This article mainly explores the design and application effect of the individualized learning path of a big data-driven business English course under the OBE concept based on artificial intelligence (AI). To achieve the research goal, this article designs a set of individualized learning path frameworks, including key links such as goal setting, demand analysis, content customization, path generation and assessment feedback. Furthermore, a recommendation algorithm based on user behavior data and a learning path planning algorithm based on knowledge maps are developed to dynamically generate learning paths that meet students’ individual needs. In the experimental part, a certain number of business English learners are selected as experimental subjects, and they are randomly divided into an individualized learning path group and a traditional learning path group for comparative experiments. The experimental results show that the learners of the individualized learning path group have obvious advantages in learning efficiency, academic performance, and satisfaction. They can quickly master business English knowledge and skills, improve their academic performance, and are highly satisfied with the learning path. The framework and algorithm model of individualized learning path designed in this study are effective and feasible, which is of great practical significance to the teaching reform of the business English course.