The DrishtiIAS article on Integration of Artificial Intelligence (AI) in Education outlines a structured and strategic approach to embedding AI within India’s educational system, emphasising that it should go far beyond mere adoption of technology to meaningful, ethical, and effective learning transformation. At the centre of this framework is the “Three A’s” model — Adoption, Absorption, and Application — which guides how educational institutions can progressively integrate AI into pedagogy and curriculum. This model is designed to move the system away from rote learning toward critical thinking, problem‑solving, and real‑world application of knowledge, aligning with the vision of National Education Policy (NEP) 2020.
Under the framework, “Adoption” involves introducing students and teachers to AI tools and interfaces (such as large language models and educational assistants) in a way that builds familiarity and confidence rather than fear of technology. “Absorption” goes deeper, asking learners to understand how AI works, its limitations, biases, and ethical implications, so they can critically evaluate AI‑generated outputs. Finally, “Application” focuses on using AI practically to solve real problems — from data analysis to creative design and innovation — making learners creators, not just consumers of technology.
The analysis also highlights major challenges to effective AI integration. These include infrastructure deficits in many Indian schools (lack of reliable internet, devices, and compute power), cognitive dependency risks where students might rely on AI without understanding underlying concepts, gaps in teacher training and capacity, and issues around exam systems that still prioritise memorisation. Additionally, concerns about data sovereignty and privacy arise when students’ information is processed by global AI models, underscoring the need for sovereign solutions like a national AI cloud and robust ethical safeguards.
To strengthen AI’s role in education, DrishtiIAS suggests policy measures such as building infrastructure that reduces digital and compute divides, introducing AI citizenship and ethics modules early in schooling, and reforming evaluation systems toward process‑based assessments that value reasoning and understanding. Teacher training reforms and a phased, modular curriculum rollout are also seen as crucial for ensuring AI enhances learning outcomes and prepares students for a future where AI literacy is as essential as reading and numeracy.
