Accessibility bugs affect 15-20% of your users. They're also the bugs most consistently missed by AI coding tools.
AI coding tools generate visually correct UIs that are often inaccessible. Missing alt text on images. Form inputs without labels. Interactive elements that can't be reached with keyboard navigation. Color contrast ratios that don't meet WCAG standards. Focus management that traps users in modal dialogs.
These bugs are invisible to sighted developers using a mouse. They're showstoppers for users with disabilities. And they're increasingly a legal liability — ADA lawsuits targeting inaccessible websites continue to rise year over year.
Why AI Coding Tools Generate Inaccessible Code
AI models are trained on the web as it exists. The web is overwhelmingly inaccessible. Most training data contains HTML without semantic structure, images without alt text, and interactive elements without ARIA attributes. The model reproduces what it learned.
The result: AI-generated code looks correct in a browser but fails screen readers, keyboard navigation, and other assistive technologies.
What to Test
Image alt text present and descriptive
Form inputs have associated labels
All interactive elements reachable via keyboard
Focus order is logical
Color contrast meets WCAG AA (4.5:1 for text)
ARIA attributes used correctly
Error messages announced to screen readers
Modal focus trapping and escape
TestSprite's testing includes accessibility checks as part of the comprehensive test suite. When the agent interacts with form elements, it verifies label associations. When it encounters images, it checks for alt text. When it navigates, it verifies keyboard accessibility.
Accessibility testing on every PR means a11y bugs are caught before they affect users or create legal exposure.