LEADERSHIP STRATEGIES FOR MANAGING CHANGE IN AI-INFUSED EDUCATIONAL SYSTEMS

Abstract

This study aimed to identify and evaluate effective leadership strategies required for successfully managing organizational change in educational institutions adopting AI technologies. Guided by three research questions and two hypotheses, a descriptive correlational survey was used to explore school leaders’ perceptions in South-East Nigeria. The population comprised public and private university administrative leaders, with a stratified random sample of 250 drawn. A self-developed questionnaire, validated by five educational technology experts (CVI = 0.92) and reliability-tested (Cronbach α = 0.84), measured perceived challenges, leadership strategies (transformational, collaborative, agile), and attitudes toward AI. Data were collected electronically and analyzed using descriptive statistics, Pearson correlation, and linear regression at p < 0.05. Major findings revealed that major challenges include skill gaps, resistance to change, and inadequate infrastructure; transformational and collaborative leadership were most effective for fostering AI adoption; and leaders’ positive attitudes significantly predicted implementation success. Transformational leadership correlated strongly with adoption success (r = 0.68, p < .01), supporting Ha₁, while Ha₂ was also supported by a significant regression coefficient (β = 0.54, p < .001). Implications indicate that investing in AI-focused leadership training and infrastructure can facilitate smoother change. Recommendations include embedding leadership development and ethical governance into institutional AI strategies. One limitation is reliance on self-reported perceptions. Further research should examine student outcomes in AI-infused systems.