India stands at an inflection point in Artificial Intelligence (AI). The debate is often framed as a binary choice: Should India invest in building its own large language models (LLMs), or should it simply build AI applications on top of models developed elsewhere? This is the wrong question. The right strategy is not “build versus use.” It is “build enough to remain technologically sovereign while winning commercially at the platform and application layers.”

There is little doubt that the greatest commercial opportunity over the next five years lies above the foundation model layer. Intelligent model routing, enterprise AI infrastructure, trusted data platforms, multimodal AI, edge deployment, and domain-specific systems for health care, agriculture, education, manufacturing, finance, etc, will create enormous value. These are areas where India enjoys significant structural advantages: world-class engineering talent, Digital Public Infrastructure, cost-efficient innovation, and access to large, real-world datasets.

However, it would be a profound strategic mistake to conclude that India can dominate these higher layers without investing seriously in foundational AI research. Every major breakthrough in the next generation of AI — reasoning models, autonomous agents, neuro-symbolic systems, and architectures that may eventually succeed today’s transformers — will emerge from deep understanding of current foundation models. No nation can leapfrog technologies it has never mastered. The organisations that define tomorrow’s AI will be those that understand today’s AI. I know this from 50 years of my own experience in semiconductor technologies; Today’s semiconductor miracles could not exist without 50 years of foundational learning. Every innovation at the frontier of semiconductors today is not a departure from the past — it is the past,........

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