Vehicular Adhoc Networks (VANETs) are wireless communication networks that allow smart vehicles to communicate in real time. This communication can happen in multiple ways: Vehicle-to-Vehicle (V2V), where cars share information directly with each other, and Vehicle-to-Infrastructure (V2I), where vehicles connect with roadside systems like traffic lights. VANETs help improve road safety and traffic management. These networks utilize various Internet of Things (IoT) devices, including cameras, sensors and GPS modules to share real-time information with each other, such as location, speed and condition of the road. However, the increased connectivity comes with a greater exposure to cyber threats such as service disruption, identity spoofing, and manipulation of data, which can subsequently compromise the safety of the driver and the integrity of the network. Unfortunately, traditional security mechanisms are incapable of addressing evolving and context-specific cyber threats in VANETs. This chapter deals with an exploratory approach to how Artificial Intelligence (AI) can help counter these challenges through anomaly detection, attack prediction, and adaptive security measures. Integrating AI-driven security mechanisms into IoT-enabled VANETs can transform the transportation ecosystem, making it safer, smarter, and more resilient.