The goal of this research is to examine Artificial Intelligence management and how it is used in the field of public transportation. The obstacles and requirements needed to apply AI on public transportation to improve urban mobility are the main topics of data analysis using a qualitative methodology with data gathering from observation and literature review. In addition to the important components of AI management covered in the following topics: 1) Source finance for AI in Mass Public Transport Project 2) Reform of Traditional Procurement Process 3) Create bias-free AI Develop a legal and policy framework. 4. Avoid the temptation of over-relying on AI. The goal of this research is to provide a reference and recommendations for local governments as they formulate future AI and transportation policies. According to the research analysis, AI can solve difficulties with traffic management, traffic safety, public transportation, and urban mobility. The AI implementation in Chennai, India still requires work to make it more user-friendly and ensuring that it is integrated with a variety of public transportation options. It is advised to create an all-encompassing integrated application system with a single point of entry, as well as a legal and regulatory framework for the applications.

SGD, Momentum, RMSPROP.