AI Income Risk · Real Estate

Illinois

ProofIndex score 62/100 (High Risk) · medium confidence

ProofIndex score: 62/100 — High Risk risk.

Scoring period 2026-Q2 · medium data confidence

Illinois (United States) ranks among the higher-risk markets covered by ProofIndex, with a ProofIndex score of 62/100 (High Risk). The biggest contributor is income concentration. This measures how concentrated local income is in higher-paid, AI-exposed work.

Key risk drivers

Resilience Factors — 80/100
Local economic buffers such as savings, benefits, and job diversity that can absorb an income shock.
Income Concentration — 78/100
How concentrated local income is in higher-paid, AI-exposed work.
Employment Vulnerability — 71/100
How exposed local jobs are to AI automation, based on the area’s occupation mix.
Housing Leverage — 57/100
How leveraged local mortgage borrowers are, based on loan-to-value, debt-to-income, and price-to-income.

Where this score comes from

Every ProofIndex pillar uses published statistics. Review the sources behind this area's score, when each was released, and its known limitations.

Modeled EVI limitation: US Employment Vulnerability (EVI) is modeled, not directly measured. It is inferred from ACS sector and education patterns rather than direct BLS OEWS occupation employment. Because EVI contributes 35% of the score, treat this component as directional.

Employment Vulnerability — US Census Bureau + ProofIndex model
Derived ACS occupation proxy · Proxy · State · vintage 2020-2024 ACS 5-year. Occupation exposure is inferred from sector and education signals, not direct OEWS occupation employment.
Income Concentration — US Census Bureau — ACS 5-year
ACS state indicators · Official statistics · State · vintage 2020-2024 ACS 5-year. Official survey data; state-level values can hide MSA-level concentration.
Housing Leverage — Zillow Research
Zillow home value index · Market data · State · vintage May 2026 file release. Market data series; rental and mortgage stress inputs may be derived from home-value and income relationships.
Rental Market Exposure — Zillow Research
Zillow home value index · Market data · State · vintage May 2026 file release. Market data series; rental and mortgage stress inputs may be derived from home-value and income relationships.
Resilience Factors — US Department of Labor ETA
US safety-net parameters · Official statistics · State · vintage 2026. Statutory and public program parameters; savings and absorption are still proxy estimates.

Frequently asked questions

Is Illinois at risk from AI job losses?

Yes. Illinois ranks among the higher-risk United States markets covered by ProofIndex. It scores 62/100 (High Risk) overall, and 71/100 on employment vulnerability, which measures how much local work overlaps with tasks 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 comes from work that AI is changing.

How exposed is the Illinois housing market to AI automation?

Illinois scores 62/100 (High Risk) on ProofIndex, which blends how exposed local incomes are to AI with how leveraged the local housing market is. The largest contributor is income concentration at 78/100. This measures how concentrated local income is in higher-paid, AI-exposed work. Housing leverage scores 57/100, based on loan-to-value, debt-to-income, and price-to-income among local borrowers. Local resilience scores 80/100. Savings, benefits, and job diversity reduce the final score. Scores are normalized 0–100 within United States, so this compares Illinois with other United States markets. It cannot be compared directly with markets abroad.

Why is Illinois rated High Risk?

High Risk is the risk tier ProofIndex assigns to a composite score of 62/100. The composite weights employment vulnerability at 35%, income concentration at 25%, housing leverage at 25%, and subtracts local resilience at 15%. For Illinois the risk pillars rank income concentration 78/100, employment vulnerability 71/100, housing leverage 57/100. Confidence in the underlying data for this area is medium.

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