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Intellectual disability (ID), characterised by significant limitations in both intellectual functioning and adaptive behaviour, constitutes one of the most prevalent and consequential neurodevelopmental conditions worldwide. In India, the burden of intellectual disability is substantial, with millions of individuals affected, yet services remain markedly inadequate. Artificial intelligence (AI), encompassing machine learning, deep learning, natural language processing, and computer vision, has in recent years emerged as a transformative force in healthcare and disability services, offering unprecedented potential to address longstanding gaps in detection, assessment, intervention, and education. This comprehensive review systematically examines the advances and challenges associated with the application of AI technologies in the domain of intellectual disability, with a particular focus on the Indian context. A systematic search of major academic databases was conducted to identify relevant literature published between January 2005 and January 2026, with seminal earlier studies also included on methodological grounds. The review traces the evolution of AI-based screening and diagnostic tools, machine learning-driven adaptive assessment systems, augmentative and alternative communication technologies, assistive robotics, and personalised learning platforms. It further analyses the Indian policy and regulatory landscape, indigenous research contributions, and the distinctive socio-technical challenges—including data scarcity, the digital divide, linguistic heterogeneity, ethical considerations, and professional capacity deficits—that complicate the translation of global AI advances into workable solutions for Indian populations. Findings revealed that AI represents a genuinely transformative set of technologies for intellectual disability services, with demonstrated potential across the domains of early screening and diagnosis, cognitive assessment, communication support, assistive technology, and personalised education. In India, where specialised services remain severely limited and human specialist capacity is critically constrained, AI offers possibilities for extending the reach, improving the quality, and reducing the cost of essential support. However, the translation of these advances into the Indian context is constrained by major challenges including scarcity of representative datasets, digital divide and infrastructure limitations, linguistic and cultural diversity, and unresolved ethical and regulatory concerns. Recent trends, including federated learning, explainable AI, and multimodal systems, are also discussed alongside future directions. The review concludes that whilst AI holds considerable promise for transforming intellectual disability services in India, realising this promise demands concerted investment in culturally adapted datasets, equitable digital infrastructure, robust ethical governance, and interdisciplinary collaboration.
Published in: Journal of Education Society and Behavioural Science
Volume 39, Issue 2, pp. 121-136