AI-driven smart charging, vehicle-to-grid (V2G) systems, and decentralized energy trading enable the effective utilization of renewable energy (RE), supporting grid stability and reducing dependency on fossil fuels. This chapter provides a comprehensive overview of the methodologies and technologies driving AI applications in EV energy management. By harnessing the power of AI algorithms, sensor integration, and edge computing, we unlock new possibilities for optimizing efficiency, enhancing safety, and reducing environmental impact in the transportation sector. The journey towards a cleaner, greener, and more sustainable transportation ecosystem is ongoing, and AI remains a crucial enabler in this endeavor. V2G systems facilitate the bidirectional flow of electric current between automobiles and the power grid, offering benefits such as grid stabilization, demand response, and the integration of RE. The connection between EVs and the power grid allows for efficient use of resources, making the grid more stable and helping us move towards a future that uses RE and is less centralized. AI improves the user experience by giving personalized advice on charging stations, routes, and how to drive to save energy. As AI becomes more widely used in smart energy systems for EVs, strong cybersecurity measures are needed to protect against possible threats and keep data private. To fully unlock the potential of AI in the development of sustainable transportation solutions, we need to work together across disciplines, set up rules and regulations, and get stakeholders involved. In short, merging AI with smart energy systems in EVs can potentially transform the future of transportation. With continued research, innovation, and teamwork, AI-powered smart energy systems will be crucial in creating a transportation system that is cleaner, greener, and more adaptable.