Anthropic AI Usage Index

Anthropic AI Usage Index

The Anthropic AI Usage Index (AUI) measures whether Claude is over- or underrepresented in a geography relative to that geography’s working-age population.

Key points

  • An AUI above 1 means a country or region uses Claude more intensively than its share of working-age population would predict; below 1 means lower-than-expected usage [src-069].
  • Global Claude.ai usage remains uneven and strongly associated with GDP per capita [src-069, src-070].
  • At country level, a 1% increase in GDP per capita is associated with a 0.7% increase in Claude usage per capita [src-069].
  • Within the US, workforce composition matters more than income: states with more computer and mathematical workers tend to have higher usage [src-069].
  • US state-level usage became more evenly distributed from August to November 2025, with a cautious 2-5 year convergence estimate if the pattern persists [src-069, src-070].
  • Globally, there was no clear sign of low-use countries catching up or high-use countries pulling away [src-069].
  • Anthropic’s public summary adds a use-case interpretation: lower-income countries skew toward educational coursework, while higher-income countries show more work and personal use [src-070].
  • The March 2026 report updates the convergence picture: US state-level usage kept converging, but the equalization estimate slowed from 2-5 years to 5-9 years [src-071].
  • Across countries, usage became slightly more concentrated: the top 20 countries’ share of population-adjusted usage rose from 45% to 48% [src-071].

Related entities

Related concepts

Source references

  • [src-069] Anthropic – “Anthropic Economic Index report: Economic primitives” (2026-01-15)
  • [src-070] Anthropic – “Anthropic Economic Index: New building blocks for understanding AI use” (2026-01-15)
  • [src-071] Anthropic – “Anthropic Economic Index report: Learning curves” (2026-03-24)

Robin Cartier perspective

This page is part of Robin Cartier's working AI knowledge graph: a practical research layer for production AI, recommendation systems, experimentation, GEO, and agentic web readiness.

The useful next step is to connect this concept back to applied product leadership and operating models.

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