The Role of AI in Web Accessibility: Benefits and Limitations

AI is playing an increasingly important role in web accessibility. But the claims around what AI can actually do? All over the map. From automated testing to automatic fixes, AI is often framed as a fast, scalable fix.

The reality is more nuanced. AI tools have made great strides in the accessibility world, but they are only effective when paired with human expertise.

Below, we’ll explore the role of AI in web accessibility — where it can improve accessibility, and where its limitations make the human touch essential.

How AI Is Used in Web Accessibility Today

Web accessibility focuses on removing digital barriers so people with disabilities can use websites and digital content more easily. Standards like the Web Content Accessibility Guidelines (WCAG) provide the foundation for what makes digital content accessible, and AI is now being used to help teams apply those standards more consistently and at scale. 

An important note: AI accessibility tools can’t replace human efforts entirely, but they are well-suited for repeatable, technical tasks, including:

• Automated issue detection: AI can scan a website for common accessibility errors, like missing alt text, poor color contrast, or improperly labeled form fields. These automated checks can help teams catch common issues early and prioritize fixes more efficiently. An important note: not all detection is the same — every tool will vary in what its automation can identify, meaning one tool may catch some issues that another might miss.

• Content analysis: It can analyze text, images, and media to identify what’s happening and summarize it. This supports tasks such as identifying images that need alt text, summarizing long content, and detecting potential accessibility gaps in multimedia.

• Assistive feature support: Al also powers features that improve access to content in real time, including live captions for videos, speech recognition, and text-to-speech functionality. These features can enhance usability for people with a wide range of access needs.

Benefits of AI and Digital Accessibility

AI is especially powerful for grand-scale tasks, rapid implementation, and 24/7 monitoring, which is something humans can’t easily do. Here are some areas where AI accessibility tools excel in website optimization:

Scale

AI can scan thousands of pages instantly to quickly identify accessibility issues and generate recommendations for fixes at scale. Some AI tools can even apply fixes for specific issues. For example, an e-commerce company with hundreds of product pages could use AI to generate alt text for each product image, which can then be reviewed and refined by humans.

Detection

AI can easily detect common accessibility errors and find opportunities for improvement. This can streamline the path to accessibility and compliance with key accessibility laws by giving organizations a clear starting point. For example, teams can use AI to flag content that may cause issues for screen reader users and receive recommendations for improvement.

Consistency

AI can apply the same logic throughout a website by identifying patterns. For example, if a site contains inconsistent headings that jump from H1s to H3s, AI can identify it, giving teams a clear, easy starting point for correcting and standardizing markup across other pages.

Affordability

AI tools can lower the barrier of entry for organizations with limited resources by reducing manual effort and increasing efficiency. Batch processing and automated tools can save teams hundreds of hours, allowing them to focus human expertise where it’s needed most.

Illustration of an online submission form

Limitations of AI in Accessibility

One of the biggest mistakes organizations make with artificial intelligence accessibility is installing it once and walking away, leaving it to run quietly in the background. This ultimately results in several problems (some of which are severe) as AI can’t do everything. 

While AI can identify certain accessibility issues with higher accuracy than manual testing, even the best automated tools can reliably detect online around two-thirds of WCAG issues with automation alone. This means an AI-only strategy could leave you non-compliant with accessibility standards and with a false sense of compliance. Below are additional ways in which AI-powered accessibility testing can leave you exposed: 

No Context

While AI performs well in checking text content and basic technical issues, they often miss contextual and semantic nuances — such as interpreting whether a magnifying glass icon is for  search, zoom, or viewing more details — because they lack human understanding of intent. This can result in false positives, false negatives, or incomplete recommendations unless complemented by human review.

Lack of Lived Experience

AI lacks human experience and cannot exercise empathy. As a result, it can’t understand how someone with a disability experiences digital content. This limitation is especially evident in navigating complex workflows, such as a checkout process or completing a multi-field form.

Balancing Accessibility Across Disabilities

AI-driven tools may improve usability for people with one type of disability while unintentionally creating barriers for others. Because accessibility needs vary widely, there is no single “fix” to improve web accessibility for everyone; the goal is to reduce friction across experiences and enhance usability for as many users as possible. 

Bottom line: A page might technically meet accessibility guidelines on paper but still create friction for users if these nuances are missed.

Common Misconceptions of AI in Web Accessibility

As AI has become more commonplace in web accessibility efforts, several misconceptions have followed. To avoid gaps in WCAG conformance and unintended accessibility risks, it’s important to understand these oversights.

Myth: Accessibility overlays will keep my website up to par

An AI plugin or “accessibility script” cannot guarantee 100% WCAG conformance. In many cases, overlays interfere with assistive technologies such as screen readers and often fail to address underlying accessibility issues in the source code.

Myth: AI can automate all accessibility testing

Automated scans are effective at identifying specific technical issues, but they cannot evaluate usability or replicate human experiences or emotions. A combination of AI or automated tools and expert testing is essential for meaningful accessibility improvements.

Myth: AI-generated alt text is good enough for screen readers

While AI accessibility tools can save hours on manual tasks, such as identifying and writing meaningful alt text, they can miss important context. For example, text reading: “man standing on stage” isn’t the same as “Sundar Pichai speaking at the 2025 Google Cloud Next conference.”

Illustration of three diverse people at a table with laptops, including a person in a wheelchair, collaborating and discussing.

Why Human Expertise Still Matters

AI is effective at identifying two-thirds of WCAG violations, making human verification essential. While automated tools excel at objective tasks (e.g., “summarize this paragraph” or read the text on this page), they struggle with nuance, context, and intent. That’s where human review becomes necessary.

Only human reviewers can assess how accessible a page actually feels in use. They can determine whether an image conveys meaningful information, whether content hierarchy makes sense when read aloud by a screen reader, or whether an interface becomes overwhelming once interaction begins.

Automation scales quickly and can help catch many technical issues, but many of the types of barriers that affect people with disabilities can be identified by human expertise. Without that human review, organizations remain exposed to real legal risk — because it’s often those subtle, context-based issues that lead to complaints and lawsuits.

Digital accessibility is not about passing automated checks; it’s about creating experiences that are usable, intuitive, and inclusive. That level of quality requires human expertise working alongside AI — not automation alone.

AI Accessibility Tools as Part of a Broader Strategy

The best web accessibility strategy combines both approaches: AI to provide speed, scalability, and automation, and human experts to perform hands-on audits and deep dives into what’s truly accessible and usable for users.

If you plan to use AI for accessibility, integrate it early in the design process rather than adding it as an afterthought. AI-powered tools can help catch common issues, but they don’t fix the underlying problem. Plus, they can inadvertently introduce new errors or interfere with assistive technology. That’s why human review and testing should be part of any AI workflow, validating results and ensuring recommendations make sense in context.

Accessibility Doesn’t Stop with a Scan

AI has expanded what accessibility teams can do — helping them move faster, monitor more consistently, and manage complex sites at scale. But accessibility isn’t something you install and walk away from. It requires ongoing attention, informed judgment, and accountability as content changes and user needs evolve.

That’s why the most successful accessibility efforts focus on outcomes, not just outputs — ensuring real people can actually use the experience, not just pass a scan.