O*NET
Occupation taxonomy, task statements, skills and task importance
CC BY 4.0Periodic releases
Source ↗US-first · AI Impact Monitor
AI Jobs & Work Monitor
A living view of how AI is changing work in the real economy — combining structural task exposure with observed AI use, hiring pressure, entry-level access, wages and skill demand. The goal is not to predict whether a job “dies.” It is to show what is changing, how strong the evidence is, and what to watch next.
Occupation lookup · two independent exposure views
How much is AI touching the job — and how exposed is it relative to others?
Search observed professional usage from Anthropic alongside the official BLS five-source category. One measures current task coverage; the other compares relative exposure across occupations. Both are evidence — neither is a job-loss probability.
Loading verified occupation evidence and stored U.S. labor context…
Source architecture
Built from open evidence, not a single black box.
The first U.S. version is designed around public or openly licensed sources so the core product can remain inexpensive, reproducible and highly automated.
U.S. Bureau of Labor Statistics
Employment, wages, projections and official five-source AI exposure categories
U.S. government public dataMonthly / annual by dataset
Source ↗U.S. Census Bureau — BTOS
Business adoption and operating-condition evidence, including AI use
U.S. government public dataHigh-frequency releases
Source ↗Anthropic Economic Index
Observed AI task usage, automation and augmentation evidence
CC BY data / MIT code where publishedVersioned dataset releases
Source ↗AI Risk Index
Optional external structural occupation exposure, substitution and augmentation scores
CC BY 4.0 for scores and derived data; attribution + version requiredVersioned index releases; API availability may vary
Source ↗Stanford Digital Economy Lab — Canaries Dashboard
Early-career employment evidence in AI-exposed occupations
Use as cited research evidence; verify terms per releaseUpdated research dashboard
Source ↗How the monitor thinks
From exposure to real-world change.
A high structural score alone is not a forecast of unemployment. The monitor deliberately separates capability from adoption and realized labor-market outcomes.
01Structural exposure
How exposed are the occupation's tasks to current AI capability?
02Observed AI use
Is AI actually being used for those tasks in the real economy?
03Labor-market pressure
Are hiring, entry-level access, wages or skill premiums changing?
04Interpretation
Is the role being substituted, augmented, reorganized — or is the evidence still weak?
05Watch next
Which next data point would materially change the current picture?
No synthetic “job loss probability” will be shown unless the underlying evidence supports it. When evidence is incomplete, the product says so.