STRATAHELM · COMMUNITY AI EXPOSURE & RESILIENCE INDEX

Spartanburg County, South Carolina

CAERI NationalSouth Carolina › Spartanburg County · FIPS 45083 · caeri:45083
45.1
CAERI score (national basis)
25th–50th
National percentile band
#2072
Ranked of 3142 U.S. counties
#35
Ranked in South Carolina (of 46)
High
Confidence

Two comparisons, both shown. The national basis ranks Spartanburg 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 South Carolina'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
68
P2 · Economic concentration
12
P3 · Adaptive capacity (inverted)
67
P4 · Regional buffer (inverted)
60
P5 · Fiscal sensitivity
67
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 Spartanburg County

Spartanburg County scores 45.1 on the national CAERI basis — 2072nd of 3,142 scored U.S. counties, placing it in the 25th–50th band nationally by percentile, with a high-confidence rating. Within South Carolina it ranks 35th of 46 counties (25th 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 68th national percentile. The largest concentrations of locally estimated employment in high-exposure occupations are customer service representatives, office clerks, general, secretaries and administrative assistants, except legal, medical, and executive. The share of exposed-industry jobs held by workers under 25 is 8% — well above the state median of 7%; 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 27% (below the state median) — a higher share historically means slower workforce adjustment when industries restructure. Fiscal sensitivity ranks at the 69th percentile among South Carolina's counties. Census of Governments data shows state aid at 9% of this county's general revenue (above the state median), and wage- and consumption-sensitive streams (sales, income, and similar own-source taxes, where levied) at 23% of own-source revenue. Property taxes, which respond to economic change more slowly, are counted separately and are not part of that sensitive share. How this state's aid formulas and tax structure carry economic change into local budgets is covered in the state-specific fiscal analysis available to subscribers. 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 195 high-exposure occupations (top quartile of ensemble exposure) with estimated local employment, Spartanburg County has an estimated 41,792 jobs — 23.8% of county employment — carrying an estimated $3B annual wage bill in high-exposure work. The five largest:

OccupationEst. local employment*Exposure (0–1)Median wage (area)
Customer Service Representatives3,2270.42$39,220
Office Clerks, General3,1770.44$37,360
Secretaries and Administrative Assistants, Except Legal, Medical, and Executive1,8450.50$40,770
Sales Representatives, Wholesale and Manufacturing, Except Technical and Scientific Products1,7400.43$67,570
Elementary School Teachers, Except Special Education1,5370.43$59,500
*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

Spartanburg CountySouth Carolina median
Share of exposed-industry jobs held by workers under 25 (entry rung) 8.3%6.9%
Share of exposed-industry jobs held by workers 55+ (adjustment friction) 26.9%30.6%

🔒 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:45083 — this URL is permanent; if the address scheme ever changes, the old address will redirect. StrataHelm. (2026). Spartanburg County, South Carolina — Community AI Exposure & Resilience Index (CAERI v0.3.1) [Data set]. Retrieved August 4, 2026, from https://stratahelm.com/counties/south-carolina/spartanburg/ “Spartanburg County, South Carolina — CAERI.” StrataHelm, 2026, stratahelm.com/counties/south-carolina/spartanburg/. Accessed 4 August 2026. StrataHelm. “Spartanburg County, South Carolina — Community AI Exposure and Resilience Index (v0.3.1).” 2026. https://stratahelm.com/counties/south-carolina/spartanburg/
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/south-carolina/spartanburg/embed/" width="420" height="275" loading="lazy" title="CAERI — Spartanburg County, SC"></iframe>

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

Nearby and comparable counties

Lee Co., SC (in state)Laurens Co., SC (in state)Chesterfield Co., SC (in state)Merced Co., CA (similar score)Kenedy Co., TX (similar score)Newton Co., TX (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_sc_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_sc.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_sc_county_revenue_mix: 2022 Census of Governments, Survey of Government Finances; lodes_sc_county_flows: LEHD LODES8 OD 2023, JT00/S000; sources: sc_main, sc_aux, ga_aux, nc_aux; qwi_sc_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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