AI-Driven Innovation in Educational Management: A Multi-Case Study of Chinese Higher Education Institutions

Abstract

This article presents an in-depth, multi-case study examining the implementation and impacts of AI-driven innovations in the management of Chinese higher education. Drawing on data from 35 higher education institutions in the Yangtze River Delta region, the study seeks to understand how the complex interplay between technological readiness and organizational learning capacity influences implementation outcomes. The empirical analysis is based on 847 valid survey responses from administrators, faculty members, and students. The results indicate that successful implementation depends on both technical infrastructure and organizational capabilities. A significant asymmetry was observed between the effects of technological readiness and organizational learning capacity on implementation success. Threshold effects were identified for both dimensions, with optimal implementation performance occurring in medium-scale institutions. Temporal analyses revealed that while technological readiness yields immediate benefits, its long-term impact is overshadowed by that of organizational learning capacity. These findings have important implications for theoretical research on educational technology implementation and for guiding institutional strategies in adopting AI-driven innovations in educational management.