Transformational Leadership and Heterogeneity in Teachers’ Readiness for AI Integration: A Complementary Variable- and Person-Centered Approach

Artificial intelligence (AI) in education has attracted increasing global attention. Existing studies have mainly examined teachers’ AI adoption intention in relation to technology-related perceptions and broader school-level conditions, but the role of transformational leadership remains underexplored. Drawing on complementary perspectives from the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) and Self-Determination Theory (SDT), this study examined transformational leadership in relation to teachers’ readiness for AI integration using complementary variable- and person-centered analyses of data from 596 Chinese in-service K-12 teachers. The variable-centered results showed that transformational leadership was positively associated with teachers’ behavioral intention to use AI tools, with indirect associations involving willingness to develop AI competence and constructivist teaching beliefs. The person-centered analysis identified four readiness profiles: (1) Favorable Orientation but Behavioral Hesitation, (2) Limited Orientation and Behavioral Hesitation, (3) Low Orientation and Weak Behavioral Inclination, and (4) Favorable Orientation and Behavioral Inclination. Profiles 1 and 4 both showed relatively high constructivist beliefs and willingness to develop AI competence, but Profile 4 reported stronger behavioral intention to use AI tools. Profiles 2 and 3 were below the sample average across all three indicators, with Profile 3 showing the lowest behavioral intention. Relative to Profile 1, higher transformational leadership was associated with greater odds of membership in Profile 4 and lower odds of membership in Profile 3. These findings suggest that teachers’ readiness for AI integration varies in both level and configuration, highlighting the need for differentiated leadership and professional support.