ABSTRACT. This paper investigates the evaluation systems of faculty performance in Kuwait’s private higher education, emphasizing the transformative potential of artificial intelligence (AI) in refining these frameworks. In reviewing the existing scientific literature, the paper identifies a gap in incorporating advanced technologies, particularly AI, in performance evaluation processes. It points out that while traditional methods provide a foundation, they often fall short in capturing the dynamic and multifaceted nature of faculty contributions and satisfaction. The research employs a thorough snowball sampling technique, gathering data from 71 participants to explore facets such as faculty engagement, research activities, use of technology, and non-academic contributions. The methodology investigates how these dimensions influence overall satisfaction with existing evaluation systems. Research questions probe the extent to which current evaluations align with faculty expectations and how AI might address existing shortcomings. Key findings reveal faculty engagement as a primary influencer of satisfaction levels, with teaching effectiveness, service contributions, and diversity and equity initiatives being vital components. Moreover, the study underscores the impact of professional development opportunities on enhancing engagement, research output, and technological proficiency. Notably, the analysis advocates for AI integration to automate, optimize, and personalize the evaluation process, offering a nuanced understanding of faculty performance.
JEL codes: I23; J24; M12; O33; C81

Keywords: faculty performance evaluation; artificial intelligence; higher education management; professional development; faculty engagement

How to cite: Alakoum, A., Nica, E., and Abiad, M. (2024). “Revolutionizing Faculty Performance Evaluation: The Future Role of AI in Higher Education,” Journal of Self-Governance and Management Economics 12(1): 25–49. doi: 10.22381/jsme12120242.

Received 8 April 2024 • Received in revised form 13 June 2024
Accepted 13 June 2024 • Available online 20 June 2024