Federal AI Intelligence · U.S. Government AI Observatory

Federal AI landscape: executive briefing

Filtered: topic = Science; AI type = classical_ml; sourcing = unknown

Generated 2026-10-12 05:13 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: topic = Science; AI type = classical_ml; sourcing = unknown · 353 records

Key findings

353 use-case records from 7 agencies: 0 deployed (0%), 0 pilots, 353 in development or acquisition, 0 retired, 0 with no stage reported.
5 records are designated high-impact; 0 of them (0%) answered at least one minimum-practice question.
NASA, DOI, DOE report 335 of 353 use cases (95%).
Sourcing is reported for 0% of use cases. Where reported, n/a involve in-house development.

Lifecycle

Stage	Records	Share
Pre-deployment	353	100%

AI technology

Classification	Records	Share	Deployed
Classical / predictive ML	353	100%	0

Agencies

Agency	Records	High-impact	Completeness
NASA · National Aeronautics and Space Administration	242	0	58%
DOI · Department of the Interior	47	0	83%
DOE · Department of Energy	46	5	62%
USDA · Department of Agriculture	11	0	58%
HHS · Department of Health and Human Services	5	0	58%
VA · Department of Veterans Affairs	1	0	58%
TREAS · Department of the Treasury	1	0	58%

High-impact designation

Designation	Records
High-impact	5
Presumed high-impact, determined not	1
Not high-impact	347

Governance evidence: use cases designated high-impact

Practice	No answer	In scope
Pre-deployment testing	5	5
AI impact assessment	5	5
Independent review	5	5
Ongoing monitoring	5	5
Operator training	5	5
Fail-safe	5	5
Appeal process	5	5
User and public consultation	5	5

"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 353 records, deployed first. The full list is available as CSV from the explorer with the same filters.

Record	Agency ID	Agency	Use case	Stage
R0104	NASA-1	NASA	Anomaly Detection and Precursor Identification in UAV flight data	Pre-deployment
R0108	NASA-10	NASA	ExoMiner discovery of ExoPlanets via data from the Kepler and TESS space telescopes	Pre-deployment
R0114	NASA-21	NASA	Machine Learning Airport Surface Model: Estimated ON Time Prediction	Pre-deployment
R0115	NASA-22	NASA	Machine Learning Airport Surface Model: Taxi-in Prediction	Pre-deployment
R0120	NASA-35	NASA	Aero-Engines AI - a machine-learning app for aircraft engine system-performance prediction	Pre-deployment
R0121	NASA-40	NASA	Graph Neural Networks for Airfoil Performance Prediction	Pre-deployment
R0122	NASA-41	NASA	Inverse Design of Materials	Pre-deployment
R0124	NASA-64	NASA	Applying machine learning techniques to enhance the sensitivity and selectivity of multifunctional sensor platform	Pre-deployment
R0125	NASA-66	NASA	Artificial Intelligent Co-Processor Slice with Google Coral TPU For Automated Onboard Data-Product Generation	Pre-deployment
R0128	NASA-93	NASA	Deep Learning for Communication-Limited Spacecraft	Pre-deployment
R0129	NASA-97	NASA	Development of new tools for detecting and assessing resilient agriculural systems farm performance	Pre-deployment
R0130	NASA-100	NASA	Earth Information System Fire Pilot	Pre-deployment
R0131	NASA-105	NASA	Enabling Autonomous Differential Drag Control and Attitude Maneuvering Using Onboard Artificial Intelligence (AI) for SmallSat Distributed Space Missions (DSMs)	Pre-deployment
R0132	NASA-113	NASA	Forest responses to climate change	Pre-deployment
R0133	NASA-123	NASA	From Single Spacecraft to Synchronized Swarms: Fault Diagnosis for Distributed Spacecraft Mission Resilience	Pre-deployment
R0134	NASA-127	NASA	HEASARC X-ray Spectra and Light Curve data sets	Pre-deployment
R0135	NASA-128	NASA	High Rate Digital Spectrometer Enhancement with Neural Network AI	Pre-deployment
R0136	NASA-129	NASA	High Resolution Earth and Planetary Atmospheric Predictions using Machine Learning	Pre-deployment
R0137	NASA-133	NASA	HyperMapping with Hyperspectral Precise Pointing Optical Sensor (HYPPOS) for Decadal Survey Mission Pathfinder Activities	Pre-deployment
R0139	NASA-148	NASA	M4OPT: Multi-Mission Multi-Messenger Observation Planning Toolkit	Pre-deployment
R0140	NASA-149	NASA	Machine Intelligence for Small Satellites	Pre-deployment
R0141	NASA-154	NASA	Machine Learning of Ocean Worlds Laboratory Analog Seawater Volatiles	Pre-deployment
R0142	NASA-161	NASA	MERRAMax Automated feature selection	Pre-deployment
R0143	NASA-166	NASA	Multi-temporal analytic center framework	Pre-deployment
R0144	NASA-169	NASA	Optimization of Machine Learning Algorithms for Lidar to Detect Aerosols, Clouds, and the PBL (Planetary Boundary Layer)	Pre-deployment
R0145	NASA-171	NASA	Parameter estimation, emulator building, model tuning and sensitivity analysis of the ocean carbon cycle using ML	Pre-deployment
R0146	NASA-172	NASA	PIC-ASIC Spectrometer Demonstration for Ultrawideband and Hyperspectral Microwave Sounding	Pre-deployment
R0148	NASA-182	NASA	RAMjET: RApid Machine lEarned Triage - AI to classify astrophysical phenomena in photometric lightcurves	Pre-deployment
R0150	NASA-185	NASA	Research in Aritificial Intelligence for Spacecraft Resilience (RAISR)	Pre-deployment
R0152	NASA-189	NASA	Semi-Automatic Landslide Detection (SALaD)	Pre-deployment
R0153	NASA-192	NASA	SpectraClass: Semi-supervised learning in a Jupyter Notebook	Pre-deployment
R0154	NASA-198	NASA	SWaP-efficient, fast-wavelength-steering and time-division-multiplexing lidar technology capable of multi-beam ranging and concurrent hyper-spectral imaging	Pre-deployment
R0155	NASA-201	NASA	Toward Resilient Spacecraft: Artificially Intelligent Reasoning for Diagnosing Safe Modes	Pre-deployment
R0156	NASA-202	NASA	Towards Scientific Autonomy: Applying Machine Learning to MOMA Science Data	Pre-deployment
R0157	NASA-204	NASA	Training Data for Streamflow Estimation	Pre-deployment
R0158	NASA-208	NASA	Unification of laboratory and observational data via learning algorithms for robust models of ice microphysics	Pre-deployment
R0160	NASA-213	NASA	Vlasov Informed Super Resolution (VISR)	Pre-deployment
R0162	NASA-215	NASA	Agile Science	Pre-deployment
R0167	NASA-227	NASA	Groundwater data interpolation in California’s Central Valley using multimodal data fusion and multivariate sequence-to-sequence transformation models	Pre-deployment
R0171	NASA-235	NASA	Neural network accelerated radiative transfer modeling	Pre-deployment

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