APTA has released a primer and guidance briefs on artificial intelligence and machine learning in public transit. The materials provide public transit agencies with a comprehensive resource for understanding, evaluating, and deploying AI and ML tools across their operations.
The primer and guidance briefs draw on a survey of transit agencies and staff interviews to capture current and planned AI applications across eight functional domains: back office, operations, customer support, maintenance, safety and security, customer analytics, planning, and fares and ticketing. The primer includes real-world examples from member agencies. The four guidance briefs cover tool and infrastructure needs, policy and governance needs, agency readiness and staff capacity, and implementation guidance.
Key findings show that customer support and customer analytics are the most common areas of AI deployment. When including public transit agencies’ plans to deploy AI, back office and operations functions top the list, with 50 percent and 47 percent of survey respondents, respectively, indicating current or planned use.
APTA President and CEO Paul P. Skoutelas said, “Public transit agencies of all sizes are deploying AI to make service more reliable, more efficient, and more responsive to riders. These resources give our member organizations a clear picture of where the industry stands and a practical roadmap for moving forward responsibly—from the largest metro systems to small rural providers.”
The materials were developed with research support from EBP and Foursquare ITP. Findings were drawn from an online survey of 32 APTA member transit agencies, supplemented by interviews with agency staff and a review of publicly available documentation on agency AI deployments.
Access the primer and guidance briefs on APTA’s website: Artificial Intelligence and Machine Learning in Public Transit.