From Scans to Descriptions: How AI is Shaping Accessibility

As a blog writer focused on accessibility topics such as standards, laws, tools, best practices, and the latest trends and developments, I spend roughly 40 – 50% of my 40-hour week conducting research. That means reading reports and specs, cross-referencing sources, combing through other blog posts, and scrolling LinkedIn for insights, updates, and signals about what’s new in accessibility testing, remediation, and education.

Every article, report, and blog I research has the potential to take me down a rabbit hole. And these days, those rabbit holes can be found around two topics:

AI-powered accessibility testing tools and AI-generated ALT text

They’re getting a lot of attention and a lot of words devoted to them. And for good reason.

Trend #1: AI-Powered Accessibility Testing Tools

AI-powered accessibility testing tools are gaining significant traction, and their pitch is very compelling: they promise faster scanning, broader issue detection, reduced reliance on manual testing, and the ability to deliver more accessible digital experiences without slowing development timelines.

The Upside

AI-powered testing tools help ensure that websites, apps, or digital content meet higher accessibility standards than they would otherwise. They catch common issues, flag problems, and provide a starting point for accessible content built on a more solid foundation. They efficiently scan large websites, identify common WCAG violations, spot patterns humans might miss, and surface problems earlier in the design and development cycle. For teams with limited accessibility maturity or limited resources, this represents a substantial advantage. Automation can also allow accessibility specialists to shift their focus toward higher-level concerns, such as usability, user journeys, and real-world assistive technology behavior.

The Downside

Despite these advances, AI tools cannot experience a website or a PDF in the same way a human user does. They can't determine whether a workflow is intuitive, whether the instructions are clear, or whether a screen reader user might become disoriented during a task. There's also an increasing risk of overreliance. A clean automated report can be misinterpreted as full accessibility compliance, even when significant barriers persist. While automation is a powerful asset, it is not a substitute for human testing. It’s a co-pilot, not the pilot.

Trend #2: AI-Generated ALT text

AI-generated ALT text has rapidly become the go-to solution. Companies like Microsoft and Google offer AI-generated ALT text directly inside all of their tools. Now, folks can upload an image, get an ALT text, and move on with their day. For organizations that manage thousands of images, this is likely the ideal solution.

The Upside

AI can quickly add baseline descriptions, identify objects, and help teams make progress in bringing their images into conformance with SC 1.1.1: Non-text Content (Level A), where manual writing would be exhaustive and expensive. It’s also a helpful starting point in reducing the sheer volume of backlog many teams face.

The Downside

Some people may say that AI-generated ALT text is better than having no ALT text at all. I have to disagree. Context is everything, and AI doesn’t always get it right. It can misidentify people, miss the point of an image, or describe details that are irrelevant (or worse, misleading). ALT text isn’t about what an image is; it’s about what an image means in context. When AI-generated descriptions go straight to production without review, the result can be confusing, inaccurate, or unintentionally harmful.

Looking Ahead

Neither of these trends will disappear when the next big thing arrives. AI is the next big thing and is clearly becoming a permanent part of the accessibility toolbox. The real question isn’t if we use it, but how we use it responsibly. The most sustainable approach for that is to practice balance. Use AI to scale and accelerate, but keep humans in the loop for judgment, nuance, and lived experience. Let automation handle the heavy lifting, and let people handle the meaning.

For now, we need to continue watching how AI tools evolve, how teams adapt, what guardrails look like and whether they work, and how the accessibility community continues to push for solutions that prioritize real users over shiny shortcuts.

I expect the discussion around AI and accessibility to get louder and to take center stage. And I'll be researching and writing about that as well. 🤖

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A human author creates the DubBlog posts. The AI tools Gemini and ChatGPT are sometimes used to brainstorm subject ideas, generate blog post outlines, and rephrase certain portions of the content. Our marketing team carefully reviews all final drafts for accuracy and authenticity. The opinions and perspectives expressed remain the sole responsibility of the human author.