This qualitative paper examines how cultural and social dimensions shape the integration of Artificial Intelligence (AI) technologies in inclusive classrooms. Employing a case-study methodology, the study explores experiences across different socio-cultural settings and draws insights for educators, policymakers, and technologists. Three illustrative case studies represent diverse educational contexts: (1) an urban public school serving multilingual learners, (2) a rural community school with limited digital infrastructure, and (3) a private inclusive institution emphasizing neurodiversity. Through semi- structured interviews, observations, and thematic analysis, the study investigates the interplay of cultural values, social norms, digital equity, and pedagogical design in influencing AI’s effectiveness. Key findings highlight that cultural attitudes toward technology, language diversity, equity in access, and teacher beliefs critically mediate AI’s potential in inclusive learning. For instance, failure to localize AI tools linguistically and culturally can marginalize learners from non–mainstream backgrounds, while teacher readiness and community trust significantly affect adoption. The discussion addresses both affordances (personalized learning, timely support, differentiation) and pitfalls (digital bias, cultural misalignment, unequal access). The conclusion underscores the importance of culturally responsive AI design, inclusive policy frameworks, teacher preparation, and community participation. This research contributes to a growing understanding of how AI can be leveraged ethically and equitably within inclusive education, advocating for culturally informed implementation to ensure AI advances educational inclusion globally.
Megha Ram (Sat,) studied this question.