The automotive and mobility industry is undergoing a major transformation driven by advances in vehicle connectivity, autonomous systems, and electrification, with vehicles producing massive amounts of data that fuel demand for connected and electric cars. Companies are integrating artificial intelligence (AI), battery electric vehicles (BEVs), and software-defined vehicles (SDVs) to stay competitive, although managing fleets of connected vehicles presents challenges due to the vast data they generate. The global fleet management market is expected to grow significantly, with AI and machine learning playing crucial roles in optimizing operations, such as route planning and driver safety. Agentic AI applications, which can autonomously take actions using available data, are becoming pivotal in fleet management, processing real-time data to optimize routes and enhance safety. MongoDB's flexible document model is highlighted as an ideal solution for handling the diverse data types required by agentic AI applications, offering scalability, flexibility, and built-in vector search capabilities to support the dynamic needs of connected car platforms. The integration of AI agents with MongoDB is exemplified through use cases like the connected fleet incident advisor, which uses AI models and MongoDB's data infrastructure to streamline diagnostics and recommendations. This transformation in fleet management underscores the growing importance of robust data management solutions like MongoDB in harnessing the potential of AI and connectivity in the automotive sector.