AI in Knowledge Sharing and Collaboration: Enhancing Faculty Motivation and Academic Excellence in Universities

This research investigates the contribution of Artificial Intelligence (AI) towards knowledge sharing, staff motivation, and ethical issues in higher education collaboration among university academics (N = 290). Correlation analysis indicated a moderate to weak positive correlation between AI and knowledge sharing (r = 0.213, p = 0.000) and AI and staff motivation (r = 0.298, p = 0.000), indicating that AI contributes to greater involvement and knowledge sharing. Still, regression analysis indicated that the influence of AI on academic productivity was statistically non-significant (R² = 0.000, p = 0.970), implying that AI, by itself, does not impact faculty motivation much. Also pointed out were the ethical issues related to data privacy, bias of AI, and intellectual property concerns, supporting the importance of having institutional policies and ethical frameworks in place for adopting AI in academic environments. These conclusions indicate that although AI is a useful tool for cooperation and productivity, its applications are limited without adequate faculty training and policy structures. Future studies must investigate longitudinal studies and qualitative analyses to determine the long-term effect of AI on academic quality.