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Snapshot · OMB 2025 inventory · processed Oct 11, 2026
Federal AI Intelligence · U.S. Government AI Observatory

Custom inventory report

Filter: agency = USDA; stage = pilot

Generated 2026-10-12 13:55 UTCDataset: 2025 Federal Agency AI Use Case Inventory (individually reported use cases), Office of Management and Budget (OMB). Version 2025-inventory@62d5baa65fa3, processed 2026-10-11, rules 2026.10.1. Static snapshot.Applied filters: agency = USDA; stage = pilot · 47 records

Key findings

  • 47 use-case records from 1 agencies: 0 deployed (0%), 47 pilots, 0 in development or acquisition, 0 retired, 0 with no stage reported.
  • 0 records are designated high-impact; 0 of them (n/a) answered at least one minimum-practice question.
  • Sourcing is reported for 100% of use cases. Where reported, 89% involve in-house development.

Lifecycle

StageRecordsShare
Pilot47100%

AI technology

ClassificationRecordsShareDeployed
Generative AI36%0
Classical / predictive ML3370%0
Natural language processing49%0
Computer vision613%0
Agentic AI12%0

Agencies

AgencyRecordsDeployedHigh-impactCompleteness
USDA · Department of Agriculture4700100%

High-impact designation

DesignationRecords
Presumed high-impact, determined not1
Not high-impact46

Governance evidence: use cases designated high-impact

PracticeIn placeIn progressNot in placeN/A or precludedOtherNo answerIn scope
Pre-deployment testing0000000
AI impact assessment0000000
Independent review0000000
Ongoing monitoring0000000
Operator training0000000
Fail-safe0000000
Appeal process0000000
User and public consultation0000000

"In place" means the agency reported the practice as established. "No answer" means the field was blank; it says nothing about whether the practice exists.

Method

All figures are computed directly from the normalised inventory records. Category labels are normalised from the source answer options; original values are kept on each record. Governance answers are classified as in place, in progress, not in place, not applicable, precluded, waived, other or no answer, and blanks are never read as "no". See the Methodology page for full rules.

Limitations

  • Figures are what agencies reported in the 2025 inventory. They are not verified, and registration of use cases is not complete for every agency.
  • A blank answer is missing evidence, not evidence that a practice or safeguard is absent.
  • Counts are use-case records. A larger portfolio does not indicate better performance or greater AI maturity, and agencies differ in how they split systems into use cases.
  • The inventory has no budget, cost, accuracy or outcome data. None is shown or inferred here.
  • This is a disclosure analysis. It is not an audit, a compliance determination or an official government assessment.

Source records

First 40 of 47 records, deployed first. The full list is available as CSV from the explorer with the same filters.

RecordAgency IDAgencyUse caseStage
R1319USDA-011USDALCAT - Land Change Analysis TechniquePilot
R1323USDA-017USDARaster ToolsPilot
R1326USDA-021USDAForest Health Detection MonitoringPilot
R1345USDA-043USDAGenomic Analyses of Pathogen SubtypesPilot
R1346USDA-044USDAFoodborne Illness Source AttributionPilot
R1353USDA-052USDAFSA FLP ChatbotPilot
R1358USDA-057USDAFile RenamePilot
R1370USDA-069USDAXyloTron/XyloPhone Wood Identification SystemPilot
R1375USDA-074USDAFire Resilient LandscapesPilot
R1377USDA-076USDASpread and Balance Sample DesignPilot
R1378USDA-077USDARegression, Classification, Clustering with Hilbert CurvesPilot
R1385USDA-086USDAWildlife Deterrent SystemPilot
R1396USDA-098USDAAxon+ Copilot Studio ChatbotPilot
R1398USDA-100USDANWRC ND Field Station Birds and Agriculture ProjectPilot
R1399USDA-101USDANWRC LSS Bioinformatic CodingPilot
R1400USDA-102USDANWRC Rabies ML A.D.Pilot
R1401USDA-103USDANWRC Rabies ML M.H.Pilot
R1402USDA-104USDANWRC Pepin ML & AIPilot
R1403USDA-105USDANWRC Genetics MetadataPilot
R1405USDA-107USDAGovChatPilot
R1415USDA-117USDAVegetation Specifications Suite (VegSpec)Pilot
R1416USDA-118USDANETS automated waterway designPilot
R1418USDA-120USDADigital Soil MappingPilot
R1419USDA-121USDAAnnual Soil Refresh Data Staging Server AutomationPilot
R1424USDA-126USDASpecies Distribution Data analysisPilot
R1429USDA-131USDARandom Forest with Aquatic Effectiveness MonitoringPilot
R1430USDA-132USDAForest fire effects remote sensing modelsPilot
R1432USDA-134USDASelect Tree MappingPilot
R1433USDA-135USDAYearly Incident Procurement Classification ReportPilot
R1434USDA-136USDAAmerican Recovery Act Classification ToolPilot
R1435USDA-137USDAAutomated Road MappingPilot
R1441USDA-143USDABugnetPilot
R1442USDA-144USDARecreation site chatbotPilot
R1444USDA-146USDAForest Mapping using G-LiHT airborne data in interior AlaskaPilot
R1446USDA-148USDAForest Health Protection: Survey and mapping of forest damage from insects and diseases using machine learningPilot
R1449USDA-151USDAPredicting fire severity potential in future wildfires in CaliforniaPilot
R1450USDA-152USDAForest Inventory and Cruising using GAIA AIPilot
R1452USDA-154USDAApp for predicting soil temperature during prescribed burnsPilot
R1453USDA-155USDAWildfire effects and postfire forest dynamicsPilot
R1455USDA-157USDAForest habitat mapping for marbled murreletsPilot

Prepared with Federal AI Intelligence by Irakli Petriashvili. Source: https://github.com/ombegov/2025-Federal-Agency-AI-Use-Case-Inventory