AI Income Risk · Real Estate
Praha-východ
ProofIndex score 81/100 (Critical) · medium confidence
ProofIndex score: 81/100 — Critical risk.
Scoring period 2026-Q2 · medium confidence in the underlying data
Praha-východ (Czech Republic) ranks among the higher-risk markets ProofIndex tracks, with a ProofIndex score of 81/100 (Critical). 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
- Housing Leverage — 98/100
- How leveraged local mortgage borrowers are — loan-to-value, debt-to-income, and price-to-income.
- Income Concentration — 87/100
- How concentrated local income is in higher-paid, AI-exposed work.
- Employment Vulnerability — 86/100
- How exposed local jobs are to AI automation, based on the area’s occupation mix.
- Resilience Factors — 66/100
- Local economic cushioning — savings, benefits, and job diversity that absorb an income shock.
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 — ProofIndex model
- Interpolated regional proxy · Proxy · Sub-regional · vintage 2026-Q1. Used where direct local measurement is unavailable; treat as directional rather than precise.
- Income Concentration — ProofIndex model
- Interpolated regional proxy · Proxy · Sub-regional · vintage 2026-Q1. Used where direct local measurement is unavailable; treat as directional rather than precise.
- Housing Leverage — ProofIndex model
- Interpolated regional proxy · Proxy · Sub-regional · vintage 2026-Q1. Used where direct local measurement is unavailable; treat as directional rather than precise.
- Rental Market Exposure — ProofIndex model
- Interpolated regional proxy · Proxy · Sub-regional · vintage 2026-Q1. Used where direct local measurement is unavailable; treat as directional rather than precise.
- Resilience Factors — ProofIndex model
- Interpolated regional proxy · Proxy · Sub-regional · vintage 2026-Q1. Used where direct local measurement is unavailable; treat as directional rather than precise.
Frequently asked questions
Is Praha-východ at risk from AI job losses?
Relative to other Czech Republic markets, yes — Praha-východ ranks among the higher-risk markets ProofIndex tracks. It scores 81/100 (Critical) overall, and 86/100 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 Praha-východ housing market to AI automation?
Praha-východ scores 81/100 (Critical) 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 98/100 — 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 98/100. Local resilience — savings, benefits, and job diversity that absorb an income shock — scores 66/100 and pulls the composite down. Scores are normalized 0–100 within Czech Republic, so this ranks Praha-východ against other Czech Republic markets rather than against markets abroad.
Why is Praha-východ rated Critical?
Critical is the risk tier ProofIndex assigns to a composite score of 81/100. The composite weights employment vulnerability at 35%, income concentration at 25%, housing leverage at 25%, and subtracts local resilience at 15%. For Praha-východ the risk pillars rank housing leverage 98/100, income concentration 87/100, employment vulnerability 86/100. Confidence in the underlying data for this area is medium.
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Other Czech Republic markets
- Hlavní město Praha — 86/100
- Praha-západ — 82/100
- Brno-venkov — 80/100
- Brno-město — 78/100
- Jihomoravský kraj — 78/100
- Mladá Boleslav — 77/100