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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 = vendor; feedback = blank

Generated 2026-10-12 16:17 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 = vendor; feedback = blank · 13 records

Key findings

  • 13 use-case records from 7 agencies: 6 deployed (46%), 4 pilots, 3 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, FDIC, DOE report 9 of 13 use cases (69%).
  • 0% of reported deployed use cases (0 of 6) are classified as generative or agentic AI.
  • Sourcing is reported for 100% of use cases. Where reported, 0% involve in-house development.

Lifecycle

StageRecordsShare
Deployed646%
Pilot431%
Pre-deployment323%

AI technology

ClassificationRecordsShareDeployed
Other13100%6

Agencies

AgencyRecordsDeployedHigh-impactCompleteness
DOT · Department of Transportation41071%
FDIC · Federal Deposit Insurance Corporation320100%
DOE · Department of Energy210100%
NTSB · National Transportation Safety Board100100%
HHS · Department of Health and Human Services110100%
DOI · Department of the Interior11092%
TREAS · Department of the Treasury100100%

High-impact designation

DesignationRecords
Not high-impact13

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 13 records.

RecordAgency IDAgencyUse caseStage
R0961HHSDeepEMhancerDeployed
R1087FDIC-67FDICDigital Asset Liquidity Risk AnalysisDeployed
R1089FDIC-71FDICBackground Check Tool for Fraud InvestigationsDeployed
R1261DOT-1000067DOTIdentification of Similar Continued Operational Safety (COS) EventsDeployed
R2730DOI-0015DOIDeployed
R3602DOE-747DOENA-CI SalesforceDeployed
R0085NTSB-0003NTSBDataminrPilot
R1055FDIC-22FDICFDIC Deposit Insurance MisrepresentationPilot
R1263DOT-1000069DOTCourt Reporting and Testimony Management PlatformPre-deployment
R1264DOT-1000070DOTAI-Assisted Legal ResearchPre-deployment
R1266DOT-1000072DOTCase and Document Management CopilotPre-deployment
R2789REQ-2025-02155TREASApplication to AI services integration POCPilot
R3592DOE-734DOECoPilotPilot

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