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

Custom inventory report

Filter: monitoring = blank; feedback = affirmative

Generated 2026-10-12 18:01 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: monitoring = blank; feedback = affirmative · 19 records

Key findings

  • 19 use-case records from 3 agencies: 2 deployed (11%), 3 pilots, 14 in development or acquisition, 0 retired, 0 with no stage reported.
  • 1 records are designated high-impact; 1 of them (100%) answered at least one minimum-practice question.
  • 50% of reported deployed use cases (1 of 2) are classified as generative or agentic AI.
  • Of 1 deployed high-impact use cases, 0 report a completed AI impact assessment and 0 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 100% of use cases. Where reported, 74% involve in-house development.

Lifecycle

StageRecordsShare
Deployed211%
Pilot316%
Pre-deployment1474%

AI technology

ClassificationRecordsShareDeployed
Generative AI1474%1
Classical / predictive ML15%0
Computer vision15%1
Agentic AI15%0
Other211%0

Agencies

AgencyRecordsDeployedHigh-impactCompleteness
DOE · Department of Energy140098%
EAC · Election Assistance Commission41094%
SSA · Social Security Administration111100%

High-impact designation

DesignationRecords
High-impact1
Not high-impact18

Governance evidence: use cases designated high-impact

PracticeIn placeIn progressNot in placeN/A or precludedOtherNo answerIn scope
Pre-deployment testing0000011
AI impact assessment0100001
Independent review0000011
Ongoing monitoring0000011
Operator training0000011
Fail-safe1000001
Appeal process0001001
User and public consultation1000001

"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 19 records.

RecordAgency IDAgencyUse caseStage
R2065EAC-3EACGrants Lifecycle Application SystemDeployed
R3122SSADigital Identity Verification ServicesDeployed
R2063EAC-1EACAI Answers in Clearinghouse NetworkPilot
R2064EAC-2EACInternal Generative AI Tools for Staff ProductivityPilot
R2066EAC-4EACRouting emails from shared inboxesPilot
R3380DOE-522DOEAsk CASPre-deployment
R3400DOE-544DOEPoseidonPre-deployment
R3424DOE-569DOEAsk AlanPre-deployment
R3441DOE-587DOEDIRECTIVESPre-deployment
R3460DOE-604DOEFindMATIDPre-deployment
R3470DOE-615DOEAsk ITPre-deployment
R3494DOE-638DOEChatSRSPre-deployment
R3498DOE-642DOEUNSPSC CodesPre-deployment
R3551DOE-695DOESindriPre-deployment
R3561DOE-704DOEAsk HRPre-deployment
R3563DOE-707DOEmass3Pre-deployment
R3581DOE-723DOECricketsPre-deployment
R3582DOE-724DOENeptunePre-deployment
R3583DOE-725DOEAccessAIPre-deployment

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