Smart classrooms, smarter futures: how AI is revolutionizing education for people with disabilities

Purpose This opinion paper aims to examine how artificial intelligence (AI), including generative AI, is reshaping education for people with disabilities. Traditional classroom environments have long created barriers to equitable learning, but emerging AI-driven tools now offer adaptive, personalized support that enhances accessibility, engagement and independence. The paper explores how AI functions as a socio-technical infrastructure that reconfigures disability and ability in educational contexts. By synthesizing evidence across AI in education, assistive technologies and inclusive pedagogy, it highlights three interrelated themes – personalization, barrier reduction and democratized access – to illustrate how AI can enable more inclusive and responsive learning environments. Design/methodology/approach As an opinion piece, this paper synthesizes existing literature to examine current and emerging uses of AI in inclusive education. It integrates research on intelligent tutoring systems, educational data mining, universal design for learning and AI-powered assistive technologies. The approach emphasizes conceptual analysis rather than empirical evaluation, drawing on illustrative examples to demonstrate how personalization, generative AI content creation, real-time accessibility features and cloud-based tools support diverse learners. The synthesis is organized around themes that highlight both opportunities and systemic considerations involved in integrating AI into disability-inclusive educational practice. Findings The synthesis indicates that AI has substantial potential to reduce long-standing educational barriers by enabling real-time adaptation to individual needs, generating accessible learning materials and embedding assistive features into mainstream technologies. Intelligent tutoring systems, speech-to-text tools, generative AI applications and cloud-based platforms collectively enhance personalization, accessibility and learner engagement. However, the review also identifies critical challenges, including privacy concerns, algorithmic bias affecting disabled learners, limited educator preparedness and questions around governance and equity. These issues must be addressed to ensure that AI-driven innovations advance inclusive rather than exclusionary educational practices. Research limitations/implications The findings carry important implications for practice, policy and research. Educators can use AI to identify barriers, personalize support and scaffold learners' use of assistive tools, but they require targeted professional development. Institutions and policymakers must prioritize accessible procurement, transparent governance and infrastructure that protects disability-related data. Future research should evaluate not only learning outcomes but also participation, autonomy and equity for diverse disabled learners. Co-design with disabled students and educators will be essential for shaping responsible and inclusive AI deployment. Together, these implications highlight the need for a coordinated approach to building accessible, AI-enabled learning environments. Originality/value This paper offers a novel conceptual framing by positioning AI, particularly generative AI, as a socio-technical infrastructure that reshapes how disability and ability are configured in educational settings. It synthesizes current evidence through three integrative themes: personalization, barrier reduction and democratized access. The paper foregrounds disability-specific considerations often absent from mainstream AI-in-education debates and critically examines both opportunities and risks. By articulating clear implications for educators, institutions and policymakers, it provides a timely and distinctive contribution to ongoing discussions about inclusive AI adoption in education.