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

Custom inventory report

Filter: high-impact = high_impact; function = cyber_detection

Generated 2026-10-14 06:12 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: high-impact = high_impact; function = cyber_detection · 6 records

Key findings

  • 6 use-case records from 2 agencies: 1 deployed (17%), 1 pilots, 4 in development or acquisition, 0 retired, 0 with no stage reported.
  • 6 records are designated high-impact; 1 of them (17%) answered at least one minimum-practice question.
  • 0% of reported deployed use cases (0 of 1) 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 33% of use cases. Where reported, 0% involve in-house development.

Lifecycle

StageRecordsShare
Deployed117%
Pilot117%
Pre-deployment467%

AI technology

ClassificationRecordsShareDeployed
Generative AI117%0
Classical / predictive ML350%1
Natural language processing233%0

Agencies

AgencyRecordsDeployedHigh-impactCompleteness
DOJ · Department of Justice31372%
VA · Department of Veterans Affairs30364%

High-impact designation

DesignationRecords
High-impact6

Governance evidence: use cases designated high-impact

PracticeIn placeIn progressNot in placeN/A or precludedOtherNo answerIn scope
Pre-deployment testing0100056
AI impact assessment0100056
Independent review0100056
Ongoing monitoring0100056
Operator training0100056
Fail-safe0100056
Appeal process0100056
User and public consultation0100056

"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 6 records.

RecordAgency IDAgencyUse caseStage
R1611DOJ-0169DOJUAS Threat DetectorDeployed
R1627DOJ-0190DOJNarrative Analysis for Fusion DesktopPre-deployment
R1628DOJ-0191DOJNarrative Analysis for DOJ MISPre-deployment
R2068VA-25-6956VACyber Authorization Memo GenerationPre-deployment
R2076VA-25-3685VACSOC AI Analyst Accelerator (Andesite AI)Pre-deployment
R2205VA-25-6479VASecure Access Service Edge (SASE)Pilot

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