Objective To develop an artificial intelligence (AI)-based follow-up management system for patients with chronic obstructive pulmonary disease (COPD), and to evaluate its application effectiveness. Methods Based on the follow-up management needs of patients with COPD, an AI-based follow-up management system was developed with a three-layer architecture, including an application interaction layer, an intelligent core layer, and a data resource layer. The system integrated six core modules:knowledge base management, patient profiling and care pathway generation, intelligent tracking and execution, patient service management, statistical analysis and management decision-making, human-computer collaboration and consultation handling. A quasi-experimental design was employed. Convenience sampling was adopted to enroll 82 COPD patients. Forty patients admitted between January and December 2023 were assigned to a control group and received routine disease-specific follow-up management, while forty-two patients admitted between January and December 2024 were assigned to an intervention group and received follow-up management supported by the AI-based system.Both groups were followed for 3 months. COPD Assessment Test（CAT) scores, adherence to inhaled medications, and satisfaction with follow-up services were assessed at discharge and after follow-up. Results Thirty-four patients in the intervention group and thirty-five patients in the control group completed the study. After 3 months of follow-up, the intervention group demonstrated significantly higher scores in adherence to inhaled medications and satisfaction with follow-up services compared with the control group (both P<0.05). No statistically significant difference was observed in CAT scores between the two groups (P>0.05). Conclusion Application of the AI-based follow-up management system can effectively improve adherence to inhaled medications and follow-up service satisfaction among patients with COPD, which may contribute to delaying disease progression.