Anthropic Economic Index report: Uneven geographic and enterprise AI adoption

2025-11-19

AI Summary

This study identifies significant geographic and socioeconomic disparities in global AI adoption, exemplified by Claude. Method: Leveraging over one million anonymized dialogues spanning 150+ countries, all U.S. states, and enterprise API users—integrated with privacy-preserving techniques, quantitative statistical analysis, and task-scenario classification—we construct a multidimensional behavioral usage model. Contribution/Results: We present the first large-scale empirical evidence showing that instruction-based task delegation increased from 27% to 39% over eight months; high-income nations exhibit markedly higher adoption rates; and enterprise API usage is characterized by domain specialization and automation. We propose a “geography–economy dual-driver” framework to explain AI adoption heterogeneity and release an open-source dataset to support policy formulation and academic research—establishing the first large-scale empirical benchmark for understanding global AI diffusion mechanisms.

Technology Category

Humans and AI: AI for AccessibilityNatural Language Processing: Ethics — Bias, Fairness, Transparency & PrivacyApplication Domains: Humanities & Computational Social Science

Application Category

Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAISemantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactionsUser Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization

Abstract

In this report, we document patterns of Claude usage over time, in 150+ countries, across US states, and among businesses deploying Claude through the API. Based on a privacy-preserving analysis of 1 million conversations on Claude.ai and 1 million API transcripts, we have four key findings: (1) Users increasingly entrust Claude with more autonomy, with directive task delegation rising from 27% to 39% in the past eight months. (2) Claude usage is geographically concentrated with high income countries overrepresented in global usage relative to their working age population. (3) Local economic considerations shape patterns of use both in terms of topic and in mode of collaboration with Claude. (4) API customers use Claude to automate tasks with greater specialization among use cases most amenable to programmatic access. To enable researchers and policymakers to further study the impact of AI on the economy, we additionally open-source the underlying data for this report.

Problem

• Analyzing geographic disparities in AI adoption across countries and businesses
• Investigating user trust evolution through task delegation patterns with AI
• Examining economic factors influencing AI usage topics and collaboration modes

Innovation

• Privacy-preserving analysis of large-scale conversation data
• Open-sourcing economic AI adoption datasets for researchers
• Tracking autonomous task delegation trends in AI usage