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

Custom inventory report

Filter: high-impact = not_high_impact; AI type = unknown; sourcing = unknown

Generated 2026-10-12 15:46 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: high-impact = not_high_impact; AI type = unknown; sourcing = unknown · 246 records

Key findings

  • 246 use-case records from 16 agencies: 0 deployed (0%), 0 pilots, 0 in development or acquisition, 246 retired, 0 with no stage reported.
  • 0 records are designated high-impact; 0 of them (n/a) answered at least one minimum-practice question.
  • HHS, VA, DHS report 106 of 246 use cases (43%).
  • Sourcing is reported for 0% of use cases. Where reported, n/a involve in-house development.

Lifecycle

StageRecordsShare
Retired246100%

AI technology

ClassificationRecordsShareDeployed
Not reported246100%0

Agencies

AgencyRecordsDeployedHigh-impactCompleteness
HHS · Department of Health and Human Services490017%
VA · Department of Veterans Affairs310017%
DHS · Department of Homeland Security260017%
STATE · Department of State230017%
USDA · Department of Agriculture190017%
DOE · Department of Energy150039%
FDIC · Federal Deposit Insurance Corporation140017%
DOI · Department of the Interior130042%
SEC · Securities and Exchange Commission120017%
DOL · Department of Labor110017%
DOJ · Department of Justice100017%
TREAS · Department of the Treasury100017%
EPA · Environmental Protection Agency60017%
FHFA · Federal Housing Finance Agency40017%
HUD · Department of Housing and Urban Development20017%
NASA · National Aeronautics and Space Administration10017%

High-impact designation

DesignationRecords
Not high-impact246

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

First 40 of 246 records, deployed first. The full list is available as CSV from the explorer with the same filters.

RecordAgency IDAgencyUse caseStage
R0003SEC-1SECComment Letter Review and AnalysisRetired
R0004SEC-2SECForms FiledRetired
R0005SEC-3SECTailored Shareholder Report (TSR)Retired
R0008SEC-7SECMobile Phone Artificial Intelligence FeaturesRetired
R0010SEC-10SECEDGAR Filing Certification Review SolutionRetired
R0012SEC-12SECEDGAR Filing Audit Report SolutionRetired
R0013SEC-14SECEDGAR Technical Support Public ChatbotRetired
R0014SEC-15SECEDGAR Filing Signature Review SolutionRetired
R0015SEC-16SECEDGAR Filing Risk Disclosure Review SolutionRetired
R0016SEC-17SECTesting Developer WorkflowsRetired
R0020SEC-22SECTesting of Various AI Algorithms and ModelsRetired
R0025SEC-27SECUsing AI to Help with Coding-Related Tasks/QuestionsRetired
R0071FHFA-5FHFAPublic Comments Summarization and Topic Classifications Pilot ProjectRetired
R0073FHFA-7FHFAAnalytics,, Search, Queries and LLM integration for data management on OracleRetired
R0074FHFA-8FHFAPython modules to support AI/MLRetired
R0075FHFA-9FHFAR modules to support AI/MLRetired
R0177NASA-249NASAVolcano SensorWebRetired
R0541HUD-2024-005HUDQuantitative Text AnalysisRetired
R0542HUD-2024-006HUDTranslation of Digital MediaRetired
R0596HHSDesign Your FacilityRetired
R0598HHSGrant Spend Health AnalysisRetired
R0602HHSUnaccompanied Children Process Model Digital TwinsRetired
R0603HHSAnalyzing Public Comments on Proposed RuleRetired
R0604HHSOutreach List SegmentationRetired
R0609HHSPolicy Knowledge Base Data MigrationRetired
R0611HHSIntakes Referral ParserRetired
R0612HHSTraining and Technical Assistance (TTA) GenAI ChatbotRetired
R0613HHSFunding Opportunity Redundancy AnalysisRetired
R0623HHSChatbotRetired
R0624HHSChatbotRetired
R0625HHSEnhancing Diversity in Peer Review - PilotRetired
R0626HHSNLQuery- As Data or PulseRetired
R0627HHSQuality and Safety Review System AI-enabled automated abstractionRetired
R0629HHSUSPSTF Public Forms Data AI IntegrationRetired
R0637HHSHaMLET: Harnessing Machine Learning to Eliminate TuberculosisRetired
R0638HHSAdverse Childhood Experiences (ACEs) Literature Review DashboardRetired
R0661HHSA reusable NLP pipeline for clinical narratives preprocessing and characterizationRetired
R0666HHSEvaluating Generative AI for polio containment.Retired
R0683HHSDevelopment of in-silico genomic and patient datasets using generative ML algorithmsRetired
R0686HHSRetrieval Augmented Generation (RAG) with Q-BankRetired

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