Build With AI in India

In India, 19.31% of sampled conversations were matched to education & learning tasks. In Korea that figure is 11.21%.

What the data says about India

The number that upends the usual assumptions is 0.3. India’s Anthropic Usage Index sits at 102 of 121 countries — by raw usage, barely on the chart. Korea, for comparison, posts 3.78. If you stopped there, you’d expect India’s conversations to be shallow or tentative. They are not. The mix of what actually gets asked is one of the most technically concentrated in the dataset: 16.22% of sampled conversations are matched to software development tasks, against a global average of 11.51%, and 19.31% match education and learning, against 13.23% globally. Low volume, high density. Whatever is limiting overall usage — access, cost, device mix, language coverage — it is not a lack of serious intent.

The Korea comparison makes this concrete. On education and learning, India’s share runs 72.3% higher than Korea’s (19.31% versus 11.21%). On software development, 55.7% higher (16.22% versus 10.42%). Korea uses these tools far more overall, yet a larger fraction of India’s conversations are aimed squarely at code and at learning. That is the part a simple rich-country/poor-country ranking would never predict.

The task-level detail fills in the picture. Conversations matched to coursework make up 19.95% of India’s traffic versus 16.45% globally, and the job-task category of educational instruction and library work also over-indexes at 14.85% against 12.79%. Read carefully — this describes what the conversations looked like, not who was having them. The honest reading is that these tools are being used as a study partner and a working reference at an unusual rate. Meanwhile, hobbies and lifestyle conversations come in at 5.7%, about 40% below the global 9.49%. Casual, exploratory chat is comparatively rare; the sessions skew instrumental.

Two more signals support that. Work-related conversations are 44.14%, essentially the global 43.36% — so this is not a population dabbling outside work hours. And the automation-versus-augmentation split leans toward automation at 51.87% to 48.13%, while globally it tips the other way at 48.62%. People are handing over concrete tasks and asking for finished output, not just a second opinion. A plausible guess: when each session carries more weight, it gets spent on deliverables — a draft, a script, a working function.

Which is exactly the kind of work Seunghan likes to dig into. If you’re in India and building something with AI, he offers free, informal help — no pitch, no programme. Getting an app actually shipped to the App Store or Play Store, wiring up AI agents and MCP tooling, backend and auth design, mobile development, and the reliability work that keeps a service standing after launch. India is a few hours behind Seoul, so working hours overlap comfortably. Bring the thing you’re stuck on.

The numbers

Most common request topics

Job-task categories these conversations matched

Where India is ahead of Korea

• Education & Learning — 19.31% here, 11.21% in Korea (72.3% higher)
• Software Development — 16.22% here, 10.42% in Korea (55.7% higher)

Ask me something

I’m Seunghan, an engineer in Seoul. I answer questions about shipping apps, AI agent tooling, backends, and reliability — free, and for anyone. Here’s what I can help with and why.

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