The Promise of AI Accessibility Is Letting Institutions Skirt Accountability

So I was reading about a new tool the other day that was said to be an AI-powered audio learning tool promising personalized education for blind students. I won’t name it. It‘s slick, voice-driven, and uses AI to “adapt” to a learner’s pace, style, and needs. You may have heard about similar AI tools coming to market. Sounds impressive, right?

It is. Impressively misdirected, that is.

This wasn’t the first AI tool focused on accessibility that I’ve seen this week. It’s one of many that are promising to revolutionize accessibility.

Let’s be clear—this isn’t a revolution. It’s a workaround dressed in buzzwords. What these tools actually reveal is not how far we’ve come, but how far we’re still willing to go to get around the root issues.

For 25+ years, accessibility advocates have asked, begged, litigated, and lobbied for educational systems, materials, and platforms to be inherently accessible. That means designing for everyone from the start, not bolting on a fix later.

But here we are again, Applauding a tool that retrofits learning for blind students because the core systems still won’t—or don’t want to??

Let’s unpack what’s really happening here.

AI Is the New Excuse for Everything

First, the AI hype is a convenient distraction. It’s like digital snake oil – “Don’t worry that the textbook isn’t accessible, we’ve got an AI that’ll read it to you and quiz you at your level!” Never mind that universal design principles exist. Never mind that standards for accessible educational materials (WCAG, EPUB accessibility, DAISY) are already out there collecting dust while institutions continue to adopt inaccessible tools year after year.

It saddens me deeply as one of those advocates that has begged for so many years.

Personalized ≠ Inclusive

Personalization is not the same as inclusion. Saying “We’ll customize learning for blind students” assumes that blind students are the edge case—a deviation from the norm that needs special handling. But blindness isn’t an edge case. Neither is dyslexia. Neither is ADHD. People are people, and designing for the full range of human experiences shouldn’t require a separate platform.

But when you’re building an AI product addressing accessibility, you’re not solving inclusion. You’re solving for the fact that the mainstream remains exclusionary. You’re making a sidecar for the same broken motorcycle and hoping the ride feels smoother.

This Is Not the Future—It’s a Cop-Out

Look, if these AI tools help someone learn who would otherwise be left out, that’s a win. I’m not knocking the tool itself. I’m knocking the fact that we still need tools like this in the first place.

A truly inclusive future wouldn’t require a blind student to switch platforms, formats, or apps just to engage with the same material as their peers. It wouldn’t glorify these solutions. It would demand systems that are built access-first—textbooks, LMS platforms, courseware, testing tools, all of it.

Instead, we get tech band-aids and a PR spin about “next-generation learning.”

Accessibility as an Afterthought (Again)

In the end, these AI tools aren’t a solution to the accessibility gap in education—they are pushing disabled students into side channels, then celebrating the ingenuity of these tools to counter their own creations.

We shouldn’t be wowed by how good these tools are. We should be angry that we still need them at all.