Noncancerous skin lesions often mimic malignant ones in both clinical and dermoscopic appearances. Examples of skin cancer mimickers include seborrheic keratosis, dermatofibroma, hemangioma, and melanocytic nevi. Differentiating benign from malignant lesions is clinically important to avoid unnecessary surgical procedures and follow-ups. AI-based classification systems offer several benefits, such as the early detection of precancerous lesions or distinguishing benign from malignant lesions using binary or multicomponent classification systems. Malignant conditions are more frequently misclassified as other malignancies rather than as benign conditions. Most studies published include benign cutaneous lesions as seborrheic keratosis, hemangioma, or dermatofibromas, and their report serves as control examples, aiming to outline the performance of the AI-models to detect skin cancers rather than the benign lesions. Future directions should be placed on AI models’ ability to detect the most atypical presentations of certain benign lesions, whose differentiation from a cutaneous cancerous lesion can be challenging.