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

Custom inventory report

Filter: function = fraud_integrity; testing = blank

Generated 2026-10-12 18:20 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: function = fraud_integrity; testing = blank · 26 records

Key findings

  • 26 use-case records from 11 agencies: 10 deployed (38%), 1 pilots, 13 in development or acquisition, 1 retired, 1 with no stage reported.
  • 6 records are designated high-impact; 1 of them (17%) answered at least one minimum-practice question.
  • HHS, DOJ, DHS report 15 of 26 use cases (58%).
  • 10% of reported deployed use cases (1 of 10) are classified as generative or agentic AI.
  • Of 2 deployed high-impact use cases, 0 report a completed AI impact assessment and 1 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 42% of use cases. Where reported, 55% involve in-house development.
  • 1 use cases (4%) have no reported development stage.

Lifecycle

StageRecordsShare
Deployed1038%
Pilot14%
Pre-deployment1350%
Retired14%
Not reported14%

AI technology

ClassificationRecordsShareDeployed
Generative AI415%1
Classical / predictive ML1454%6
Natural language processing14%0
Computer vision312%2
Other28%1
Not reported28%0

Agencies

AgencyRecordsDeployedHigh-impactCompleteness
HHS · Department of Health and Human Services71164%
DOJ · Department of Justice41369%
DHS · Department of Homeland Security43090%
VA · Department of Veterans Affairs31169%
GSA · General Services Administration21033%
FDIC · Federal Deposit Insurance Corporation110100%
DOL · Department of Labor10017%
FERC · Federal Energy Regulatory Commission10067%
TREAS · Department of the Treasury110100%
DOC · Department of Commerce1008%
SSA · Social Security Administration111100%

High-impact designation

DesignationRecords
High-impact6
Presumed high-impact, determined not4
Not high-impact13
Not reported3

Governance evidence: use cases designated high-impact

PracticeIn placeIn progressNot in placeN/A or precludedOtherNo answerIn scope
Pre-deployment testing0000066
AI impact assessment0100056
Independent review0000066
Ongoing monitoring0000066
Operator training0000066
Fail-safe1000056
Appeal process0001056
User and public consultation1000056

"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 26 records.

RecordAgency IDAgencyUse caseStage
R1033HHSGrantSolutions Recipient Risk ToolDeployed
R1089FDIC-71FDICBackground Check Tool for Fraud InvestigationsDeployed
R1167GSALogin.gov: artificial intelligence technology used for detecting and mitigating fraud for remote unsupervised identity verificationDeployed
R1496DOJ-0022DOJNational Insurance Crime Bureau ISO ClaimSearchDeployed
R1935DHS-81DHSPassport Anomaly ModelDeployed
R1960DHS-68DHSEmpty Container Detection Model (Cargo Insights Team)Deployed
R1987DHS-2605DHSLexis NexisDeployed
R2232VA-24-3291VAPayment Redirect Fraud (PRF) ModelDeployed
R2843TREAS-IRS-59TREASIdentity VerificationDeployed
R3122SSADigital Identity Verification ServicesDeployed
R0614HHSUnaccompanied Child Sponsor Identity VerificationPre-deployment
R0741HHSEnhanced Direct Enrollment Outlier DetectionPre-deployment
R0744HHSRisk Adjustment Outlier AnalysisPre-deployment
R0745HHSAgent/Broker Fraud Analysis (ABCQI)Pre-deployment
R0768HHSArtificial Intelligence Use Case Pilot in Medical Review on Medicare Fee-For-Service (FFS) Improper Payment Measurement (Comprehensive Error Rate Testing Program) DataPre-deployment
R0776HHSContract Invoice Analyzer AssistantPre-deployment
R1164GSAAI-Powered Visibility for Supply and Vendor Risk ResiliencePre-deployment
R1295DOL-26DOLWeb Scraping to Identify Potentially Fraudulent Multiple Employer Welfare Arrangements (MEWAs)Retired
R1621DOJ-0184DOJEnhanced Proactive Financial Analysis Techniques for Fusion DesktopPre-deployment
R1739DOJ-0314DOJClaims Program Predictive Fraud AnalyticsPre-deployment
R1764DOJ-0339DOJAI-driven Fraud DetectionPre-deployment
R1840DHS-2724DHSProgram Integrity (RRAD-PI) AI Counter-Fraud Enhancement MeasuresPre-deployment
R2059FERC-0003FERCEnhance Market Surveillance and Fraud Detection Use CasePre-deployment
R2167VA-24-1360VAPotential Fraud or WastePre-deployment
R2217VA-24-2307VAAudit Service Connection Designations Associated with PrescriptionsPilot
R3091DOC-220DOCPatent Fraud Detection & MitigationNot reported

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