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COMMUNITY AI EXPOSURE & RESILIENCE INDEX
CAERI · pronounced “CARE-ee”

Know where your community stands as AI reshapes local economies.

CAERI scores every U.S. county on how concentrated local employment is in occupations that published research identifies as exposed to current AI capabilities — and how well-positioned the local economy is to adapt. Built entirely from public federal data, with a published methodology and a confidence rating on every score.

Alabama — 67 countiesAlaska — 29 countiesArizona — 15 countiesArkansas — 75 countiesCalifornia — 58 countiesColorado — 64 countiesConnecticut — 9 countiesDelaware — 3 countiesDistrict of Columbia — 1 countiesFlorida — 67 countiesGeorgia — 159 countiesHawaii — 4 countiesIdaho — 44 countiesIllinois — 102 countiesIndiana — 92 countiesIowa — 99 countiesKansas — 105 countiesKentucky — 120 countiesLouisiana — 64 countiesMaine — 16 countiesMaryland — 24 countiesMassachusetts — 14 countiesMichigan — 83 countiesMinnesota — 87 countiesMississippi — 82 countiesMissouri — 115 countiesMontana — 56 countiesNebraska — 93 countiesNevada — 17 countiesNew Hampshire — 10 countiesNew Jersey — 21 countiesNew Mexico — 33 countiesNew York — 62 countiesNorth Carolina — 100 countiesNorth Dakota — 53 countiesOhio — 88 countiesOklahoma — 77 countiesOregon — 36 countiesPennsylvania — 67 countiesRhode Island — 5 countiesSouth Carolina — 46 countiesSouth Dakota — 66 countiesTennessee — 95 countiesTexas — 254 countiesUtah — 29 countiesVermont — 14 countiesVirginia — 133 countiesWashington — 39 countiesWest Virginia — 55 countiesWisconsin — 72 countiesWyoming — 23 counties

Click your state to see its counties. Alaska and Hawaii are shown as insets.

Browse the national index →   Methodology   Request access
New to CAERI? Start here — Position, Not Prophecy: what CAERI is, what it isn’t, and how to read a score. CAERI is a flood map for AI’s effect on local labor markets — it does not say the storm is coming, it says where your community sits relative to the water, and how high your ground is. Read the briefing →
Latest article · October 20, 2026 — Not Just Another Committee. The moment a community starts worrying about AI and jobs, someone proposes a task force — and most convene, issue a report, pose for a photo and dissolve, having changed nothing. The failure is in the design, not the people: no baseline, no authority, no deadline, no metrics, no end state. Who belongs at the table, how to anchor the group to the five dimensions of community AI exposure with a named owner for each, the structural rules that keep it from going symbolic, and a template agenda built around the five pillars. Read the article →
3,142
Counties scored
51
States + DC
314
In the top 10% nationally
786
In the top quarter nationally
5
Pillars per county
100%
Public federal data

Where we stand on AI

An organization that measures AI-driven job disruption is easy to mistake for an organization that opposes AI. We are not one. Our position, stated plainly in our position article:

Read the full position: “Where We Stand” →

Built for institutions, not headlines

Every county receives a full scorecard: composite score and tier, five pillar percentiles (occupational exposure, economic concentration, adaptive capacity, regional buffer, fiscal sensitivity), the locally largest high-exposure occupations, and the age structure of exposed employment — each with plain-language interpretation and a confidence rating. The methodology is published, the limitations are documented, and the index never claims to be a forecast.

Every county is scored on two bases: a national percentile (its standing among all U.S. counties) and an in-state percentile (its standing within its own state) — the county pages show both. As of v0.2.0 the index universe includes government employment — public schools, universities, and hospitals — alongside private payrolls. As of v0.3.0, county estimates in metro areas that cross state lines are built from the whole metro's counties on both sides of the border, improving accuracy in border counties.