STRATAHELM · COMMUNITY AI EXPOSURE & RESILIENCE INDEX

Mille Lacs County, Minnesota

CAERI NationalMinnesota › Mille Lacs County · FIPS 27095 · caeri:27095
34.4
CAERI score (national basis)
Bottom 25%
National percentile band
#2976
Ranked of 3142 U.S. counties
#67
Ranked in Minnesota (of 87)
High
Confidence

Two comparisons, both shown. The national basis ranks Mille Lacs County against every scored U.S. county — its percentile band above is a relative national standing, not a condition. The in-state basis ranks it against Minnesota's other counties (rank and percentile only — bands aren't meaningful within a single state). A county can stand out in its own state while sitting mid-pack nationally. Neither is a forecast.

Pillar breakdown — national percentile ranks

P1 · Direct occupational exposure
26
P2 · Economic concentration
19
P3 · Adaptive capacity (inverted)
43
P4 · Regional buffer (inverted)
52
P5 · Fiscal sensitivity
24
Zone shading marks percentile quartiles; darker and warmer means more concerning. Capacity and buffer bars (inverted before aggregation) read mirrored — for those, a higher percentile is the safer pale end.

What this means for Mille Lacs County

Mille Lacs County scores 34.4 on the national CAERI basis — 2976th of 3,142 scored U.S. counties, placing it in the Bottom 25% band nationally by percentile, with a high-confidence rating. Within Minnesota it ranks 67th of 87 counties (24th in-state percentile). The score summarizes how concentrated local employment is in AI-exposed occupations against the economy's measured capacity to adapt; these are relative-standing bands, not a projection of local job change.

Direct occupational exposure stands at the 26th national percentile. The largest concentrations of locally estimated employment in high-exposure occupations are office clerks, general, customer service representatives, elementary school teachers, except special education. The share of exposed-industry jobs held by workers under 25 is 12% — well above the state median of 10%; research on AI-era payrolls finds early-career roles in exposed work are where hiring patterns shift first, so this share indicates how soon exposure could be felt, not how large it is.

The share of exposed-industry jobs held by workers 55 and over is 29% (near the state median) — a higher share historically means slower workforce adjustment when industries restructure. Fiscal sensitivity ranks at the 48th state percentile. In Minnesota the transmission runs through the property-tax base — commercial-industrial property is taxed at higher classification rates than homesteads, so softness in commercial values shifts levy burden or squeezes capacity — and through state aid, 15% of general revenue here (well below the state median): Local Government Aid is financed from the state general fund and moves with statewide economic conditions, not only local ones. Local-option sales taxes are a minimal share of revenue here, leaving property values and state aid as the channels that matter. Minnesota local governments levy no local income tax. All county occupation figures on this page are model-based ESTIMATES with the confidence rating shown above.

Largest locally-estimated employment in high-exposure occupations

Across all 211 high-exposure occupations (top quartile of ensemble exposure) with estimated local employment, Mille Lacs County has an estimated 1,988 jobs — 17.9% of county employment — carrying an estimated $146M annual wage bill in high-exposure work. The five largest:

OccupationEst. local employment*Exposure (0–1)Median wage (area)
Office Clerks, General1690.44$47,860
Customer Service Representatives1590.42$48,030
Elementary School Teachers, Except Special Education970.43$76,100
Secretaries and Administrative Assistants, Except Legal, Medical, and Executive950.50$51,240
Sales Representatives, Wholesale and Manufacturing, Except Technical and Scientific Products900.43$77,700
*County-level occupation figures are model-based ESTIMATES, not surveyed counts (see methodology §5 summary); every county carries the confidence rating shown above. Wage = area median.

Age structure of exposed-industry employment

Mille Lacs CountyMinnesota median
Share of exposed-industry jobs held by workers under 25 (entry rung) 11.8%10.0%
Share of exposed-industry jobs held by workers 55+ (adjustment friction) 29.2%28.6%

🔒 City-level detail for its cities and towns

The county number above averages over every community in it. City- and place-level exposure profiles, employer-mix detail, trend monitoring, and peer benchmarking are part of the CAERI subscription for local governments and regional organizations.

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Cite this page

Canonical identifier: caeri:27095 — this URL is permanent; if the address scheme ever changes, the old address will redirect. StrataHelm. (2026). Mille Lacs County, Minnesota — Community AI Exposure & Resilience Index (CAERI v0.3.1) [Data set]. Retrieved August 4, 2026, from https://stratahelm.com/counties/minnesota/mille-lacs/ “Mille Lacs County, Minnesota — CAERI.” StrataHelm, 2026, stratahelm.com/counties/minnesota/mille-lacs/. Accessed 4 August 2026. StrataHelm. “Mille Lacs County, Minnesota — Community AI Exposure and Resilience Index (v0.3.1).” 2026. https://stratahelm.com/counties/minnesota/mille-lacs/
Embed this county's score card — attribution to StrataHelm CAERI and the link back are part of the embedded page and cannot be stripped:<iframe src="https://stratahelm.com/counties/minnesota/mille-lacs/embed/" width="420" height="275" loading="lazy" title="CAERI — Mille Lacs County, MN"></iframe>

Machine-readable: this county's JSON · national dataset download and data dictionary on the methodology page.

Nearby and comparable counties

Aitkin Co., MN (in state)Douglas Co., MN (in state)Kandiyohi Co., MN (in state)Jefferson Co., IL (similar score)Clay Co., IN (similar score)Fond du Lac Co., WI (similar score)

Links point to the economically nearest counties (in-state, and similar national score). County-level geographic adjacency is not part of the public reference data, so proximity here is by rank, not by shared border.

Sources & provenance

LayerSources (vintage)
Employment & occupation structurecbp_mn_county_naics4: Census CBP 2023 API (NAICS2017 classification; PAYANN in $1,000s; noise infusion G/H/J bands, D = withheld -&gt; NaN); county_soc_estimates.meta.json; exposure_scores: 2026-07-04; matrix_staffing_patterns: 2024-34 National Employment Matrix (base year 2024)
AI-exposure research baseAnthropic Economic Index; Felten, Raj & Seamans (AIOE); Eloundou et al. — combined as a weighted ensemble with cross-source disagreement feeding the confidence rating
Capacity, buffer & fiscalgovfin_mn_county_revenue_mix: 2022 Census of Governments, Survey of Government Finances; lodes_mn_county_flows: LEHD LODES8 OD 2023, JT00/S000; sources: mn main+aux, wi/nd/sd/ia aux; qwi_mn_county_naics3_age: Census QWI (qwi/sa), quarters [&#x27;2024-Q4&#x27;, &#x27;2025-Q1&#x27;, &#x27;2025-Q2&#x27;, &#x27;2025-Q3&#x27;], sex=0, ownercode=A05 (private), 96 NAICS-3 + &#x27;00&#x27; all-industry
MethodologyCAERI v0.3.1 · public methodology · scores generated 2026-07-12 · page generated 2026-08-04
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