The central flaw in this strategy lies in the fundamental change in the technology value chain due to a complete reversal of the economic gravity of the technology world (see diagram). To make matters worse, more than 90% of that 15% application sliver is directly captured by frontier model authors. Independent “thin wrapper” applications are facing the “SaaS apocalypse” as the underlying model rapidly absorbs downstream functionality. Lacking a unique native frontier model, Indian companies are simply renting space on a pipeline where value flows upstream.
India’s IT services boom relied on scale, labor arbitrage, and headcount-linked revenues to maintain a deterministic code and provide support services. But in the AI era, deep innovation and hard intellectual property (IP) will be rewarded. The US and China are actively blocking three true frontiers: frontier models, semiconductors, and physical AI.
While India is building wrappers, the US is leading in closed models (OpenAI, Anthropic) and hardware (NVIDIA, Broadcom, Intel). China dominates the open source and open weight space with inference-focused models such as DeepSeek, Qwen, and Kimi. In silicon, Chinese semiconductor champions Moore Threads (Huagang architecture) and Huawei (Ascend 910C) are circumventing export controls to power large inference clusters and rapidly closing the technology gap with the US giants.
Additionally, China’s regional funds are pouring billions into physical AI, enabling startups like Meg-aRobo and Kepler Robotics to deploy humanoids. In the United States, Figure AI, Boston Dynamics, and Tesla’s Optimus are racing toward the same goal. The ultimate expression of AI is intelligent code that animates physical machines and restructures manufacturing. Without chips and robotics IP, India will be excluded from this impending industrial revolution.
Building AI requires computing. Data centers are required to house computing. On this fundamental front, India faces a massive computing and data center chasm. The US has added 13 GW of capacity this year alone (rising to 95 GW by 2027), and China is targeting 60 GW by 2030. India as a whole has only 1.6 GW of operational capacity. We’re bringing sticks and knives to planetary laser combat.
History offers a stark warning to those who dismiss this infrastructure race as a temporary bubble. The dot-com boom of 1999 poured billions of dollars into building dark fiber networks and the Internet backbone. When the market crashed, overvalued and “bubbly” dot-com applications disappeared. But the physical infrastructure (thousands of miles of fiber optic cables run underground) survived. It was this underlying physical foundation that later enabled the birth of modern Internet giants, especially Amazon, Google, and Facebook. The lessons for 2026 are clear. Even if the initial stock market is volatile, those who build the physical infrastructure will win the long game.
Global capital markets have already begun passing judgment on India’s current trajectory. Foreign portfolio investors are increasingly draining money from Indian equities to pursue pure AI bets in markets that control the hardware and model layers. For the first time in recent memory, no Indian company ranks in the top 100 market capitalization rankings.
Institutional investors are closely monitoring India’s traditional IT and business services export strategy, sensing a structural threat. If the frontier models of Silicon Valley and Beijing can automate 80% of service workflows, India’s traditional cost arbitrage model will collapse. Global Capital believes that India is on the wrong side of the AI ledger, exposing itself to the destructive liability of automation that does not own the intellectual property that generates economic returns. This overwhelmingly negative verdict has the potential to deplete India of much-needed global capital and poses an immediate threat to the broader India story and the journey towards Vikshit Bharat.
AI is a foundational technology as important to human history as the invention of the steam engine, the construction of railroads, the harnessing of electricity, and the mastery of nuclear energy. In the geopolitical structure, a state that does not have sovereign capabilities in basic technology inevitably becomes a vassal state.
If India remains content to simply consume Western and Chinese AI technologies, it risks entering a new era of AI colonization. It’s time to stop building wrappers and start building the machines themselves using the dramatically reimagined Sovereign AI Blueprint (more on that in Part 2 of this series). We must abandon application layer security and fight for a seat at the foundation model, semiconductor, and data center table. Our transition to Vikshit Bharat depends on it.
(Part 1 of a two-part series. The author is Chairman of Hyperion Ventures Corporation, a global AI-driven manufacturing platform focused on semiconductors, rare earth magnets, and electronic components. Views are personal.)
