STRATAHELM · COMMUNITY AI EXPOSURE & RESILIENCE INDEX

Panola County, Mississippi

CAERI NationalMississippi › Panola County · FIPS 28107 · caeri:28107
50.7
CAERI score (national basis)
50th–75th
National percentile band
#1461
Ranked of 3142 U.S. counties
#17
Ranked in Mississippi (of 82)
Medium
Confidence

Two comparisons, both shown. The national basis ranks Panola 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 Mississippi'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
43
P2 · Economic concentration
43
P3 · Adaptive capacity (inverted)
31
P4 · Regional buffer (inverted)
32
P5 · Fiscal sensitivity
29
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 Panola County

Panola County scores 50.7 on the national CAERI basis — 1461st of 3,142 scored U.S. counties, placing it in the 50th–75th band nationally by percentile, with a medium-confidence rating. Within Mississippi it ranks 17th of 82 counties (80th 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 43rd national percentile. The largest concentrations of locally estimated employment in high-exposure occupations are secretaries and administrative assistants, except legal, medical, and executive, office clerks, general, customer service representatives. The share of exposed-industry jobs held by workers under 25 is 6% — well below 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 30% (above the state median) — a higher share historically means slower workforce adjustment when industries restructure. Fiscal sensitivity ranks at the 84th percentile among Mississippi's counties. Census of Governments data shows state aid at 24% of this county's general revenue (below the state median), and wage- and consumption-sensitive streams (sales, income, and similar own-source taxes, where levied) at 6% 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 179 high-exposure occupations (top quartile of ensemble exposure) with estimated local employment, Panola County has an estimated 2,435 jobs — 22.3% of county employment — carrying an estimated $113M annual wage bill in high-exposure work. The five largest:

OccupationEst. local employment*Exposure (0–1)Median wage (area)
Secretaries and Administrative Assistants, Except Legal, Medical, and Executive2410.50$33,480
Office Clerks, General2390.44$30,520
Customer Service Representatives1690.42$35,120
Bookkeeping, Accounting, and Auditing Clerks1590.51$40,540
First-Line Supervisors of Office and Administrative Support Workers1430.47$50,450
*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

Panola CountyMississippi median
Share of exposed-industry jobs held by workers under 25 (entry rung) 5.9%7.5%
Share of exposed-industry jobs held by workers 55+ (adjustment friction) 29.9%27.2%

🔒 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.

Request city-level access

Cite this page

Canonical identifier: caeri:28107 — this URL is permanent; if the address scheme ever changes, the old address will redirect. StrataHelm. (2026). Panola County, Mississippi — Community AI Exposure & Resilience Index (CAERI v0.3.1) [Data set]. Retrieved August 4, 2026, from https://stratahelm.com/counties/mississippi/panola/ “Panola County, Mississippi — CAERI.” StrataHelm, 2026, stratahelm.com/counties/mississippi/panola/. Accessed 4 August 2026. StrataHelm. “Panola County, Mississippi — Community AI Exposure and Resilience Index (v0.3.1).” 2026. https://stratahelm.com/counties/mississippi/panola/
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/mississippi/panola/embed/" width="420" height="275" loading="lazy" title="CAERI — Panola County, MS"></iframe>

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

Nearby and comparable counties

Claiborne Co., MS (in state)Pearl River Co., MS (in state)Jones Co., MS (in state)Terrell Co., GA (similar score)Garrard Co., KY (similar score)Columbia 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_ms_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_ms.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_ms_county_revenue_mix: 2022 Census of Governments, Survey of Government Finances; lodes_ms_county_flows: LEHD LODES8 OD 2023, JT00/S000; sources: ms_main, ms_aux, al_aux, ar_aux, la_aux, tn_aux; qwi_ms_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
LicenseFree to reuse under a Creative Commons Attribution 4.0 International (CC BY 4.0) license: reuse or redistribute with attribution to &ldquo;StrataHelm CAERI&rdquo; and a link back to this page. https://creativecommons.org/licenses/by/4.0/