By Dipak Kurmi
When the Ministry of Education announced that artificial intelligence (AI) would become part of the national school curriculum from Class III onward, beginning in the 2026–27 academic session, it was hailed by many as a visionary step. India, they said, was preparing its young minds for a technology-driven economy — a future where AI literacy could be as essential as reading or arithmetic. Yet, beneath the rhetoric of innovation and progress lies a more complex question: Are we truly ready to teach AI to children who have yet to master the fundamentals of digital learning?
In July 2025, the government launched the SOAR (Skilling for AI Readiness) initiative under the Central Board of Secondary Education (CBSE). Through SOAR, nearly 18,000 schools are already offering AI as a “skill subject” from Class VI onwards — with 15-hour introductory modules for classes VI to VIII and comprehensive 150-hour elective courses for classes IX to XII. This ambitious move, we are told, aims to build a generation of AI-ready citizens who can lead India’s technological revolution. The CBSE is reportedly developing a framework for “AI integration across grades”, a vision that suggests AI will eventually be embedded into every layer of learning — from primary arithmetic to higher-level problem-solving.
This enthusiasm, however, stands in stark contrast with the state of AI education in universities. Only a handful of higher education institutions have introduced mandatory AI courses, and even those are restricted to Science and Engineering departments. There is no parallel effort to integrate AI into social sciences, humanities, or interdisciplinary streams, where its ethical, philosophical, and social dimensions could be better understood. This disconnect raises a critical question: If AI education at the university level is still in its infancy, what wisdom is there in rushing it into classrooms filled with eight-year-olds?
The official justification is both noble and ambitious. The government argues that SOAR will help “bridge the digital divide” and open new opportunities for students from underprivileged and rural backgrounds. The logic is simple: teach AI early, and you empower children to participate in the digital economy. Yet, this optimism borders on irony in a nation where most schools still struggle with electricity, internet access, or basic digital literacy. Many teachers have never used a computer for instruction, let alone trained in AI pedagogy. In such a context, teaching AI as a bridge to equality feels less like inclusion and more like a mirage — a well-intentioned idea that risks deepening the very divide it seeks to close.
The problem is not the aspiration itself, but the misalignment between vision and reality. To understand this better, consider an analogy. The mobile phone has arguably been the most transformative technology of the last three decades, reshaping how we live, work, and connect. Yet we do not teach the principles of mobile network engineering to schoolchildren. Instead, we guide them on how to use phones responsibly, safely, and productively — skills that are age-appropriate and directly relevant to their daily lives. By contrast, thrusting technical AI concepts like “neural networks”, “reinforcement learning”, or “natural language processing” into the syllabi of children who are still learning fractions or sentence construction risks overwhelming rather than empowering them.
Moreover, the term “AI in schools” is used so loosely that it has come to mean many different things to different stakeholders. For some, it refers to AI literacy — a basic understanding of how AI shapes our lives. For others, it means deploying AI tools in classrooms to assist teaching or personalize learning. Tech companies talk of using AI to assess individual student performance and tailor content accordingly. Governments speak of “data-driven education” and “tracking every child’s progress”. Meanwhile, educators interpret AI in schools as a call to use ChatGPT-like systems to generate lesson plans or automate administrative work. This confusion is not benign — it risks creating an educational labyrinth in which policy, pedagogy, and technology move in different directions.
The current AI curriculum under CBSE exemplifies this tension. At the middle-school level, the curriculum introduces students to three AI domains — computer vision, natural language processing (NLP), and statistical data. Class VII textbooks describe how AI can promote sustainability and societal development through concepts such as Sustainable Development Goals (SDGs), systems thinking, and system maps. By Class VIII, students are expected to grasp the “AI Project Cycle”, AI ethics, and responsible AI practices. In Class IX, they encounter mathematical foundations for AI and even an introduction to generative AI. By Class X, the syllabus expands to cover supervised, unsupervised, and reinforcement learning, clustering, and neural networks.
