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Snapshot · OMB 2025 inventory · processed Oct 11, 2026
Federal AI Intelligence · U.S. Government AI Observatory

Custom inventory report

Filter: agency = NASA; AI type = computer_vision

Generated 2026-10-12 06:11 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; AI type = computer_vision · 47 records

Key findings

  • 47 use-case records from 1 agencies: 5 deployed (11%), 0 pilots, 41 in development or acquisition, 1 retired, 0 with no stage reported.
  • 1 records are designated high-impact; 0 of them (0%) answered at least one minimum-practice question.
  • 0% of reported deployed use cases (0 of 5) are classified as generative or agentic AI.
  • Of 1 deployed high-impact use cases, 0 report a completed AI impact assessment and 1 leave every minimum-practice field blank.
  • Interpretation: Blank practice fields are missing evidence, not evidence that a safeguard is absent. They mark where follow-up questions to the agency are most useful.
  • Sourcing is reported for 11% of use cases. Where reported, 80% involve in-house development.

Lifecycle

StageRecordsShare
Deployed511%
Pre-deployment4187%
Retired12%

AI technology

ClassificationRecordsShareDeployed
Computer vision47100%5

Agencies

AgencyRecordsDeployedHigh-impactCompleteness
NASA · National Aeronautics and Space Administration475163%

High-impact designation

DesignationRecords
High-impact1
Presumed high-impact, determined not1
Not high-impact45

Governance evidence: use cases designated high-impact

PracticeIn placeIn progressNot in placeN/A or precludedOtherNo answerIn scope
Pre-deployment testing0000011
AI impact assessment0000011
Independent review0000011
Ongoing monitoring0000011
Operator training0000011
Fail-safe0000011
Appeal process0000011
User and public consultation0000011

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

RecordAgency IDAgencyUse caseStage
R0175NASA-244NASASPOC (Soil Property and Object Classification)Deployed
R0226NASA-398NASAAutonomous WAiting Room Evaluation (AWARE)Deployed
R0227NASA-401NASAPre-trained microscopy image neural network encodersDeployed
R0416NASA-753NASAIntelligent Camera Analytics for Security and OperationsDeployed
R0497NASA-900NASAGLOBE Program - Image processingDeployed
R0106NASA-8NASADeep Learning for Flood Mapping (DELTA)Retired
R0127NASA-89NASACreating U-Net + LSTM Hybrid Architecture for Image Series AnalysisPre-deployment
R0147NASA-175NASAPortable flow inferencing device using Fourier Ptychography and Deep Learning for detection of biosignaturesPre-deployment
R0159NASA-210NASAUsing Machine Learning to Detect and Build Calibrated CME DatasetsPre-deployment
R0173NASA-240NASAProviding 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) missionPre-deployment
R0174NASA-241NASASCOTI (Scientific Captioning of Terrain Images)Pre-deployment
R0178NASA-256NASAClassification of features in Crew Earth Observations imageryPre-deployment
R0179NASA-258NASACloud masks from Crew Earth Observations imageryPre-deployment
R0181NASA-260NASACrew Earth Observations automated georeferencing/geolocationPre-deployment
R0193NASA-313NASAEstimation of Multilayered Cloud Properties from Geostationary Satellite Imager DataPre-deployment
R0197NASA-320NASAIdentifying flaws in manufacturing of compositesPre-deployment
R0208NASA-340NASAPolar Nighttime Cloud Detection Using an Artificial Neural NetworkPre-deployment
R0211NASA-349NASASevere Storm Prediction via Overshooting Cloud Top and Above Anvil Cirrus Plume Image Recognition from Satellite Imager DataPre-deployment
R0213NASA-359NASAAirplane detectionPre-deployment
R0215NASA-362NASADeep Learning-based Hurricane Intensity EstimatorPre-deployment
R0219NASA-374NASAPhenomena Detection PortalPre-deployment
R0220NASA-375NASAPixel-Level Smoke Detection Model with Deep LearningPre-deployment
R0222NASA-380NASAShip detectionPre-deployment
R0235NASA-415NASAImproved Differential Dynamic Microscopy (DDM) tool for characterization of soft matterPre-deployment
R0240NASA-420NASARover ML-based vision systemPre-deployment
R0241NASA-426NASAImageLabelerPre-deployment
R0242NASA-428NASAOceanic cold pool detection using scatterometer windsPre-deployment
R0243NASA-429NASASimilarity Search for Earth Science Image ArchivePre-deployment
R0244NASA-443NASAPASSION ComputerPre-deployment
R0261NASA-498NASABorescope Artificial Intelligence (BAI)Pre-deployment
R0280NASA-543NASAAerial AId: Visual data processing with AI in emergency scenarios for quick decision makingPre-deployment
R0380NASA-684NASASuper Resolution to enhance climate reanalysis dataPre-deployment
R0381NASA-685NASASuper-Resolution for Nighttime LightsPre-deployment
R0387NASA-693NASATowards an Integrated Observation System for OH: A Case Study in the TropicsPre-deployment
R0388NASA-694NASATowards Learning-based Visual Perception with GAVIN: the Goddard AI Verification and INtegration Tool SuitePre-deployment
R0389NASA-703NASADepth from Spectral Defocus for Lunar RegolithPre-deployment
R0390NASA-704NASANeural Scene Representations for Lunar Terrain ModelingPre-deployment
R0392NASA-706NASASafe Autonomous Taxiing with Vision-Based NavigationPre-deployment
R0440NASA-831NASATransiting Exoplanet Survey Satellite (TESS) Neural Network (NN)Pre-deployment
R0444NASA-838NASAGround-based Detection of Martian Dust Devils With a Fine-tuned Fast R-CNNPre-deployment

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