AI Income Risk · Real Estate

Plzeňský kraj

ProofIndex score 60/100 (High Risk) · medium confidence

ProofIndex score: 60/100 — High Risk risk.

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

Plzeňský kraj (Czech Republic) ranks among the higher-risk markets ProofIndex tracks, with a ProofIndex score of 60/100 (High Risk). The biggest contributor is housing leverage — how leveraged local mortgage borrowers are — loan-to-value, debt-to-income, and price-to-income.

Key risk drivers

Resilience Factors — 78/100
Local economic cushioning — savings, benefits, and job diversity that absorb an income shock.
Housing Leverage — 72/100
How leveraged local mortgage borrowers are — loan-to-value, debt-to-income, and price-to-income.
Income Concentration — 69/100
How concentrated local income is in higher-paid, AI-exposed work.
Employment Vulnerability — 63/100
How exposed local jobs are to AI automation, based on the area’s occupation mix.

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 — ČSÚ — VŠPS
Labour Force Survey occupation mix · Official statistics · Regional · vintage 2024. Occupation mix is direct at regional level; smaller districts may inherit and adjust regional structure.
Income Concentration — ČSÚ — Czech Statistical Office
Czech statistical indicators · Official statistics · Regional / district · vintage 2024-2025. Official regional data; some district-level housing inputs are modelled from available market and labor indicators.
Housing Leverage — ČSÚ — Czech Statistical Office
Czech statistical indicators · Official statistics · Regional / district · vintage 2024-2025. Official regional data; some district-level housing inputs are modelled from available market and labor indicators.
Rental Market Exposure — ČSÚ — Czech Statistical Office
Czech statistical indicators · Official statistics · Regional / district · vintage 2024-2025. Official regional data; some district-level housing inputs are modelled from available market and labor indicators.
Resilience Factors — ČSÚ — Czech Statistical Office
Czech statistical indicators · Official statistics · Regional / district · vintage 2024-2025. Official regional data; some district-level housing inputs are modelled from available market and labor indicators.

Frequently asked questions

Is Plzeňský kraj at risk from AI job losses?

Relative to other Czech Republic markets, yes — Plzeňský kraj ranks among the higher-risk markets ProofIndex tracks. It scores 60/100 (High Risk) overall, and 63/100 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 Plzeňský kraj housing market to AI automation?

Plzeňský kraj scores 60/100 (High 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 housing leverage at 72/100 — how leveraged local mortgage borrowers are — loan-to-value, debt-to-income, and price-to-income. Housing leverage — loan-to-value, debt-to-income, and price-to-income among local borrowers — scores 72/100. Local resilience — savings, benefits, and job diversity that absorb an income shock — scores 78/100 and pulls the composite down. Scores are normalized 0–100 within Czech Republic, so this ranks Plzeňský kraj against other Czech Republic markets rather than against markets abroad.

Why is Plzeňský kraj rated High Risk?

High Risk is the risk tier ProofIndex assigns to a composite score of 60/100. The composite weights employment vulnerability at 35%, income concentration at 25%, housing leverage at 25%, and subtracts local resilience at 15%. For Plzeňský kraj the risk pillars rank housing leverage 72/100, income concentration 69/100, employment vulnerability 63/100. Confidence in the underlying data for this area is medium.

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