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

Custom inventory report

Filter: AI type = other; sourcing = unknown; monitoring = blank

Generated 2026-10-12 11:22 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: AI type = other; sourcing = unknown; monitoring = blank · 35 records

Key findings

  • 35 use-case records from 7 agencies: 2 deployed (6%), 0 pilots, 33 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.
  • DOT, NASA, HHS report 27 of 35 use cases (77%).
  • 0% of reported deployed use cases (0 of 2) are classified as generative or agentic AI.
  • Sourcing is reported for 0% of use cases. Where reported, n/a involve in-house development.

Lifecycle

StageRecordsShare
Deployed26%
Pre-deployment3394%

AI technology

ClassificationRecordsShareDeployed
Other35100%2

Agencies

AgencyRecordsDeployedHigh-impactCompleteness
DOT · Department of Transportation201060%
NASA · National Aeronautics and Space Administration40056%
HHS · Department of Health and Human Services30058%
DOI · Department of the Interior30083%
DOE · Department of Energy30075%
GSA · General Services Administration11033%
TREAS · Department of the Treasury10058%

High-impact designation

DesignationRecords
Not high-impact34
Not reported1

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 35 records.

RecordAgency IDAgencyUse caseStage
R1202GSATier 1 Use CasesDeployed
R1231DOT-1000036DOTIntegration of small Unmanned Aircraft System (sUAS) Geospacial Information System (GIS) TechnologieDeployed
R0126NASA-80NASAcFS High Performance Computing Framework (cFS HPCF)Pre-deployment
R0284NASA-556NASAImplementing Intelligent Extensible Mission Architectures (IEMA)Pre-deployment
R0418NASA-775NASAFoundation Model for Lunar SciencePre-deployment
R0469NASA-867NASASpace Grade LinuxPre-deployment
R0636HHSThe NEF DSI/AI project addresses local validation of AI-based clinical decision support (CDS)/decision support interventions (DSI) in provider settings.Pre-deployment
R0886HHSNOFO Compliance AssistantPre-deployment
R0917HHSGenerative AI (GenAI) Still Image TaggingPre-deployment
R1207DOT-1000005DOTAI Support and Collaboration Center (AISCC)Pre-deployment
R1219DOT-1000021DOTRegulatory Compliance Mapping ToolPre-deployment
R1220DOT-1000022DOTJASC Code classification in Safety Difficulty Reports (SDR)Pre-deployment
R1222DOT-1000025DOTCourse Deviation Identification for Multiple Airport Route Separation (MARS)Pre-deployment
R1224DOT-1000027DOTDetermining Surface Winds with Machine Learning SoftwarePre-deployment
R1225DOT-1000028DOTRemote Oceanic Meteorological Information Operations (ROMIO)Pre-deployment
R1226DOT-1000030DOTHead Kinematics PredictionPre-deployment
R1227DOT-1000031DOTCrash Parameter PredictionPre-deployment
R1228DOT-1000033DOTCrushed Aggregate Gradation Evaluation SystemPre-deployment
R1229DOT-1000034DOTAutomatic Track Change Detection Demonstration and AnalysisPre-deployment
R1232DOT-1000038DOTGeolocating and Identifying Vehicle Hard Brake, Acceleration and Seat Belt Usage with CV DataPre-deployment
R1234DOT-1000040DOTExploratory Advanced Research group of projectsPre-deployment
R1236DOT-1000042DOTTransportation Use Case Knowledge Repository (TrUCKR)Pre-deployment
R1237DOT-1000043DOTNETT Council AI Coordination and Activities (AICA) Working GroupPre-deployment
R1238DOT-1000044DOTDOT Workforce Acquisitions and Training TeamPre-deployment
R1239DOT-1000045DOTNETT Council Safety, Rights, and Security Review (SR2) CommitteePre-deployment
R1240DOT-1000046DOTDOT AI Procurement TeamPre-deployment
R1241DOT-1000047DOTDOT AI Emerging Technology TeamPre-deployment
R1254DOT-1000060DOTRemote Maintenance Monitoring (RMM) Analyzer CopilotPre-deployment
R2503DOI-0260DOIROV Smart Touch Subsea Pipeline InspectionsPre-deployment
R2509DOI-0254DOIDevelopment of a computer vision model to monitor for early detection of habitat loss across the landscape. [2024 INV#DOI-65]Pre-deployment
R2579DOI-0184DOISummarization of documents and output to ECOSphere species workflow [2024 INV#DOI-63]Pre-deployment
R2830TREAS-IRS-126TREASIntegrated Data Retrieval System ModernizationPre-deployment
R3429DOE-573DOEDNA-P Use Cases Leaverging Artificial Intellegence (Pre-Development)Pre-deployment
R3510DOE-654DOEATLASPre-deployment
R3548DOE-692DOEHALO AIPre-deployment

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