The Impact of Artificial Intelligence on Knowledge Management: Faculty Perspectives from the University of Zawia’s Faculties of Economics, Management, and Law

The rapid technological advancements in the educational management enforce institutions to adopt new innovative approaches in knowledge management in ways that support innovation, decision-making, and institutional development. Artificial intelligence (AI) has emerged as a transformative tool with significant potential to enhance knowledge management (KM) practices. However, in many developing contexts, including Libya, the integration of AI in higher education remains limited and underexplored. This study investigates the impact of artificial intelligence (AI) on knowledge management (KM) within academic institutions, focusing on faculty awareness, utilization, perceived benefits, and encountered challenges. The researchers, using a structured questionnaire distributed to 210 academic staff members from faculty of Economy, Management and Law, employed a quantitative research design. This study reveals critical challenges to AI adoption in Libyan institution, including insufficient infrastructure, resistance to change, and a lack of technical expertise among faculty. Compared with previous studies conducted in technologically advanced contexts, this research contributes novel insights by examining AI in relation to KM integration in a developing academic environment as a gap in the literature. The findings reveal that a generally low level of AI awareness among participants, with limited understanding of core AI concepts and its future implications for higher education. However, moderate use of AI was reported in specific KM functions such as archiving and institutional support. The study concludes that while AI integration in academic knowledge systems is in its early stages, there exists a clear recognition of its value. Limitations of the study include its focus on one institution, which is the University of Zawia, Libya, and its reliance on self-reported data. Future research should consider longitudinal studies, cross-institutional comparisons, and qualitative investigations to deepen understanding of AI's evolving role in academic institutions. Recommendations include targeted faculty training, infrastructural investments, strategic policy development, and the promotion of a culture acceptance of new to technologies.