Abstract: The current applications of artificial intelligence（AI） technologies in power electronics and electric drive systems are investigated, covering three major stages: design, control, and operation and maintenance（O＆M）. In the design stage, intelligent optimization algorithms and machine learning models are employed for parameter configuration, device selection, and topology optimization of power electronic equipment, thereby improving design efficiency and overall performance. In the control stage, deep learning and reinforcement learning have advanced control strategies toward higher levels of intelligence and adaptability, enabling systems to maintain stability and efficiency under complex operating conditions. In the O＆M stage, AI integrated with big data analytics facilitates state monitoring, health assessment, and fault prediction, which significantly reduces equipment failure rates and maintenance costs. Furthermore, key challenges in applying AI to power electronics and electric drives are analyzed, including strong data dependence, insufficient interpretability, and high computational complexity, and future research directions are proposed in terms of applications to new objects, solutions to emerging problems, and the adoption of novel AI techniques. The findings suggest that AI will serve as a critical driving force for the intelligent, digital, and efficient development of power electronics and electric drive systems.