AI Accessibility Checker: Find and Fix WCAG Issues

An AI accessibility checker can review a page’s HTML, explain each problem in plain words and write the fix, which is something classic automated scanners rarely do well. It is not a replacement for testing with a keyboard, a screen reader and real users, and it cannot certify that a site meets WCAG. Used together with those checks, though, it turns a long list of cryptic warnings into a prioritised to-do list a developer can actually finish.

This guide explains what an AI accessibility checker is good at, what it misses, a practical review workflow, prompts you can reuse and the most common WCAG issues an assistant can help you fix.

Why accessibility matters now

Accessibility means people can use your site whether they navigate by keyboard, use a screen reader, zoom to 200%, have low vision or colour blindness, or simply use a phone in bright sunlight. It is good practice and good business, and in the EU it is increasingly a legal requirement. The European Accessibility Act has applied since 28 June 2025 to many consumer-facing products and services, including a wide range of e-commerce sites, with exemptions for microenterprises providing services.

The technical reference almost everyone uses is the Web Content Accessibility Guidelines. The current version, WCAG 2.2, organises requirements under four principles: content must be perceivable, operable, understandable and robust. Most laws and procurement rules point to conformance level AA.

What an AI accessibility checker does well

Automated rule-based scanners are good at finding certain issues, such as missing alt attributes or low contrast, but their output is often a long list of codes. An assistant adds three things.

Explanation. It tells you who is affected and why: “A screen reader user hears ‘button’ with no name, so they cannot tell this is the search button.”
Fixes in your code. It rewrites the actual snippet, in your framework, instead of linking to a generic rule page.
Judgement on content. It can suggest meaningful alt text, clearer link text, better error messages and simpler wording, which pure rule checkers cannot.

Issues an assistant spots reliably in markup

Images without alt text, or with alt text like “image123.jpg”.
Form inputs without associated labels.
Buttons and links with no accessible name, such as icon-only buttons.
Skipped heading levels and missing page landmarks.
Links that all say “read more” or “click here”.
A missing lang attribute on the page.
div elements used as buttons without keyboard support.
ARIA attributes used incorrectly, which can make things worse than no ARIA at all.

What it misses, and why you still need manual testing

An assistant reading HTML sees the code, not the experience. Several important problems only show up when you use the page.

Keyboard traps and focus order. Whether you can tab through a menu, open a dialog, close it and land in a sensible place.
Visible focus. Whether the focused element is actually visible with the final CSS.
Dynamic content. Error messages, toasts and live updates added by JavaScript after load.
Real contrast. Text over images, gradients and hover states, where colours are not in the HTML.
Screen reader experience. Whether the page makes sense when read aloud in order.
Cognitive load. Whether instructions are clear and the process is forgiving of mistakes.

The W3C’s guide to evaluating web accessibility describes how automated tools, manual checks and user testing fit together. No tool, AI or not, can claim full WCAG conformance on its own.

A practical review workflow

Step 1: pick the pages that matter

Do not try to audit everything at once. Start with the templates most users touch: the home page, a product or service page, the contact or sign-up form, the checkout or booking flow, and the main navigation. Fixing a template fixes every page that uses it.

Step 2: run an automated scan

Use a browser-based accessibility checker or your browser’s built-in developer tools for a first pass. Save the results.

Step 3: give the assistant the code and the scan

Paste the rendered HTML of the page or component, or point the assistant at the URL if it can read pages, and include the scanner output. Then ask for explanation and prioritisation, not just fixes.

Step 4: test manually with a keyboard

Unplug the mouse, or just stop using it. Tab through the page. Can you reach every interactive element, see where you are, open and close menus and dialogs, and submit forms? Note every problem and give the notes to the assistant for fixes.

Step 5: try a screen reader on the key flows

Every major operating system includes a free screen reader. Even ten minutes on your sign-up form teaches more than an hour of reading guidelines.

Step 6: fix, then re-test

Apply fixes in small batches, review them like any other code change and re-run both the scan and the keyboard test. Our guide to code review with AI describes a good review routine.

Prompts for an AI accessibility checker

Full-page review

“Review this HTML for accessibility against WCAG 2.2 level AA. For each issue: quote the element, name the success criterion, explain in one sentence who is affected and how, rate the impact as high, medium or low, and give the corrected code. List high-impact issues first. Then list what you cannot check from the HTML alone and what I should test manually.”

Component fix

“This dropdown menu is built with divs and JavaScript. Rewrite it so it works with a keyboard and a screen reader: correct roles or native elements, focus management, Escape to close and visible focus. Keep my class names. Explain each change briefly.”

Alt text for real images

“Here are the product images and their context on the page. Write alt text for each: describe what matters for a shopper, under 125 characters, no ‘image of’. Mark purely decorative images that should have empty alt.”

Form errors

“Rewrite these form error messages so they say what went wrong and how to fix it, and show me the markup that connects each message to its field for screen readers.”

