Federal AI Intelligence · U.S. Government AI Observatory

Federal AI landscape: executive briefing

Filtered: agency = DOE; AI type = classical_ml

Generated 2026-10-12 08:41 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 = DOE; AI type = classical_ml · 105 records

Key findings

105 use-case records from 1 agencies: 21 deployed (20%), 13 pilots, 71 in development or acquisition, 0 retired, 0 with no stage reported.
7 records are designated high-impact; 0 of them (0%) answered at least one minimum-practice question.
0% of reported deployed use cases (0 of 21) are classified as generative or agentic AI.
Sourcing is reported for 39% of use cases. Where reported, 66% involve in-house development.

Lifecycle

Stage	Records	Share
Deployed	21	20%
Pilot	13	12%
Pre-deployment	71	68%

AI technology

Classification	Records	Share	Deployed
Classical / predictive ML	105	100%	21

Agencies

Agency	Records	Deployed	High-impact	Completeness
DOE · Department of Energy	105	21	7	75%

High-impact designation

Designation	Records
High-impact	7
Presumed high-impact, determined not	3
Not high-impact	95

Governance evidence: use cases designated high-impact

Practice	No answer	In scope
Pre-deployment testing	7	7
AI impact assessment	7	7
Independent review	7	7
Ongoing monitoring	7	7
Operator training	7	7
Fail-safe	7	7
Appeal process	7	7
User and public consultation	7	7

"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
R3277	DOE-195	DOE	Machine Learning for geophysical data inversion	Deployed
R3290	DOE-347	DOE	Network Security and Analysis	Deployed
R3293	DOE-351	DOE	Elucidating Genetic and Environmental Risk Factors for Antipsychotic-induced Metabolic Adverse Effects Using AI	Deployed
R3298	DOE-356	DOE	Physics-Informed Learning Machines for Multiscale and Multiphysics Problems (PhILMs)	Deployed
R3300	DOE-358	DOE	Regional waste feedstock conversion to biofuels	Deployed
R3331	DOE-456	DOE	Machine Learning components within Splunk Enterprise Security	Deployed
R3332	DOE-458	DOE	Machine Learning components within CrowdStrike	Deployed
R3343	DOE-477	DOE	OPQ-AI	Deployed
R3419	DOE-563	DOE	ServiceNow Classification Prediction	Deployed
R3425	DOE-57	DOE	Elastic Stack Technology (ELK)	Deployed
R3444	DOE-59	DOE	Cognitive Prescreen Tool (CPT)	Deployed
R3450	DOE-595	DOE	AI and natural-language powered search	Deployed
R3489	DOE-632	DOE	Invoice Scanning System	Deployed
R3493	DOE-637	DOE	ServiceNow Cluster Analysis	Deployed
R3495	DOE-64	DOE	high level synthesis for machine learning (previously hls4ml)	Deployed
R3499	DOE-643	DOE	ServiceNow Similarity Analysis	Deployed
R3501	DOE-645	DOE	Georeference Figures	Deployed
R3514	DOE-658	DOE	pComply-AI-High Risk	Deployed
R3515	DOE-659	DOE	Groundwater Modeling	Deployed
R3522	DOE-665	DOE	OpenText for Records Management (File share auto-classification)	Deployed
R3556	DOE-70	DOE	READS: Real-time Edge AI for Distributed Systems	Deployed
R3272	DOE-118	DOE	Natural Language Processing	Pre-deployment
R3273	DOE-120	DOE	DOE AI Data Infrastructure System	Pre-deployment
R3274	DOE-125	DOE	Creation of polymer datasets and inverse design of polymers with targeted backbones having High CO2 permeability and high CO2/N2 selectivity.	Pre-deployment
R3275	DOE-150	DOE	To use AI to calibrate the simulation model by matching simulation data with production history data.	Pre-deployment
R3276	DOE-179	DOE	Data discovery, processing, and generation using machine learning for a range of CCS data and information	Pre-deployment
R3282	DOE-331	DOE	ORNL: AI for Transportation and Mobility	Pre-deployment
R3283	DOE-333	DOE	ORNL: AI for Energy Generation and Distribution	Pre-deployment
R3284	DOE-334	DOE	ORNL: AI for Advanced Manufacturing	Pre-deployment
R3287	DOE-338	DOE	ORNL: AI for Neutron Science	Pre-deployment
R3289	DOE-340	DOE	ORNL: AI for Fusion Energy	Pre-deployment
R3294	DOE-352	DOE	APT Analytics	Pre-deployment
R3299	DOE-357	DOE	Managing curb allocation in cities	Pre-deployment
R3302	DOE-360	DOE	AI techniques for identification of suitable delivery parking spaces in an urban scenario	Pre-deployment
R3303	DOE-361	DOE	Surrogate models for probabilistic Bayesian inference	Pre-deployment
R3328	DOE-453	DOE	MI8 Collimators Surogate Model	Pilot
R3348	DOE-485	DOE	Unleashing AI Transformer Models on FPGAs for Accelerating LHC and Particle Physics	Pre-deployment
R3366	DOE-506	DOE	Advanced Peer to Peer Transactive Energy Platform with Predictive Optimization	Pre-deployment
R3368	DOE-508	DOE	ServiceNow Predictive Intelligence	Pre-deployment
R3372	DOE-513	DOE	Nanoparticle growth kinetics and mechanism	Pre-deployment

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