A Systematic Review on the Relationship Between Artificial Intelligence Techniques and Knowledge Management Processes

Abstract

AbstractKnowledge management (KM) processes and artificial intelligence (AI) techniques, two sides of the same coin, define the ontologies and rules required for knowledge-based systems. However, a systematic review on the relationship between AI techniques and KM processes is neglected. Therefore, this systematic review aims to identify the common AI techniques and their relationships with KM processes. Out of 20,834 articles identified, 29 studies met the eligibility criteria and were thoroughly analyzed. The main results showed that support vector machine (SVM), decision trees, logistic regression, and artificial neural network (ANN) were the most frequent AI techniques used in the extant literature. The results also indicated a significant relationship between the knowledge creation process and data mining techniques. In contrast, only a few studies examined the relationship between knowledge storage and AI techniques. Further, none of the analyzed studies examined the relationship between AI techniques and knowledge protection. This systematic review is believed to be a useful resource for scholars and practitioners interested in gaining more insights into the challenges and opportunities associated with AI techniques and their relationships with KM processes.KeywordsArtificial intelligence techniquesKnowledge management processesSystematic review