Assessing the Digital Leadership Preparedness for the AI Era: A Latent Profile Analysis Based on the ACC Model

Abstract

Purpose This study investigates the digital leadership of Chinese K-12 educational administrators in the context of rapid artificial intelligence (AI) development. Design/Approach/Method Drawing on survey data from 1,426 educational administrators in Guangxi Zhuang Autonomous Region, the research empirically validates the Attitude–Cognition–Capability (ACC) model as a multidimensional framework for assessing educational digital leadership. Findings Chinese educational administrators displayed generally positive attitudes and reasonable cognitive understanding regarding digital technologies but showed lower levels of practical capability, highlighting an “implementation gap.” Four distinct leadership profiles were identified—Hesitant Adopters, Enthusiastic Implementers, Balanced Moderates, and Comprehensive Experts. MANOVA and R3STEP latent profile analyses indicate that male leaders and those with higher educational attainment consistently exhibit higher digital leadership, while age, work experience, and administrative positions play more limited roles. The explained variance by demographic and professional factors remains modest, suggesting that broader contextual and organizational factors warrant future investigation. Originality/Value These findings offer a foundation for targeted professional development and underscore the importance of building robust, multidimensional digital leadership capacity to navigate the opportunities and challenges of AI-driven educational transformation in China.