In a bid to tackle the challenges of sluggish participant recruitment in clinical trials and the inability to swiftly pinpoint and monitor a vast pool of potential patients, the CSCO Smart Healthcare Session has embarked on establishing an AI-assisted professional certification framework for clinical trial patient navigators, along with unveiling an AI-powered patient navigator tailored for lung nodules. Concurrently, it has declared the development of the 'Chinese Expert Consensus on Navigation for Prospective Participants in Oncology Clinical Trials.' Leveraging insights from the industrial closed-loop established through over 35 years of patient navigation evolution in the United States, domestic implementations have commenced at institutions like Peking University Cancer Hospital and the First Affiliated Hospital of Guangzhou Medical University. Utilizing an AI-driven patient navigation operational system that integrates AI algorithms, hospital-based navigation teams, and operational protocols, a seamless human-machine collaboration is realized, markedly enhancing enrollment efficacy and bridging the service void for patients prior to their entry into projects under conventional recruitment paradigms. Presently, pertinent standards are in the process of being formulated, and training for the inaugural cohort of patient navigators is in full swing. Numerous premier GCP institutions are progressively integrating into this framework, and institutions are also encouraged to engage in industry-wide cooperation, with the anticipation of fundamentally resolving the participant recruitment dilemmas.