Data · Methodology
How the AI Automation Index is built.
Every risk score on this site is the output of a documented model. Here's the math, the sources, and the caveats that matter when you interpret the numbers.
Tiers
How we bucket risk.
Every role is assigned one of four tiers by the composite risk score. Tiers are presented alongside an expected horizon for when the shift begins to land materially.
High probability of significant automation within the near term.
Substantial automation likely across most task categories.
Partial automation with meaningful human-in-the-loop remaining.
Minimal automation threat for the foreseeable horizon.
Sources
The primary inputs.
WEF Global Future of Jobs Report
Annual survey of 800+ companies across 50+ countries on job creation and displacement, with employment impact forecasts by role and region.
Goldman Sachs — Generative AI and the Future of Work
Research on generative AI's potential impact on labor markets. Estimates 300M full-time-equivalent jobs could be affected by automation.
O*NET Occupational Data
US Department of Labor occupational database with detailed task, skill, and ability requirements for 900+ occupations.
BLS Employment Projections
Ten-year employment projections, wage data, and labor-market statistics for every major occupation.
IMF — Technology and Inequality
International analysis of how AI adoption varies by country, region, and development level.
Academic research
Peer-reviewed studies from leading institutions on automation, AI, labor economics, and workforce disruption.
Caveats
Read the fine print.
- 01
Risk percentages are estimates based on available data. New developments can change risk levels significantly.
- 02
The model focuses on technical automatability, not economic feasibility or regulatory constraints.
- 03
Individual job security depends on factors beyond automation risk — industry growth, salary, and geography all matter.
- 04
This analysis should inform career planning, not replace judgment in a major career decision.
- 05
Historical technological disruption consistently creates new opportunities — though transitions can be painful.