India ranks low on Claude usage, but leads in coding and job-related tasks: Anthropic report

India's engagement with Anthropic’s Claude AI tool is currently trailing behind global usage levels, yet the focus of its application reveals a distinct inclination towards coding and productivity enhancement. As highlighted in Anthropic’s recent Economic Index report, which analyzed Claude usage in February 2026, India ranks 98th out of 116 countries, showcasing a usage index of just 0.28x compared to a global average of 1x. Despite this relatively low adoption rate, Indian users are making their mark with specific use cases. The primary application of AI in India is centered on developing, debugging, and modifying websites and web applications, which constitutes 6.7% of total usage. Other notable applications include academic assistance at 3.8%, the development of business software at 3.4%, troubleshooting technical systems at 3.4%, and the creation of marketing and SEO content at 3.0%. The report further reveals that India excels in certain tasks, surpassing global averages significantly. For instance, web development activities are 1.9 times more prevalent, while support for resumes and job applications is 1.8 times higher. Additionally, programming tasks are engaged in 1.6 times more, UI/UX and design work 1.5 times more, and code debugging 1.4 times more than the average worldwide. A notable trend highlighted in the report is the widening gap in AI utilization across the globe. Anthropic's findings indicate that seasoned users, predominantly skilled technical professionals, are leveraging tools like Claude more proficiently. These individuals are able to collaborate more effectively with AI, assign complex tasks, and achieve superior outcomes as they continue to engage with these technologies. This phenomenon, termed “learning-by-doing,” suggests that increased interaction with AI leads to improved proficiency. However, this trend also signals a significant shift in labor markets. The very group of skilled workers most susceptible to disruption from AI advancements is simultaneously gaining the most from early adoption. The report indicates that this could potentially expedite “skill-biased technological change,” wherein those adept at utilizing AI advance more rapidly, leaving others behind in the race to keep up.