AI Won't Solve Accessibility, But It Definitely Can Help

Have you noticed how AI tools for accessibility are becoming increasingly popular? It’s like they’re popping up everywhere. Viral posts, LinkedIn engagement, or just plain flooding the market, they're everywhere.

And some of these tools are genuinely impressive! Take automated alt text generation, for example. It can be incredibly helpful for teams managing hundreds or thousands of images.

But here's where it gets interesting.
The quality really depends on how you use it.

Let us share a real example. When AI encounters the Access Time logo, it might describe it as "a blue background with white text reading Access Time in bold letters." Technically accurate, sure, but for a company logo, "Access Time" would be much more appropriate and concise.

This isn't a flaw in the AI because it's doing exactly what it's designed to do, describe what it sees in detail. The key is understanding when that level of detail helps users and when it creates unnecessary cognitive load. Sometimes you want rich descriptions, sometimes you need focused brevity.

This is where human guidance becomes essential. AI can provide an excellent starting point, especially for teams with large content libraries, but it works best when combined with human judgment about context, purpose, and user needs.

Understanding What AI Does Well (And What It Doesn't)

Let's start with the basics and build our understanding from there. AI excels at pattern recognition, automation of repetitive tasks, and processing large amounts of data quickly. In accessibility terms, this translates to some genuinely useful capabilities.

AI can scan your website and identify images without alt text, flag color contrast issues, and detect missing form labels. It's excellent at finding the technical basics, or what the industry likes to say, the low-hanging fruit that creates obvious barriers for users with disabilities. Think of AI as a really thorough, tireless intern who never gets bored checking for common problems.

Where AI starts to struggle is with context, nuance, and understanding human needs. That team photo we mentioned earlier? A human might describe it as "The development team celebrating the launch of their new mobile app, smiling and holding champagne glasses in the company break room." The AI just saw shapes and objects.

This difference matters because accessibility is beyond the technical compliance. It should enables us to create meaningful, inclusive experiences for real people with diverse needs and contexts.

The Power of AI as an Accessibility Assistant

Despite its limitations, AI can be incredibly powerful when used as a tool rather than a solution. Let me share some examples of where AI genuinely shines in supporting accessibility efforts.

Automated testing and monitoring works well as part of a comprehensive accessibility strategy. AI tools can handle the systematic scanning of websites, identifying potential issues and tracking changes over time, while human experts focus on interpreting results and making informed decisions about priorities and solutions.

Content optimization suggestions represent another area where AI adds real value. AI can analyze your content and suggest improvements for readability, identify jargon that might confuse users with cognitive disabilities, and even recommend simpler sentence structures. It's like having a writing coach who's specifically trained in accessibility best practices.

Pattern recognition across large datasets helps organizations understand accessibility issues at scale. AI can analyze thousands of user sessions to identify common points where users with disabilities get stuck, spot patterns in customer support requests that indicate accessibility problems, and even predict which parts of your website are most likely to have accessibility issues based on similar sites.

The key insight here is that AI works best when it augments human expertise rather than replacing it. It can handle the routine, systematic work that would take humans forever, freeing up people to focus on the creative, contextual, and empathetic aspects of accessibility.

Where Human Insight Remains Essential

Let's be clear about what AI can't do, and why that matters for creating truly accessible experiences.

Understanding user intent and context requires human empathy and experience that AI simply doesn't have. When someone with a disability visits your website, they're not just completing tasks, they're trying to accomplish meaningful goals in their life. Understanding those goals, the context around them, and the emotional journey users are on requires human insight.

Cultural and community sensitivity is another area where human judgment is irreplaceable. The disability community has its own culture, language, and sensitivities. AI might suggest changing "person with a disability" to "disabled person" or vice versa without understanding the nuanced preferences within different disability communities.

Creative problem-solving for complex accessibility challenges still requires human creativity. When standard solutions don't work, when you're dealing with innovative interfaces, or when you're trying to make emerging technologies accessible, you need human designers and developers who can think creatively about novel solutions.

User testing and feedback interpretation is fundamentally about human connection. AI can't sit with a user who's frustrated with your interface, understand their emotional response, or ask the follow-up questions that reveal deeper insights about their experience.

Finding the Sweet Spot: AI as a Force Multiplier

The most successful accessibility implementations I've seen use AI as a force multiplier for human expertise, not a replacement for it.

Here's what this looks like in practice.

Smart teams use AI to handle the repetitive, systematic work like scanning for technical issues, monitoring for regressions, and flagging obvious problems. This frees up their human experts to focus on the harder challenges: like understanding user needs, designing inclusive experiences, and solving complex usability problems.

And we're serious about taking a coffee break after solving a hard challenges!

AI becomes particularly powerful when it's trained on good human decisions. For example, if your team has spent time writing high-quality alt text for your industry, you can train AI tools to suggest alt text that matches your style and context. The AI learns from human expertise rather than replacing it.

The best AI accessibility tools also make it easy for humans to review and override AI decisions. They present suggestions rather than making automatic changes, and they provide context to help humans make informed decisions about what to keep, modify, or reject.

Most importantly, remember that AI tools are only as good as the people using them. Teams with strong accessibility expertise will get much more value from AI tools than teams that are just starting their accessibility journey.

AI can accelerate good practices, but it can't create expertise from scratch.

The Future is Collaborative

The future of AI in accessibility is about creating more powerful collaborations between human insight and machine efficiency. The best outcomes happen when AI handles what it does well (systematic analysis, pattern recognition, routine tasks) while humans focus on what they do best (empathy, creativity, contextual understanding).

This collaborative approach is already producing some remarkable results. Teams are catching more accessibility issues faster, creating more consistent experiences across large websites, and freeing up time to focus on innovative inclusive design solutions.

Taking Your Next Step Forward

If you’re curious about what we’ve been exploring with AI, give Access Lens a try while it’s still in beta. Behind the scenes, we’ve been working on how AI can speed up accessibility reporting that making scans faster and more accurate, while still keeping the human touch where it matters most.

We’re careful about finding that sweet spot. Knowing when AI can add real efficiency, and when only human judgment can truly capture the nuance of accessibility.

AI works based on data. And the catch is, there just aren’t that many accessible websites out there to begin with. That means the baseline data AI would need to truly “understand” what an accessible website looks like is still thin.

So while AI can be a great helper in many areas, when it comes to accessibility it can’t yet vibe-code its way into compliance. Accessibility still requires human judgment, design sensibility, and lived experience to get it right.

The goal isn't to automate accessibility, we can aim better to create accessible experiences more efficiently and effectively.

AI can be a powerful ally in that mission, as long as we remember that true accessibility is fundamentally about understanding and serving human needs.

Ready to explore how AI and human expertise can work together in your accessibility journey? Visit our contact page to learn more about AccessTime consultancy services, or try Access Lens to discover where technology might best support your current efforts.