Verbit Launches AI Audio Description for ADA Title II Compliance

Verbit has released an AI audio description product aimed at organizations racing to scale video accessibility before ADA Title II compliance deadlines arrive, the company announced in a release picked up by The Star Press.

The release positions the tool against a specific regulatory clock. In April 2024, the U.S. Department of Justice finalized its rule under Title II of the Americans with Disabilities Act, requiring state and local government entities — including public universities, municipalities and school districts — to bring their web content and mobile offerings into conformance with WCAG 2.1 Level AA. Large public entities face the earliest deadlines, with compliance expected by April 2026 and smaller entities following in 2027.

Audio description sits at the center of that obligation. WCAG 2.1 Success Criterion 1.2.3 (Audio Description or Media Alternative, Level A) and 1.2.5 (Audio Description, Level AA) require narrated descriptions of essential visual information for prerecorded video. For institutions holding thousands of lecture recordings, archival footage and public-meeting broadcasts, human-produced description has historically been too slow and too expensive to apply across a full catalog.

What does the product actually change?

Verbit's release frames the workflow shift in concrete terms. Instead of sending video files to human describers and waiting days for turnaround, organizations can generate descriptions through an automated pipeline and apply them across entire libraries at once. The company positions this as the difference between remediating content one video at a time and meeting a fixed statutory deadline.

The company already sells transcription and captioning into higher education and legal markets, where it serves institutions processing high volumes of recorded media. AI audio description extends that portfolio to the one accessibility artifact its existing tooling did not produce: a secondary audio track that narrates on-screen action, text and scene changes for blind and low-vision viewers.

For procurement and accessibility offices, the appeal is operational. A single lecture capture system at a mid-sized university can accumulate tens of thousands of hours of video per year. Human description typically runs at several times the duration of the source material to produce. Automated generation compresses that bottleneck, though institutions will still need to validate output quality against WCAG conformance requirements — automation changes the cost curve, not the standard itself.

Why the timing matters

The DOJ rule gives public entities a compliance path but little slack. Content published after the deadline must conform immediately, and older content falls under the same requirement unless it qualifies for a limited exception. Vendors serving this market are racing to package remediation as a product rather than a services engagement.

Verbit is betting that audio description follows the same adoption curve as automated captioning, which moved from a specialist service to baseline infrastructure across education and enterprise video over the past decade. If that pattern holds, expect AI description to become a checkbox feature of lecture-capture and video platforms within the current procurement cycle — with competition turning on accuracy, review tooling and audit trails rather than availability.