Why an application-first AI strategy will lead to irrelevance

A dangerous consensus is hardening within India’s corporate and policy ecosystem. The narrative suggests that while the U.S. and China fight expensive “compute and model wars”, India can simply build applications on top of foreign models. This is a dangerous delusion. It misunderstands the value accrual algebra, misjudges our historical strengths, and risks ceding our technological sovereignty. An application-first strategy is a recipe for strategic irrelevance.

The core flaw of this strategy lies in a fundamental shift in the technology value chain with the economic gravity of the technology world being completely inverted (see graphic). Worse, over 90% of that 15% application sliver is captured directly by frontier model creators. As foundational models rapidly absorb downstream features, independent “thin-wrapper” applications face a “SaaS-apocalypse”. Lacking a distinctive native frontier model, Indian enterprises are merely renting space on a pipeline where value is drained away upstream.

The illusion of labour arbitrage

India’s IT services boom relied on scale, labour arbitrage and headcount-linked revenue to maintain deterministic code and provide support services. The AI era, however, rewards deep innovation and hard intellectual property (IP). The U.S. and China are aggressively locking down the three true frontiers: Frontier Models, Semiconductors, and Physical AI.

While India builds wrappers, the U.S. leads in closed models (OpenAI, Anthropic) and hardware (NVIDIA, Broadcom, Intel). China dominates the open-source and open-weight space with reasoning-focussed models such as DeepSeek, Qwen, and Kimi. In silicon, Chinese semiconductor champions Moore Threads (Huagang architecture) and Huawei (Ascend 910C) are bypassing export controls to power massive inference clusters and rapidly bridging the technology gap with the U.S. majors.

Furthermore, China’s regional funds pump billions into physical AI, enabling startups such as Meg-aRobo and Kepler Robotics to deploy humanoids. In the U.S., Figure AI, Boston Dynamics, and Tesla’s Optimus race towards the same goal. The ultimate expression of AI is intelligent code ani-mating physical machines to reshape manufacturing. Without chips or robotics IP, India is excluded from this impending industrial revolution.

The compute chasm and the 1999 infrastructure lesson

To build AI, you need compute; to house compute, you need data centres. On this foundational front, India is facing a massive compute and data centre chasm. The U.S. is adding 13 GW of capacity this year alone (climbing to 95 GW by 2027), and China is targeting 60 GW by 2030. India’s entire operating capacity sits at just 1.6 GW. We are bringing sticks and knives to a planetary laser fight.

History offers a stark warning to those who dismiss this infrastructure race as a temporary bubble. During the 1999 dot-com boom, billions of dollars were poured into building dark fibre networks and internet backbones. When the market crashed, overvalued and “frothy” dot-com applications vanished into thin air. However, the physical infrastructure—the thousands of miles of fibre-optic cables laid beneath the earth—survived. It was this exact underlying physical foundation that later enabled the birth of the modern internet giants, notably Amazon, Google, and Facebook. The lesson for 2026 is unambiguous: those who build the physical infrastructure win the long war, even if the initial equity markets turn volatile.

The global capital verdict: AI is a threat to the India story

Global capital markets have already begun delivering their verdict on India’s current trajectory. Foreign portfolio investors are increasingly migrating capital out of Indian equities to chase pure-play AI bets in markets that control the hardware and model layers. For the first time in recent memory, no Indian corporation ranks within the Top 100 global companies by market capitalisation.

Institutional investors are looking closely at India’s traditional IT and business service export strategies and sense a structural threat. If a frontier model in Silicon Valley or Beijing can automate 80% of a service workflow, the traditional Indian cost-arbitrage model collapses. Global capital believes India is on the wrong side of the AI ledger—exposed to the disruptive liabilities of automation without owning the IP that accrues economic benefits. This resounding negative verdict has the potential to starve India of necessary global capital and poses an immediate threat to the broader India story and the journey to Viksit Bharat.

AI is a foundational technology as consequential to human history as the invention of the steam engine, creation of the railroad, the harnessing of electricity, or the mastering of nuclear energy. In the architecture of geopolitics, nations that do not possess sovereign capability in foundational technologies inevitably become client states.

If India remains content in merely consuming western and Chinese AI technologies, we risk entering a new era of AI colonisation. It is time to stop building the wrappers and start building the machine itself with a dramatically reimagined Sovereign AI Blueprint (details of which will be covered in Part 2 of this series). We must abandon the safety of the application layer and fight for a seat at the foundational model, semiconductor and data centre table. Our transition to Viksit Bharat depends on it.

(Part 1 of a two-part series. The author is chairman of Hyperion Ventures Corporation, a global AI-led manufacturing platform focussed on semiconductors, rare-earth magnets and electronic components. Views are personal.)