Federal AI Intelligence · U.S. Government AI Observatory

Custom inventory report

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

Generated 2026-10-12 23:58 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 = DOE; AI type = generative; sourcing = unknown · 21 records

Key findings

21 use-case records from 1 agencies: 0 deployed (0%), 0 pilots, 21 in development or acquisition, 0 retired, 0 with no stage reported.
10 records are designated high-impact; 0 of them (0%) 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	21	100%

AI technology

Classification	Records	Share	Deployed
Generative AI	21	100%	0

Agencies

Agency	Records	Deployed	High-impact	Completeness
DOE · Department of Energy	21	0	10	62%

High-impact designation

Designation	Records
High-impact	10
Not high-impact	11

Governance evidence: use cases designated high-impact

Practice	No answer	In scope
Pre-deployment testing	10	10
AI impact assessment	10	10
Independent review	10	10
Ongoing monitoring	10	10
Operator training	10	10
Fail-safe	10	10
Appeal process	10	10
User and public consultation	10	10

"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 21 records.

Record	Agency ID	Agency	Use case	Stage
R3279	DOE-328	DOE	ORNL: Foundational AI Research	Pre-deployment
R3280	DOE-329	DOE	ORNL: AI for Materials Science	Pre-deployment
R3285	DOE-336	DOE	ORNL: AI for Bio and Health Sciences	Pre-deployment
R3288	DOE-339	DOE	ORNL: AI for Earth Systems	Pre-deployment
R3326	DOE-451	DOE	ServiceNow AI Search	Pre-deployment
R3329	DOE-454	DOE	AI for High Risk Property	Pre-deployment
R3340	DOE-472	DOE	Argonne Resilience AI Assistant ARAIA (nee CALLM)	Pre-deployment
R3406	DOE-550	DOE	CURIE - Conversational Unified Research Information Engine	Pre-deployment
R3416	DOE-560	DOE	AI for QA Audit	Pre-deployment
R3461	DOE-606	DOE	AI Enabled Code Review	Pre-deployment
R3476	DOE-620	DOE	AI Video Creation	Pre-deployment
R3492	DOE-635	DOE	QuantomVision	Pre-deployment
R3496	DOE-640	DOE	Knowledge Capture Agent (KCA)	Pre-deployment
R3497	DOE-641	DOE	AI Support Agent Chatbot	Pre-deployment
R3504	DOE-648	DOE	O365 Copilot	Pre-deployment
R3506	DOE-650	DOE	Critical Materials	Pre-deployment
R3538	DOE-681	DOE	AI for Vendor Compliance	Pre-deployment
R3546	DOE-690	DOE	Copilot Studio	Pre-deployment
R3552	DOE-696	DOE	AI Safety Tool	Pre-deployment
R3564	DOE-708	DOE	Microsoft 365 Copilot	Pre-deployment
R3595	DOE-738	DOE	FY19 Lab Call – Livewire Data Sharing Platform	Pre-deployment

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