With the rapid advancement of artificial intelligence (AI) and its widespread applications across various fields, AI education in higher education institutions has become crucial for cultivating future talent. However, current AI curricula often suffer from homogenization and insufficient disciplinary adaptability, failing to meet the diverse needs of students from different academic backgrounds. This paper proposes a hierarchical AI education framework, systematically analyzing the current state of AI education in domestic and international universities, and constructing a three-tier curriculum system comprising foundational, intermediate, and advanced levels tailored for general education, interdisciplinary applications, and specialized talent development, respectively. Research indicates that this model effectively enhances teaching pertinence, facilitates the deep integration of AI with other disciplines, and promotes innovative teaching methods such as adaptive learning and virtual laboratories. Finally, the paper offers recommendations for future development in interdisciplinary collaboration, industry-academia partnerships, and ethical education, providing theoretical and practical insights for the construction of AI education systems in higher education.

AI Education, Hierarchical Teaching, Curriculum Design, Interdisciplinary Integration, Innovative Teaching Methods