Feb 2026 · 178 Countries · 923 Occupations

Mapping AI adoption across the global economy

GAIA synthesizes behavioral data from Anthropic's Economic Index, OpenAI's occupational exposure ratings, and Brynjolfsson et al.'s machine-learning suitability scores to track how AI is reshaping work worldwide.

178
Countries tracked
via Claude.ai behavioral data
923
Occupations rated
O*NET-SOC standard codes
70%
Global task-success rate
across all Claude.ai requests
34.5%
Avg AI exposure
across all occupations (beta)

Work is the leading use case — ahead of personal and coursework

Nearly half of all Claude.ai requests in February 2026 were work-related. Personal use follows at 42%, and educational use accounts for 12% — signaling that AI has already crossed from experimentation into daily professional workflows.

  • 45.2%
    Work
  • 42.3%
    Personal
  • 12.4%
    Coursework

Which jobs are most — and least — exposed to AI?

AI-rated exposure (beta) estimates the share of tasks within an occupation that AI can meaningfully assist with. Knowledge-intensive roles lead; physical and service roles trail.

Highest AI exposure
Mathematicians
100%
Proofreaders & Copy Markers
98%
Blockchain Engineers
97%
Correspondence Clerks
96%
Court Reporters
96%
Lowest AI exposure
Athletes & Sports Competitors
0%
Orderlies
0%
Cooks, Fast Food
0%
Cooks, Short Order
0%
Dining Room Attendants
0%
Browse all 923 occupations →

How people collaborate with AI at work

Claude.ai logs show six distinct collaboration modes. Directive use — giving direct instructions to complete tasks — dominates, followed by task iteration and learning.

32.6%
Directive
User issues explicit instructions for AI to execute
25.6%
Task Iteration
Refining outputs through back-and-forth exchanges
22.4%
Learning
Using AI to build understanding or gain knowledge
11.5%
Feedback Loop
Giving AI structured feedback to improve responses
4.9%
Validation
AI checks or confirms human-generated work
3.0%
None / Other
Unclassified or minimal interaction patterns

Built on open, peer-reviewed data

GAIA combines three complementary datasets — real-world AI usage behavior, occupational AI exposure ratings, and crowd-sourced machine-learning suitability scores from academic research.

Anthropic Economic Index

Behavioral data from Claude.ai across 178 countries, covering task success, collaboration modes, autonomy levels, and use-case classification. Release: Feb 5–12, 2026.

1M+ requests analyzed

OpenAI Occupational Exposure

AI and human expert ratings of occupational task exposure across 923 O*NET-SOC codes, using alpha (high), beta (moderate), and gamma (any) exposure tiers.

923 occupations rated

SML — What Can Machines Learn?

Crowd-sourced susceptibility to machine learning (SML) scores at the task level, aggregated to 813 occupations via O*NET DWA ratings. Brynjolfsson, Mitchell & Rock (2018).

813 occupations scored

IMF AI Preparedness Index

Country-level composite index measuring readiness for AI adoption across four pillars: digital infrastructure, innovation & economic integration, human capital, and regulation. IMF 2023.

174 countries scored

Google Trends — AI Awareness

Weekly "ChatGPT" search interest from Nov 2022 to Apr 2026 for the top 20 countries by Claude.ai usage. Reveals the AI awareness shock wave spreading globally after ChatGPT's launch.

20 countries · 183 weeks

Gallup World Poll — AI Sentiment

Public attitudes toward AI across 119 countries: share who believe AI will mostly help vs. mostly harm society. Net optimism scores from the 2021 Gallup wave via Our World in Data.

119 countries · 2021

OECD.AI — Policy Initiatives

Total number of national AI policy initiatives per country tracked by the OECD AI Policy Observatory, including strategies, regulations, and recommendations. Data as of 2024.

138 countries · OECD.AI 2024

Eurostat — Firm AI Adoption

Share of enterprises with 10+ employees using AI technologies, from the Eurostat ICT survey. Covers 33 European countries with data for 2021, 2023, and 2024.

33 EU countries · Eurostat 2024