Artificial Intelligence for Transit Asset Management

Transit Asset Management (TAM) is the strategic and systematic practice of procuring, operating, inspecting, maintaining, rehabilitating, and replacing transit capital assets to manage their performance, risks, and costs over their life cycles, for the purpose of providing safe, cost-effective, and reliable public transportation. Federal law (49 CFR Part 625) requires all U.S. transit agencies to maintain a TAM plan that includes a capital asset inventory, condition assessments, investment prioritization, and a decision support tool. This tool may consist of an analytic process or methodology used to prioritize state of good repair investments based on asset condition and objective criteria, or to assess long-term financial needs for asset investments. Artificial intelligence (AI) can strengthen these capabilities by helping transit agencies analyze large and complex datasets, detect patterns and anomalies, automate routine tasks, and support predictive decision-making. As a result, AI can help transit agencies:
• Predict asset failures before they occur;
• Optimize maintenance scheduling and workforce deployment;
• Improve inspection accuracy and frequency;
• Enhance lifecycle cost forecasting;
• Support real-time asset monitoring; and
• Improve operational reliability and customer service.