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May 17, 2026Agriculture0 citationsOpen Access

Factors Influencing Artificial Intelligence Adoption in Wine Marketing: An Empirical Investigation of Internal and External Drivers

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MIMarzia IngrassiaSCStefania ChironiPCPietro Chinnici

Key Points

  • This study explores factors affecting the adoption of AI in wine marketing, focusing on internal and external drivers.
  • Conducted in-depth semi-structured interviews with marketing managers of 17 wineries in Italy and Spain.
  • Developed process flows and social network analysis to investigate marketing structures and digitalization levels.
  • Analyzed the suitability for technological innovation in wine marketing contexts.
  • Wine marketing processes are primarily data-driven but show partial and fragmented implementation.
  • Wineries exhibit moderate digitalization, with available data but limited data collection and integration capabilities.
  • Social network analysis indicates a dense relational network, yet inter-firm collaboration is largely absent.

Abstract

Although AI systems are increasingly being used as strategic tools in the agri-food sector, empirical evidence regarding their use and integration into wine marketing by wineries has been limited to date. The reasons for this delay may lie in various factors, both internal and external to the companies. This study aims to help fill this gap by examining some possible causes that could influence the propensity to use this technology and by attempting to analyze them. In-depth semi-structured interviews with marketing managers of 17 selected wineries in Italy and Spain were carried out. Process flows and Social Network Analysis (SNA) were developed to investigate marketing structures, levels of digitalization, and suitability for technological innovation. Findings show that wine marketing processes are data-driven systems integrating strategic and operational dimensions, but their implementation remains partial and fragmented. The observed wineries exhibit a moderate level of digitalization, characterized by the potential availability of data but limited capabilities in data collection and integration. SNA reveals a dense and homogeneous relational network, which could support shared data management systems; however, inter-firm collaboration is largely absent. Overall, the study identifies a latent potential for AI-driven marketing transformation, which is hindered by limited internal capabilities, and cultural resistance.

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Cite This Study

Ingrassia et al. (2026) studied this question.

synapsesocial.com/papers/6a095b5d7880e6d24efe1185https://doi.org/10.3390/agriculture16101085
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