Federal AI Intelligence · U.S. Government AI Observatory

Custom inventory report

Filter: high-impact = not_high_impact; AI type = computer_vision; sourcing = unknown

Generated 2026-10-12 12:46 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: high-impact = not_high_impact; AI type = computer_vision; sourcing = unknown · 67 records

Key findings

67 use-case records from 11 agencies: 0 deployed (0%), 0 pilots, 66 in development or acquisition, 1 retired, 0 with no stage reported.
0 records are designated high-impact; 0 of them (n/a) answered at least one minimum-practice question.
NASA, USDA, DHS report 53 of 67 use cases (79%).
Sourcing is reported for 0% of use cases. Where reported, n/a involve in-house development.

Lifecycle

Stage	Records	Share
Pre-deployment	66	99%
Retired	1	1%

AI technology

Classification	Records	Share	Deployed
Computer vision	67	100%	0

Agencies

Agency	Records	Completeness
NASA · National Aeronautics and Space Administration	42	58%
USDA · Department of Agriculture	8	58%
DHS · Department of Homeland Security	3	58%
VA · Department of Veterans Affairs	3	58%
TREAS · Department of the Treasury	3	61%
DOJ · Department of Justice	2	58%
DOI · Department of the Interior	2	83%
SEC · Securities and Exchange Commission	1	58%
HHS · Department of Health and Human Services	1	58%
STATE · Department of State	1	58%
DOE · Department of Energy	1	58%

High-impact designation

Designation	Records
Not high-impact	67

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

First 40 of 67 records, deployed first. The full list is available as CSV from the explorer with the same filters.

Record	Agency ID	Agency	Use case	Stage
R0062	SEC-69	SEC	Comparing EDGAR system access request forms	Pre-deployment
R0106	NASA-8	NASA	Deep Learning for Flood Mapping (DELTA)	Retired
R0127	NASA-89	NASA	Creating U-Net + LSTM Hybrid Architecture for Image Series Analysis	Pre-deployment
R0147	NASA-175	NASA	Portable flow inferencing device using Fourier Ptychography and Deep Learning for detection of biosignatures	Pre-deployment
R0159	NASA-210	NASA	Using Machine Learning to Detect and Build Calibrated CME Datasets	Pre-deployment
R0173	NASA-240	NASA	Providing visualization tools and streamlining the detection and tracking of wildfire-induced smoke plumes during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) mission	Pre-deployment
R0174	NASA-241	NASA	SCOTI (Scientific Captioning of Terrain Images)	Pre-deployment
R0178	NASA-256	NASA	Classification of features in Crew Earth Observations imagery	Pre-deployment
R0179	NASA-258	NASA	Cloud masks from Crew Earth Observations imagery	Pre-deployment
R0181	NASA-260	NASA	Crew Earth Observations automated georeferencing/geolocation	Pre-deployment
R0193	NASA-313	NASA	Estimation of Multilayered Cloud Properties from Geostationary Satellite Imager Data	Pre-deployment
R0197	NASA-320	NASA	Identifying flaws in manufacturing of composites	Pre-deployment
R0208	NASA-340	NASA	Polar Nighttime Cloud Detection Using an Artificial Neural Network	Pre-deployment
R0211	NASA-349	NASA	Severe Storm Prediction via Overshooting Cloud Top and Above Anvil Cirrus Plume Image Recognition from Satellite Imager Data	Pre-deployment
R0213	NASA-359	NASA	Airplane detection	Pre-deployment
R0215	NASA-362	NASA	Deep Learning-based Hurricane Intensity Estimator	Pre-deployment
R0219	NASA-374	NASA	Phenomena Detection Portal	Pre-deployment
R0220	NASA-375	NASA	Pixel-Level Smoke Detection Model with Deep Learning	Pre-deployment
R0222	NASA-380	NASA	Ship detection	Pre-deployment
R0235	NASA-415	NASA	Improved Differential Dynamic Microscopy (DDM) tool for characterization of soft matter	Pre-deployment
R0240	NASA-420	NASA	Rover ML-based vision system	Pre-deployment
R0241	NASA-426	NASA	ImageLabeler	Pre-deployment
R0242	NASA-428	NASA	Oceanic cold pool detection using scatterometer winds	Pre-deployment
R0243	NASA-429	NASA	Similarity Search for Earth Science Image Archive	Pre-deployment
R0244	NASA-443	NASA	PASSION Computer	Pre-deployment
R0261	NASA-498	NASA	Borescope Artificial Intelligence (BAI)	Pre-deployment
R0280	NASA-543	NASA	Aerial AId: Visual data processing with AI in emergency scenarios for quick decision making	Pre-deployment
R0380	NASA-684	NASA	Super Resolution to enhance climate reanalysis data	Pre-deployment
R0381	NASA-685	NASA	Super-Resolution for Nighttime Lights	Pre-deployment
R0387	NASA-693	NASA	Towards an Integrated Observation System for OH: A Case Study in the Tropics	Pre-deployment
R0388	NASA-694	NASA	Towards Learning-based Visual Perception with GAVIN: the Goddard AI Verification and INtegration Tool Suite	Pre-deployment
R0389	NASA-703	NASA	Depth from Spectral Defocus for Lunar Regolith	Pre-deployment
R0390	NASA-704	NASA	Neural Scene Representations for Lunar Terrain Modeling	Pre-deployment
R0392	NASA-706	NASA	Safe Autonomous Taxiing with Vision-Based Navigation	Pre-deployment
R0440	NASA-831	NASA	Transiting Exoplanet Survey Satellite (TESS) Neural Network (NN)	Pre-deployment
R0444	NASA-838	NASA	Ground-based Detection of Martian Dust Devils With a Fine-tuned Fast R-CNN	Pre-deployment
R0466	NASA-863	NASA	Identifying global dust and smoke over ocean using MODIS sensor	Pre-deployment
R0477	NASA-875	NASA	CHESS: Coronal Hole Extraction with Semantic Segmentation	Pre-deployment
R0492	NASA-894	NASA	AI assisted Image recognition for EEE parts kitting and auditing	Pre-deployment
R0512	NASA-917	NASA	SAS Vision	Pre-deployment

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