Using AI for Digital Accessibility

This three-part series explores how public-sector teams can use AI-assisted tools to identify, address, and monitor digital accessibility barriers across government websites, applications, documents, and services.

As governments expand digital service delivery, accessibility is both a legal requirement and a core public responsibility. Conventional automated testing identifies only a portion of the accessibility issues people encounter, leaving many barriers to be found through manual testing by accessibility professionals and people who use assistive technologies. AI-powered tools may expand what can be detected automatically, but questions remain about their accuracy, consistency, potential bias, and ability to interpret context.

The series follows the accessibility lifecycle from identifying barriers to remediating them and maintaining conformance over time. Participants will consider where AI-assisted tools may add value, where human judgment remains essential, and how agencies can evaluate vendor claims. Because testing, remediation, and monitoring tools increasingly overlap, the series will also examine how responsibilities and safeguards can remain clear as vendors expand across multiple parts of the accessibility process.

Series Learning Goals

By the end of the series, participants will be able to:

• Identify accessibility barriers: Explore how AI-assisted tools can support accessibility testing across government websites, applications, documents, and digital services, while recognizing their limitations.

• Support remediation: Assess how AI-assisted tools can help address accessibility issues and identify where human expertise and manual review remain essential.

• Monitor accessibility: Explore practical approaches to using AI-assisted tools to monitor accessibility, maintain conformance, and identify emerging barriers over time.

• Evaluate tools responsibly: Assess vendor claims, tool accuracy, and potential risks, and identify appropriate safeguards to ensure that automation complements human judgment, lived experience, and inclusive design.