Anshi Sinha
AI has become a part of people’s everyday lives, especially students’. There is a great deal of debate among educational circles regarding the use of AI in academic work and its implications for the future of education systems. While many applaud and welcome the latest advancement in the history of technology, few are also sceptical about the potential loss of students’ capacity for independent thinking. This is a global-level discussion, but it is especially important in the Indian context, where the expansion of institutional resources has not always kept pace with the country’s growing population.
Class sizes at Indian universities are frequently large, faculty-to-student ratios are often stretched thin, and one-on-one academic support is not always readily available. Under these conditions, an AI tool that can explain a difficult concept on demand, at any hour, without requiring an appointment, is a fairly rational adaptation. This framing does not deny that complete dependency is a genuine risk. It does, however, suggest a different starting question. Rather than asking whether students are becoming overly reliant on AI, another approach might ask whether students are treating AI as one tool among several improvised solutions to a resource-constrained academic environment.
On the count, India’s policy updates for AI in education are recent and firm. The National Education Policy (NEP 2020) names AI as one of the key skills students should learn for the future. This vision was anticipated by NITI Aayog’s National Strategy for Artificial Intelligence, #AIforAll, which identified education as one of the five national priority sectors expected to benefit most from AI. More recently, the government’s IndiaAI Mission, approved in 2024 with a budgetary outlay of thousands of crores of rupees, has extended this vision into concrete programmes: AI skill initiatives such as YUVAI for all and free AI courses on the online SWAYAM platform.
The University Grants Commission has incorporated AI and data science components into model curricula, and the All India Council for Technical Education has integrated AI modules into technical syllabus, alongside dedicated faculty training programmes. At the school level, the CBSE and NCERT have offered AI as a subject since 2019, extending it progressively from middle school onward. Taken together, this represents a substantial and growing body of policy work, built up in stages over nearly a decade. Whether students have begun to take advantage of these policies in their everyday academic work remains an open question.
This is the more urgent matter at hand: bridging these policy updates with students’ actual awareness of them. AI can plan revisions, generate quizzes, explain topics, and assist with research and much more. Students across every field use it differently. A law student can use the tools to summarise case material, an engineering student can use them to debug code, or a humanities student may use them to research materials for writing articles. Understanding what AI means for distinct disciplines, rather than treating “student AI use” as a single, uniform behaviour, is crucial to strengthening the implementation of this policy architecture in classrooms.
An important factor in this discussion is teaching students the ethical use of AI. Instead of offloading all their academic work to AI, students can benefit far more by learning to work alongside it. If it is used as a replacement for their thinking, it carries a risk of cognitive offloading. Risko and Gilbert’s (2016) foundational work on cognitive offloading offers a useful framework for this – sustained, high-frequency reliance on external tools, they argue, gradually restructures internal cognitive habits. It may lead to a reduction in reasoning and problem-solving capabilities. This is not an argument against using AI altogether, but a reminder that how a tool is used tends to matter as much as its frequency.
Some universities have begun experimenting with more structured responses to this challenge. They are encouraging classroom discussions on appropriate AI use and designing assignments that explicitly ask students to show their reasoning process alongside any AI-assisted output. These remain early and uneven efforts, but they suggest that the gap between policy and practice still remains and that individual institutions also have a crucial role to play in implementing broader national frameworks.
One cannot say explicitly that AI’s growing presence in Indian classrooms is simply good or simply bad for students’ learning. It suggests instead that the answer will depend on how quickly policy reaches across disciplines, how willing institutions are to experiment in the meantime, and how deliberately students and educators choose to use AI as a tool for thinking rather than a substitute for it. What is clear, at this stage, is only that the conversation is far from settled, and that the coming years will likely tell a more complete story.
REFERENCES:
- Press Information Bureau. (2026, March 3). AI in education: Building India’s talent pipeline for global leadership [Press release]. Government of India. https://www.pib.gov.in/PressReleasePage.aspx?PRID=2234853®=3&lang=1
- Risko, E. F., & Gilbert, S. J. (2016). Cognitive offloading. Trends in Cognitive Sciences, 20(9), 676–688. https://doi.org/10.1016/j.tics.2016.07.002
About the contributor: I am Anshi Sinha, currently a student at Manipal Institute of Social Sciences, Humanities and Arts, MAHE, Manipal, pursuing an MA in Sociology. I have completed my Bachelor’s degree in Economics and Mathematics from SGTB Khalsa College, University of Delhi. She is a fellow of the Public Policy and Qualitative Participatory Action Research Fellowship Cohort-7.0.
Disclaimer: All views expressed in the article belong solely to the author and not necessarily to the organisation.
Read more at IMPRI:
Shanti Act 2025 India’s Nuclear Needs and Right to Life
SUSTAINABLE SAND GOVERNANCE IN PRACTICE : EVALUATING RAJASTHAN’S M-SAND POLICY
Acknowledgement: This article was posted by Shivashish Narayan, a visiting researcher at IMPRI.
