Artificial intelligence (AI) in dermatology has high accuracy in classifying skin cancer, particularly in collaboration with dermatologists. Although clinical studies have evaluated AI tools on both single-timepoint lesion images and sequential imaging data, they lack reporting on clinical utility in real-world settings. We retrospectively evaluate performances of 2 AI models for lesion change and malignancy risk assessment.