Federal AI Intelligence · U.S. Government AI Observatory

Custom inventory report

Filter: agency = DOI; stage = pre_deployment

Generated 2026-10-12 07:56 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; stage = pre_deployment · 105 records

Key findings

105 use-case records from 1 agencies: 0 deployed (0%), 0 pilots, 105 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 19% of use cases. Where reported, 90% involve in-house development.

Lifecycle

Stage	Records	Share
Pre-deployment	105	100%

AI technology

Classification	Records	Share
Generative AI	10	10%
Classical / predictive ML	76	72%
Natural language processing	9	9%
Computer vision	4	4%
Agentic AI	1	1%
Reinforcement learning	1	1%
Other	4	4%

Agencies

Agency	Records	Deployed	High-impact	Completeness
DOI · Department of the Interior	105	0	0	85%

High-impact designation

Designation	Records
Not high-impact	105

Governance evidence: use cases designated high-impact

Practice	In place	In progress	Not in place	N/A or precluded	Other	No answer	In scope
Pre-deployment testing	0	0	0	0	0	0	0
AI impact assessment	0	0	0	0	0	0	0
Independent review	0	0	0	0	0	0	0
Ongoing monitoring	0	0	0	0	0	0	0
Operator training	0	0	0	0	0	0	0
Fail-safe	0	0	0	0	0	0	0
Appeal process	0	0	0	0	0	0	0
User and public consultation	0	0	0	0	0	0	0

"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

First 40 of 105 records, deployed first. The full list is available as CSV from the explorer with the same filters.

Record	Agency ID	Agency	Use case	Stage
R2500	DOI-0266	DOI	Use of AI to Enhance Flash Flood Forecast Tool [2024 Inv#WO0000000110323]	Pre-deployment
R2501	DOI-0265	DOI	Bird Nest Detection [2024 Inv#WO0000000110506]	Pre-deployment
R2502	DOI-0264	DOI	Remote Sensing Coastal Change - Shoreline Change	Pre-deployment
R2503	DOI-0260	DOI	ROV Smart Touch Subsea Pipeline Inspections	Pre-deployment
R2506	DOI-0257	DOI	Level 1 Survey Report Corrosion Level Classification	Pre-deployment
R2507	DOI-0256	DOI	Well Activity Report Classification	Pre-deployment
R2508	DOI-0255	DOI	Autonomous Drone Inspections	Pre-deployment
R2509	DOI-0254	DOI	Development of a computer vision model to monitor for early detection of habitat loss across the landscape. [2024 INV#DOI-65]	Pre-deployment
R2517	DOI-0246	DOI	ChatGPT to write Python scripts for ArcGIS Pro Maps to be CVD-Friendly [2024 INV#WO0000000107402]	Pre-deployment
R2519	DOI-0244	DOI	Harmful Algal Bloom prediction and detection system for Williams Fork Reservoir [2024 INV#WO0000000184339]	Pre-deployment
R2523	DOI-0240	DOI	Use modern AI/ML approaches to gain insight into USGS unstructured data such as text [2024 INV#WO0000000131706]	Pre-deployment
R2524	DOI-0239	DOI	Parsing large quantities of text data [2024 INV#WO0000000113692]	Pre-deployment
R2527	DOI-0236	DOI	Avian population estimates from passive acoustic monitoring [2024 INV#WO0000000109725]	Pre-deployment
R2528	DOI-0235	DOI	FEMA mixed population flood-frequency analysis [2024 INV#WO0000000109723]	Pre-deployment
R2532	DOI-0231	DOI	Mapping sagebrush from drones to satellites [2024 INV#WO0000000109568]	Pre-deployment
R2535	DOI-0228	DOI	Reinforcement Learning for Helmholtz Coil Operation and Simulation [2024 INV#WO0000000109497]	Pre-deployment
R2537	DOI-0226	DOI	Machine Learning algorithm for stream velocity prediction [2024 INV#WO0000000109319]	Pre-deployment
R2543	DOI-0220	DOI	Wildlife species recognition and distance from camera estimation [2024 INV#WO0000000109245]	Pre-deployment
R2546	DOI-0217	DOI	Development of a Strategic Framework for Use and Implementation of Machine Learning in Energy Resource Program Workflows [2024 INV#WO0000000109216]	Pre-deployment
R2552	DOI-0211	DOI	Predicting Sparse (Geothermal) Resources Availability by using Machine Learning [2024 INV#WO0000000109195]	Pre-deployment
R2557	DOI-0206	DOI	SAMPLE Toolbox [2024 INV#WO0000000109123]	Pre-deployment
R2558	DOI-0205	DOI	Mapping wildfire fuels in previously burned landscapes [2024 INV#WO0000000109121]	Pre-deployment
R2560	DOI-0203	DOI	Advancing image-based surveys to support sea duck conservation along the Pacific Flyway [2024 INV#WO0000000109096]	Pre-deployment
R2563	DOI-0200	DOI	Predicting inundation dynamics of small forested wetlands [2024 INV#WO0000000109089]	Pre-deployment
R2565	DOI-0198	DOI	Environmental streamflows in the United States: historical patterns and predictions [2024 INV#WO0000000109075]	Pre-deployment
R2574	DOI-0189	DOI	Zero shot segmentation to expedite Quaternary geologic mapping [2024 INV#WO0000000108739; 2024 INV#WO0000000109150]	Pre-deployment
R2576	DOI-0187	DOI	Tracking wetlands and water movement across watersheds [2024 INV#WO0000000108734]	Pre-deployment
R2577	DOI-0186	DOI	Everglades-Flux, Digital Surveys [2024 INV#WO0000000108630]	Pre-deployment
R2579	DOI-0184	DOI	Summarization of documents and output to ECOSphere species workflow [2024 INV#DOI-63]	Pre-deployment
R2580	DOI-0183	DOI	Cell Phone Application for Oil Spill Detection [2024 INV#WO0000000108285]	Pre-deployment
R2582	DOI-0181	DOI	National Wildlife Disease Database (NWDD) [2024 INV#WO0000000108149; 2024 INV#WO0000000109192]	Pre-deployment
R2589	DOI-0174	DOI	Data-driven approaches to filling missing time-series data within the San Francisco Bay-Delta [2024 INV#WO0000000107683; INV#WO0000000107488]	Pre-deployment
R2596	DOI-0164	DOI	Mapping ecohydrological headwater refugia	Pre-deployment
R2597	DOI-0166	DOI	Machine Learning based shoreline detection and sea ice dynamics using coastal cameras [2024 INV#WO0000000108008]	Pre-deployment
R2598	DOI-0165	DOI	Tsunami Hazard Analysis [2024 INV#WO0000000108470]	Pre-deployment
R2599	DOI-0167	DOI	Machine learning for streamflow forecasting [2024 INV#WO0000000109317]	Pre-deployment
R2600	DOI-0163	DOI	Determining the resource potential of critical minerals in seafloor massive sulfide deposits [2024 INV#WO0000000109311]	Pre-deployment
R2602	DOI-0157	DOI	Remote sensing of particulate and filter passing mercury species: models and proxies	Pre-deployment
R2605	DOI-0154	DOI	An integrated sensor network and data driven approach to satellite remote sensing of Dissolved Organic Matter	Pre-deployment
R2608	DOI-0153	DOI	Machine Learning for Rapid Earthquake Magnitude Estimation	Pre-deployment

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