By Amit Kapoor and Anandita Doda
AI as an economic story, not a tech story: where India is strong, where is it hollow?
India has entered the AI era where the technology is moving from experimentation to everyday operations. A McKinsey survey finds that 88% of organisations used AI in at least one business function in 2025, yet only 31% were scaling it and just 7% had fully deployed it, suggesting an economy where AI is easy to try but hard to integrate. This gap between experimentation and integration is where the economic story begins for India.
Globally, AI is diffusing faster than ownership. While many economies are learning to deploy AI at scale, only a few nations, notably the United States and China, are accumulating the compute, capital, and research depth needed to capture most of the economic rents. These two remain the dominant AI superpowers, supported by general purpose models, advanced chips, and deep pools of private capital. The Stanford AI Index Report notes that US-based institutions produced 40 notable AI models in 2024 versus 15 from China, and that the US accounted for $109.1 billion in private AI investment in 2024 a scale advantage that compounds into talent concentration, compute access, and platform dominance. China continues to lead in several volume indicators such as AI publications and patents, reinforcing that the frontier is both technologically and economically concentrated.
Source: Stanford AI Index Report, 2025
India sits differently in this landscape as it has yet to build sovereign frontier models. The country is already a major AI economy by breadth and India’s share of AI publications in computer science reached 9.22% in 2023, comparable to the United States (9.20%). However, AI publications per capita in 2025 are far lower for India (4.45) than the US (22.90) and China (15.16), showing that India’s research intensity is diluted by population scale even when aggregate output looks large. The International Monetary Fund AI Preparedness Index places India at 0.492 (rank 72/174), below China (0.63) and far below the US (0.77), signalling gaps in digital infrastructure, innovation depth, and governance capacity that make scaling harder than piloting.