AI-Powered Academic Knowledge Management

Abstract

The implementation of artificial intelligence (AI) into knowledge management (KM) practices within academic institutions has the potential to fundamentally revolutionize research and education. Academic institutions are currently facing the complex task of dealing with the significant increase in data and information. This has led to the realization that traditional KM systems are no longer adequate in effectively managing, organizing, and sharing this vast amount of knowledge. The integration of AI into academic KM has the potential to bring about a paradigm shift. By leveraging advanced tools and technologies, AI can automate intricate processes including data organization, retrieval, and dissemination. This has the capacity to revolutionize the way academic knowledge is managed. The implementation of automation in research activities has been found to have several benefits. One of the key advantages is the streamlining of research processes, which allows to allocate more time and effort toward higher-order thinking and innovation. Additionally, automation has been observed to facilitate collaboration among researchers by breaking down disciplinary barriers and promoting seamless communication across different fields of study. Furthermore, the utilization of AI in academic research and administration can greatly enhance decision-making processes. This is primarily due to AI remarkable capability to analyze extensive datasets and effectively identify intricate patterns and emerging trends. Through the utilization of real-time insights and predictive analytics, AI has the potential to offer valuable guidance in shaping research directions, enhancing the allocation of resources, and tailoring educational experiences to individual students. The incorporation of AI into KM systems has the potential to enhance the development of increasingly dynamic and interactive learning environments. This integration enables the continuous improvement of teaching methods through the utilization of data-driven insights. Thus, the present chapter will aim to explore the theoretical implications of AI-driven KM in the context of academia. The focus of the discussion will be on AI Technologies and Tools for academic KM, with an emphasis on providing a forward-looking perspective that highlights both the transformative potential and the complexities associated with this shift.

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