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

Custom inventory report

Filter: agency = STATE; AI type = unknown

Generated 2026-10-12 20:40 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 = STATE; AI type = unknown · 23 records

Key findings

  • 23 use-case records from 1 agencies: 0 deployed (0%), 0 pilots, 0 in development or acquisition, 23 retired, 0 with no stage reported.
  • 0 records are designated high-impact; 0 of them (n/a) answered at least one minimum-practice question.
  • Sourcing is reported for 0% of use cases. Where reported, n/a involve in-house development.

Lifecycle

StageRecordsShare
Retired23100%

AI technology

ClassificationRecordsShareDeployed
Not reported23100%0

Agencies

AgencyRecordsDeployedHigh-impactCompleteness
STATE · Department of State230017%

High-impact designation

DesignationRecords
Not high-impact23

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

All 23 records.

RecordAgency IDAgencyUse caseStage
R3212STATEFOIA Web ML Document IndexerRetired
R3217STATETravel.State.Gov (TSG) Enhanced Search and ChatbotRetired
R3218STATETravel.state.gov (TSG) Content Refinement with AI Text EditorRetired
R3219STATEPredictive Analytics PlatformRetired
R3220STATEInnovation and Transformation Measurement and PredictionRetired
R3221STATECodeGen - AI-assisted IT Application DevelopmentRetired
R3225STATEViolence Against Civilians ModelRetired
R3226STATEUser and Entity Behavior Analytics (UEBA)Retired
R3228STATEFOIA 360 AI Matching ToolRetired
R3233STATEDT Data Analytics and Assessment (DAA) AI Use Case ITCP Data HarvestRetired
R3234STATEPOA&M OrchestrationRetired
R3236STATEJ Reports Data Collection & Management Tool (DCT)Retired
R3238STATEForeignAssistance.gov Processing for Mismatched DataRetired
R3244STATEFSI Enterprise Operations - Gaming and SimulationsRetired
R3245STATEEnhancing Training Effectiveness in FSILearn Using AIRetired
R3246STATEFSI Continuous Learning SolutionsRetired
R3254STATENatural Language Processing (NLP) to pull key information from unstructured textsRetired
R3256STATEECA Program Management and Outreach - SummarizationRetired
R3257STATEStoryzyRetired
R3258STATEAI Tools to Enhance PD WorkflowsRetired
R3259STATEMass Mobilization ModelRetired
R3260STATESenturion AlphaRetired
R3263STATETranslation of Consular Content using AIRetired

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