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Optimization Tool or Radical Transformation? The Ambivalent Role of Generative AI in Organizational Innovation

Aug 2026 · European Conference on Knowledge Management · 0 citations · 27 references

TL;DR

The study identifies a hybrid domain, labelled knowledge reconfiguration, where GenAI drives transformation from within existing knowledge structures by reshaping roles, decision-making processes, and cognitive practices and introduces knowledge reconfiguration as a distinct mode of innovation, where radical change emerges from the transformation of established competences.

Abstract

The rapid diffusion of Generative Artificial Intelligence (GenAI) is transforming how organizations create, manage, and leverage knowledge, raising fundamental questions about its role in innovation processes. While existing studies emphasize either efficiency gains or disruptive potential, limited attention has been paid to how GenAI interacts with organizational knowledge structures and how its uses relate to different types of innovation. This study addresses this gap by examining whether the organizational uses of GenAI predominantly support incremental or radical innovation, and the extent to which they align with knowledge exploitation or exploration dynamics. Drawing on a qualitative case study of a small and medium-sized enterprise (SME) operating in the IT sector, the research analyses semi-structured interviews through a two-dimensional framework combining the incremental–radical innovation distinction and organizational ambidexterity. The findings reveal that GenAI operates as a transversal technology, spanning all quadrants of the analytical matrix. However, its use is predominantly oriented toward incremental innovation and exploitation, particularly in applications related to task automation, documentation, and knowledge formalization. At the same time, GenAI enables exploratory and radical dynamics, especially in the development of new services and analytical capabilities. The study identifies a hybrid domain, labelled knowledge reconfiguration, where GenAI drives transformation from within existing knowledge structures by reshaping roles, decision-making processes, and cognitive practices. These findings contribute to the literature by showing that GenAI is not inherently incremental or radical, but assumes different innovation roles depending on its use. The study further suggests that GenAI acts as an ambidexterity-enabling technology and introduces knowledge reconfiguration as a distinct mode of innovation, where radical change emerges from the transformation of established competences.

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