Abstract: Computer-aided drug design（CADD） is a key instructional module in medicinal chemistry.However, due to limited class hours, high front-line complexity, and abstract theoretical content, traditional teaching approaches often fail to achieve the desired outcomes.Given that CADD itself inherently integrates computing and artificial intelligence（AI） concepts, achieving a dual integration of teaching content and pedagogical methods may be a crucial breakthrough for improving instructional effectiveness and optimizing learning experiences.This paper systematically analyzes the intrinsic coherence of AI applications at the levels of logical reasoning, algorithmic foundations, and data-processing architecture.It further elucidates the implementation pathways through which AI technologies can activate cutting-edge content, diversify teaching methodologies, and reshape dynamic evaluation systems.This “dual integration” not only enhances students’ professional identity but also comprehensively fosters their scientific literacy and overall competence, injecting new vitality into talent cultivation in medicinal chemistry.