One of the most common cancers in the world is still skin cancer, and better patient outcomes and efficient treatment depend on early detection. Dermatologists are essential in diagnosis, yet the accuracy of conventional techniques may be limited. In order to improve dermatology diagnostic accuracy, this study investigates the application of artificial intelligence (AI), specifically deep learning models. AI-driven solutions that use convolutional neural networks (CNNs) and hybrid models perform on par with skilled dermatologists, promoting early identification and expediting clinical procedures. This study also addresses the difficulties in applying AI in dermatology, highlighting the necessity of ongoing development and ethical issues to guarantee its efficacy in clinical settings.