<p>Wheezing, a prevalent respiratory symptom in children, poses diagnostic and management complexities due to its clinical and etiological diversity and the challenge of capturing objective data on pediatric airway inflammation and function. Despite recent advances in understanding pediatric wheezing illnesses, challenges remain in early etiologic diagnosis, phenotype classification, and management. These are mainly attributed to the absence of standardized diagnostic methodologies and effective personalized treatment protocols. The evolution of artificial intelligence (AI) technology introduces new opportunities for managing pediatric wheezing illnesses. The utilization of AI in healthcare has shown considerable promise in disease identification, treatment suggestions, and personalized medicine. Although the application of AI in pediatric wheezing is relatively minimal currently, its utilization in diseases related to pediatric wheezing, specifically in the diagnosis and management of pneumonia and asthma, has seen numerous successful instances. Consequently, this review primarily summarized the application of AI in pediatric wheezing illnesses, and explored the use of AI in pediatric pneumonia and asthma, with an aim to culminate valuable experience from these domains, thereby enriching the application of AI in pediatric wheezing illnesses.</p>