Peripheral arterial disease (PAD) is associated with a high risk of mortality and amputation. However, many PAD patients remain asymptomatic or present with atypical symptoms, leading to low awareness and diagnostic rates. With an aging population and the increasing prevalence of risk factors, the burden of PAD is expected to grow. Artificial intelligence (AI), encompassing machine learning, deep learning, natural language processing, and computer vision, refers to machines and algorithms capable of simulating human intelligence and performing human-like tasks. Although the application of AI in PAD is still in its early stages, its potential is substantial. This article reviews the current clinical applications and limitations of AI in the management of PAD patients.