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

Federal AI landscape: executive briefing

Filtered: stage = pilot; function = image_analysis

Generated 2026-10-12 18:42 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: stage = pilot; function = image_analysis · 18 records

Key findings

  • 18 use-case records from 4 agencies: 0 deployed (0%), 18 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.
  • DOI, USDA, DOJ report 17 of 18 use cases (94%).
  • Sourcing is reported for 100% of use cases. Where reported, 83% involve in-house development.

Lifecycle

StageRecordsShare
Pilot18100%

AI technology

ClassificationRecordsShareDeployed
Classical / predictive ML1056%0
Computer vision739%0
Other16%0

Agencies

AgencyRecordsDeployedHigh-impactCompleteness
DOI · Department of the Interior1400100%
USDA · Department of Agriculture200100%
DOJ · Department of Justice100100%
DOE · Department of Energy100100%

High-impact designation

DesignationRecords
Not high-impact18

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

All 18 records.

RecordAgency IDAgencyUse caseStage
R1319USDA-011USDALCAT - Land Change Analysis TechniquePilot
R1385USDA-086USDAWildlife Deterrent SystemPilot
R1730DOJ-0305DOJData Triage and ProcessingPilot
R2538DOI-0225DOIAutomated otolith aging using image processing [2024 INV#WO0000000109315]Pilot
R2564DOI-0199DOIMachine-learning model to delineate sub-surface agricultural drainage from satellite imagery [2024 INV#WO0000000109078]Pilot
R2571DOI-0192DOIMachine learning-based landscape feature classification using satellite and airborne imagery [2024 INV#WO0000000108791; 2024 INV#WO0000000108794]Pilot
R2573DOI-0190DOIMachine Learning Image Classification of Wetlands and Soil moisture [2024 INV#WO0000000108779]Pilot
R2581DOI-0182DOIWave runup and total water level observations from time series imagery at several sites with varying nearshore morphologies [2024 INV#WO0000000108262]Pilot
R2588DOI-0175DOIDeep Learning based image segmentation [2024 INV#WO0000000107975]Pilot
R2625DOI-0137DOIRandom forest models for predicting water quality of inland waters from remotely sensed imageryPilot
R2646DOI-0114DOIImproving Prediction Capabilities for Barrier Island Landscape ChangePilot
R2647DOI-0113DOILake-wide monitoring and assessment of Great Lakes fisheries with autonomous vehicles and image analysisPilot
R2666DOI-0087DOIDeveloping land cover maps for barrier islands using satellite imageryPilot
R2677DOI-0079DOIFlor-AI: Developing a Remotely Sensed Image Classification Method for Inventory and Monitoring of Flora in Digital UAS ImageryPilot
R2678DOI-0075DOIAutomating the Detection and Classification of Wildlife in Aerial Imagery [2024 INV#WO0000000109409]Pilot
R2690DOI-0063DOIMapping wood and wood hazards in the Willamette Basin, OregonPilot
R2720DOI-0028DOIImplementation of Artificial Intelligence to Estimate Population Size of a Migratory Bird from Aerial Thermal Imagery [2024 INV#DOI-67]Pilot
R3396DOE-539DOEDrone Imagery AnalysisPilot

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