Explore the evidence / United States
Look inside the United States.
A state map, the complete county distribution, and searchable data for every supplied local geography.
Find a chart, dataset, or source
- Acceptance of AI-produced newsWorld geography · nine-country attitudes
- Enterprise spending intensityOrganisations · supplementary survey
- Australia: perceived recruitment effectsWork · ABS reported vacancy effects
- Australia: productivity gains in liaisonWork · RBA approximate context
- OECD technology co-useOrganisations · 28 countries and published mean
- US business and employee-use reportsOrganisations · two separate business measures
- Reuters Institute: weekly use and search exposureAccess & geography · separate survey measures
- UK business AI use and skills barriersOrganisations · separate UK survey
- One world. Two different measures.World geography
- How many people use generative AI?World geography
- Where is Claude used disproportionately?World geography
- Read one place across the evidence.World geography
- United Arab EmiratesWorld geography
- Use rises. The gaps remain.World geography
- Adoption rises; the North–South gap widens.World geography
- All 147 economies move upward.World geography
- The ten largest gainsWorld geography
- All four periods, side by side.World geography
- Population reachWorld geography
- National averages conceal local variation.United States
- Every county counts once.United States
- From states to individual counties.United States
- Adoption differs across European economies.Organisations
- Where European firms have adopted AIOrganisations
- Read sector growth with its coverage.Organisations
- Sector growth needs a coverage lensOrganisations
- Size, scaling and returns answer different questions.Organisations
- Larger firms pull ahead with agentsOrganisations
- Personal gains and organisational returnsOrganisations
- Deployment expanded across functions.Organisations
- Use differs by education and role.Work & learning
- Use across the workforceWork & learning
- Access differs by education and roleWork & learning
- Faster work is one outcome among several.Work & learning
- What AI users reportWork & learning
- Widespread use meets uneven provision.Work & learning
- Students use more than institutions provide.Work & learning
- A gap between teacher use and training.Work & learning
- Adoption does not establish critical use.Work & learning
- Critical use is uneven within adoption.Work & learning
- What adoption leaves unresolved.Work & learning
- Conversations extend beyond paid work.AI tasks
- Purpose of Claude conversationsAI tasks
- Answers, documents and guidance are common outputs.AI tasks
- Three common outputsAI tasks
- The same output can serve different purposes.AI tasks
- The same output, different purposesAI tasks
- Behind the headline numbers.Evidence library
- Microsoft research in brief.Evidence library
- Five reports. Every page.Evidence library
- Global · H1 2025Evidence library
- Global · H2 2025Evidence library
- Global · Q1 2026Evidence library
- Global · Q2 2026Evidence library
- United States · Q1 2026Evidence library
- Data, reports and source files.Evidence library
- Microsoft geographic dataEvidence library
- Survey, sector and geographic evidenceEvidence library
- Five original reportsEvidence library
- Transcriptions and provenanceEvidence library
- Methods, caveats and attribution.Evidence library
- Know what each number can carry.Evidence library
- The Microsoft collection: definitions and provenance.Evidence library
- All datasets and downloads · CSV, JSON, PDF and textEvidence library
- Read all 94 original report pagesEvidence library
- Search 65 transcribed tables and recordsEvidence library
- Complete methods, caveats, provenance and licencesEvidence library
- 147 economies · four-period table and country searchWorld geography
- US states, metros and all 3,143 counties · search, filter, exportUnited States
- Science · eight research tasks, two interfacesAI tasks · session shares
No matching views. Try a broader topic, or browse the six areas above.
01 / State map
National averages conceal local variation.
Estimated AI user share across 50 states and D.C. Select a state on the map to find its exact value below.
02 / County distribution
Every county counts once.
The median county has an estimated user share of 19.8%. Estimates range from 6.7% in Shannon County, Missouri, to 73.2% in Williamsburg city, Virginia.
