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Generative AI Solutions for Enhancing Knowledge Management: A Literature Review and Roadmap

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Date
2024
Author(s)
Pimentel Bernal, Paul Marcelo
Veliz Palomino, José Carlos
Metadata
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Abstract
This article explores the potential of Generative Artificial Intelligence (GenAI) to improve knowledge management in organizations. Despite growing interest in GenAI, a thorough review of its applications and effectiveness in knowledge management is still needed. GenAI has shown promise in automating content creation, synthesizing information, and improving decision-making processes. However, its integration into knowledge management systems remains fragmented. This study seeks to consolidate existing knowledge and chart a path for future research in this area. The research uses a systematic literature review (SLR) following PRISMA guidelines, complemented by a thematic analysis to ensure a comprehensive assessment of the existing literature. We reviewed articles published between 2020 and 2024, focusing on GenAI applications in knowledge management. A thematic analysis was conducted to identify key themes and trends. This paper contributes to the academic and professional environment by providing a detailed review of GenAI applications in knowledge management, identifying best practices, and offering strategic recommendations for leveraging GenAI to improve organizational processes. The review highlights key areas where GenAI can improve knowledge management: automating the generation of knowledge assets, enhancing knowledge discovery and retrieval, supporting collaboration, and improving decision making through advanced analytics. In addition, it addresses ethical considerations and potential challenges, such as data privacy and the need for human oversight. © 2024 Academic Conferences Limited. All rights reserved.
URI
https://hdl.handle.net/20.500.12724/22552
DOI
https://doi.org/10.34190/eckm.25.1.2770
Publisher
Academic Conferences and Publishing International Limited
Subject
Pendiente
Event
Proceedings of the European Conference on Knowledge Management, ECKM
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