility in mind.
Key Insights
The breakthrough with Accessibility Tracker isn’t sophisticated AI trying to automate fixes. It’s the simple connection between AI and your actual audit data. This connection transforms AI from a generic assistant into a specialized guide that helps any team member fix accessibility issues correctly.
By starting with real audit reports instead of scans, the AI works with complete, accurate information. By pre-configuring tools for specific accessibility tasks, team members don’t need prompt engineering skills. By providing guidance tailored to each exact issue, fixes happen faster with fewer validation rounds.
The result: teams without accessibility experience can successfully remediate issues, projects complete 2.5x faster, and organizations build permanent accessibility capability through practical learning.
FAQ
How is this different from using ChatGPT for accessibility help?
With ChatGPT, you need to copy audit details, provide context, and craft prompts. Tracker’s AI already has your audit data loaded and offers pre-configured tools designed for specific accessibility tasks. No copying, no prompting, just immediate guidance.
Can team members really fix issues without accessibility training?
Yes. The AI provides step-by-step guidance specific to each issue. A designer fixing color contrast gets exact ratio requirements and alternative color suggestions. A developer fixing ARIA gets working code examples. The guidance is precise enough that team members can make correct fixes without prior knowledge.
What happens if the AI makes a mistake?
AI can make errors, which is why Tracker includes validation workflows. After team members mark issues as fixed, auditors validate the implementations. The AI dramatically reduces errors compared to unguided fixes, but validation ensures correctness.
Do we still need accessibility consultants?
You’ll need fewer consultant hours. AI handles routine questions and implementation guidance. Consultants focus on complex architectural decisions and validation rather than answering basic implementation questions.
How does AI know about our specific code and implementation?
The AI receives the complete audit data for each issue, including the applicable code snippets, URLs, and auditor recommendations. When you ask for help, the AI already understands your specific context.
Can AI fix the issues automatically?
No. AI cannot automate accessibility fixes. It provides guidance, code examples, and explanations, but your team implements the actual fixes. This ensures fixes work correctly with your specific implementation and design requirements.
