Generative artificial intelligence brings important opportunities for the reform and innovation of ideological and political education in universities. The situational teaching of ideological and political courses in universities is rooted in the theory of situational cognition, emphasizing the situational, embodied, and interactive nature of learning. It has important value in enhancing teaching affinity, promoting deep thinking, and emotional resonance. Generative artificial intelligence can empower the situational teaching of ideological and political courses through four mechanisms: optimizing the creation of teaching contexts, enhancing human-computer interaction experiences, promoting teaching mode changes, and assisting in the construction of learning communities. It effectively reshapes the teaching scenarios, experiential environments, and interactive contexts of ideological and political courses. In order to better utilize generative artificial intelligence to empower the situational teaching of ideological and political courses, it is necessary to optimize the teaching situation and promote the deep reconstruction of the teaching field, emphasize human-computer interaction and enhance students’ understanding and identification, build intelligent scenarios to improve the effectiveness of teaching models in nurturing students, and assist in co-creating and build a collaborative learning community.