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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 = DOI; feedback = in_progress

Generated 2026-10-12 14:41 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 = DOI; feedback = in_progress · 9 records

Key findings

  • 9 use-case records from 1 agencies: 1 deployed (11%), 2 pilots, 6 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.
  • 0% of reported deployed use cases (0 of 1) are classified as generative or agentic AI.
  • Sourcing is reported for 67% of use cases. Where reported, 100% involve in-house development.

Lifecycle

StageRecordsShare
Deployed111%
Pilot222%
Pre-deployment667%

AI technology

ClassificationRecordsShareDeployed
Generative AI111%0
Classical / predictive ML889%1

Agencies

AgencyRecordsDeployedHigh-impactCompleteness
DOI · Department of the Interior91092%

High-impact designation

DesignationRecords
Not high-impact9

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 9 records.

RecordAgency IDAgencyUse caseStage
R2592DOI-0171DOIRangeland Condition Monitoring Assessment and Projection (RCMAP) [2024 INV#WO0000000107126]Deployed
R2594DOI-0169DOICHS Q Business AI Assistant (theKraken)Pilot
R2597DOI-0166DOIMachine Learning based shoreline detection and sea ice dynamics using coastal cameras [2024 INV#WO0000000108008]Pre-deployment
R2598DOI-0165DOITsunami Hazard Analysis [2024 INV#WO0000000108470]Pre-deployment
R2600DOI-0163DOIDetermining the resource potential of critical minerals in seafloor massive sulfide deposits [2024 INV#WO0000000109311]Pre-deployment
R2609DOI-0152DOILead attribution modelPre-deployment
R2637DOI-0121DOI[Un]supervised clustering of [non-]earthquake signals commonly recorded on regional seismic networksPre-deployment
R2638DOI-0110DOIInference of PFAS precursor compositionsPre-deployment
R2682DOI-0071DOIPathogen identification in salmonPilot

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