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

Custom inventory report

Filter: topic = Procurement and Financial Management; AI type = classical_ml; failsafe = blank

Generated 2026-10-12 17:55 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: topic = Procurement and Financial Management; AI type = classical_ml; failsafe = blank · 27 records

Key findings

  • 27 use-case records from 10 agencies: 15 deployed (56%), 3 pilots, 9 in development or acquisition, 0 retired, 0 with no stage reported.
  • 6 records are designated high-impact; 0 of them (0%) answered at least one minimum-practice question.
  • NCUA, TREAS, FDIC report 16 of 27 use cases (59%).
  • 0% of reported deployed use cases (0 of 15) are classified as generative or agentic AI.
  • Of 6 deployed high-impact use cases, 0 report a completed AI impact assessment and 6 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 56% of use cases. Where reported, 73% involve in-house development.

Lifecycle

StageRecordsShare
Deployed1556%
Pilot311%
Pre-deployment933%

AI technology

ClassificationRecordsShareDeployed
Classical / predictive ML27100%15

Agencies

AgencyRecordsDeployedHigh-impactCompleteness
NCUA · National Credit Union Administration66585%
TREAS · Department of the Treasury63086%
FDIC · Federal Deposit Insurance Corporation40058%
DOJ · Department of Justice430100%
VA · Department of Veterans Affairs22175%
NASA · National Aeronautics and Space Administration10058%
HUD · Department of Housing and Urban Development110100%
GSA · General Services Administration10033%
USDA · Department of Agriculture100100%
DOE · Department of Energy10058%

High-impact designation

DesignationRecords
High-impact6
Presumed high-impact, determined not4
Not high-impact16
Not reported1

Governance evidence: use cases designated high-impact

PracticeIn placeIn progressNot in placeN/A or precludedOtherNo answerIn scope
Pre-deployment testing0000066
AI impact assessment0000066
Independent review0000066
Ongoing monitoring0000066
Operator training0000066
Fail-safe0000066
Appeal process0000066
User and public consultation0000066

"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 27 records.

RecordAgency IDAgencyUse caseStage
R0538HUD-2024-002HUDSubledger Data Quality Machine LearningDeployed
R1488DOJ-0014DOJDun & Bradstreet Business Establishments DataDeployed
R1496DOJ-0022DOJNational Insurance Crime Bureau ISO ClaimSearchDeployed
R1500DOJ-0029DOJSouthwest Border Transaction Record Analysis Center (SWBTRAC)Deployed
R2232VA-24-3291VAPayment Redirect Fraud (PRF) ModelDeployed
R2318VA-24-1815VAAnalytics, Data, and Decision Support Unified Platform (ADDSUP)Deployed
R2434NCUA_E&I-01NCUAMachine Learning Data ValidationDeployed
R2435NCUA_ONES-02NCUASupervisory Stress TestingDeployed
R2436NCUA_ONES-03NCUARisk Indicator ModelDeployed
R2437NCUA-12-2025NCUAMoody’s Stress Test ModelingDeployed
R2438NCUA-13-2025NCUAADCo MBS/CMO ModelingDeployed
R2439NCUA-14-2025NCUACoStar CRE ModelingDeployed
R2770BEP-25TREASSub-Asset Maintenance ModelDeployed
R2772BEP-42TREASInventory Replenishment ForecastDeployed
R2773BEP-67TREASIDV ModelDeployed
R0259NASA-494NASAOCFO Credit Risk and Defaul Estimation ToolPre-deployment
R1059FDIC – 34FDICFDIC Predictive Budget AnalysisPre-deployment
R1063FDIC – 39FDICCFOO Transactional Data AnalysisPre-deployment
R1065FDIC – 41FDICFDIC Financial Audit ReportPre-deployment
R1067FDIC – 44FDICFDIC Investment Portfolio ManagementPre-deployment
R1164GSAAI-Powered Visibility for Supply and Vendor Risk ResiliencePre-deployment
R1433USDA-135USDAYearly Incident Procurement Classification ReportPilot
R1698DOJ-0273DOJOptical Character Recognition Tool 3Pilot
R2771BEP-41TREASInk and Paper Consumption Forecast (IPCF)Pre-deployment
R2859TREAS-IRS-9TREASVendor Risk AnalyticsPilot
R2870TREASURY-OFR-008TREASProcurement IntelligencePre-deployment
R3598DOE-742DOEAI for Financial AnalysisPre-deployment

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