Cardiovascular diseases (CVDs) are the leading cause of death among both urban and rural residents in China, which are characterized by an extended disease course, diverse symptoms, and complex etiological factors, posing significant challenges to their diagnosis and management. In recent years, the rapid development of artificial intelligence (AI) technologies has provided unprecedented opportunities for early health management and disease prediction in CVDs. By leveraging deep learning and the intelligent analysis of massive health data, AI technologies can accurately identify the potential risks for CVDs and facilitate personalized health management, effectively reducing their incidence and delaying disease progression. The applications of AI technologies have facilitated the improvement of early health monitoring and CVD prevention, as well as improved the accuracy and effectiveness of diagnostic imaging and surgical interventions. In addition, AI technologies have also been applied in biological big data analysis and new drug development. The purpose of this review is to summarize the current applications of AI technologies in CVDs, exploring their prospects and potential challenges in improving diagnostic and therapeutic efficiency. It is anticipated that AI technologies will play an increasingly critical role in the prevention, diagnosis, and treatment of CVDs, thus promoting the advancement of smart healthcare and precision medicine.