<![CDATA[Blind and low-vision users continue to face significant challenges when interacting with modern dynamic and visually complex web applications. Traditional screen readers often fall short due to the rapid changes in content, single-page applications, and intricate layouts. This paper introduces Screen Reader AI, a novel conversational web accessibility assistant implemented as a browser extension, designed to provide adaptive and context-rich support for non-visual navigation. Unlike conventional screen readers, Screen Reader AI constructs and continuously updates a live semantic scene graph by integrating the Document Object Model (DOM) and the Accessibility Object Model (AOM). Leveraging multimodal vision-language reasoning powered by GPT-4o, it generates detailed visual interpretations, detects interface structures and interactive elements, and conveys this information through natural, conversational dialogue. This approach allows users to request clarifications, discover relationships between interface components, and receive proactive notifications about dynamic content updates. The system features a modular architecture that ensures compatibility with evolving AI models and web standards, while maintaining an intuitive user interface. Core capabilities include adaptive task guidance, an interactive dashboard with contextual summaries, nested menus, live feeds, and predictive navigation assistance across diverse content types such as forms and multimedia. An evaluation framework outlines expected improvements in user experience, including reduced task completion times, enhanced understanding of page layouts, and greater autonomy during browsing. Initial findings suggest that conversational interaction can decrease cognitive load by reducing repetitive commands and streamlining information retrieval. Screen Reader AI represents a paradigm shift in digital accessibility by embedding adaptive intelligence into assistive technology, empowering independence and inclusivity while making accessibility an integral part of web innovation.]]>