Accessibility testing methods compared

Method	Finds	Misses	Effort	Explains the fix
Rule-based automated scanner	Missing alt, labels, contrast in plain text, ARIA errors	Focus, meaning, dynamic content, user experience	Low	Partly, with generic rule pages
AI accessibility checker on HTML	Markup issues, unclear text, weak alt text, semantic problems	Final rendered contrast, focus visibility, runtime behaviour	Low	Yes, in your own code
Manual keyboard test	Focus order, traps, hidden focus, unusable widgets	Screen reader wording, markup details	Medium	No
Screen reader test	Reading order, missing names, confusing announcements	Visual issues	Medium to high	No
Testing with disabled users	Real barriers and workarounds	Rarely misses what matters	High	Through their feedback
Professional audit	Full WCAG review with documentation	Depends on scope	High	Yes

The most common WCAG issues and how AI helps fix them

Low colour contrast

WCAG AA asks for a contrast ratio of at least 4.5:1 for normal text and 3:1 for large text. An assistant can calculate the ratio between two colour values and suggest the closest shade that passes while keeping your brand look. If you are choosing new colours, our guide to the AI colour palette generator covers building accessible palettes from the start.

Missing or poor alt text

Every meaningful image needs alt text that conveys its purpose; decorative images need an empty alt so screen readers skip them. AI is very good at drafting alt text, but check that it describes what matters in context, not just what is visible.

Unlabelled form fields

Placeholder text is not a label. Each input needs a visible label connected in the markup, and required fields and errors must be announced too.

Icon-only buttons and vague links

A magnifying-glass button needs an accessible name such as “Search”. Link text should make sense out of context, which also helps search engines.

Custom widgets without keyboard support

Menus, tabs, sliders and dialogs built from generic elements are the source of many serious barriers. Native HTML elements solve much of this for free; the assistant can often replace a custom widget with a native one.

Missing language and page structure

A page language attribute, one clear H1, logical headings and landmarks such as header, nav, main and footer help screen reader users jump around the page.

Cautions when using AI for accessibility

Do not accept ARIA by default. AI tools sometimes add roles and ARIA attributes everywhere. The first rule of ARIA is to use native HTML when it exists.
Verify every claim about a success criterion. Assistants can cite the wrong criterion number or level. Check against the official WCAG overview.
Test the fix, not just the code. A change that looks right can break focus elsewhere.
Be wary of overlays. Scripts that promise one-line accessibility on top of an inaccessible site rarely fix the underlying problems and are widely criticised by disabled users.
Never claim conformance based on an AI review. An accessibility statement must reflect real testing.

The general advice in when not to trust AI-generated code applies fully here.

Using Ask Mio as an AI accessibility checker

Ask Mio can review accessibility in several ways. The Page & SEO audit tool checks a live page for title, headings, images without alt text, robots and canonical tags. The Web page reader and Live browser tools let Mio open a URL, with the live browser running JavaScript like a real visitor; our article on the live browser vs web page reader explains the difference. In Code mode, on the Coding and Business plans, Mio reviews pasted HTML, CSS or components and writes fixes, and the UI/UX designer or Senior developer expert can stay active for the whole review. With the GitHub connector, Mio can read your repository files when you ask it to.

What Ask Mio does not do: run a screen reader, test keyboard focus in your browser for you, or certify WCAG conformance. For a formal audit or an accessibility statement backed by evidence, work with an accessibility specialist and include disabled users in testing.

Frequently Asked Questions

Can an AI accessibility checker make my site WCAG compliant?

No tool can do that alone. An AI accessibility checker is very useful for finding markup issues, explaining them and writing fixes, but several WCAG requirements can only be confirmed by testing with a keyboard, a screen reader and the final rendered design. Use AI to speed up the work, then confirm the result with manual tests and, for important sites, a professional audit.

What is the difference between WCAG A, AA and AAA?

They are conformance levels. Level A covers the most basic requirements, AA adds the requirements most laws and contracts expect, and AAA is the strictest and is not usually required for entire sites. In practice, aim for WCAG 2.2 level AA. An assistant can tell you which level each issue belongs to, but check important points against the official text.

Does the European Accessibility Act apply to my website?

It may. Since 28 June 2025 it covers many consumer-facing products and services in the EU, including much of e-commerce, while microenterprises providing services are exempt. Whether your site is in scope depends on what you sell, to whom and your company size. Check your national implementing law or ask a legal adviser rather than relying on an AI answer.

Can AI write good alt text for my images?

Usually, yes, especially when you give it the context: the page, the product and why the image is there. Ask for short descriptions focused on purpose, and mark decorative images for empty alt text. Review the results, because AI may describe irrelevant details or miss what a user actually needs, such as the text on a chart or the colour of a product variant.

How often should I check accessibility?

Check whenever you change a template, add a new component or redesign a flow, and run a broader review a few times a year. Building checks into code review prevents most problems from reaching users. An assistant can review each pull request for accessibility issues in the same pass as other code quality checks, which keeps the cost of staying accessible low.

The Bottom Line

An AI accessibility checker is a fast, patient reviewer that explains problems and writes the fixes in your own code. Pair it with an automated scan, a keyboard test and a short screen reader session, and you will catch most barriers before your users do. Never treat an AI review as proof of conformance, but do use it to make accessibility a routine part of building. To review your own pages in Code mode, see the Coding and Business plans on the Ask Mio pricing page.