Transforming organizational knowledge creation through artificial intelligence: a systematic review of the emergent literature

Purpose This literature review aims to examine the use of artificial intelligence (AI) to facilitate conversions between tacit and explicit knowledge, driving organizational knowledge creation. Design/methodology/approach Drawing on Nonaka’s socialization, externalization, combination and internalization (SECI) model, the authors applied thematic coding to 82 academic articles to analyze how AI facilitates the four key processes of knowledge creation. Findings The authors generated five propositions that highlight the multifaceted role of AI in organizational knowledge creation. Research limitations/implications This systematic review serves as a stocktake of current knowledge. Its scope is limited by the time frame, which may exclude insights beyond the emergent phase. Future researchers should examine a broader period to capture the evolution of AI capabilities over time. Practical implications Insights from the systematic review can help organizations strengthen their organizational knowledge creation by aligning AI tools with human expertise. Originality/value The findings of this review can be used to refine the SECI model and enhance the limited theoretical understanding of the role of AI in organizational knowledge creation. The study offers a process-based account of how AI facilitates the generation, augmentation and updating of organizational knowledge through micro-level processes.

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Publication Details

Journal
VINE Journal of Information and Knowledge Management Systems
Published
2025-11-13
DOI
https://doi.org/10.1108/vjikms-08-2024-0296
Citations
2
Primary Topic
Organizational and Employee Performance
Type
article
Field-Weighted Citation Impact
4.96
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article

Transforming organizational knowledge creation through artificial intelligence: a systematic review of the emergent literature

Benjamin Fath, Junle Yan, Kenneth Husted
2 citations
VINE Journal of Information and Knowledge Management Systems
Organizational and Employee Performance
4.96
article

Transforming organizational knowledge creation through artificial intelligence: a systematic review of the emergent literature

Benjamin Fath, Junle Yan, Kenneth Husted
article en
2 citations

Abstract

Purpose This literature review aims to examine the use of artificial intelligence (AI) to facilitate conversions between tacit and explicit knowledge, driving organizational knowledge creation. Design/methodology/approach Drawing on Nonaka’s socialization, externalization, combination and internalization (SECI) model, the authors applied thematic coding to 82 academic articles to analyze how AI facilitates the four key processes of knowledge creation. Findings The authors generated five propositions that highlight the multifaceted role of AI in organizational knowledge creation. Research limitations/implications This systematic review serves as a stocktake of current knowledge. Its scope is limited by the time frame, which may exclude insights beyond the emergent phase. Future researchers should examine a broader period to capture the evolution of AI capabilities over time. Practical implications Insights from the systematic review can help organizations strengthen their organizational knowledge creation by aligning AI tools with human expertise. Originality/value The findings of this review can be used to refine the SECI model and enhance the limited theoretical understanding of the role of AI in organizational knowledge creation. The study offers a process-based account of how AI facilitates the generation, augmentation and updating of organizational knowledge through micro-level processes.

VINE Journal of Information and Knowledge Management SystemsVol. 56(2)
University of Auckland (NZ)
Openalex Percentile: Top 4%
Organizational and Employee Performance
4.96
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