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Article

Artificial Intelligence in Web Accessibility: Towards a Theory of LLM-Assisted Remediation for Visual Disabilities

by
Guillermo Vera-Amaro
1,
Rodolfo Vera-Amaro
2,*,
Miguel Felix Mata-Rivera
2,* and
José Rafael Rojano-Cáceres
1,*
1
Facultad de Estadística e Informática, Universidad Veracruzana, Xalapa-Enríquez 91020, Veracruz, Mexico
2
Sección de Estudios de Posgrado e Investigación (SEPI)–Unidad Profesional Interdisciplinaria de Ingeniería y Tecnologías Avanzadas (UPIITA), Instituto Politécnico Nacional, Mexico City 07740, Mexico
*
Authors to whom correspondence should be addressed.
Technologies 2026, 14(5), 287; https://doi.org/10.3390/technologies14050287
Submission received: 13 April 2026 / Revised: 2 May 2026 / Accepted: 3 May 2026 / Published: 8 May 2026
(This article belongs to the Section Information and Communication Technologies)
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Abstract

Recent research on web accessibility has explored the use of artificial intelligence (AI), particularly large language models (LLMs), to support accessibility remediation. However, the field lacks a theoretical perspective explaining how LLMs can be integrated to systematically support this process. This study proposes a theory of LLM-assisted web accessibility remediation. It is built through the integration of qualitative evidence, prior literature, accessibility standards, and empirical studies on LLM-based remediation. The resulting theory provides an explanatory framework describing how LLMs can assist web accessibility remediation through iterative cycles of analysis, transformation, and validation, and identifies key factors including prompting strategies, input representations, and validation mechanisms. This work provides a conceptual foundation for understanding and systematically studying LLM-assisted accessibility remediation, and supports both research and practice by guiding future studies and informing the design of models, methods, tools, and accessibility engineering practices.
Keywords: software engineering; process theory; web accessibility; thematic analysis; large language models; grounded theory software engineering; process theory; web accessibility; thematic analysis; large language models; grounded theory

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MDPI and ACS Style

Vera-Amaro, G.; Vera-Amaro, R.; Mata-Rivera, M.F.; Rojano-Cáceres, J.R. Artificial Intelligence in Web Accessibility: Towards a Theory of LLM-Assisted Remediation for Visual Disabilities. Technologies 2026, 14, 287. https://doi.org/10.3390/technologies14050287

AMA Style

Vera-Amaro G, Vera-Amaro R, Mata-Rivera MF, Rojano-Cáceres JR. Artificial Intelligence in Web Accessibility: Towards a Theory of LLM-Assisted Remediation for Visual Disabilities. Technologies. 2026; 14(5):287. https://doi.org/10.3390/technologies14050287

Chicago/Turabian Style

Vera-Amaro, Guillermo, Rodolfo Vera-Amaro, Miguel Felix Mata-Rivera, and José Rafael Rojano-Cáceres. 2026. "Artificial Intelligence in Web Accessibility: Towards a Theory of LLM-Assisted Remediation for Visual Disabilities" Technologies 14, no. 5: 287. https://doi.org/10.3390/technologies14050287

APA Style

Vera-Amaro, G., Vera-Amaro, R., Mata-Rivera, M. F., & Rojano-Cáceres, J. R. (2026). Artificial Intelligence in Web Accessibility: Towards a Theory of LLM-Assisted Remediation for Visual Disabilities. Technologies, 14(5), 287. https://doi.org/10.3390/technologies14050287

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