Is AI-driven personalization reshaping hospitality and gastronomy? An analysis of key factors driving transformation

Purpose This study seeks to explore the impact of AI-driven personalization in the hospitality and gastronomy sectors by identifying key variables and thematic clusters that shape current digital transformation practices. Design/methodology/approach A Systematic Literature Review (SLR, WoS, IEEE, April–May 2025, N = 25) was conducted, followed by a Multiple Correspondence Analysis (MCA) using R software and based on the HOMALS framework. This resulted in the identification of multidimensional relationships between customization, AI, and sector-specific challenges. Findings The findings suggest the need to align AI-based personalization strategies with ethical principles, user trust, and employee inclusion. Future research should investigate how to bridge the gap between operational efficiency and human-centered values. Practical implications The study provides practical insights for businesses in the sector seeking to implement AI tools without compromising user experience or ethical standards. It also highlights societal concerns related to dehumanization and trust, urging a more balanced integration of AI into relational services contexts. Originality/value This research offers a novel combination of qualitative coding and multivariate statistical analysis to examine how AI technologies shape customization practices in hospitality and gastronomy. It also introduces a variable-based perspective to understand conceptual differences within the field.