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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: agency = VA; AI type = nlp

Generated 2026-10-12 11:27 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: agency = VA; AI type = nlp · 57 records

Key findings

  • 57 use-case records from 1 agencies: 24 deployed (42%), 6 pilots, 27 in development or acquisition, 0 retired, 0 with no stage reported.
  • 24 records are designated high-impact; 0 of them (0%) answered at least one minimum-practice question.
  • 0% of reported deployed use cases (0 of 24) are classified as generative or agentic AI.
  • Of 7 deployed high-impact use cases, 0 report a completed AI impact assessment and 7 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 53% of use cases. Where reported, 67% involve in-house development.

Governance evidence: use cases designated high-impact

PracticeIn placeIn progressNot in placeN/A or precludedOtherNo answerIn scope
Pre-deployment testing000002424
AI impact assessment000002424
Independent review000002424
Ongoing monitoring000002424
Operator training000002424
Fail-safe000002424
Appeal process000002424
User and public consultation000002424

"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
VA2400 of 192

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

RecordAgency IDAgencyUse caseStage
R2224VA-24-1938VAAutomated Claims ProcessingDeployed
R2225VA-24-2430VATERA Memorandum AutomationDeployed
R2231VA-24-2184VANational Training Team | Schools — FAQ Gen AI DashboardDeployed
R2234VA-24-4763VAMail Automation ServicesDeployed
R2235VA-24-790VAPension Optimization Initiative (POI)Deployed
R2308VA-25-2168VASleep ApneaDeployed
R2309VA-25-2209VACoordinated Care Tracking System (CCTS) Generative AI SupportDeployed
R2324VA-25-3234VAeDiscovery (VASI 2460): Predictive CodingDeployed
R2326VA-25-967VACHAMPVA AutomationDeployed
R2329VA-25-5163VACustomer SentimentDeployed
R2331VA-24-954VAMedallia Software as a Service (SaaS) - VSignals and ESignalsDeployed
R2336VA-24-2348VAReflexAIDeployed
R2337VA-24-2426VAApp feedback model for NLP tasksDeployed
R2339VA-24-2672VAApp Feedback categorization modelDeployed
R2341VA-24-3045VAVA Supply Chain Knowledge Management DashboardDeployed
R2342VA-24-3164VAHuman-Centered Design (HCD) User Feedback Summary, Analysis, and DesignDeployed
R2347VA-24-4148VADragon Medical OneDeployed
R2348VA-24-4193VADeep-Learning approaches to develop candidate lists of terms for use in text searchesDeployed
R2349VA-24-4472VAIdentify access to genetic testing in Veterans with breast cancer.Deployed
R2352VA-24-5665VAVA CART Myocardial Ischemia NLPDeployed
R2353VA-24-5706VAVA CART Ejection Fraction NLPDeployed
R2354VA-24-913VALimited Use of Azure Speech Services in PETALS PlatformDeployed
R2355VA-25-2291VAHospital Acquired InfectionsDeployed
R2356VA-25-3043VAUse of Large Language Models to improve classification of identified text snippets from the CLEVER natural language processing pipelineDeployed
R2071VA-24-2758VAVA VoiceBot for Call Center ModernizationPre-deployment
R2082VA-25-6276VASummarization of Clinical DataPre-deployment
R2088VA-25-393VAPredictive Claims Processing Capability POCPre-deployment
R2096VA-24-3082VATeledermatology Clinical Outcome ClassificationPre-deployment
R2097VA-24-3365VASummarize Progress NotesPre-deployment
R2100VA-24-4431VAReportability of Cancer Diagnosis InformationPre-deployment
R2101VA-24-4439VAPredict Patient SuicidePre-deployment
R2102VA-24-4554VAExtract patients’ diagnosis information and map the diagnosis to oncotreePre-deployment
R2103VA-24-4595VACancer Patients Symptom BurdenPre-deployment
R2118VA-25-3415VAJLV BoosterPre-deployment
R2125VA-25-4632VAFreed AI Medical ScribePre-deployment
R2128VA-25-4951VAClinical Trial MatchingPre-deployment
R2130VA-25-5182VALeveraging Acoustic-Linguistic Analytics and Social Determinants to Enhance Suicide Prevention Efforts in Veterans Crisis Line InterventionsPre-deployment
R2131VA-25-5693VAVAHC CRM- Veteran Self-ServicePre-deployment
R2132VA-25-5821VAEvidence, Policy, and Implementation Center (EPIC) QUERIPre-deployment
R2139VA-25-7910VAElectronic Mammogram Reporting (eMAMR)Pre-deployment

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