Artificial Intelligence in Knowledge Management: Mapping a Decade of Research and Emerging Directions
DOI:
https://doi.org/10.63541/z157nq33Keywords:
artificial intelligence , bibliometrix, innovation, knowledge management, science mappingAbstract
This study maps the intellectual landscape of research at the intersection of artificial intelligence (AI) and knowledge management (KM) to clarify how the field has evolved, who shapes its development, and which themes dominate and emerge over time. A science-mapping study was conducted on 209 English-language journal articles indexed in Scopus (2015–2025). The dataset was analyzed using Biblioshiny to generate performance indicators, collaboration patterns, and thematic structures derived from keyword co-occurrence and factorial clustering. The results indicate a clear acceleration of KM–AI publications after 2020, signaling a shift from early exploratory work toward a rapidly expanding domain. Social-structure mapping shows that knowledge production is globally distributed but concentrated among a core set of countries, institutions, and author networks, with collaboration patterns shaping the diffusion of dominant topics. Conceptually, the field is organized around three interlinked streams: (i) AI-enabled decision support and analytics for KM, (ii) people- and leadership-related adoption dynamics influencing knowledge sharing and innovation, and (iii) governance and sustainability concerns associated with responsible knowledge processes and risk management. This study consolidates fragmented KM–AI scholarship into an integrated map, differentiates core versus peripheral streams, and proposes a focused research agenda that prioritizes mechanisms, boundary conditions, and evaluation approaches for AI-enabled KM in organizational settings.
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