Federal AI Intelligence · U.S. Government AI Observatory

Federal AI landscape: executive briefing

Filtered: agency = NASA; stage = pilot

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 = NASA; stage = pilot · 21 records

Key findings

21 use-case records from 1 agencies: 0 deployed (0%), 21 pilots, 0 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 100% of use cases. Where reported, 100% involve in-house development.

Lifecycle

Stage	Records	Share
Pilot	21	100%

AI technology

Classification	Records	Share
Generative AI	5	24%
Classical / predictive ML	11	52%
Natural language processing	2	10%
Agentic AI	1	5%
Reinforcement learning	2	10%

Agencies

Agency	Records	Deployed	High-impact	Completeness
NASA · National Aeronautics and Space Administration	21	0	0	98%

High-impact designation

Designation	Records
Presumed high-impact, determined not	1
Not high-impact	20

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 21 records.

Record	Agency ID	Agency	Use case	Stage
R0110	NASA-13	NASA	Anomaly detection in aeronautics data with quantum-compatible discrete deep generative model	Pilot
R0245	NASA-445	NASA	Instantaneous Clarity of Ambient eNvironment Capability (ICAN-C)	Pilot
R0254	NASA-487	NASA	AI Digital Assistants (HRP) [was "Doc in a Box" for Earth Independent Medical Operations (EIMO)]	Pilot
R0255	NASA-488	NASA	Data Fracking (HRP)	Pilot
R0270	NASA-526	NASA	Design Optimization of Turbomachinery Rotor Blades using Neural Network Surrogate Models	Pilot
R0278	NASA-539	NASA	ChatGSFC	Pilot
R0281	NASA-545	NASA	Implement machine learning in NMIS to assist with mishap coding	Pilot
R0394	NASA-709	NASA	GenAI Agent for Interacting with Robots (https://github.com/nasa-jpl/rosa)	Pilot
R0395	NASA-711	NASA	SLIM: Software Lifecycle Improvement & Modernization	Pilot
R0396	NASA-712	NASA	Using LLMS for Documents and Requirements Analysis	Pilot
R0412	NASA-746	NASA	AI-enabled Risk-Informed Assessment Selection (RIAS) tool	Pilot
R0422	NASA-798	NASA	AI Based Digital Twin Interoporability Schema	Pilot
R0428	NASA-808	NASA	Adversarial Policy Evolution via AI	Pilot
R0429	NASA-809	NASA	Adaptive Problem Solving / Hyperparameter Optimization	Pilot
R0433	NASA-814	NASA	Time Series Forecasting, Evaluation and Deployment (Time-FED)	Pilot
R0434	NASA-815	NASA	AI Risk-aware task and motion planning for snake-like robots in icy enviroments	Pilot
R0455	NASA-850	NASA	Retrieving stratospheric NO2 profiles from OMPS Limb Profiler measurements	Pilot
R0464	NASA-861	NASA	Quantification of Uncertainty Analysis Toolkit (QUAnT)	Pilot
R0498	NASA-901	NASA	Cloud Account Allocation Plan (CAAP) Cost Analytics Support	Pilot
R0524	NASA-932	NASA	Machine learning for prediction and factor analysis of laser forming parameters	Pilot
R0527	NASA-935	NASA	RDUST Regolith Dust Universal System Tracker	Pilot

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