TITLE:
The Core Logic and Practical Pathways for AI-Driven Deep Transformation in Higher Education
AUTHORS:
Zhanjun Bai, Yonghua Fu, Ran Cheng
KEYWORDS:
Artificial Intelligence, Higher Education, Deep Transformation, Factor Coupling, Implementation Pathways
JOURNAL NAME:
Creative Education,
Vol.17 No.3,
March
13,
2026
ABSTRACT: Amid the wave of digital intelligence, artificial intelligence (AI) technology has emerged as the core engine driving high-quality development in higher education, reshaping its developmental ecosystem and operational logic with transformative force. This study addresses the contemporary imperative for AI-higher education integration, grounded in the policy orientation of the Outline of the National Education Development Plan (2024-2035). It delves into the core elements and interrelationships of AI-driven innovation in higher education, systematically elucidating its intrinsic mechanisms. It then explores practical pathways for AI-empowered deep transformation in higher education across three dimensions: constructing a “dual-circulation” practice approach, fostering a multi-dimensional collaborative development model, and establishing a comprehensive risk prevention and control mechanism. This study aims to provide theoretical references and practical guidance for the digital transformation of higher education and the advancement of educational modernization, thereby supporting the development of education-strong provinces and the implementation of the national strategy for building an education powerhouse.