Artificial knowledge generation: investigating the revolutionary role of generative AI in knowledge management

Generative artificial intelligence (GenAI), with its potential to autonomously generate new content in the form of text, video, audio and code, holds disruptive potential to revolutionize knowledge management (KM) processes. An enormous number of studies have been published in recent years on the application of GenAI and this number is expected to increase further. Nevertheless, there are relatively few studies that systematize this research domain, and they are scarce from a KM perspective. For this reason, this study intends to bridge the current gap by offering both qualitative and quantitative insights in this research field using a bibliometric literature review, combining descriptive analysis with science mapping techniques, to analyse the impact GenAI has on KM processes. In particular, the aims of this paper are to provide a structured overview of how GenAI research contributes to the evolution of KM, to identify inconsistencies in the understanding of GenAI’s role in knowledge creation, and to propose directions for future theoretical and empirical research. In addition, our contribution proposes both the introduction of a new conceptual dimension, namely the machine dimension, which may extend traditional knowledge generation models, and a conceptual taxonomy for analysing GenAI readiness that is useful for managers and practitioners.