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Role of Artificial Intelligence in Implementing NEP 2020 in India

Author

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  • Aastha Choudhary
  • Nagendra Kumar Sharma
  • Suman Shrivastava

Abstract

The National Education Policy 2020 (NEP 2020) represents a landmark commitment to dismantling systemic inequities in India's educational landscape through a holistic, flexible, and technology-integrated framework. At the same time, Artificial Intelligence (AI) is rapidly emerging as a powerful equaliser in global education systems, offering unprecedented possibilities for democratising access, personalising learning, and reducing structural disadvantages faced by marginalised communities. This doctrinal research examines AI's potential as a catalyst for educational equity within the NEP 2020 framework, critically analysing how policy directives envision technology's role in achieving equity, quality, affordability, and accountability for all learners including those from rural, tribal, and socio-economically disadvantaged backgrounds. The study identifies key integration pathways aligned with NEP 2020's equity mandate while critically mapping persistent challenges such as the digital divide, insufficient infrastructure, data privacy concerns, linguistic barriers, and uneven teacher preparedness. A cooperative, equity-centred strategy balancing technological innovation with cultural sensitivity and pedagogical soundness is proposed for policy makers, academic institutions, and technology developers. Ultimately, this paper argues that AI and NEP 2020, if implemented with deliberate attention to inclusion, together offer an unparalleled opportunity to bridge long-standing educational inequalities and prepare every Indian learner for a shared digital future.

Suggested Citation

  • Aastha Choudhary & Nagendra Kumar Sharma & Suman Shrivastava, 2025. "Role of Artificial Intelligence in Implementing NEP 2020 in India," International Journal of Scientific Research in Science and Technology, Technoscience Academy, vol. 12(4), pages 1213-1221, August.
  • Handle: RePEc:etm:ijsrst:v12:y2025:i4:id:1483
    DOI: 10.32628/IJSRST25123173
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