In recent years, artificial intelligence (AI) has made significant progress in the field of dermatological image analysis. Its diagnostic sensitivity and specificity have approached the high level of dermatologists, and it can effectively enhance the ability to differentiate dermatological conditions. AI-assisted teaching has also been proven to cultivate trainees′ communication skills, laying the foundation for the application of AI in dermatopathology teaching. Dermatopathology serves as a bridge connecting clinical practice and pathological diagnosis. Traditional dermatopathology teaching is mainly conducted through microscopic slide review teaching, instructor-led demonstrations, and case discussions. Therefore, there are issues such as uneven distribution of teaching resources, insufficient high-quality specimens, and a relatively passive learning process. For military academy students, the burden of rigorous training, uneven regional resources, and the disconnect between the curriculum and military career requirements have led to insufficient learning motivation, severely limiting the systematic cultivation of their dermatopathological diagnostic abilities. AI technology leverages whole slide imaging, convolutional neural networks, and multimodal models to achieve automated slide recognition and annotation, personalized learning pathway recommendations, and virtual reality-based immersive instruction. Specifically, in basic morphology teaching, it automatically marks and integrates multi-source information for case simulation training, providing adaptive tests and real-time feedback, and building lifelong learning platforms in continuing education to ensure that military academy students maitain access to premium resources throughout their professional lives. However, currently the application of AI technology in the fields of technology, educational practice, ethics, and law still faces many challenges, such as excessive reliance on AI, difficulties in identifying rare diseases, data privacy and security risks, etc. Future efforts should focus not only on technological advancement but also on pedagogical reform, positioning AI as a primary adjunct in clinical teaching and driving military dermatopathology education toward intelligent, personalized, and precision-based paradigms.