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

Custom inventory report

Filter: stage = deployed; function = forecasting

Generated 2026-10-12 06:05 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 = deployed; function = forecasting · 33 records

Key findings

  • 33 use-case records from 12 agencies: 33 deployed (100%), 0 pilots, 0 in development or acquisition, 0 retired, 0 with no stage reported.
  • 5 records are designated high-impact; 2 of them (40%) answered at least one minimum-practice question.
  • HHS, DHS, FHFA report 15 of 33 use cases (45%).
  • 3% of reported deployed use cases (1 of 33) are classified as generative or agentic AI.
  • Of 5 deployed high-impact use cases, 1 report a completed AI impact assessment and 3 leave every minimum-practice field blank.
  • Interpretation: Blank practice fields are missing evidence, not evidence that a safeguard is absent. They mark where follow-up questions to the agency are most useful.
  • Sourcing is reported for 97% of use cases. Where reported, 84% involve in-house development.

Lifecycle

StageRecordsShare
Deployed33100%

AI technology

ClassificationRecordsShareDeployed
Generative AI13%1
Classical / predictive ML2885%28
Natural language processing39%3
Reinforcement learning13%1

Agencies

AgencyRecordsDeployedHigh-impactCompleteness
HHS · Department of Health and Human Services660100%
DHS · Department of Homeland Security661100%
FHFA · Federal Housing Finance Agency330100%
FRB · Federal Reserve Board330100%
DOI · Department of the Interior330100%
TREAS · Department of the Treasury330100%
DOJ · Department of Justice221100%
VA · Department of Veterans Affairs22275%
DOE · Department of Energy220100%
GSA · General Services Administration11033%
USDA · Department of Agriculture110100%
NCUA · National Credit Union Administration111100%

High-impact designation

DesignationRecords
High-impact5
Presumed high-impact, determined not1
Not high-impact26
Not reported1

Governance evidence: use cases designated high-impact

PracticeIn placeIn progressNot in placeN/A or precludedOtherNo answerIn scope
Pre-deployment testing1100035
AI impact assessment1100035
Independent review1100035
Ongoing monitoring1100035
Operator training1100035
Fail-safe1100035
Appeal process0101035
User and public consultation0100135

"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 33 records.

RecordAgency IDAgencyUse caseStage
R0068FHFA-2FHFANeural Networks for FHFA Modeling Analytics Platform (FMAP)Deployed
R0078FHFA-12FHFAAnalytics, Indexing, and Anomaly Detection for Data Management on SQL ServerDeployed
R0079FHFA-13FHFAWorkflow automation and predictive analytics using ServiceNowDeployed
R0558FRB-0001FRBEconomic Trend ModelingDeployed
R0566FRB-0016FRBManufacturer Sentiment AnalysisDeployed
R0567FRB-0017FRBSupply Chain EstimationsDeployed
R0655HHSShort-term Forecasting of Severe Outcomes for Seasonal and Epidemic PathogensDeployed
R0688HHSNowcasting Burden and Infection Trends for Seasonal and Epidemic PathogensDeployed
R0695HHSMachine Learning with Premier Healthcare Data to inform predictive modeling of antibiotic useDeployed
R0820HHSMedWatch DashboardDeployed
R0832HHSResource Capacity PlanningDeployed
R0833HHSSupply Chain Resilience Program, Office of Supply Chain Resilience (OSCR) - ForesightDeployed
R1179GSAElastic Machine Learning Threat Detection (Phase 1)Deployed
R1332USDA-027USDAOperational Water Supply Forecasting for Western US RiversDeployed
R1483DOJ-0008DOJBloomberg GovernmentDeployed
R1567DOJ-0119DOJInsider Threat Management and User Activity MonitoringDeployed
R1890DHS-2391DHSIllicit TradeDeployed
R1937DHS-95DHSTrade Entity Risk ModelDeployed
R1959DHS-399DHSCyber Threat Analysis (Recorded Future)Deployed
R1963DHS-106DHSCritical Infrastructure Network Anomaly DetectionDeployed
R1970DHS-2722DHSIndividual Assistance (IA) Predictive Models for Program QuantitiesDeployed
R1983DHS-2432DHSAirport Throughput Predictive ModelDeployed
R2261VA-24-4152VAStratification Tool for Opioid Risk Mitigation (STORM)Deployed
R2264VA-24-4234VAREACH VET Suicide Risk Prediction and Recovery EngagementDeployed
R2435NCUA_ONES-02NCUASupervisory Stress TestingDeployed
R2533DOI-0230DOIDelineating sub-surface drainage using satellite imagery [2024 INV#WO0000000109525]Deployed
R2658DOI-0100DOIPredicting post-fire tree mortalityDeployed
R2729DOI-0016DOIPerformance Modeling / Performance ForecastingDeployed
R2770BEP-25TREASSub-Asset Maintenance ModelDeployed
R2772BEP-42TREASInventory Replenishment ForecastDeployed
R2773BEP-67TREASIDV ModelDeployed
R3293DOE-351DOEElucidating Genetic and Environmental Risk Factors for Antipsychotic-induced Metabolic Adverse Effects Using AIDeployed
R3295DOE-353DOEAI used for predictive modeling and real time control of traffic systemsDeployed

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