STRATAHELM · COMMUNITY AI EXPOSURE & RESILIENCE INDEX

Placer County, California

CAERI NationalCalifornia › Placer County · FIPS 06061 · caeri:06061
61.0
CAERI score (national basis)
75th–90th
National percentile band
#473
Ranked of 3142 U.S. counties
#9
Ranked in California (of 58)
Medium
Confidence

Two comparisons, both shown. The national basis ranks Placer 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 California'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
95
P2 · Economic concentration
61
P3 · Adaptive capacity (inverted)
76
P4 · Regional buffer (inverted)
53
P5 · Fiscal sensitivity
49
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 Placer County

Placer County scores 61.0 on the national CAERI basis — 473rd of 3,142 scored U.S. counties, placing it in the 75th–90th band nationally by percentile, with a medium-confidence rating. Within California it ranks 9th of 58 counties (85th 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 95th national percentile. The largest concentrations of locally estimated employment in high-exposure occupations are office clerks, general, management analysts, 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 28% (near the state median) — a higher share historically means slower workforce adjustment when industries restructure. Fiscal sensitivity ranks at the 55th percentile among California's counties. Census of Governments data shows state aid at 25% of this county's general revenue (well below the state median), and wage- and consumption-sensitive streams (sales, income, and similar own-source taxes, where levied) at 18% 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 214 high-exposure occupations (top quartile of ensemble exposure) with estimated local employment, Placer County has an estimated 64,593 jobs — 34.1% of county employment — carrying an estimated $6B annual wage bill in high-exposure work. The five largest:

OccupationEst. local employment*Exposure (0–1)Median wage (area)
Office Clerks, General3,9610.44$48,000
Management Analysts3,6040.46$82,180
Customer Service Representatives2,8460.42$47,750
Accountants and Auditors2,8270.48$89,680
Computer User Support Specialists2,6890.48$102,430
*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

Placer CountyCalifornia median
Share of exposed-industry jobs held by workers under 25 (entry rung) 5.9%7.1%
Share of exposed-industry jobs held by workers 55+ (adjustment friction) 28.4%28.8%

🔒 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:06061 — this URL is permanent; if the address scheme ever changes, the old address will redirect. StrataHelm. (2026). Placer County, California — Community AI Exposure & Resilience Index (CAERI v0.3.1) [Data set]. Retrieved August 4, 2026, from https://stratahelm.com/counties/california/placer/ “Placer County, California — CAERI.” StrataHelm, 2026, stratahelm.com/counties/california/placer/. Accessed 4 August 2026. StrataHelm. “Placer County, California — Community AI Exposure and Resilience Index (v0.3.1).” 2026. https://stratahelm.com/counties/california/placer/
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/california/placer/embed/" width="420" height="275" loading="lazy" title="CAERI — Placer County, CA"></iframe>

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

Nearby and comparable counties

El Dorado Co., CA (in state)Inyo Co., CA (in state)Contra Costa Co., CA (in state)Haskell Co., OK (similar score)Douglas Co., NV (similar score)Harrisonburg Co., VA (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_ca_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_ca.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_ca_county_revenue_mix: 2022 Census of Governments, Survey of Government Finances; lodes_ca_county_flows: LEHD LODES8 OD 2023, JT00/S000; sources: ca_main, ca_aux, az_aux, nv_aux, or_aux; qwi_ca_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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