Abstract: Scars are a common pathological healing outcome following skin injury or surgical procedures, characterized by excessive fibrous proliferation of tissue, and are often accompanied by pruritus and pain. Scars located at special anatomical sites may lead to functional limitation, substantially impairing patients′ quality of life. Conventional diagnostic and therapeutic approaches are highly subjective and low efficiency, and are associated with marked treatment resistance and a high postoperative recurrence rate. The rapid advances of artificial intelligence (AI) in medical image analysis and multi-source data modeling have offered new insights for the precision diagnosis and treatment of scars. The authors systematically review research progress regarding AI in scar image recognition and diagnosis, treatment prediction, and therapeutic effect evaluation, and further discuss the application prospect of AI combined with radiotherapy in preventing and treating scar recurrence. At present, the application of AI still faces challenges including data quality, privacy protection, model interpretability, and ethical supervision, which urgently require interdisciplinary collaboration to improve relevant systems and criterions. Nevertheless, AI has demonstrated great potential in the diagnosis, treatment and prognostic assessment of scars, and is expected to facilitate the realization of precision diagnosis and treatment of scars.