Abstract: This study examines how artificial intelligence (AI) tools are incorporated into university leadership practice and whether the intensity of AI use is associated with leaders' perceived effectiveness. A convergent mixed-methods design was integrated into a quantitative survey of 69 administrative leaders, faculty in leadership roles, and professional staff at the University of Sharjah, with 60 qualitative narratives. Descriptives and ordinary least squares regression assessed associations, and inductive thematic analysis elaborated mechanisms and boundary conditions. Respondents reported moderate familiarity (M=3.30, SD=1.26) and moderate use of AI in leadership tasks (M=3.49, SD=1.41); 57.9% used AI at least weekly. Agreement that AI improves decision making was high (M=3.70, SD=1.09). The dominant barrier was lack of training (60.8%), followed by concerns about recommendation reliability (39.1%), data privacy (33.3%), and ethics (30.4%). AI use was positively associated with perceived leadership effectiveness (R=.492, R²=.242, p<.001). Some narratives emphasized time savings and increased clarity of communication, while others described ethical expectations regarding privacy, bias, accessibility, and academic integrity. Realization of value relies on (capability; role-specific AI literacy), (governance; privacy, assurance, bias, integrity), and (technology; reliable, low-friction tools). Our findings offer unique institution-level evidence from the Gulf context around the use of AI in relation to perceived leadership effectiveness and distil a pragmatic agenda which higher education leaders may find useful.

Keywords: artificial intelligence, leadership, higher education, mixed methods, governance, capability, Gulf universities, data ethics

Pages: 325-338