Accessibility in the Age of Generative AI Web Based Builders: Evaluating Web Design Tools for Inclusive Practices

Abstract

As generative AI (GenAI) becomes more widely used in web content creation, assessing the accessibility of AI-generated websites is increasingly important for ensuring inclusive digital experiences. This study evaluates the accessibility performance of two GenAI-based website builders, Wix and Framer, using the Web Content Accessibility Guidelines (WCAG) as a benchmark. Accessibility was assessed using a combination of automated testing with the WAVE evaluation tool and manual inspection by two reviewers. Common issues included missing or vague alternative text, improper heading structures, inaccessible keyboard navigation, and inconsistently labeled interactive elements. While both platforms demonstrated some progress toward accessible design, neither consistently produced content that fully met WCAG 2.1 requirements. However, Wix-generated sites contained fewer accessibility errors and more consistent semantic HTML structure than those produced by Framer. Notably, Wix outperformed Framer according to the manual evaluations, indicating that platform design has a greater impact on accessibility outcomes than user prompts alone. These findings highlight ongoing gaps in current AI-driven website generation tools and underscore the need for better training models, stronger semantic understanding, and real-time accessibility guidance during content creation.

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