Reclaiming Research, Innovation, and Sovereignty in Indian Academia
Civilisations do not rise on infrastructure alone; they rise on imagination. In Indian mythology, creation is always preceded by drishti; vision. Brahma visualises the cosmos before manifestation; Arjuna is granted Krishna’s Vishwaroopa before action becomes possible. Vision precedes form. Insight precedes execution. Yet, paradoxically, India’s modern education and research ecosystem has increasingly constrained imagination at precisely the institutions meant to cultivate it.
The problem begins early. Walk into a primary school and ask children to paint freely. Disturbingly often, the output is identical; twin mountains, a hut, a tree, two birds, and a rising sun. This is not innocence; it is conditioning. Imagination is disciplined into templates. Originality is penalised; correctness rewarded. By the time students enter universities, curiosity has been replaced by compliance, and exploration by instruction-following. What emerges is not first-principles thinking, but pattern replication.
This conditioning persists and hardens in higher education. Universities proudly announce drone labs, AI centres, and innovation cells, yet struggle to answer a foundational question: to what real problem will these technologies be applied? Drones are built without use cases; AI models are trained without production pathways; patents are filed without commercialisation strategies. Innovation becomes documentation rather than transformation.
India has witnessed a sharp rise in patent filings in recent years, yet only a small fraction are operationalised into deployable products, scalable enterprises, or societal solutions. Knowledge is created, but not translated. Capability is demonstrated, but not compounded.
Chanakya never envisioned scholars as isolated teachers. He designed them as architects of systems, advisors to power, and creators of economic value. Knowledge, in the Indian civilisational view, is incomplete without action. Gyan without karma is inert.
At the heart of the present dysfunction lies a structural flaw: the way research and academic work are institutionally treated. Professors are confined to teaching, examinations, and administrative compliance. Policies implicitly discourage enterprise creation, applied research, or commercial engagement. The result is a tragic underutilisation of intellectual capital. Universities become knowledge warehouses rather than engines of national capability.
This stands in sharp contrast to global academic ecosystems. Professors such as Andrew Ng and Philip Kotler exemplify a different paradigm; one where teaching, research, and enterprise reinforce one another. Their academic work seeded companies, industries, and schools of thought, generating societal value alongside financial reward. Importantly, their engagement with real-world problems enriched their pedagogy rather than diluting it.
India does not lack talent; it lacks permission structures.
The Missing Architecture: What Prevents Change
The constraints inhibiting India’s research-to-impact journey are not ideological; they are structural:
Innovation is allowed, but not mandated.
Higher Education Institutions (HEIs) may incubate ideas and commercialise research, but this remains discretionary, peripheral, and poorly incentivised.Fragmented applicability.
Reforms apply unevenly across central universities, state universities, colleges, and research institutions, creating islands of excellence rather than systems of scale.Government research labs operate in silos.
Publicly funded laboratories generate enormous knowledge, yet much of it remains trapped in reports and prototypes.Scientists are administratively misclassified.
Scientists and engineers in government labs are evaluated through bureaucratic lenses rather than innovation outcomes.Mobility is discouraged.
Movement between academia, research labs, and industry R&D remains institutionally complex and culturally suspect.Technology governance lacks a unified visioning authority.
Decisions are dispersed across departments without a coherent, technocratic foresight mechanism.Data is archived, not activated.
India generates vast data but lacks production-grade frameworks for inferencing, labelling, and AI translation.
The Structural Reset: What Must Change
To move from sporadic excellence to systemic leadership, the following reforms must be instituted deliberately and uniformly:
Mandate innovation as a core academic function.
Incubation, translational research, and enterprise creation must be compulsory for HEIs; embedded into accreditation, funding, and faculty evaluation.Apply reforms uniformly across all institutions.
This mandate must extend to central, state-run, and private universities and colleges without exception.Extend the same logic to government-funded research labs.
Knowledge created in these institutions must be commercialised, licensed, or deployed at scale.Grant scientists freedoms equivalent to academics.
Scientists must be allowed to participate in startups, spin-offs, and industry collaborations without career penalties.Separate scientific cadres from bureaucratic cadres.
Evaluation and promotion must be based on knowledge creation, translation, and impact; not administrative tenure.Tie all research labs to academic institutions.
This ensures continuous circulation of students, faculty, ideas, and real-world problems.Enable structured mobility across ecosystems.
Movement of technologists between academia, research labs, and industry R&D must be encouraged and codified in regulation.Revamp apex science administration.
A reconstituted national science and technology foresight body; led by technocrats; must envision sectoral research ecosystems.Endorse all major government technology decisions through this forum.
This ensures coherence, continuity, and first-principles rigor.
Data, Inferencing, and Sovereignty
As these reforms take effect, they will generate a humongous volume of data. Data is the new raw material; but its value lies not in accumulation, rather in inferencing. Without curation, metadata, and training frameworks, data remains locked.
India has already experienced a sustained flight of data. Through foreign browsers, operating systems, app stores, and platforms, Indian behavioural and linguistic data is continuously siphoned offshore. Inferencing; and therefore strategic advantage; is generated elsewhere.
Regulation alone cannot reverse this. India must build sovereign digital rails: indigenous browsers, app ecosystems, and large-scale data centres. This requires power, capital, and long-term certainty.
Critically, the state must recognise data as a commodity; measurable, tradable, and financeable. Just as power producers secure financing through long-term Power Purchase Agreements (PPAs), the government can tender long-term data curation and AI training contracts. Each forward contract can unlock multi-fold productivity gains across the economy.
Academia as the Rishi to the State
A frequently overlooked dimension is the relationship between academia and bureaucracy. Bureaucracy often operates under informational constraints. Professors, when unshackled from narrow teaching mandates, can become powerful allies; designing decision-support systems, policy simulations, and data-driven governance frameworks.
In civilisational terms, academia must become the rishi to the state; not retreating to forests, but embedded within institutions of action.
Conclusion
In essence, imagination must be institutionalised, not romanticised. Only then can India move from sporadic excellence to systemic leadership; a transition already exemplified in frugal, first-principles institutions such as ISRO, and in global academia through figures like Andrew Ng and Philip Kotler.
The task now is not to admire these models, but to architect conditions in which they become the norm rather than the exception.
The future does not belong to those who teach the past best. It belongs to those who have the courage to invent what does not yet exist; and the wisdom to build systems that allow imagination to endure.
For this transformation to occur, both constitutional and academic reforms are required. At a policy level, academic freedom must explicitly include the freedom to build, commercialise, and participate in enterprises derived from research. At an institutional level, pedagogy must shift from lecture-centric instruction to problem-centric creation. Students should graduate having built solutions, not just answered questions.
In Indian philosophy, knowledge (gyan) is incomplete without action (karma). Universities must rediscover this synthesis. When professors are liberated to create, when students are encouraged to imagine beyond templates, when data is transformed into intelligence, and when institutions align vision with execution, India can move from being a generator of talent to an architect of destiny.
The future does not belong to those who teach the past best; it belongs to those who have the courage to invent what does not yet exist. That too; follows from the Indian belief system. The lack of evidence does not mean the lack of existence. We just need to enable and empower the optics of those that work on the ground raising nurseries of talent, aka; the teachers. We need to curate data and defend our sovereignty that today stands on legs on foreign browsers, app stores and software and mines our passwords making India vulnerable in the face of the march of AI.
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