Wine marketing strategies with AI for resilience of small and medium-sized enterprises

This study investigates the application of Artificial Intelligence (AI) in the wine sector for marketing-related processes,with a specific focus on its implications for marketing analytics. Adopting the PRISMA protocol, a Systematic LiteratureReview (SLR) was conducted, leading to the identification and analysis of 31 scientific contributions. The findings revealthat AI applications are predominantly concentrated in technical and production-related domains, such as quality control,traceability, and process optimization, mainly relying on machine learning and data-driven approaches. In contrast, a morelimited body of research addresses AI in marketing contexts, where consumer data is used to support marketing analyt-ics functions, including segmentation, personalization, and demand prediction. The results highlight a structural gap inliterature: despite the widespread adoption of AI technologies across the wine system, their integration into marketinganalytics remains limited. A conceptual framework is proposed that distinguishes between direct and indirect AI-drivendata pathways in marketing analytics. Implications for Small and Medium-sized Enterprises (SMEs) and ethical consider-ations related to AI use are also acknowledged. These findings suggest important directions for future research aimed atbridging the gap between technological capabilities and marketing analytics applications.