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ABSTRACT

Objective. This study examined the scientific literature addressing the relationship between artificial intelligence (Al) and knowledge management (KM) to identify the main issues around this binomial.

Design/Methodology/Approach. We used co-word analysis as our bibliometric technique. We only worked with each article's keyword and keyword plus variable. Each cluster within the map was assigned a generic name according to the theme it represented. We also conducted some analysis based on the degree of centrality of keywords per cluster. We also performed qualitative analyses of each cluster's terms and word relationships.

Results/Discussion. The co-occurrence map of terms revealed nine clusters related to the relationship between KM and Al: (1) main and central themes, (2) innovation and system design, (3) knowledge representation and learning, (4) theoretical models and information management, (5) collaborative networks and dynamics, (6) natural language processing, (7) ethics and governance, (8) visualization and knowledge representation, and (9) emerging and specialized areas.

Conclusions. This study contributes to closing a gap in the literature by demonstrating that integrating Al and KM is a key alliance to meet the challenges of the knowledge society. Al strengthens conventional KM processes and opens new opportunities to create organizational and societal value. However, implementing Al requires a balanced approach that combines technological innovation with ethical and human considerations.

Keywords: knowledge management; artificial intelligence; big data; machine learning; co-word analysis; literature mapping.

1.INTRODUCTION

KNOWLEDGE management (KM) is one of the main components of organizations (Renukappa, Suresh, & Jallow, 2020). According to Kayworth and Leidner (2004), KM comprises four processes: knowledge creation, storage, transfer, and application.Sanzogni, Guzman, and Busch (2017) state that there has been considerable debate about the feasibility of codifying tacit knowledge and the role of technology in KM. Artificial intelligence (AT) plays a crucial role in this. "Artificial intelligence (AT) aims to create machines which can perform tasks that normally require human intelligence, such as problem-solving, decision-making, and natural language processing" (Subaveerapandiyan, Sunanthini, & Amees, 2023, p. 503). AI tools are based on various methodologies to emulate human intelligence, such as supervised machine learning (ML), neural networks, and deep learning (Jarrahi et al., 2023). Organizations often do not implement АТ due to its costs or insecurity concerning its benefits (Pai et al., 2022). Studies have shown that IA contributes...

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