We produce the first nationally consistent, county-level estimates of AI usage in the United States. Extending AI User Share\u2014a population-normalized metric of active AI use\u2014from national to subnational scales is complicated by small county samples, IP-geolocation noise, and differences in local digital infrastructure. We address these challenges by combining anonymized, aggregated Microsoft telemetry on active use of major AI services with a Bayesian spatial small-area model that borrows information across neighboring counties, state effects, and demographic covariates. County estimates are aggregated using working age population weights to produce state, metropolitan statistical area, and urbanicity summaries. The resulting data products provide a consistent, population-normalized view of AI adoption across U.S. geographies.<\/p>\n","protected":false},"excerpt":{"rendered":"
We produce the first nationally consistent, county-level estimates of AI usage in the United States. Extending AI User Share\u2014a population-normalized metric of active AI use\u2014from national to subnational scales is complicated by small county samples, IP-geolocation noise, and differences in local digital infrastructure. 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