Automated Testing of Web Accessibility: Leveraging AI and Machine Learning for Enhanced Compliance and User Experience

Antony Ronald Reagan Panguraj

doi:10.5281/zenodo.14715756

Automated Testing of Web Accessibility: Leveraging AI and Machine Learning for Enhanced Compliance and User Experience

Author(s)	Antony Ronald Reagan Panguraj
Country	United States
Abstract	Website accessibility is a very important component of making digital environments usable to all citizens without discriminating against their disability status. While websites are grown to be more and more sophisticated and diversified, utilizing the manual technique for checking accessibility compliance is practically unattainable. Computer-aided testing of Web accessibility seems to hold the key to these challenges. Forcing a web content evaluation to retain compliance to standard web accessibility guidelines such as the WCAG is made simpler and efficient by applying AI and ML techniques in development. The use of AI technologies can help reveal complications with Web accessibility more effectively and reliably than by a conventional approach, which improves both compliance and user satisfaction. The current paper discusses the deployment of AI and ML in automated web accessibility testing, advantages, and disadvantages, and possibilities of transforming organizational perspective on web accessibility. Not only does the implementation of these technologies reduce time in compliance but also in helping to improve user experience for disabled with better digital accessibility. Applying and advancing these technologies like AI and ML in different firms, means will help enhance detection skills and minimize human interference, further enhance infringement of different barriers to accessibility. In the end, the integration of the use of AI in integrating ML with the focus on web accessibility will greatly improve the experience of every user with different abilities or disabilities during their interaction with the global web.
Keywords	Automated Testing, Web Accessibility, Artificial Intelligence, Machine Learning, Compliance, User Experience.
Field	Engineering
Published In	Volume 11, Issue 2, July-December 2020
Published On	2020-08-04
Cite This	Automated Testing of Web Accessibility: Leveraging AI and Machine Learning for Enhanced Compliance and User Experience - Antony Ronald Reagan Panguraj - IJAIDR Volume 11, Issue 2, July-December 2020. DOI 10.5281/zenodo.14715756
DOI	https://doi.org/10.5281/zenodo.14715756
Short DOI	https://doi.org/g82qsr

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Automated Testing of Web Accessibility: Leveraging AI and Machine Learning for Enhanced Compliance and User Experience

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