AI use-case explorer
AI use cases
Search and filter every reported use case. Open a record for the agency's full description, governance answers and source provenance.
Columns (7)
| Use case | Agency | Stage | High-impact | Topic area | AI classification | Sourcing |
|---|---|---|---|---|---|---|
| Automated Walrus Haulout Monitoring [2024 INV#WO0000000110052] DOI-0247 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| PAWSC Ecotoxicology PFAS Machine Learning [2024 INV#WO0000000112908] DOI-0238 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Delineating sub-surface drainage using satellite imagery [2024 INV#WO0000000109525] DOI-0230 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Oil Spill Response for Ice-Covered Rivers [2024 INV#WO0000000109142] DOI-0208 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Pacific Northwest Stream Flow Permanence [2024 INV#WO0000000109137] DOI-0207 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Climate Futures for Lizards and Snakes in Western North America [2024 INV#WO0000000109092] DOI-0201 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Office of Grants Management (PGM) Grants Utility Tool DOI-0180 · OS | DOI | Deployed | Not high-impact | Procurement and Financial Management | Agentic AI | Developed in-house |
| Using Machine Learning in USGS StreamStats to make suspended sediment and bedload predictions [2024 INV#WO0000000107977] DOI-0176 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Seabird and Marine Mammal Surveys Near Potential Renewable Energy Sites Offshore Central and Southern California [2024 INV#WO0000000107535] DOI-0173 · USGS | DOI | Deployed | Not high-impact | Science | Computer vision | Purchased from vendor |
| Rangeland Condition Monitoring Assessment and Projection (RCMAP) [2024 INV#WO0000000107126] DOI-0171 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| use of random forest for species distribution modeling DOI-0161 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| PRObability of Streamflow PERmanence (PROSPER models) [2024 INV#WO0000000109074] DOI-0156 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Machine Learning for automatic fracture mapping and rock identification [2024 INV#WO0000000109499] DOI-0155 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Machine Learning for Avalanche Frequency Modeling DOI-0148 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Classifying CWD-Infected Elk Using Recurrent Neural Networks on GPS Movement Data DOI-0135 · USGS | DOI | Deployed | Not high-impact | Energy and the Environment | Classical / predictive ML | Developed in-house |
| Deep?learning Integrations into NEIC Operations [2024 INV#WO0000000109496] DOI-0119 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| USGS Flow Photo Explorer [2024 INV#WO0000000109196] DOI-0117 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Contract and in-house |
| Coastal Change Likelihood: Synthesizing change factors using supervised learning DOI-0115 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Purchased from vendor |
| Predicting post-fire tree mortality DOI-0100 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Global food-and-water security-support analysis data (GFSAD) project [2024 INV#WO0000000107073] DOI-0095 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Frog vocalization recognition from digital recordings DOI-0092 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Patterns in the Landscape – Analyses of Cause and Effect DOI-0090 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Estimates of Habitat Suitability of Reed Canarygrass (Phalaris arundinacea) in Upper Mississippi River Floodplain Forest Understories DOI-0084 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Submersed Aquatic Vegetation Vulnerability Evaluation Application (SAVVEA) DOI-0081 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| U.S. Wind Turbine Database DOI-0080 · USGS | DOI | Deployed | Not high-impact | Energy and the Environment | Computer vision | Developed in-house |
| Machine learning in remote sensing-based wildfire and natural resource risk assessments DOI-0072 · USGS | DOI | Deployed | Not high-impact | Emergency Management | Classical / predictive ML | Developed in-house |
| Telemetry Analysis Learning Algorithm (TALA) DOI-0070 · USGS | DOI | Deployed | Not high-impact | Other | Classical / predictive ML | Developed in-house |
| LANDFIRE DOI-0069 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Invasive Grass Mapping DOI-0068 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Evapotranspiration mapping and monitoring DOI-0067 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| National Land Cover Database (NLCD) [2024 INV#WO0000000107887] DOI-0066 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| DocketScope DOI-0040 · FWS | DOI | Deployed | Not high-impact | Administrative Functions | Natural language processing | Purchased from vendor |
| Microsoft eDiscovery Attorney-Client Privilege Detection DOI-0021 · SOL | DOI | Deployed | Not high-impact | Other | Classical / predictive ML | Purchased from vendor |
| FOIA Request Lexical Similarity Tool in the Document Review Platform (Term Frequency – Inverse Document Frequency (TF-IDF) - Cosine) DOI-0020 · SOL | DOI | Deployed | Not high-impact | Other | Natural language processing | Developed in-house |
| Enabling FOIA Request Clustering Capability in the Document Review Platform (Density Based Algorithm alongside Term Frequency – Inverse Document Frequency (TF-IDF)) DOI-0019 · SOL | DOI | Deployed | Not high-impact | Other | Natural language processing | Developed in-house |
| FOIA Request Clustering Tool (Embedding based clustering alongside Term Frequency – Inverse Document Frequency (TF-IDF)) DOI-0018 · SOL | DOI | Deployed | Not high-impact | Other | Natural language processing | Developed in-house |
| FOIA Request Conceptual Similarity Tool (Semantic Similarity Score Generation) DOI-0017 · SOL | DOI | Deployed | Not high-impact | Other | Natural language processing | Developed in-house |
| Performance Modeling / Performance Forecasting DOI-0016 · SOL | DOI | Deployed | Not high-impact | Administrative Functions | Classical / predictive ML | Developed in-house |
| Effects of vehicle traffic on space use and road crossings of caribou in the Arctic [2024 INV#WO0000000110111] DOI-0007 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| (unnamed) DOI-0015 · FWS | DOI | Deployed | Not high-impact | Law Enforcement | Other | Purchased from vendor |
| VoiceAtlas no-code chatbot framework DOI-0248 · USGS | DOI | Pilot | Not high-impact | Science | Agentic AI | Purchased from vendor |
| Machine Learning approach to predict the composition of seafloor massive sulfide deposits [2024 INV#WO0000000108420] DOI-0245 · USGS | DOI | Pilot | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Google Cloud Vision [2024 INV#WO0000000154445] DOI-0243 · USGS | DOI | Pilot | Not high-impact | Science | Computer vision | Purchased from vendor |
| Google Vertex AI Document workbench [2024 INV#WO0000000154393] DOI-0242 · USGS | DOI | Pilot | Not high-impact | Science | Computer vision | Purchased from vendor |
| USGS Azure OpenAI ChatGPT [2024 INV#WO0000000154392] DOI-0241 · USGS | DOI | Pilot | Not high-impact | Science | Classical / predictive ML | Purchased from vendor |
| Prioritized Constituents: Sediment [2024 INV#WO0000000109726] DOI-0237 · USGS | DOI | Pilot | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Data-Driven Streamflow Drought [2024 INV#WO0000000109714] DOI-0234 · USGS | DOI | Pilot | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| National-Extent Groundwater Quality Prediction for the National Water Census and Regional Integrated Water Availability Assessments [2024 INV#WO0000000109709] DOI-0233 · USGS | DOI | Pilot | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Use of artificial intelligence tools for optimization and documentation for computer codes [2024 INV#WO0000000109681] DOI-0232 · USGS | DOI | Pilot | Not high-impact | Science | Generative AI | Contract and in-house |
| Vegetation mapping on the Hawaiian island of Lanai [2024 INV#WO0000000109501] DOI-0229 · USGS | DOI | Pilot | Not high-impact | Science | Classical / predictive ML | Developed in-house |
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