Electric and Flying Vehicles (EnFVs) represent a transformative shift in transportation, promising enhanced efficiency and reduced environmental impact. However, their integration into interconnected digital ecosystems poses significant cybersecurity challenges, including cyber-physical threats, privacy vulnerabilities, and supply chain risks. This paper comprehensively explores these challenges and investigates artificial intelligence (AI)-driven solutions to bolster EnFV cybersecurity. The study begins with an overview of EnFV cybersecurity issues, emphasizing the increasing complexity of threats in digital transportation systems. Methodologically, the paper reviews existing literature to identify gaps and assesses recent advancements in AI for cybersecurity applications. Key methodologies include AI-powered intrusion detection, threat analysis leveraging machine learning algorithms, predictive maintenance strategies, and enhanced authentication protocols. Results underscore the effectiveness of AI technologies in mitigating EnFV cybersecurity risks, demonstrating improved threat detection and response capabilities. The study concludes by outlining future research directions, highlighting the need for continued innovation in AI, quantum computing resilience, blockchain applications, and ethical considerations. These findings contribute to a clearer understanding of EnFV cybersecurity dynamics and provide a roadmap for enhancing the security and reliability of future transportation systems.