India is at the pivotal stage of technological development. Artificial Intelligence (AI) has ceased to be a far-fetched and exclusive concept of researchers or big corporations. It is rapidly becoming the instrument that enables people to create, develop, and grow ideas with quicker results than ever before. Tasks that required huge workforce and even months to accomplish can now be achieved by an individual in a few weeks. This change is not merely a technological one, but it is having a fundamental redefinition of who is able to be innovative.
However, our higher education has not kept abreast.
Engineering and business education have been independent of each other over the decades. Engineers had been trained to construct. Business graduates were educated to be managers. However, in the era of AI, it does not make sense to have this division. The future constructors will also be required to think strategically, make decisions, and behave as entrepreneurs.
The limitations of traditional education are not only structural but also pedagogical. Much of undergraduate learning continues to prioritise theoretical knowledge over practical engagement. Students are trained to absorb information, reproduce it in examinations, and eventually apply it in professional settings that often bear little resemblance to the controlled environment of a classroom. This model is ill-suited to a world where knowledge is constantly evolving and where the ability to experiment, iterate, and adapt is more valuable than the ability to recall established frameworks.
In contrast, the demands of the AI-driven economy point towards a different kind of learning—one that is interdisciplinary, experiential, and closely aligned with real-world contexts. Students must be equipped not only with technical expertise but also with the capacity to identify problems, design solutions, and bring them to fruition. This requires a shift from passive learning to active creation, where education becomes a process of building rather than merely understanding.
Some emerging models are beginning to reflect this shift. The Scaler School of Technology, for instance, has introduced an undergraduate programme in AI and business that combines technical training with entrepreneurial learning. In its later stages, students are encouraged to build AI startups, engaging directly with product development, users, and funding ecosystems.
Such approaches recognise that innovation does not occur in isolation. It is shaped by ecosystems that provide mentorship, resources, and opportunities for collaboration. In the absence of these conditions, even the most talented individuals may struggle to translate their ideas into meaningful outcomes. This is particularly relevant in the Indian context, where the availability of talent is rarely in question, but the pathways for nurturing and sustaining innovation remain uneven.
The emphasis on ecosystem also challenges the longstanding belief that expertise must precede action. In many traditional settings, students are expected to accumulate knowledge for years before attempting to create something of their own. The AI era disrupts this sequence. Young individuals, often with limited formal experience, are already developing products, generating revenue, and contributing to technological advancement. Their success suggests that the barriers to entry have shifted, making it possible to participate in innovation much earlier than before.
At the same time, this transformation raises important questions about the purpose of higher education. If information is readily accessible and tools are increasingly intuitive, what should universities aim to provide? The answer may lie not in the transmission of knowledge alone, but in the cultivation of judgement, creativity, and resilience. Students must learn how to navigate ambiguity, how to evaluate the implications of their work, and how to respond to failure as an integral part of the learning process.
This also necessitates a reconsideration of how merit is defined. Conventional metrics such as examination scores offer only a limited view of a student’s potential. In a rapidly changing technological landscape, qualities such as curiosity, initiative, and the willingness to take risks may be far more indicative of future success. Educational institutions must, therefore, broaden their criteria to recognise and nurture these attributes.
India’s position in the global AI landscape makes this rethinking particularly urgent. The country possesses a vast and diverse talent pool, a growing startup ecosystem, and increasing access to digital infrastructure. These factors create a unique opportunity to move beyond incremental adaptation and towards more fundamental innovation. However, realising this potential will require an education system that is not merely responsive but anticipatory, capable of preparing students for a future that is still taking shape.
AI has already transformed the world.
The actual problem is who will create that future.
This article is authored by Anshuman Singh, dean, Scaler School of Technology, Bangalore.
