Leveraging generative artificial intelligence for process innovation: the moderating role of IT culture and organisational flexibility

Giuliano Marolla, Parisa Sabbagh, Angelo Rosa and Olivia McDermott

European Journal of Innovation Management, 2026, vol. 29, issue 11, 427-444

Abstract: PurposeThis study explores the role of generative artificial intelligence (G-AI) as a lever for process innovation in food firms. In particular, it analyses how different levels of G-AI implementation influence innovation performance (incremental, frugal, radical) and how this relationship is moderated by two key organisational factors: IT culture and organisational flexibility.Design/methodology/approachThe empirical investigation is based on a questionnaire administered to 3,250 European, US and Australian companies operating in the primary food processing (P-FM) sector. The questionnaire was constructed from scales validated in the literature and pre-tested for clarity and semantic consistency. After the data cleaning process, 281 complete questionnaires were considered valid. The collected data were analysed using structural equation modelling (SEM).FindingsThe results show that generative artificial intelligence has a positive and significant impact on incremental and frugal innovations but not on radical ones. IT culture and organisational flexibility positively moderate the effect of G-AI on all types of innovation, with a synergistic effect for less complex innovations. The positive influence of radical innovation strongly depends on the combination of high organisational capabilities and firm size.Originality/valueTo realise the potential of G-AI, companies need to invest in widespread digital culture and adaptive organisational structures. Policymakers should foster access to innovation networks and training supports to enable even small and medium-sized enterprises (SMEs) to realise meaningful and sustainable innovations.

Keywords: Generative AI; Innovation management; Innovation culture; Food sector; Process innovation; Organisational capabilities (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:eme:ejimpp:ejim-09-2025-1269

DOI: 10.1108/EJIM-09-2025-1269

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