Digital transformation: the role of generative AI in the evolution of knowledge management systems

Abstract

Purpose Generative artificial intelligence (GenAI) constitutes an emerging domain with potential implications for organisational knowledge management (KM). Whilst the absorptive capacity (ACAP) framework is well-established, understanding of how GenAI is applied to the processes within its dimensions remains fragmented. This study mapped and synthesised existing knowledge about GenAI in knowledge management processes, considering the dimensions of absorptive capacity (recognition, acquisition, assimilation, transformation and application). Design/methodology/approach A systematic review was conducted using the Scopus and Web of Science databases. The strategy combined terms related to absorptive capacity and knowledge management with specific GenAI descriptors. A total of 126 articles were initially identified, of which 13 were selected for final analysis. Findings Four thematic groups emerged: integration with existing systems (31%), as the principal theme; adoption factors (31%), focusing on recognition and application; sharing and application (23%), characterised by high centrality but low density; and knowledge creation (15%), a specialised area. The analysis identified asymmetric development across ACAP dimensions, with concentration in recognition and knowledge application, contrasting with gaps in assimilation. Originality/value The study offers a preliminary theoretical contribution by identifying the pattern of dimensional asymmetry in emerging literature on GenAI-mediated ACAP, wherein technological democratisation may challenge assumptions of traditional KM theories. For practice, evidence suggests that organisations may consider ACAP readiness assessment in implementation, prioritising the development of knowledge assimilation capabilities through structured validation protocols.

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