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

Governance disclosure assessment

Filtered: AI type = unknown

Generated 2026-10-12 11:29 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 = unknown · 662 records

Key findings

  • 662 use-case records from 21 agencies: 3 deployed (0%), 5 pilots, 12 in development or acquisition, 304 retired, 338 with no stage reported.
  • 55 records are designated high-impact; 0 of them (0%) answered at least one minimum-practice question.
  • DOC, VA, TVA report 354 of 662 use cases (53%).
  • 0% of reported deployed use cases (0 of 3) are classified as generative or agentic AI.
  • Sourcing is reported for 0% of use cases. Where reported, n/a involve in-house development.
  • 338 use cases (51%) have no reported development stage.

Governance evidence: use cases that answered at least one practice question

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.

Agencies with high-impact records

AgencyHigh-impactAnswered any practicePractice answers in place
VA4100 of 328
DOJ900 of 72
DHS400 of 32
TREAS100 of 8

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 662 records, deployed first. The full list is available as CSV from the explorer with the same filters.

RecordAgency IDAgencyUse caseStage
R00877NSFServiceNow GenAI "Now Assist"Deployed
R010253NSFMicrosoft 365 (M365) AI Builder pre-built Generative Pre-trained Transformer (GPT) for SummarizationDeployed
R0529CFTC-001CFTCAnomaly Detection for Data QualityDeployed
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
R00888NSFBudget Area Topic Classification ToolPre-deployment
R00899NSFAI voice overPilot
R009010NSFAdobe PhotoshopPre-deployment
R009119NSFResubmit CheckerPre-deployment
R009222NSFAmazon Web Services(AWS) Assisted Software Development (DIS AI Assisted Development)Pre-deployment
R009324NSFMine Potential Reviewer's areas of expertisePre-deployment
R009425NSFUse AI to populate reviewer "areas of expertise" and state of potential Regional Engines submitters (members of organizations)Pre-deployment
R009526NSFEnhancing Technology, Innovation and Partnerships (TIP) Awards: Efficient Tagging for the 10 Key Technology Areas (KTAs)Pre-deployment
R009635NSFOpen-source topic identification for the Public Engagement with Science Initiative data analysis.Pre-deployment
R009738NSFHand-written text extraction using Textract for the Public Engagement with Science InitiativePilot
R009848NSFNSF AI-Ready Research Performance Progress Reports (RPPR) DataPre-deployment
R009949NSFTechnology, Innovation and Partnerships (TIP) Microsoft (MS) Copilot PilotPilot
R010051NSFA document summarizer via Natural Language ProcessingPre-deployment
R010152NSFDocument similarity analysis via Natural Language ProcessingPre-deployment
R010356NSFComparison of proposal similarities at different levels of National Science Foundation (NSF) organizationPilot
R0177NASA-249NASAVolcano SensorWebRetired
R0530CFTC-003CFTCStress Testing Scenarios with Deep LearningPre-deployment
R0531CFTC-004CFTCMPD Entity Risk ModelingPilot
R0541HUD-2024-005HUDQuantitative Text AnalysisRetired
R0542HUD-2024-006HUDTranslation of Digital MediaRetired
R0596HHSDesign Your FacilityRetired

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