With the rapid advancement of artificial intelligence (AI) technology, exploring how to integrate AI with traditional genetic experiment courses has become a key focus of current teaching reform. Based on the conventional teaching system of genetic experiments, this study introduced an innovative student-led module focused on AI-assisted experimental design, thereby establishing a model for the deep integration of AI and genetic experiment teaching. Practice results demonstrate that this integrated model not only significantly improves teaching efficiency and quality, but also effectively breaks down the disciplinary barriers inherent in traditional teaching. It provides students with a cross-disciplinary perspective for innovative thinking, stimulates their learning interest and independent creativity, and further enhances their practical ability and scientific literacy in using AI tools to explore complex scientific problems. In addition, the multi-dimensional evaluation system constructed based on AI technology realizes the automated collection and precise analysis of student learning behavior data, which further improves the comprehensive quality evaluation mechanism for students. This study offers a practical approach to the digital reform of experimental teaching in universities and holds significant theoretical and practical value for advancing experimental teaching innovation and cultivating high-quality innovative talents in the digital era.