AI Income Risk · Real Estate

Groningen

ProofIndex score 37/100 (Low Risk) · medium confidence

ProofIndex score: 37/100 — Low Risk risk.

Scoring period 2026-Q2 · medium confidence in the underlying data

Groningen (Netherlands) is relatively insulated in ProofIndex’s scoring, with a ProofIndex score of 37/100 (Low Risk). The biggest contributor is employment vulnerability — how exposed local jobs are to AI automation, based on the area’s occupation mix.

Key risk drivers

Employment Vulnerability — 69/100
How exposed local jobs are to AI automation, based on the area’s occupation mix.
Resilience Factors — 51/100
Local economic cushioning — savings, benefits, and job diversity that absorb an income shock.
Housing Leverage — 20/100
How leveraged local mortgage borrowers are — loan-to-value, debt-to-income, and price-to-income.
Income Concentration — 4/100
How concentrated local income is in higher-paid, AI-exposed work.

Where this score comes from

Every ProofIndex pillar is computed from published statistics. These are the sources behind this area's score, with the vintage of each and the limitation we know about it.

Employment Vulnerability — CBS — Statistics Netherlands
Dutch occupation classification · Official statistics · Province · vintage 2024. Direct province-level occupation data; COROP areas may inherit adjusted province mix.
Income Concentration — CBS — Statistics Netherlands
Dutch official regional statistics · Official statistics · Province / COROP · vintage 2024-2025. Official national statistics; COROP-level values may combine direct series with derived regional ratios.
Housing Leverage — CBS — Statistics Netherlands
Dutch official regional statistics · Official statistics · Province / COROP · vintage 2024-2025. Official national statistics; COROP-level values may combine direct series with derived regional ratios.
Rental Market Exposure — CBS — Statistics Netherlands
Dutch official regional statistics · Official statistics · Province / COROP · vintage 2024-2025. Official national statistics; COROP-level values may combine direct series with derived regional ratios.
Resilience Factors — CBS — Statistics Netherlands
Dutch official regional statistics · Official statistics · Province / COROP · vintage 2024-2025. Official national statistics; COROP-level values may combine direct series with derived regional ratios.

Frequently asked questions

Is Groningen at risk from AI job losses?

Less than most — Groningen is relatively insulated among the Netherlands markets ProofIndex tracks. It scores 37/100 (Low Risk) overall, and 69/100 on employment vulnerability — how much of the local occupation mix overlaps with work today’s AI can already do. ProofIndex measures how exposed local incomes are, not how many jobs will go: a higher score means more of the local wage base sits in work that AI is changing.

How exposed is the Groningen housing market to AI automation?

Groningen scores 37/100 (Low Risk) on ProofIndex, which blends how exposed local incomes are to AI with how leveraged the local housing market is. The largest single contributor is employment vulnerability at 69/100 — how exposed local jobs are to AI automation, based on the area’s occupation mix. Housing leverage — loan-to-value, debt-to-income, and price-to-income among local borrowers — scores 20/100. Local resilience — savings, benefits, and job diversity that absorb an income shock — scores 51/100 and pulls the composite down. Scores are normalized 0–100 within Netherlands, so this ranks Groningen against other Netherlands markets rather than against markets abroad.

Why is Groningen rated Low Risk?

Low Risk is the risk tier ProofIndex assigns to a composite score of 37/100. The composite weights employment vulnerability at 35%, income concentration at 25%, housing leverage at 25%, and subtracts local resilience at 15%. For Groningen the risk pillars rank employment vulnerability 69/100, housing leverage 20/100, income concentration 4/100. Confidence in the underlying data for this area is medium.

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Full pillar breakdowns, peer benchmarking, and data sources with confidence ratings.

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