Federal AI Intelligence · U.S. Government AI Observatory

Governance disclosure assessment

Filtered: topic = Transportation; AI type = classical_ml

Generated 2026-10-12 23:13 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 = Transportation; AI type = classical_ml · 17 records

Key findings

17 use-case records from 6 agencies: 5 deployed (29%), 0 pilots, 12 in development or acquisition, 0 retired, 0 with no stage reported.
2 records are designated high-impact; 2 of them (100%) answered at least one minimum-practice question.
NASA, DOT, DHS report 14 of 17 use cases (82%).
0% of reported deployed use cases (0 of 5) are classified as generative or agentic AI.
Of 2 deployed high-impact use cases, 2 report a completed AI impact assessment and 0 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 47% of use cases. Where reported, 75% involve in-house development.

Governance evidence: deployed high-impact use cases

Practice	In place	N/A or precluded	In scope
Pre-deployment testing	2	0	2
AI impact assessment	2	0	2
Independent review	2	0	2
Ongoing monitoring	2	0	2
Operator training	2	0	2
Fail-safe	2	0	2
Appeal process	1	1	2
User and public consultation	2	0	2

"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.

Agencies with high-impact records

Agency	High-impact	Answered any practice	Practice answers in place
DHS	2	2	15 of 15

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 17 records.

Record	Agency ID	Agency	Use case	Stage
R1210	DOT-1000008	DOT	Certified Professional Controller (CPC) On-Board Success Evaluator	Deployed
R1381	USDA-082	USDA	Predictive flood modeling	Deployed
R1915	DHS-327	DHS	Credential Authentication Technology with Camera System (CAT-2) and AutoCAT (CAT-2 in an e-gate form factor)	Deployed
R1916	DHS-345	DHS	PreCheck Touchless Identity Solution	Deployed
R1934	DHS-65	DHS	Aircraft Landing Location Predictor (KESTREL)	Deployed
R0109	NASA-11	NASA	Explainable and robust deep semi-supervised model for multi-class anomaly detection in flight data	Pre-deployment
R0111	NASA-18	NASA	Machine Learning Airport Surface Model: Airport Configuration Prediction	Pre-deployment
R0112	NASA-19	NASA	Machine Learning Airport Surface Model: Arrival Runway Prediction	Pre-deployment
R0113	NASA-20	NASA	Machine Learning Airport Surface Model: Departure Runway Prediction	Pre-deployment
R0116	NASA-23	NASA	Machine Learning Airport Surface Model: Taxi-out Prediction	Pre-deployment
R0119	NASA-33	NASA	Unsupervised anomaly detection in flight data with deep variational autoencoders	Pre-deployment
R1211	DOT-1000009	DOT	Automated Delay detection using voice processing	Pre-deployment
R1212	DOT-1000010	DOT	Technical Operations Predictive Maintenance	Pre-deployment
R1230	DOT-1000035	DOT	Predictive Analytics Using Autonomous Track Geometry Measurement System (ATGMS) Data	Pre-deployment
R1863	DHS-2397	DHS	OTA Automated Passenger Screening Gate System	Pre-deployment
R2652	DOI-0104	DOI	Improving recreation opportunities and access to public lands through machine learning and transportation planning	Pre-deployment
R3299	DOE-357	DOE	Managing curb allocation in cities	Pre-deployment

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