Abstract With the rapid advancement of connected vehicle technologies, infotainment Electronic Control Units (ECUs) have become central to user interaction and connectivity within modern vehicles. However, this enhanced functionality has introduced new vulnerabilities to cyberattacks. This paper explores the application of Artificial Intelligence (AI) in enhancing the cybersecurity framework of infotainment ECUs. The study introduces AI-powered modules for threat detection and response, presents an integrated architecture, and validates performance through simulation using MATLAB, CANoe, and NS-3. This approach addresses real-time intrusion detection, anomaly analysis, and voice command security. Key benefits include zero-day exploit resistance, scalability, and continuous protection via OTA updates. The paper references real-world automotive cyberattack cases such as Tesla's OTA vulnerability patches, BMW ConnectedDrive exploits, and Jeep Cherokee's Uconnect hack, emphasizing the critical need for AI-enabled proactive cybersecurity frameworks. 1. Introduction: The digital transformation of the automotive industry has significantly expanded the role of infotainment systems. Infotainment ECUs manage entertainment, navigation, communication, and vehicle-user interfaces. Their connectivity to internal (e.g., CAN, Ethernet) and external (e.g., internet, Bluetooth) networks increases the risk of cyber threats. This paper investigates how AI can enhance cybersecurity measures to protect infotainment ECUs from sophisticated and dynamic cyberattacks. The automotive sector is undergoing a significant digital transformation, integrating Internet of Things (IoT) and smart technologies into vehicles. Infotainment ECUs provide GPS navigation, media playback, Bluetooth, internet access, voice assistants, and more. These features are convenient but expand the attack surface for cybercriminals. Real Threat Example: In 2015, researchers remotely hacked a Jeep Cherokee via its Uconnect infotainment system, gaining access to steering, brakes, and transmission. This highlighted how infotainment vulnerabilities could jeopardize passenger safety. This paper investigates how AI can be integrated into the cybersecurity framework of infotainment ECUs to provide real-time, intelligent, and adaptive protection SUMMARY This research introduces an AI-enabled cybersecurity solution that: • Digitally simulates infotainment ECU behaviors using MATLAB/Simulink • Generates synthetic and real-world attack scenarios (e.g., Bluetooth intrusion, GPS spoofing, OTA malware injection) • Trains and evaluates ML/DL models (Random Forest, SVM, DNN, Autoencoders) using tools like MATLAB and CAPL • Integrates the AI models into a Hardware-in-the-Loop (HiL) testbench • Uses CANoe for simulating CAN traffic and attack injection • Uses NS-3 to simulate Ethernet and Wi-Fi-based attacks The system was evaluated based on: • Detection Accuracy • False Positive Rate • Response Latency • CPU/RAM utilization • Model explain ability using SHAP and LIME KEY BENEFITS (DETAILED) Benefit Explanation Enhanced Vehicle Safety Early detection of threats reduces the risk of system takeovers or driver harm. Zero-Day Attack Resistance AI models can detect novel threats without prior knowledge or predefined rules. Scalability & Modularity Easily integrates into different vehicle platforms and infotainment variants. Voice Command Security NLP filters out spoofed or manipulated voice commands to prevent misuse. OTA-Based Evolution AI models and firmware can be remotely updated as threats evolve. Cross-Platform Integration Can expand to protect other ECUs like ADAS or powertrain systems. Improved User Trust Transparent and explainable AI increases consumer confidence in vehicle security. Model Interpretability Tools like SHAP and LIME help engineers understand why alerts were raised. Real-Time Performance Ensures that threat detection happens quickly enough to trigger preventive actions. Regulatory Compliance Designed with standards like ISO/SAE 21434 in mind for cybersecurity governance.