For educators, the challenge is obvious. How can children meaningfully connect these abstract concepts with the AI-driven tools they use in daily life — like voice assistants or translation apps — when even many adults struggle to understand how these technologies truly work? How can teachers, most of whom have not been trained in AI themselves, translate these ideas into engaging and age-appropriate lessons? The pedagogic gap here is not a small one; it is a chasm.
This becomes clearer when one looks at some of the curricular exercises prescribed in CBSE’s AI handbook. For instance, students are asked: “Which Sustainable Development Goal focuses on gender equality and empowering all women and girls?” (a) SDG-3 (b) SDG-5 (c) SDG-8 (d) SDG-10. While the intention is to link AI education to global citizenship and awareness, the outcome is rote memorization rather than critical thinking. Whether a student can recall the numerical label of an SDG has little to do with understanding how AI systems intersect with gender bias or representation in data. If the goal is to nurture critical AI thinkers, this kind of questioning defeats the purpose.
To be clear, the debate is not whether AI should or should not be taught in schools. The real issue lies in how it should be taught, why, and to what end. Education is not merely about keeping up with technological trends; it is about preparing minds to think, question, and create meaning. Introducing AI at an early age may be defensible if the aim is to promote curiosity — to make children ask, “How does a computer see?” or “Can a machine understand emotion?” But if the intent is to produce technically skilled coders before they have learned critical reasoning or scientific temper, the effort may backfire.
There are also deep psychological and developmental concerns. Cognitive research suggests that children in primary and early middle school are still developing abstract reasoning abilities. Concepts like “machine learning models” or “sustainability through AI systems” require cognitive maturity and contextual understanding — qualities that are cultivated gradually through language, logic, and life experience. Without this foundation, teaching AI risks becoming mechanical and meaningless, reduced to buzzwords rather than comprehension.
Furthermore, AI is not a static field. The technologies and terminologies that dominate classrooms today may be obsolete in five years. This volatility demands a flexible, foundational approach to education — one that emphasizes problem-solving, creativity, and ethical thinking, rather than chasing every new wave of innovation. Ironically, these are precisely the human capacities that AI cannot replace — and which, therefore, education must strengthen.
Another pressing question is whether the AI movement in schools is driven more by technological fashion than by educational necessity. Even among computer scientists, there is active debate over whether AI represents a sustainable paradigm shift or a speculative bubble inflated by hype. To anchor school education to a field that itself is evolving so rapidly could endanger the stability and coherence of the broader curriculum. Schools are meant to provide grounding — in literacy, numeracy, values, and social understanding — not merely to chase the next algorithmic breakthrough.
In a world where digital tools are both empowering and addictive, exposing children prematurely to the seductive promise of AI may carry unintended consequences. The allure of “smart systems” could foster overreliance on machines rather than curiosity about how things work. Children may grow up as users of AI rather than thinkers about it — an outcome opposite to the one intended.
To integrate AI meaningfully in education, India must prioritize teacher capacity building, contextual curriculum design, and critical digital pedagogy. Teachers need both technical orientation and philosophical grounding in AI ethics to guide children responsibly. Schools need robust infrastructure — reliable internet, adequate hardware, and inclusive access — before any talk of AI readiness can be meaningful. Policymakers must consult educators, psychologists, and technologists alike to craft an approach that is both aspirational and achievable.
The future will indeed be shaped by artificial intelligence. But the question before us is not how quickly we can rush AI into classrooms — it is how wisely we can do so. Education must not become the testing ground for every technological trend. Rather, it must remain the sanctuary of human wisdom, a space where curiosity is balanced with conscience, and progress with prudence.
India’s dream of becoming a global AI leader is admirable. But leadership in technology does not come from teaching buzzwords to children; it comes from building a society capable of critical reflection, creative problem-solving, and ethical judgment. To achieve that, we must first strengthen the basics — literacy, numeracy, logic, and empathy — before we teach algorithms and neural networks. In the end, the challenge is not whether India can teach AI to children, but whether it can do so without forgetting what education is truly meant to be.
(The writer can be reached at dipakkurmiglpltd@gmail.com)
