AI In Transportation

AI in transportation covers the use of machine learning and related systems to operate, route, monitor, or maintain vehicles, fleets, and transit networks, including autonomous and driver-assist cars, trucks, rail, aviation, and logistics platforms. For enterprises, this area raises distinct governance questions around product liability when an automated system causes a crash, safety certification before deployment, and data privacy for location and driver-monitoring data. Regulators such as the US National Highway Traffic Safety Administration and the EU under its AI Act treat many of these systems as high-risk, so companies deploying them face heightened documentation, testing, and incident-reporting obligations.

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Corporate PolicyUS2026-11-14

FAA's $875M AI Traffic System Rolls Out Without Controller Union Input

The Federal Aviation Administration has deployed its $875 million SMART air traffic management system to all 22 air route traffic control centers across the US. This expands from an initial pilot covering Washington, DC airspace. The system uses cloud-based AI to combine weather, flight path, traffic flow, and staffing data to recommend routes and arrival sequencing. Human FAA specialists validate recommendations before they reach local controllers, who retain final authority over whether to accept them. The National Air Traffic Controllers Association, representing more than 15,000 members, stated it was not consulted in the design, testing, or implementation of SMART.

FAA critical infrastructure human oversight public sector AI labor consultation AI in transportation safety-critical AI