Intelligent Accessibility Middleware Using AI for Dynamic Inclusive User Interfaces

Abstract: Artificial Intelligence (AI) is increasingly being integrated into accessibility systems to support adaptive and inclusive user interfaces for users with diverse accessibility needs. This paper reviews recent research on AI-driven accessibility middleware and adaptive interface technologies published between 2015 and 2026. The study examines the use of machine learning, natural language processing, computer vision, reinforcement learning, and generative AI in improving digital accessibility and interface personalization. Existing approaches related to browser-based accessibility tools, automated remediation systems, adaptive user interfaces, and behavioral analytics are comparatively analyzed. The paper also discusses the significance of accessibility standards such as WCAG, WAI-ARIA, and ADA in the development of intelligent accessibility solutions. Current research trends, evaluation methods, implementation challenges, and ethical concerns associated with AI-based accessibility systems are identified. The review indicates that AI technologies have improved automation and personalization capabilities in accessibility support; however, challenges related to cognitive accessibility, transparency, fairness, and real-time adaptation continue to require further research. The paper concludes by outlining future directions for the development of reliable, user-centered, and standards-compliant accessibility middleware systems.

Keywords: Accessibility, adaptive user interfaces, artificial intelligence, assistive technology, middleware systems, inclusive design, natural language processing, computer vision, WCAG.