Aug 2026· The International Journal of Organizational Analysis· 0 citations· 63 references
TL;DR
A multilevel socio-technical framework in which AI–KM contributes to organisational sensing, seizing and reconfiguring through both a complementary direct pathway and an indirect pathway mediated by Generation Z knowledge behaviours, namely, digital collaboration, self-directed learning and openness to innovation is proposed.
Abstract
This study aims to develop a conceptual framework explaining how artificial intelligence-enabled knowledge management (AI–KM) contributes to dynamic organisational capabilities through the socio-cognitive role of Generation Z knowledge behaviours.
Drawing on the dynamic capability view and socio-technical systems theory, this study adopts a theory-building conceptual design based on a structured literature search across Scopus, Web of Science, ScienceDirect and Emerald Insight, supplemented by selected foundational and measurement sources. A final set of 64 scholarly sources informed the conceptual synthesis using a hybrid deductive-inductive thematic coding approach.
This study proposes a multilevel socio-technical framework in which AI–KM contributes to organisational sensing, seizing and reconfiguring through both a complementary direct pathway and an indirect pathway mediated by Generation Z knowledge behaviours, namely, digital collaboration, self-directed learning and openness to innovation. The framework also identifies technostress, trust in AI, digital competence, organisational learning culture, governance, industry risk and workforce composition as boundary conditions.
As a conceptual study, this framework requires future empirical validation, particularly through multilevel research designs that distinguish individual- and team-level knowledge behaviours from organisational-level capabilities.
The framework suggests that organisations should align AI-enabled knowledge infrastructures with employee learning, collaborative routines, governance mechanisms and human oversight.
This study contributes to AI–KM, human–AI collaboration and strategic management literature by refining the notion of Generation Z as a “digital bridge” into a set of contingent socio-cognitive knowledge behaviours through which AI-enabled knowledge becomes strategically consequential.
This paper aims to position artificial intelligence (AI) as a knowledge-based cognitive technology that drives organisational cognitive transformation (OCT). This paper addresses three gaps in knowledge management (KM) theory. First, there is a need to further clarify the conceptualisation of AI’s cognitive role wi...
Giovanni Schiuma· Journal of Knowledge Managem...· 1 citation
Artificial intelligence (AI) is transforming digital knowledge systems (DKS), reshaping how organizations generate, interpret, and apply knowledge in support of organizational learning and strategic decision-making. While AI-enabled systems enhance analytical capability, predictive insight, and information processing s...
Peter L. Mkhize· European Conference on Knowl...· 0 citations
This paper aims to reconceptualize knowledge management (KM) tools by integrating sociotechnical systems theory with insights from cognitive psychology.
This conceptual paper is grounded in a Critical Interpretive Synthesis (CIS) of an analytical corpus of 85 peer-reviewed studies retrieved from Scopus and W...
Hala Sibari, Asmae Houmid Bennani· Learning Organization· 0 citations
A structured framework for the literature and theory is built, showing how AI capability fuels innovation via interconnected knowledge processes across the organization, putting human judgment, epistemic governance, and knowledge validation at the center of how organizations learn and innovate with AI.
Vaivaw Kumar Singh· International Journal of Lat...· 0 citations
The findings reveal notable variations in the extent of GenAI adoption, readiness of organisational structures, maturity governance and trust in AI systems across cultures, and a context-based model combining organisational readiness, cultural dimensions, and institutional maturity is made.
Manal R. Taqatqa, Rami H. Aljbour· European Conference on Knowl...· 0 citations
This study aims to examine how generative artificial intelligence (GenAI) reshapes knowledge management (KM) in data-driven decision-making (DDDM), reconfigures principal–agent relations and creates new challenges for epistemic governance. It focuses on how GenAI influences the construction, synthesis, justificatio...
Matteo Cristofaro, A. Bañón‐Gomis, Pier Luigi Giardino· Journal of Knowledge Managem...· 0 citations
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