Managing generativity in innovation: from control to emergence

Antoine Bordas (), Gouthanan Pushpananthan, Ludvig Lindlöf and Fábio Gama
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Antoine Bordas: CGS i3 - Centre de Gestion Scientifique i3 - Mines Paris - PSL (École nationale supérieure des mines de Paris) - PSL - Université Paris Sciences et Lettres - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique
Gouthanan Pushpananthan: LIU - Linköping University
Ludvig Lindlöf: Halmstad University
Fábio Gama: Halmstad University

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Abstract: Emerging technologies such as generative AI or autonomous systems introduce new forms of generativity, namely the capacity to produce unexpected, evolving, and selfpropagating outcomes. These technologies challenge conventional management approaches. They do so by producing outcomes that cannot be fully anticipated or predefined, thereby undermining the assumptions of stability, linearity and alignment theorized in traditional management and innovation literature. Importantly, the emergence of AI provides new challenges on, for instance, how can organizations manage generative technologies? What practices, processes and structures enable organisations to leverage generative technologies? This track explores how organisations understand, design, and manage generativity as a new condition for creativity and transformation. We invite theoretical, empirical, and design-oriented contributions examining how generativity reshapes organisational creativity, learning, and strategy. The track aims to bring together researchers studying the creative, organisational, and epistemic implications of generative technologies. Description:Digitalisation has transformed the way organisations innovate, yet a new phase is unfolding, one that is characterised not merely by automation or connectivity, but by generativity. Generative technologies, including GenAI, synthetic biology, computational design, and adaptive systems, create artefacts, knowledge, and possibilities that evolve autonomously and perpetually. These technologies are not only tools or enablers; they are complex systems, capable of evolving autonomously and reconfiguring the very environments in which they operate (Thomas & Tee, 2022). This shift challenges traditional managerial models founded on prediction, control, and eRiciency. Managing innovation in generative contexts requires new forms of creativity, coordination, and learning (Haefner et al., 2021).

Date: 2026-06-22
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Published in R&D Management Conference 2026, Jun 2026, Manchester (UK), United Kingdom

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