AI & the Labor Market

499 occupations. 5 countries. One methodology.

I scored every major occupation in the Netherlands, the United States, Germany, the United Kingdom and France on AI exposure. Same JPE methodology. Same scale. The data shows: AI changes tasks, not jobs. But not everywhere at the same speed.

499occupations
159M+jobs covered
5countries
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Explore by country

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Netherlands

103 occupations Β· 6M jobs
Avg. AI score
4.9/10
Source
CBS Statline
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United States

106 occupations Β· 91M jobs
Avg. AI score
4.8/10
Source
BLS OEWS 2024
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Germany

98 occupations Β· 29M jobs
Avg. AI score
5/10
Source
Destatis 2024
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United Kingdom

106 occupations Β· 18M jobs
Avg. AI score
4.9/10
Source
ONS ASHE 2024
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France

86 occupations Β· 16M jobs
Avg. AI score
4.8/10
Source
INSEE 2024
The pattern

Software developers score 9/10 on AI exposure in all five countries. They also show the strongest employment growth. Bookkeepers score 8/10 β€” and are declining everywhere. The score is the same. The trajectory depends on whether demand outpaces automation.

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NL Career Scan103 occupations
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US Career Scan106 occupations
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DE Berufsscan98 occupations
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UK Career Scan106 occupations
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FR Career Scan86 occupations
🧭
AI Readiness ScanFor teams & orgs
Cross-country

Same score, different speed

AI exposure is a property of the work, not the country. A bookkeeper processes the same data in Rotterdam, Houston, Munich, London and Paris. What differs is how fast the score translates into actual change.

πŸ‡³πŸ‡± NetherlandsπŸ‡ΊπŸ‡Έ United StatesπŸ‡©πŸ‡ͺ GermanyπŸ‡¬πŸ‡§ United KingdomπŸ‡«πŸ‡· France
Occupations1031069810686
Jobs covered6M91M29M18M16M
Avg JPE4.94.854.94.8
Dampening0.70.70.60.750.6
ClassificationCBS BRC 2014SOC 2018KldB 2010SOC 2020PCS 2020
Read the full international comparison β†’
Research

Go deeper

Five countries comparedSame methodology, different labor markets. Dampening, AI pressure, structural factors.Patterns in the dataTop gainers and decliners, sector risk, the developer paradox, part-time analysis.Methodology (NL/general)JPE scoring rubric, forecast model, Felten AIOE validation (r = 0.87).US methodologyBLS SOC 2018, Felten AIOE normalization, US-specific forecast parameters.DE MethodikKldB 2010, Destatis, Kurzarbeit dampening, Betriebsrat context. German.Will AI take my job?The short answer, the nuanced answer, and what you should actually do.
Open data

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All datasets free under CC BY 4.0. Download, embed, or access via API.

πŸ‡³πŸ‡± NL DatasetπŸ‡ΊπŸ‡Έ US DatasetπŸ‡¬πŸ‡§ UK DatasetπŸ‡©πŸ‡ͺ DE DatasetπŸ‡«πŸ‡· FR DatasetAPI endpoint

JPE = Janssen Practical Exposure. By Simon Janssen, CTO at HappyNurse.