Federal AI Intelligence · U.S. Government AI Observatory

Custom inventory report

Filter: agency = DOI; AI type = generative; sourcing = unknown

Generated 2026-10-13 19:47 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; AI type = generative; sourcing = unknown · 8 records

Key findings

8 use-case records from 1 agencies: 0 deployed (0%), 0 pilots, 8 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

Stage	Records	Share
Pre-deployment	8	100%

AI technology

Classification	Records	Share	Deployed
Generative AI	8	100%	0

Agencies

Agency	Records	Deployed	High-impact	Completeness
DOI · Department of the Interior	8	0	0	83%

High-impact designation

Designation	Records
Not high-impact	8

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

All 8 records.

Record	Agency ID	Agency	Use case	Stage
R2623	DOI-0136	DOI	Refining Flood Risk Predictions in Hawai?i with Generative Machine Learning	Pre-deployment
R2693	DOI-0057	DOI	FBMS UPC Chatbot	Pre-deployment
R2697	DOI-0053	DOI	Assessment Inventory and Monitoring (AIM) Chatbot	Pre-deployment
R2698	DOI-0051	DOI	NEPA Document Generation	Pre-deployment
R2699	DOI-0050	DOI	GraphRAG Comment Analysis and Management Solution	Pre-deployment
R2700	DOI-0049	DOI	User guides/training provided in chat form	Pre-deployment
R2723	DOI-0024	DOI	Document Review Platform Generative AI	Pre-deployment
R2732	DOI-0013	DOI	Comprehensive Condition Assessment	Pre-deployment

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