Artificial Intelligence (AI) has emerged as a defining force in the evolution of modern mechatronic systems, transforming traditional electromechanical integration into intelligent, autonomous, and data-driven technologies. This review provides a comprehensive examination of AI-enabled advances across key mechatronic domains, including robotics and autonomous systems, smart manufacturing, healthcare and biomedical mechatronics, automotive and aerospace applications, agricultural robotics, and digital twin technologies. By synthesizing developments in machine learning, deep learning, reinforcement learning, transformers, graph neural networks, hybrid physics-informed models, and edge intelligence, the review highlights how AI enhances perception, control, prediction, adaptability, and human–machine collaboration. Furthermore, the paper discusses emerging research trends such as federated learning, neuromorphic and quantum-inspired computing, and swarm intelligence, emphasizing their potential to shape future mechatronic architectures within the context of Industry 5.0. Existing challenges, including generalization, verification, interpretability, computational constraints, and ethical considerations, are also identified. Through an integrated analysis of foundational concepts, technological advancements, and domain-specific applications, this review outlines future research opportunities and establishes AI-driven mechatronics as a critical enabler of safe, efficient, and sustainable intelligent systems.
Ghazo et al. (Fri,) studied this question.