AI-driven knowledge management: a new frontier for innovation and collaboration in higher education

Purpose This study examined how artificial intelligence (AI) tools can be integrated into knowledge management (KM) systems in higher education institutions and assessed their impact on key KM objectives and learning-related outcomes. Design/methodology/approach In terms of purpose, the research was applied and developmental. Methodologically, a qualitative approach was adopted. The study participants consisted of faculty members from Iranian universities. Sampling was conducted using the snowball technique. A total of 11 faculty members participated in the study. The primary data collection instrument was the semi-structured interview. Using a fuzzy cognitive mapping (FCM) approach, the study modeled the relationships between AI technologies, KM variables, and KM functions. Findings The results indicated that AI tools have a significant positive effect on KM outcomes in higher education. Natural language processing (NLP) showed the strongest influence on personalized learning, while intelligent assistants and chatbots had the greatest impact on real-time feedback, decision-making, and pattern recognition. Overall, AI-driven KM systems enhanced collaboration, learning outcomes, and knowledge sharing, while improving the efficiency of decision-making processes. Originality/value This study contributes to the higher education literature by offering a systemic, AI-driven KM framework based on FCM. It provides practical insights for university leaders and policymakers on utilizing AI to strengthen KM practices, foster innovation, and support collaborative and data-informed decision-making in academic institutions.