Aug 2026· European Conference on Knowledge Management· Vol 27, pp. 260-269· 0 citations· 32 references
TL;DR
By clarifying the transition from organised information to prioritised intelligence, the paper extends DIKIW within KM theory to address contemporary challenges of information instability and shows how structured quality regulation stabilises explicit knowledge repositories and supports more coherent internalisation and organisational learning.
Abstract
Organisations continue to invest in Agentic AI and advanced analytics, yet the conversion of extensive knowledge resources into sustained innovation remains uneven. This difficulty is amplified in the post-truth era, where misinformation, synthetic content, and algorithmic hallucinations undermine information reliability. Within Knowledge Management (KM) research, substantial attention has been given to knowledge creation, sharing, and organisational learning. Less attention has been paid to the structured regulation of knowledge quality as a necessary condition for dependable intelligence production. This paper argues that innovation in digitally mediated environments depends not simply on knowledge availability, but on disciplined management of knowledge quality across the data-information-knowledge-intelligence-wisdom (DIKIW) continuum. The study is grounded in a pragmatist philosophy and adopts an abductive Design Science Research approach, supported by a Systematic Literature Review. It develops a model that links structured knowledge quality to organisational intelligence production. The model comprises three interconnected elements. The first element is a foundational knowledge infrastructure governing data and information organisation. The second element is explicit knowledge quality criteria - validity, authenticity, reliability, currency, and sufficiency, intended to safeguard epistemic integrity. The third element is a structured mechanism for transforming validated knowledge into prioritised organisational intelligence relevant to both human decision-makers and Agentic AI. By clarifying the transition from organised information to prioritised intelligence, the paper extends DIKIW within KM theory to address contemporary challenges of information instability. It shows how structured quality regulation stabilises explicit knowledge repositories and supports more coherent internalisation and organisational learning. Innovation is therefore understood as contingent upon epistemic governance rather than technological capability alone. The paper contributes by conceptualising structured knowledge quality as a distinct KM capability, articulating a formalised pathway between KM and organisational intelligence, and offering a design-oriented framework derived through abductive movement between the reviewed literature, established KM theory and the identified organisational problem.
The paper concludes that the future of KMS lies not in more sophisticated repositories, but in intelligent systems capable of dynamic codification, contextual reasoning, and continuous organisational learning, redefining the balance between human and machine agency in organisational knowledge processes.
A. Antonova, Dilyan Georgiev, Anikó Csepregi· European Conference on Knowl...· 0 citations
Universities face increasing pressure not merely to archive past activity but to anticipate what is coming, as rankings, funding landscapes, and research priorities shift in response to forces no single institution can fully predict. Traditional knowledge management (KM) approaches, designed to preserve and retrieve in...
Luiza Marabyan, A. Knyazyan· European Conference on Knowl...· 0 citations
The findings show how AI enhances the organizational processes of knowledge conversion—socialization, externalization, combination, and internalization—thereby improving the consistency, traceability, and robustness of sustainability disclosures, and illustrates how AI can support compliance with leading ESG reporting...
Tamara Menichini, S. R. Miccoli, Nicoletta Maria Strollo· European Conference on Knowl...· 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
This study embarks on conceptualizing knowledge sufficiency in the era of contemporary digital technologies and elaborating the degree of technological assistance required to reach the elusive levels of knowledge sufficiency in complex, non-routine organizational tasks and processes, to overcome the hurdle related to “...
Henri Hussinki· European Conference on Knowl...· 0 citations
Purpose: The diffusion of generative artificial intelligence signals a structural transformation
in the architecture of the knowledge economy. While prior research has focused primarily on
automation and augmentation (Raisch, Krakowski, 2021; Shrestha et al., 2019), the systemic
implications of generative systems fo...
Marcin Geryk· Scientific Papers of Silesia...· 0 citations
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