Dario Amodei and the Rise of AI in India: A Deep Dive into Claude.ai Usage

Dario Amodei and the Expanding AI Landscape in India

India, already a global leader in IT services exports, is experiencing a rapid surge in its AI user base. Understanding the nuances of AI adoption in India – and how it differs from other nations – is crucial for shaping effective AI policies, attracting investment, and driving successful deployment. This article delves into the usage of Claude.ai in India, drawing on data from the fourth Anthropic Economic Index report, analyzing approximately 1 million Claude.ai conversations globally during November 2025.

India’s Position in the Global Claude.ai Ecosystem

India accounts for 5.8% of total Claude.ai usage, securing the second position worldwide, trailing only the United States. However, current adoption remains concentrated, presenting significant opportunities to broaden access across the population. The data reveals a user base that heavily applies AI in professional settings, delegates substantial autonomy to it, and utilizes Claude.ai for tasks that are considerably more time-consuming without AI assistance. This suggests Indian users are pushing the boundaries of the technology, tackling complex problems that would be difficult or impossible to solve independently.

Per Capita Usage and Regional Concentration

While India ranks second in overall Claude.ai usage, its per capita adoption rate (101st out of 116 countries) lags behind other Asian nations like Singapore and Malaysia. This disparity highlights that India’s high overall usage is largely driven by its massive population size, rather than widespread individual adoption. This presents a clear pathway for growth.

AI usage is heavily concentrated in a few key states: Maharashtra, Tamil Nadu, Karnataka, and Delhi account for over half of India’s total Claude.ai activity. This pattern mirrors the country’s IT sector geography and urban economic output, indicating that current AI adoption is primarily fueled by India’s established technology workforce.

Professional Focus: Software Development and Engineering

The occupational profile of Indian Claude.ai users, inferred from task mapping, strongly leans towards software development and engineering roles – a reflection of India’s robust IT services sector. India leads globally in the proportion of AI usage dedicated to software-related tasks (45.2% of all O*NET-mapped tasks), surpassing Vietnam (42.1%) and Egypt (39.2%). Educational applications also feature prominently, indicating a significant use case in learning and instruction.

Economic Primitives: Productivity, Autonomy, and Complexity

Anthropic’s Economic Index introduces “economic primitives” – fundamental measurements of human-AI collaboration. Comparing India to the global average reveals compelling patterns:

Productivity Speedup: Indian users experience a 15x speedup in task completion with AI (tasks taking 14.8 minutes with AI versus 3.8 hours without), compared to a 12x speedup globally.
Work Orientation: 51.3% of Indian Claude.ai use is work-related, compared to 46% globally.
AI Autonomy: Indian users delegate more decision-making autonomy to AI (3.60 on a 1-5 scale) than their global counterparts (3.38).
Human-Only Ability: 84.6% of tasks could be completed by a human alone, suggesting Indian users frequently leverage AI for tasks they couldn’t easily accomplish independently.

The Importance of Prompting Skills and Future Growth

The quality of prompts significantly impacts the quality of AI outputs. India ranks in the top 10% globally in terms of AI education level of responses, indicating that Indian users are receiving sophisticated outputs from Claude.ai. However, broadening AI’s economic impact requires expanding beyond software and IT services. Addressing structural barriers related to income, digital infrastructure, and awareness outside the IT sector is crucial for unlocking wider adoption.

Investing in AI skills, particularly for workers outside the current IT-heavy user base, could yield substantial returns. Training programs focused on effective AI use can meaningfully improve the benefits of wider AI adoption.

Methodology

This analysis is based on privacy-preserving data from Claude.ai consumer use between November 13-20, 2025, as detailed in the fourth Anthropic Economic Index report. Geographic assignment utilizes IP-based geolocation, while occupation and task classification are based on mappings to the O*NET task taxonomy and SOC occupation groups. For country-level rankings, only countries with at least 200 observations are included. The data encompasses Claude.ai Free, Pro, and Max usage. For a comprehensive overview of the methodology, global findings, and time-series analysis, refer to the Anthropic Economic Index January 2026 report.

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