The Integration of Artificial Intelligence in Contemporary Education: A Comparative Analysis of India and Global Practices
Keywords:
artificial intelligence in education, adaptive learning systems, digital equity, India education policy, personalized learning, teacher professional development, AI ethics, comparative educationAbstract
The integration of artificial intelligence into educational systems worldwide represents one of the most consequential shifts in contemporary pedagogy, yet the conditions under which this integration succeeds or stalls vary profoundly by national context. This paper presents a systematic comparative review of AI adoption in education across six countries — India, the United States, China, Finland, South Korea, and the United Kingdom — with particular emphasis on India's developmental trajectory relative to global leaders. Drawing on a systematic literature review of peer-reviewed studies published between 2019 and 2024, supplemented by government policy documents and international educational indices, the study examines five comparative dimensions: AI infrastructure and digital accessibility, policy support and public investment, teacher training and professional development, student learning outcomes, and ethical challenges including algorithmic bias and the digital divide. Findings reveal that while India has articulated strong policy intent through the National Education Policy 2020 and platforms such as DIKSHA and SWAYAM, substantial gaps in rural infrastructure, teacher preparation, and research-practice translation continue to constrain equitable AI adoption. Advanced economies demonstrate that sustained public investment, mandatory teacher training in AI literacy, and explicit ethical governance frameworks are the structural preconditions for realizing AI's educational potential. For India, the path forward requires coordinated action across infrastructure investment, regulatory reform, and professional development, informed by lessons drawn from Finland's equity-centred model and South Korea's institutional scale-up approach. The review concludes by identifying priority directions for future research, including longitudinal outcome studies, culturally adaptive AI tool design, and the development of context-specific ethical frameworks for AI deployment in diverse, multilingual educational settings.
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Copyright (c) 2025 Monalisha Saha Goswami, Suprio Biswas (Author)
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