In India, Coding Dominates AI Use While Global Trends Move Toward Diversity

India’s usage of AI tools—especially Claude.ai—is overwhelmingly dominated by software development tasks, according to the latest Anthropic Economic Index report. Over half of all AI usage in India is in coding, compared to roughly one-third globally, where more developed adopters show greater variety in how they employ AI—across education, science, business, and administrative tasks.

"Users in the United States disproportionately use Claude for household management purposes, to search for jobs, and for medical guidance compared to the global average. By contrast, India’s top disproportionate requests focus almost exclusively on software development," Anthropic said. 

One metric Anthropic introduces, the AI Usage Index (AUI), reveals that India’s AUI is only about 0.27x—meaning India uses Claude less than would be expected relative to its working-age population. Emerging economies like India are lagging in usage per capita, even though they contribute a substantial share of global usage volume.

"Singapore and Canada are among the highest countries in terms of usage per capita at 4.6x and 2.9x what would be expected based on their population, respectively. In contrast, emerging economies, including Indonesia at 0.36x, India at 0.27x and Nigeria at 0.2x, use Claude less," the startup added.

Globally, as countries move up the adoption curve, AI usage tends to shift away from pure automation of technical tasks toward collaborative, learning-oriented tasks. High-adoption regions display usage in sectors like education, arts, administrative support, and sciences. In contrast, in lower-AUI countries such as India, business users and developers lean more heavily on automation and direct problem-solving using code.

Other India-specific findings in the report include that India accounts for about 7.2% of global Claude.ai usage, but this still falls short relative to its large working-age population. The data suggest that infrastructural, economic, awareness, and possibly regulatory factors play a role in how broadly and diversely AI is adopted.