There is a strange sense of déjà vu about India’s AI moment. Confidence is nostalgic and ambition is unmistakable. But history has a way of whispering warnings when excitement outweighs economic stability. Artificial intelligence promises transformation, but past tipping points show that the real results often appear slower and last longer than applause.
India today talks about AI with legitimate ambitions. New models, data center expansion, increased investment, and bold policy signals suggest the country aspires to take its place in the next technological order. But underlying the optimism lies a harder and more important question. Can India incorporate artificial intelligence into its economy without destabilizing the economy? The Economic Survey 2025-26 contains an important realization. Artificial intelligence is no longer just about increased productivity and smarter software. It is now impacting capital, employment, and financial stability itself. When AI starts to impact these fundamentals, the discussion becomes less technical and more decidedly strategic.
India’s AI moment is therefore not about who builds the biggest models or deploys the most computing power. The question is whether countries can manage AI in a way that strengthens, rather than undermines, economic resilience. Globally, AI is being built on an unprecedented scale. Large-scale language models (LLMs) require vast data centers, uninterrupted energy supplies, and long-term capital commitments. To fund this expansion, companies are increasingly turning to complex financial arrangements such as financing, special purpose vehicles, and off-balance sheet structures.
This pattern has been seen before in history. Technological revolutions do not usually cause crises in and of themselves. A crisis occurs when economic expectations exceed economic reality. The study openly points out concerns about the economics of large-scale AI investments and warns that a sharp correction in AI infrastructure spending could spill over into broader financial markets.
Simply put, AI is starting to look more like a systemic risk variable than a simple growth story. For India, that distinction is very important. Our economy remains structurally sensitive to global financial cycles. Despite strong growth and improving fundamentals, the country runs a current account deficit and relies on foreign capital to fund investment and stabilize the rupee. As is often the case in times of uncertainty, capital flows could quickly reverse as global investors become cautious. This explains a paradox that many Indians have observed: why the rupee is depreciating despite strong growth and rising inflation.
Under control. In today’s market, growth isn’t the only reward. They price resilience, predictability, and shock-absorbing ability. Pursuing AI without macroeconomic discipline could weaken its resilience. Running large-scale AI systems requires imported hardware, huge energy inputs, and continued access to global capital. A country that imports all three cannot gain strategic autonomy. It accumulates vulnerabilities. When global liquidity tightens or geopolitical tensions rise, those vulnerabilities suddenly come to the fore. This is the correction that India’s AI story has to face. Scale without stability is not strength.
AI as a strategic force and strategic exposure
AI infrastructure is becoming increasingly geographically, economically, and technologically concentrated. Only a few countries control advanced chips. Cloud infrastructure and foundation models are dominated by a few companies. Energy-intensive data centers are now critical nodes in the nation’s power grid.
These realities have direct geopolitical implications. In a world marked by sanctions, export controls, and the weaponization of technology, reliance on external AI supply chains can quickly become a strategic risk. Disruptions to chip availability, energy prices, and capital flows can reduce a nation’s AI capabilities almost overnight. Unlike traditional industries, AI systems degrade rapidly when they lack compute, power, and data access.
Therefore, the study’s warnings about AI-related financial stress must be read in conjunction with India’s broader strategic environment. Countries that rely heavily on imported AI hardware, foreign capital, and offshore cloud infrastructure risk externalizing their digital sovereignty. In this context, economic instability becomes a national security risk. Currency fluctuations, employment shocks, and sudden capital flight weaken strategic posture just as surely as traditional threats. Another assumption in the AI debate deserves scrutiny. The idea is that AI will naturally extend India’s services-led success. India’s IT and services sector is a pillar of growth and foreign exchange. However, services can avoid weak infrastructure and uneven governance. Manufacturing cannot do that. It forces improvements in logistics, power reliability, labor regulations, and state capacity.
This distinction is important. Countries with strong manufacturing bases tend to enjoy more stable currencies and deeper institutional resilience. If AI is primarily limited to services and digital platforms, we risk repeating old patterns in which productivity gains are concentrated in narrow segments while employment disruption spreads faster than new opportunities emerge.
AI will not automatically solve India’s employment challenges. Without intentional policy design, inequalities and social tensions may actually increase.
This is where economic research’s emphasis on “entrepreneurial states” becomes important. This does not mean state control over technology. This refers to a state’s ability to manage uncertainty. AI shortens time horizons, concentrates capital, and amplifies first-mover advantages. If the national response is delayed, adjustment costs will fall on workers, small and medium-sized businesses, and public finances. Therefore, a full-fledged AI strategy cannot be created by engineers alone. It will require economists, labor planners, energy regulators and financial authorities to work together.
AI is more than just a technological change. It is a political and economic shock. India still holds an advantage. Unlike some developed countries, it is not yet overfinancialized. Its AI ecosystem remains close to practical deployment, rather than speculative excess. This provides a narrow but valuable opportunity to engineer an AI path that strengthens rather than destabilizes the economy. But that window won’t stay open forever. What does a stable and strategically sound AI approach look like?
First, AI infrastructure must be treated as national economic infrastructure, not a speculative arms race. Financial prudence is more important than speed. Today’s overleverage creates tomorrow’s vulnerabilities. Second, AI adoption must prioritize sectors that strengthen India’s economic infrastructure, such as manufacturing productivity, logistics efficiency, energy management, agriculture, and public service delivery. These increase competitiveness and reduce external vulnerability. Third, AI policies must be integrated with employment, skills and social protection systems. Ignoring labor interruptions will not prevent them. It simply defers costs. Finally, India must abandon the illusion that its AI leadership will be measured solely on technological scale. In a fragmented and fragile world order, stability itself is a strategic asset.
The temptation to chase the headlines will be strong. Bigger models, bigger data centers, and bigger announcements are easier to praise. However, nations do not stand up on spectacle alone. They thrive on discipline, systems, and long-term thinking. India is at a critical juncture. There is growth momentum, the ability to innovate, and an opportunity to integrate AI thoughtfully rather than reactively. The choice is between speed and strategy, between excitement and patience.
The sense of déjà vu surrounding India’s AI moment is no reason to hesitate. It’s a memory. History rarely repeats itself exactly, but it often sends a warning at the outset. Whether India listens will determine whether artificial intelligence becomes a source of lasting strength or the next great stress test.
The author is a theoretical physicist at the University of North Carolina at Chapel Hill in the US and the author of the forthcoming book The Last Equation Before Silence. views are personal
