Adience: AudioEye Outperforms Competitors in Detecting WCAG Accessibility Issues

Adience report finds major gaps in automated accessibility detection

TUCSON, Ariz. — A new B2B study from Adience finds wide variation in what automated accessibility tools detect, and positions AudioEye’s platform as a clear outlier in coverage. Adience evaluates five leading automated tools by scanning, measuring and validating issues mapped to WCAG Levels A, AA and AAA, and reports that AudioEye’s automated technology is detecting between 89% and 253% more valid Web Content Accessibility Guidelines (WCAG) issues than competing products across the sample set.

The report details stark differences at commonly referenced Level AA, where several tools return no findings on multiple sites while AudioEye consistently identifies issues at Levels A, AA and AAA across every tested website. At Level A, AudioEye finds 509% more valid accessibility issues than the lowest-performing tool and 68% more than the next closest; at Level AA the firm finds 380% more valid issues than the lowest-performing tool that returned results and 41% more than the next-closest tool. Adience’s Managing Director Chris Wells emphasizes that all tools are tested under identical conditions, underscoring the variation is not caused by methodology differences.

AudioEye’s CEO David Moradi frames the results in the context of rapid growth in digital content and AI tooling. He says the number of websites and apps increases 40–60% year over year as new coding tools multiply, and some large language models rely on automated detection methods with substantially lower detection rates. Moradi adds that this detection gap is driving a record number of digital accessibility lawsuits and that AudioEye leverages years of data across hundreds of thousands of sites and billions of visits, combining agentic tooling with human testing, custom fixes and continuous monitoring to scale detection and improve visibility into compliance gaps.

Testing methodology and limitations

Adience validates automated findings to separate true positives from noise, and notes that even the best automated scanners cannot fully replicate contextual human judgement. The firm concludes automation is the foundation for protection but that human evaluation remains essential to resolve complex, contextual barriers.

Regulatory and market implications

The report highlights heightened compliance risk for organizations relying solely on weaker automated detectors and signals demand for hybrid approaches that pair broad automated coverage with targeted human review, remediation and ongoing monitoring. AudioEye positions its mix of data-driven automation and human testing as a direct response to that market need.