This paper provides an in-depth study and optimisation of the teaching methods of vocational education teachers with the help of artificial intelligence. In the field of machine learning, the article develops a small-scale knowledge graph. Then, combined with the constructed knowledge graph, a recommendation algorithm integrating student interest and knowledge connectivity is proposed, and knowledge connectivity and learner interest are defined in the whole design process of the recommendation system. Based on the model, an AI-assisted teaching method for vocational education teachers is proposed in terms of teaching content, learning situation, and teaching methods, and the optimization of teaching methods is completed. The accuracy of the recommendation model proposed in this paper for teaching resource content recommendations is more than 90%. The overall satisfaction of students’ feelings about using the system also reached 95.33%. After the implementation of the teaching optimisation method for vocational education teachers, the student’s academic performance improved, and the percentage of those who expressed positive evaluations in the four aspects of learning interest, participation in the classroom, interest in the course, and satisfaction with the course reached more than 80%, which demonstrates that the intelligent recommender system proposed in this paper has an excellent assisting effect on the teaching of teachers in vocational schools and that the AI-assisted AI-assisted teaching method optimisation work based on the AI-assisted AI-assisted teaching methods carried out in this paper has been completed. Optimising Teaching Methods for Vocational Education Teachers launched in this paper has received positive feedback.