Published Online:April 2025
Product Name:The IUP Journal of Knowledge Management
Product Type:Article
Product Code:IJKM030425
DOI:10.71329/IUPJKM/2025.23.2.50-90
Author Name:Andrew Terhorst and Alexander Krumpholz
Availability:YES
Subject/Domain:Management
Download Format:PDF
Pages:50-90
Tacit knowledge—intuitive and experiential know-how that resists codification—remains a critical yet elusive driver of innovation. This paper explores its evolving role in the current digital era through a systematic literature review from 2015 onwards. Employing citation and co-author network analyses complemented by generative AI (GenAI) tools, the study synthesizes key insights, identifies emerging themes, and contextualizes tacit knowledge’s cognitive and experiential dimensions within contemporary innovation processes. The analysis reveals critical enablers, including effective leadership, social capital, and cultural sensitivity, while highlighting the risks posed by increasing reliance on digital platforms that may undervalue tacit knowledge’s intuitive and contextual nuances. Furthermore, it addresses significant gaps in understanding group-level tacit knowledge, tacit knowledge’s role in ideation, and the disruptive influence of GenAI on the interplay between tacit and explicit knowledge. The paper charts actionable pathways for integrating human expertise with AI, offering a roadmap for sustaining innovation in dynamic, interdisciplinary settings and calling for further research into these synergies.
Knowledge is a fundamental driver of innovation, shaping how individuals and organizations solve problems, generate ideas, and adapt to change. It is commonly categorized as explicit or tacit. Explicit knowledge is structured, codifiable, and quickly transferred through documentation, databases, and formal instruction. In contrast, tacit knowledge is deeply