Children′s bronchial lumen is relatively narrow, pulmonary interstitial development is superior to elastic tissue, and ciliary clearance is weak, which makes children more prone to pulmonary infection and pneumonia.The development of artificial intelligence (AI) and its application in medicine is changing the traditional disease diagnosis, assessment and treatment.AI with deep learning as the core is increasingly used in the diagnosis and prognosis evaluation of pneumonia in children, which is conducive to the early diagnosis and accurate assessment of the disease.In addition to novel coronavirus pneumonia and acute respiratory distress syndrome, researchers rarely pay attention to other viral pneumonia, bacterial pneumonia, mycoplasmal pneumonia, and fungal pneumonia.Meanwhile, there are still problems, such as small datasets, small sample sizes, incomplete algorithms, and little attention paid to pneumonia types and subtypes.In the future, a large-sample dataset of children′s pulmonary infections should be established, and learning about AI should be promoted among medical students and medical staff, so as to explore the value of AI in children′s pulmonary infection and play its auxiliary role in clinical decision-making related to diagnosis and treatment.