New Study: AI Coding Tools Do Not Write Accessible Code

AI-built sites are as nearly inaccessible as the general web

The AI-built sites averaged 55 accessibility issues per page. The average page in our 2026 Digital Accessibility Index has 62. AI-built pages are essentially as inaccessible as the modern web.

The reason is simple. These tools learned to code from the existing web, and that web is inaccessible. In WebAIM's 2026 scan(opens in a new tab) of the top one million home pages, they found the average site had 56.1 errors per page, which puts the AI-built sites in our study on par with 55. The decrease in homepage accessibility in 2026 is the first decline in six years, reversing a run of gradual improvement. WebAIM attributes the reversal in part to AI-assisted coding.

Asked to build accessible code, every tool reproduced the inaccessible practices it learned from the web. Five independent tools broke the same components in the same ways. Switching tools gets you a different version of the same problem.

Most developers are not accessibility experts, so they trust the model to get it right. But the models don’t have that expertise either. Development teams trust the output, so no one tests it, and the failures ship.

91% of the issues on AI-created sites were medium and high severity

A high-severity issue either stops a person from finishing a task or makes it much harder. Thirty-three percent of the issues we found block the task outright. Someone using a screen reader (or AI Agents) cannot check out, submit a form, or reach the content they came for.

These failures showed up on nearly every build. Thirteen of the 15 sites shipped at least one issue that blocks a task completely.

The same problems showed up on site after site: links with no description, buttons a screen reader cannot identify, and form fields with no labels. Many of the unlabeled buttons and fields sat right where customers take action, like checkout buttons and login forms.

Plaintiffs' firms cite these exact failures in most accessibility demand letters, because they stop real people from buying, signing up, or getting help. Someone who uses a screen reader reaches the checkout button and hears nothing. Someone navigating by keyboard opens the cart but cannot get into it. They do not file a complaint or contact support. They leave, and the next time you hear from them will be in a lawsuit.

That is the part most teams never see. The revenue is gone before anyone knows there was an issue, and the first signal is often a letter from a law firm. By then, the cost has compounded: the customers who left, the legal fees, and the engineering time pulled off the roadmap to answer claims about code that shipped months earlier.

AI builds the feature but skips the part that makes it work

Every accessibility feature has two parts: the code that describes it, and the behavior that code promises. In our study, the AI tools often wrote the code, but the behavior wasn’t always present.

Take skip links, which let someone using a keyboard or screen reader jump past the navigation straight to the content. It needs a link and a target that can receive keyboard focus. Twelve of the 15 sites had the link, but not one had the target wired. All 12 broke the same way. The page scrolls, but focus never moves. The person is still at the top of the navigation, tabbing through every menu item.

Nearly half the issues we found cannot be seen by reading the code. They appear only when someone uses the page: opening a menu, tabbing through a dialog, submitting a form with an error, or viewing the site at phone width.

Reading the code will not show whether focus moves, whether a keyboard can close a dialog, or whether a screen reader announces a form error. Someone has to open the page and test it with the same assistive technology a customer uses. Automated accessibility tools cover code at scale, while expert testing covers behavior. A team that reviews only the code never checks the part that actually prevents people from using the site.

The e-commerce sites had 3x more issues

The AI-built stores averaged 174 accessibility issues per page versus 55 on average across all sites.

Online stores are not usually much worse than other sites. In our 2026 Digital Accessibility Index, e-commerce pages average 65 issues against 62 for pages overall, a difference of about 5%. When AI built the stores, they came out more than three times worse than the other sites it built. AI did not fail evenly. It failed hardest on the sites where people spend money.

Bar graph showing e-commerce sites have 3 times more issues than the comparison group. E-commerce bar is fully filled; comparison has 1/3 filled.

A store has more moving parts than other sites. Shoppers filter products, search, add to a cart, and pay. Every one of those is something a person has to click, type into, or reach with a keyboard. If a filter cannot be reached by keyboard, the shopper never finds the right product. If a screen reader reads the cart button as blank, they cannot buy it.

Those are also the pages that get sued. Our 2026 Web Accessibility Litigation Report found that 78% of accessibility lawsuits target e-commerce, and that filings have doubled since 2020. AI is building the most-sued pages on the web, and building them significantly worse than anything else it builds.

Accessibility has to scale with AI

Teams are confident in their AI-generated code, even as complaints climb. In our companion survey of developers and business leaders, 81% said they are confident the AI-generated code on their site meets accessibility standards. However, almost half (46%) have received an accessibility complaint, demand letter, or lawsuit, and 71% of those respondents said that AI was involved in coding the page that received the complaint. Read the full survey.

AI can build a website in an afternoon. It cannot tell you whether a person can use it, because it doesn’t have the capability to check.

Teams are shipping AI-built pages faster than their review process was built to handle. A company that cannot review at that pace ships pages no one has checked for accessibility, and those are the pages that draw demand letters.

Scaling takes two things. A team needs coverage across every page on the site, not just the home page. Two-thirds of AI search traffic now lands on interior pages, and 64% of accessibility claims in 2025 cited issues on those pages. Scaling also requires the accessibility expertise AI was never trained on.

AudioEye Intelligence is built for exactly that, drawing on more than 1 million human expert reviews and billions of data points from live sites. In independent testing, AudioEye detected 89% to 253% more WCAG issues than other leading accessibility tools. More issues found means more issues fixed. AudioEye Intelligence is the foundation of the AudioEye Digital Accessibility Platform.

AI and accessibility are not opposing forces. AI supplies the speed. Accessibility expertise at scale supplies compliance and legal protection. Used together, they can build a web that works for everyone and that teams can actually trust.