When artificial intelligence (AI) enters into the grid, in electric vehicles (EVs), and smart energy systems, it brings with it a new era of sustainable transportation. The objective of this chapter is to explore how AI technologies optimize integrated smart energy systems within EVs with a view of their transformative potential and the key challenges involved. Energy management algorithms driven by AI allow EVs to adaptively regulate their power use and charging patterns based on real-time data from sources such as traffic conditions, customer preferences, and network dynamics. By applying predictive analytics, EVs can predict energy demand, optimize routing options, and minimize battery charging costs leading to maximum energy efficiency while reducing environmental pollution. Proactive maintenance which prolongs battery life and enhances overall vehicle reliability is also made possible with battery management systems enabled by AI. Furthermore, AI facilitates seamless integration between the electric grid and each individual EV via vehicle-to-grid (V2G) technologies. This interconnection between EVs and the grid optimizes resource usage, enhances grid stability, and promotes a shift towards a decentralized and renewable energy-driven future. Furthermore, AI enhances the user experience by providing personalized recommendations on charging stations, routes, and energy-efficient driving practices. However, as AI becomes increasingly integrated into smart energy systems for EVs, robust cybersecurity measures are essential to protect against potential threats and ensure data privacy. To fully harness the potential of AI in developing sustainable transportation solutions, it is crucial to foster interdisciplinary collaboration, establish regulations, and engage stakeholders.