AI-driven strategies for sustainable cultural tourism marketing: a case study approach to visitor engagement and environmental impact

Introduction While artificial intelligence (AI) has revolutionized real-time personalization in destination marketing, its strategic deployment to mitigate the negative externalities of cultural overtourism remains undertheorized. Methods Grounded in the Tourism 4.0 paradigm, this paper addresses this gap by introducing the AI–Sustainability–Engagement Nexus (ASEN) framework; a novel conceptual model integrating the Stimulus-Organism-Response (S-O-R) paradigm with the Technology Acceptance Model (TAM). To evaluate the model's structural propositions, we conduct an institutional multi-case desk study of secondary data from eight globally significant cultural heritage sites (e.g., The Louvre, The Palace Museum, Dunhuang Mogao Grottoes, and Machu Picchu). Results The findings suggest that AI-driven smart demarketing and spatial-temporal flow optimization is associated with alleviating localized overcrowding and carbon footprints in the cases where such effects are directly evidenced. Discussion Crucially, the analysis indicates that sustainability returns are not incidental byproducts of marketing efficiencies; rather, they require explicit environmental design parameters and robust institutional governance architectures. The paper concludes with an actionable, agenda-setting framework for destination management organizations (DMOs) to balance economic demands with heritage preservation.