Artificial Intelligence in Knowledge Management for Higher Education: Transformative Impact, Challenges, and Future Directions Post-COVID-19

Abstract

The COVID-19 pandemic has accelerated the integration of Artificial Intelligence (AI) in Knowledge Management (KM) within higher education, particularly in the Federal Technical and Vocational Training (TVT) sector. This systematic review synthesizes current research on AI-based KM in higher education during the pandemic, aiming to elucidate its effectiveness, challenges, and future directions. Following PRISMA guidelines, we conducted a comprehensive search across major databases, including Web of Science, Scopus, and ERIC, identifying 69 relevant studies published between 2020 and 2023. Our analysis reveals that AI-based KM has significantly enhanced personalized learning experiences, improved health safety measures, and increased administrative efficiency in higher education. However, challenges persist, including technological barriers, ethical concerns, and the digital divide. The review highlights a notable research gap in empirical studies validating AI's effectiveness in real-world educational settings, particularly in developing countries. Furthermore, there is a critical need for comprehensive ethical frameworks governing AI use in education. Our findings underscore the transformative potential of AI-based KM in higher education, while emphasizing the necessity for context-specific implementations and rigorous evaluation methodologies. This review provides valuable insights for educators, policymakers, and researchers, guiding future developments in AI-based KM strategies for resilient and inclusive higher education systems in the post-pandemic era.