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This research examines the transformative role of AI-powered screen readers, voice assistants, and Natural Language Processing (NLP) interfaces in promoting inclusive education for students with visual, physical, and cognitive disabilities. The novelty of this study lies in its integrated, multi-modal exploration of assistive AI technologies across a variety of disabilities and use cases, including original case analyses that demonstrate real-world application and impact. Results reveal that AI-driven interfaces significantly improve autonomy, academic engagement, and content accessibility. Additionally, the paper highlights limitations related to accuracy, infrastructure needs, educator readiness, and ethical concerns such as data privacy and algorithmic bias. To address these challenges, the study proposes policy recommendations and practical strategies for equitable and responsible AI adoption in education, including targeted educator training, funding for inclusive infrastructure, and development of ethical and technical standards. By bridging theoretical analysis with applied insights, this paper offers a valuable contribution to the discourse on AI-driven inclusivity and serves as a foundation for future empirical validations and technical innovation.
Kooli et al. (Thu,) studied this question.