Read exact bin counts
| AI user share interval | Counties |
|---|---|
| 0–2.5% | 0 |
| 2.5–5% | 0 |
| 5–7.5% | 2 |
| 7.5–10% | 25 |
| 10–12.5% | 186 |
| 12.5–15% | 374 |
| 15–17.5% | 515 |
| 17.5–20% | 490 |
| 20–22.5% | 396 |
| 22.5–25% | 312 |
| 25–27.5% | 230 |
| 27.5–30% | 188 |
| 30–32.5% | 126 |
| 32.5–35% | 90 |
| 35–37.5% | 79 |
| 37.5–40% | 59 |
| 40–42.5% | 18 |
| 42.5–45% | 25 |
| 45–47.5% | 6 |
| 47.5–50% | 6 |
| 50–52.5% | 6 |
| 52.5–55% | 0 |
| 55–57.5% | 1 |
| 57.5–60% | 2 |
| 60–62.5% | 1 |
| 62.5–65% | 3 |
| 65–67.5% | 1 |
| 67.5–70% | 1 |
| 70–72.5% | 0 |
| 72.5–75% | 1 |
| 75–77.5% | 0 |
| 77.5–80% | 0 |
03 / Find a place
From states to individual counties.
All 51 state-level records, 35 supplied metros, and 3,143 counties. Search by name or code, filter counties by state, and download the matching rows.
51 states and D.C.
| State | Code | Rank | AI user share |
|---|---|---|---|
| District of Columbia | DC | 1 | 40.3% |
| Maryland | MD | 2 | 36.3% |
| Utah | UT | 3 | 35.7% |
| Texas | TX | 4 | 35.3% |
| Virginia | VA | 5 | 34.7% |
| New Jersey | NJ | 6 | 34.5% |
| Nevada | NV | 7 | 34.2% |
| California | CA | 8 | 34.0% |
| Connecticut | CT | 9 | 34.0% |
| Georgia | GA | 10 | 33.7% |
| Florida | FL | 11 | 33.6% |
| Massachusetts | MA | 12 | 33.4% |
| Illinois | IL | 13 | 33.3% |
| New York | NY | 14 | 32.7% |
| Rhode Island | RI | 15 | 32.5% |
| Colorado | CO | 16 | 32.3% |
| Washington | WA | 17 | 32.2% |
| Arizona | AZ | 18 | 31.4% |
| Hawaii | HI | 19 | 30.6% |
| Delaware | DE | 20 | 30.6% |
| New Hampshire | NH | 21 | 30.2% |
| North Carolina | NC | 22 | 30.1% |
| South Carolina | SC | 23 | 29.1% |
| Oklahoma | OK | 24 | 28.9% |
| Idaho | ID | 25 | 28.8% |
| Kansas | KS | 26 | 28.6% |
| Tennessee | TN | 27 | 28.5% |
| Oregon | OR | 28 | 28.4% |
| Ohio | OH | 29 | 28.3% |
| Wisconsin | WI | 30 | 28.2% |
| North Dakota | ND | 31 | 28.2% |
| Michigan | MI | 32 | 27.4% |
| South Dakota | SD | 33 | 27.4% |
| Alabama | AL | 34 | 27.3% |
| Pennsylvania | PA | 35 | 27.2% |
| Indiana | IN | 36 | 26.8% |
| Missouri | MO | 37 | 26.8% |
| Nebraska | NE | 38 | 26.4% |
| Minnesota | MN | 39 | 26.3% |
| Louisiana | LA | 40 | 26.1% |
| Arkansas | AR | 41 | 26.0% |
| Wyoming | WY | 42 | 25.5% |
| Kentucky | KY | 43 | 25.1% |
| Iowa | IA | 44 | 24.4% |
| New Mexico | NM | 45 | 23.9% |
| Alaska | AK | 46 | 23.6% |
| Vermont | VT | 47 | 23.3% |
| Mississippi | MS | 48 | 22.9% |
| Montana | MT | 49 | 22.7% |
| Maine | ME | 50 | 21.4% |
| West Virginia | WV | 51 | 20.8% |
No matching places. Try a shorter name or another geographic scale.
Bars use a common 0–80% scale across all three views. Metro data cover the 35 supplied metros, not a full US metro census. Identifier strings retain their original form. The CSVs contain no uncertainty intervals; none are inferred.