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

Federal AI landscape: executive briefing

Filtered: topic = Information Technology; AI type = generative; sourcing = both

Generated 2026-10-12 16:36 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: topic = Information Technology; AI type = generative; sourcing = both · 23 records

Key findings

  • 23 use-case records from 7 agencies: 9 deployed (39%), 12 pilots, 2 in development or acquisition, 0 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, TREAS, DOE report 17 of 23 use cases (74%).
  • 100% of reported deployed use cases (9 of 9) are classified as generative or agentic AI.
  • Sourcing is reported for 100% of use cases. Where reported, 100% involve in-house development.

Lifecycle

StageRecordsShare
Deployed939%
Pilot1252%
Pre-deployment29%

AI technology

ClassificationRecordsShareDeployed
Generative AI23100%9

Agencies

AgencyRecordsDeployedHigh-impactCompleteness
HHS · Department of Health and Human Services830100%
TREAS · Department of the Treasury510100%
DOE · Department of Energy410100%
USDA · Department of Agriculture210100%
STATE · Department of State220100%
FCC · Federal Communications Commission100100%
SSA · Social Security Administration110100%

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
R0767HHSCMS ChatDeployed
R0809HHSIDR Support BotDeployed
R0810HHSEligibility & Enrollment Medicare Online (ELMO) ChatbotDeployed
R1475USDA-177USDAChatbot for IT Customer Help DeskDeployed
R2787REQ-2025-02100TREASFORMS AIDeployed
R3113SSAAgency Support Companion (ASC) chatbotDeployed
R3231STATEAI Research Engine (AIRE)Deployed
R3261STATEWHA/EX Information ManagementDeployed
R3354DOE-492DOEYurts AI search functionDeployed
R0548FCC-0001FCCAI-Enhanced ULS Reverse EngineeringPilot
R0783HHSMedicare AI Customer InsightsPilot
R0807HHSC3PO: CMS Comprehensive Cybersecurity and Privacy OptimizationPilot
R0884HHSKnowledge NavigatorPilot
R1021HHSSection 508 Azure OpenAI ChatbotPilot
R1025HHSABE (AI-driven. Beneficial. Efficient.)Pilot
R1396USDA-098USDAAxon+ Copilot Studio ChatbotPilot
R276735TREASOCC.DocChatPilot
R2778REQ-2024-01872TREASLarge Language Model (LLM) Chatbot for Proof of ConceptPilot
R2797REQ-2025-02280TREASLocal LLMs EvaluationPre-deployment
R2805TREAS-118TREASInternal Revenue Manual Research Aid (IRMA)Pilot
R3477DOE-621DOEChatGPTPilot
R3529DOE-671DOELISA Chatbot PilotPilot
R3557DOE-700DOEAmazon Q Chatbot PilotPre-deployment

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