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The relationship between knowledge management and artificial intelligence: A thematic analysis from Scopus

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Pubblicato in:Iberoamerican Journal of Science Measurement and Communication vol. 5, no. 1 (2025), p. 1
Autore principale: Girón, Daniel Cristóbal Andrade
Altri autori: Yovera, Santiago Ernesto Ramos, de Salinas, Flor de María Garivay Torres, Soto, Félix Gil Caro, Cadenas, Dalila Irene Villanueva
Pubblicazione:
Iberoamerican Journal of Science Measurement and Communication
Soggetti:
Big Data
Machine learning
Collaboration
Bibliometrics
Artificial intelligence
Boolean
Tacit knowledge
Knowledge sharing
Decision making
Knowledge management
Knowledge acquisition
Intellectual capital
Data processing
Explicit knowledge
Natural language processing
Algorithms
Keywords
Software engineering
Knowledge representation
Information management
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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.
ISSN:2709-7595
2709-3158
DOI:10.47909/ijsmc.1713
Fonte:Publicly Available Content Database