STRATAHELM · COMMUNITY AI EXPOSURE & RESILIENCE INDEX

Dakota County, Minnesota

CAERI NationalMinnesota › Dakota County · FIPS 27037 · caeri:27037
46.3
CAERI score (national basis)
25th–50th
National percentile band
#1947
Ranked of 3142 U.S. counties
#44
Ranked in Minnesota (of 87)
High
Confidence

Two comparisons, both shown. The national basis ranks Dakota 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
93
P2 · Economic concentration
14
P3 · Adaptive capacity (inverted)
81
P4 · Regional buffer (inverted)
60
P5 · Fiscal sensitivity
23
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 Dakota County

Dakota County scores 46.3 on the national CAERI basis — 1947th of 3,142 scored U.S. counties, placing it in the 25th–50th band nationally by percentile, with a high-confidence rating. Within Minnesota it ranks 44th of 87 counties (50th 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 93rd national percentile. The largest concentrations of locally estimated employment in high-exposure occupations are customer service representatives, office clerks, general, software developers. The share of exposed-industry jobs held by workers under 25 is 8% — below 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 24% (below the state median) — a higher share historically means slower workforce adjustment when industries restructure. Fiscal sensitivity ranks at the 49th 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, 16% 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 214 high-exposure occupations (top quartile of ensemble exposure) with estimated local employment, Dakota County has an estimated 64,572 jobs — 31.0% of county employment — carrying an estimated $5B annual wage bill in high-exposure work. The five largest:

OccupationEst. local employment*Exposure (0–1)Median wage (area)
Customer Service Representatives5,1700.42$48,030
Office Clerks, General4,1140.44$47,860
Software Developers3,7860.65$129,430
Sales Representatives, Wholesale and Manufacturing, Except Technical and Scientific Products2,3420.43$77,700
Accountants and Auditors2,3160.48$83,260
*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

Dakota CountyMinnesota median
Share of exposed-industry jobs held by workers under 25 (entry rung) 8.5%10.0%
Share of exposed-industry jobs held by workers 55+ (adjustment friction) 24.4%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:27037 — this URL is permanent; if the address scheme ever changes, the old address will redirect. StrataHelm. (2026). Dakota County, Minnesota — Community AI Exposure & Resilience Index (CAERI v0.3.1) [Data set]. Retrieved August 4, 2026, from https://stratahelm.com/counties/minnesota/dakota/ “Dakota County, Minnesota — CAERI.” StrataHelm, 2026, stratahelm.com/counties/minnesota/dakota/. Accessed 4 August 2026. StrataHelm. “Dakota County, Minnesota — Community AI Exposure and Resilience Index (v0.3.1).” 2026. https://stratahelm.com/counties/minnesota/dakota/
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/dakota/embed/" width="420" height="275" loading="lazy" title="CAERI — Dakota County, MN"></iframe>

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

Nearby and comparable counties

Cass Co., MN (in state)Cook Co., MN (in state)Isanti Co., MN (in state)Burleigh Co., ND (similar score)St. Mary Co., LA (similar score)Clark Co., IN (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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