Research in artificial intelligence (AI) techniques for Mobile Ad Hoc Networks (MANETs) focuses on leveraging intelligent algorithms to enhance routing, security, resource management, and network optimization in dynamic and decentralized environments. Recent studies apply machine learning, deep learning, and reinforcement learning models to predict link stability, optimize route selection, and detect intrusions or malicious behaviors. Swarm intelligence and fuzzy logic–based approaches are also utilized for efficient clustering, energy management, and adaptive QoS provisioning. Hybrid AI frameworks that combine multiple learning paradigms are being developed to improve decision-making accuracy under uncertain network conditions. These AI-driven advancements significantly enhance the adaptability, scalability, and resilience of MANETs, enabling smarter communication and autonomous operation in rapidly changing mobile network scenarios.