The AI Risk Index: How We Score 997 Jobs
Search any occupation and see its full risk profile. An interactive deep dive into our 6-dimension scoring model, the composite formula, and how 997 jobs distribute across the AI displacement spectrum.
The AI Risk Index is a composite scoring system that analyzes every occupation in the U.S. economy for AI displacement risk. It synthesizes research from 12 institutions, maps it across 6 measurable dimensions, and produces a single score from 1 to 10 for each of 997 occupations.
This isn't a prediction about when your job will disappear. It's a structural analysis of how vulnerable the job's core tasks, cognitive requirements, and work environment are to current and near-term AI capabilities — weighted against the factors that protect it.
997
Occupations Scored
12
Research Institutions
6
Risk Dimensions
Search the Index
Type any job title below to see its composite AI risk score and full 6-dimension breakdown. The radar chart shows how each dimension contributes to the overall risk profile.
Type a job title above to see its AI risk profile and dimensional breakdown.
How 997 Jobs Distribute Across the Risk Spectrum
The distribution is not uniform — it tells a story about the structure of work in the U.S. economy. Most jobs cluster in the moderate range, but a significant tail extends into high and critical risk territory. Toggle between the score histogram and category breakdown to explore the data.
4.6
Mean Score
4.3
Median Score
15.8%
High Risk (7+)
23.3%
Low Risk (<3)
The 6 Dimensions of AI Risk
Every occupation is analyzed across six independent dimensions. Three measure vulnerability — how exposed the job is to AI automation. Three measure resilience — structural factors that protect it.
Click any dimension below to see exactly what it measures, which data sources feed it, and how different jobs score on that specific factor.
The Composite Formula
The six dimension scores are combined into a single composite using a weighted formula. Vulnerability factors push the score up; resilience factors push it down. The result is calibrated to a 1–10 scale where higher means more vulnerable to AI displacement.
Composite Formula
Vulnerability − Resilience = AI Risk Score (1–10)
Task Automation + Cognitive Exposure + Physical Vulnerability, weighted against Creativity + Social Intelligence + Regulatory Barriers
Worked Example: Financial Analyst
Task Automation
7.2
Cognitive Exposure
7.8
Physical Req.
1.2
Creativity
4.5
Social Intel.
5.2
Regulatory
3.0
Vulnerability (7.2 + 7.8 + 8.8) − Resilience (4.5 + 5.2 + 3.0) = weighted composite
6.3 / 10 — Elevated Risk
12 Data Sources In Depth
Our scoring model doesn't rely on a single study or methodology. It synthesizes findings from 12 research institutions — spanning government labor statistics, peer-reviewed academic research, international economic organizations, and AI capability labs. Here's what each provides:
U.S. Department of Labor O*NET
997 occupation profiles with task descriptions, skill requirements, and work activities
Feeds: Task Automation, Cognitive Exposure, Physical Requirement
Bureau of Labor Statistics
Employment counts, median/mean wages, 10-year growth projections via OES API v2
Feeds: Report enrichment — live employment & wage data
Frey & Osborne (Oxford)
Automation probability estimates for 702 occupations, updated methodology
Feeds: Task Automation Potential calibration
OpenAI "GPTs are GPTs"
Task-level LLM exposure analysis mapping AI capabilities to job requirements
Feeds: Cognitive AI Exposure scoring
Felten AI Occupational Exposure Index
AI capability mapping to occupational requirements across 10 AI application areas
Feeds: Cross-validation of Task Automation and Cognitive Exposure
World Economic Forum
Future of Jobs Report 2025 — employer surveys across 46 countries, 800+ companies
Feeds: Creativity Demand, Social Intelligence trending
McKinsey Global Institute
800+ occupations analyzed at activity level across 46 countries
Feeds: Task Automation, Physical Requirement benchmarks
OECD Employment Outlook
G20 labor market analysis, policy frameworks, automation risk by education level
Feeds: Regulatory Barriers, cross-country calibration
ILO Global Task Index
30,000 tasks with 50,000 human evaluations of automation susceptibility
Feeds: Task Automation granular validation
IMF GenAI Analysis
40% global employment exposure study across 108 countries
Feeds: Cognitive Exposure global calibration
Stanford HAI
AI Index Report tracking human-centered AI capability benchmarks year over year
Feeds: Cognitive AI Exposure trending
Brookings Institution
36M U.S. workers exposure analysis with metropolitan-level granularity
Feeds: Regional exposure, Social Intelligence analysis
From Raw Data to Your Report
The journey from raw research data to a personalized career risk report involves six stages. Click each stage below to see exactly what happens and which systems are involved.
Transparency & Limitations
No scoring model is perfect. Here's what ours captures well and where its limitations lie:
What It Captures
- ✓ Structural vulnerability of job tasks to current AI
- ✓ Multi-dimensional analysis beyond simple automation probability
- ✓ Resilience factors that protect jobs (not just risk)
- ✓ Cross-validated against 12 independent methodologies
- ✓ Relative ranking of 997 occupations against each other
Limitations
- ⚠ Static snapshot — AI capabilities evolve faster than scores update
- ⚠ U.S.-centric occupation definitions may not perfectly map globally
- ⚠ Industry-specific context varies (a nurse in research vs. patient care)
- ⚠ Doesn't capture company-level adoption speed or policy changes
- ⚠ Composite score compresses 6 dimensions into one number
Where Does Your Job Rank?
Get your personalized AI risk report — with task-by-task analysis, career pivot plan, skills roadmap, and real-time labor market data.
Check Your Risk Score →Free score preview. Full report $29.99.