Obstructive sleep apnea (OSA) is a common sleep-related breathing disorder, and its chronic nature and high correlation with many chronic diseases make its diagnosis and long-term management a great challenge. The traditional treatment model has obvious shortcomings in terms of efficiency, resource allocation, and patient compliance. In primary care, general practice emphasizes a person-centered, comprehensive management model, playing a crucial role in the early screening, diagnosis, and long-term follow-up of OSA. In recent years, the rapid development of artificial intelligence (AI) technology and its application in OSA screening, diagnosis, personalized treatment plan development and long-term follow-up have significantly improved the efficiency and accuracy of OSA diagnosis and treatment, especially through wearable devices, telemedicine and multimodal data analysis to realize the intelligent transformation of OSA management, which provides new solutions to OSA diagnosis and treatment. This review systematically described the epidemiological characteristics of OSA, the attributes of chronic diseases, and the limitations of the existing diagnosis and treatment modes, and explored the practical applications and potentials of the deep integration of general practice and AI technology in OSA management, as well as its current challenges and future prospects. It was emphasized that the future management of OSA needed to promote multidisciplinary collaboration and strengthen the deep integration of general practice and AI technology, to achieve precise and personalized high-quality management of OSA and related chronic diseases.