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

Custom inventory report

Filter: stage = pre_deployment; AI type = unknown

Generated 2026-10-12 16:02 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: stage = pre_deployment; AI type = unknown · 12 records

Key findings

  • 12 use-case records from 2 agencies: 0 deployed (0%), 0 pilots, 12 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.
  • Sourcing is reported for 0% of use cases. Where reported, n/a involve in-house development.

Lifecycle

StageRecordsShare
Pre-deployment12100%

AI technology

ClassificationRecordsShareDeployed
Not reported12100%0

Agencies

AgencyRecordsDeployedHigh-impactCompleteness
NSF · National Science Foundation110025%
CFTC · Commodity Futures Trading Commission10017%

High-impact designation

DesignationRecords
Not reported12

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 12 records.

RecordAgency IDAgencyUse caseStage
R00888NSFBudget Area Topic Classification ToolPre-deployment
R009010NSFAdobe PhotoshopPre-deployment
R009119NSFResubmit CheckerPre-deployment
R009222NSFAmazon Web Services(AWS) Assisted Software Development (DIS AI Assisted Development)Pre-deployment
R009324NSFMine Potential Reviewer's areas of expertisePre-deployment
R009425NSFUse AI to populate reviewer "areas of expertise" and state of potential Regional Engines submitters (members of organizations)Pre-deployment
R009526NSFEnhancing Technology, Innovation and Partnerships (TIP) Awards: Efficient Tagging for the 10 Key Technology Areas (KTAs)Pre-deployment
R009635NSFOpen-source topic identification for the Public Engagement with Science Initiative data analysis.Pre-deployment
R009848NSFNSF AI-Ready Research Performance Progress Reports (RPPR) DataPre-deployment
R010051NSFA document summarizer via Natural Language ProcessingPre-deployment
R010152NSFDocument similarity analysis via Natural Language ProcessingPre-deployment
R0530CFTC-003CFTCStress Testing Scenarios with Deep LearningPre-deployment

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