To survive AI and global geopolitics, India should become a hub of knowledge creation, not just knowledge processing

The Hindu

3 days ago

Earlier this month, Tata Consultancy Services (TCS), India's largest IT services firm, confirmed it will lay off 12,000 employees. For decades, companies such as TCS symbolised India's prowess in IT-enabled services — a low-cost, high-scale model that rode the wave of globalisation. But that model is now under existential strain. The era of labour arbitrage is drawing to a close, and the age of artificial intelligence (AI) is rewriting the rules of economic competitiveness.
Generative AI, machine learning, and automation are fast replacing the very tasks that once gave India its edge: coding, data entry, support services, and even parts of analytics. The decline in headcount is not a blip; India's core export, white-collar digital labour, is being disrupted. And the country does not seem prepared as we see problems in absorbing science and engineering talent newly entering the job market.
Simultaneously, the manufacturing-led catch-up route is narrowing. For years, economists argued India could do what China did in the 1990s — turn industrial policy and export-led manufacturing into mass employment and structural transformation. But that ship has largely sailed. Countries such as Vietnam and Bangladesh have already captured the low-cost manufacturing space. Add to that rising automation and India's own infrastructure bottlenecks, the feasibility of China-style manufacturing resurgence diminishes rapidly.
What, then, is India's pathway to sustained economic relevance?
The answer lies upstream — in innovation, discovery science, and a smart, coordinated science, technology, and innovation (STI) policy. If India wants to be a rule-maker rather than a rule-taker in the AI-driven global economy, it must invest urgently in becoming a hub of knowledge creation, not just knowledge processing.
This will only be achievable with a new national compact that starts from STEM but goes above and beyond embracing STEPS — an integration of STEM with policy and society. This means building a generation of technologists who understand not just how to build systems, but how those systems affect entrepreneurship, business model and scaling, ethics, governance, and inclusion. It also means reforming curricula to include data governance, AI ethics, climate-tech, innovation economics, and intellectual property policy. Finally, it also means urgent, mission mode requirement of an integrated, State-agnostic approach where we will see not just southern India having a head start in STEM and STEPS.
The New Education Policy (NEP), 2020 provides some groundwork, but implementation must go further and deeper. From IITs to State universities, India will need a deliberate shift toward interdisciplinary innovation and doctoral-level research capacity. India's innovation-to-education pipeline is currently too weak to sustain a 21st century knowledge economy.
And sadly in this, as noted above, manufacturing likely will not save India any more. The dream of becoming the 'next China' in manufacturing is now largely unrealistic. India's manufacturing sector contributes just 14-16% of the GDP — a figure that has barely budged in a decade. More worryingly, global manufacturing is undergoing its own AI-led transformation: smart factories, predictive maintenance, and robotic assembly lines are shrinking the need for cheap labour. Competing on cost is now a losing battle.
Moreover, global supply chains are also realigning around strategic resilience and digital integration, not just wage arbitrage. India's challenge is not to attract the next garment factory but to build the next quantum computing lab or climate-resilient agri-tech platform.
Which brings us to the question of how a Triple Helix approach might be India's best shot at future-readiness. To get there, India will need a clear National Science and Innovation Strategy underpinned by deep collaboration between government, industry, and academia. No single actor can deliver the transformation needed and increasingly the need of the hour will be science-based entrepreneurship and scientist entrepreneurs. It has been done before like by Vijay Chandru, inventor of Simputer and founder of Strand Genomics, also a former IISc Professor, but one Vijay Chandru is hardly enough for a country of 1.3 billion.
Blue-sky science
Government also must invest in blue-sky science, reform its R&D funding structures, and design enabling regulatory frameworks for frontier tech (AI, biotech, semiconductors, and so on). Universities must evolve into innovation hubs, not just exam factories. They must work closely with industry, build tech transfer offices, and reward risk-taking. Industry also must move beyond short-term returns and co-invest in long-horizon research, from chip design to synthetic biology refusing to accept modest productivity gains with a middling equilibrium mindset.
Global lessons abound. The U.S.'s DARPA ecosystem, Germany's Fraunhofer Institutes, and Israel's Start-Up Nation playbook all demonstrate how strategic state support and institutional coordination can turn ideas into global advantage. India can build from their lessons, leverage on the current global geopolitical headwinds and create a national consciousness around science and innovation.
It is not just investment in science that will matter, but investment in the science of innovation itself brings in a critical evaluation mindset for upgrading based on evidence. India lacks a coherent framework to measure what works: which R&D models yield translational success? How do tech incubators perform over time? Where does research funding leak or stagnate?
A National Science of Science and Innovation Policy (NSIP) platform — a cross-ministerial, data-driven approach to governing the innovation ecosystem — could be a way forward. NITI Aayog's AI strategy and the recent National Research Foundation are steps in the right direction, but coordination and scale remain insufficient.
This effort must include dedicated funding for AI safety, public interest technologies, twin transition policies and sovereign computational infrastructure. The stakes are high: if India does not develop its own AI stack, algorithms, chips, cloud, data protocol, it will remain captive to technological colonialism.
Stagnation, inequality
The fallout from the AI transition is not hypothetical as we see in the TCS situation mentioned above. If India does not invest in science, technology, and evidence-based policy today, it will face economic stagnation, rising inequality, and geopolitical irrelevance tomorrow. The global economy will not wait for India to catch up and in fact, catching-up economies are looking for the country's leadership in these areas.
This is particularly concerning since already, a handful of countries — mostly in West and East Asia — are monopolising AI patents, funding, and talent. Without a deliberate national push, India will continue to supply coders to other nations' AI empires rather than building its own.
The good news is that India has the ingredients: a young demographic, a robust start-up ecosystem, and scientific institutions with proven excellence. What we need now is leadership, vision, and a strategic shift in mindset — from cost to creativity, from services to science, from political populism to real performance.
India can still leapfrog into the global innovation vanguard. But only if it recognises that science, technology, and smart policy are not luxuries — they are our last, best bet in the age of AI. The dragon is roaring already, will the elephant wake up?
Chirantan Chatterjee is a Professor of Development Economics, Innovation and Global Health at the University of Sussex