This study aims to explore the application effect of virtual assistants in deep English reading teaching in higher vocational colleges, so as to solve the current problems in teaching, such as rigid methods, insufficient students’ interest and ability, lack of resources, and flawed evaluation systems. The study constructs a four-dimensional driven English reading teaching model and systematically analyzes the application of virtual assistants through empirical research. The results show that this model significantly improves the academic performance of students in the experimental class, with a more concentrated score distribution and an increased proportion of high-scoring students; virtual assistants play a positive role in assisting vocabulary understanding, promoting preview and review, stimulating reading interest, and cultivating autonomous learning habits, with high-frequency users benefiting more significantly. However, there are problems such as unbalanced usage frequency and coverage, and insufficient functional adaptability. The study proposes hierarchical intervention strategies: expanding usage coverage, guiding autonomous learning in a hierarchical manner, and strengthening teaching intervention effects, providing an empirical basis and practical paths for virtual assistants to optimize deep English reading teaching in higher vocational colleges.