Chaparro et al examine the use and benefits of AI in the classification, diagnosis, and monitoring of skin lesions. To do this, the authors review articles published in PubMed, Lilacs, and Scopus from 2008 to 2024. In the end, forty-four articles were selected to be used in this study. The findings strongly support the effectiveness of AI, demonstrating that diagnostic precision was comparable to, and in some cases, better than that of dermatologists. For example, one study showed that a convolution neural network (CNN) achieved 97.1% sensitivity and 78.8% specificity when differentiating combined naevi from melanomas, compared to dermatologists who achieved a 90.6% sensitivity and 71.0% specificity. AI assistance also improved agreement with reference diagnoses among primary care physicians by 10% and nurse practitioners by 12%. The authors emphasize that AI is a crucial complementary tool to enhance, not replace, the expertise and clinical judgement of dermatologists.