From smart cities to smart tourism: GenAI, aerotainment, and the future of tourists experiences
DOI:
https://doi.org/10.70732/tijt.v35i1.80Keywords:
smart tourism cities, generative artificial intelligence, aerotainment, urban tourism management, digital visitor experienceAbstract
Purpose - The digital transformation of urban systems is reshaping how tourism destinations are planned, managed, and marketed. Within this context, generative artificial intelligence (GenAI) offers emerging opportunities to enhance visitor experiences, operational efficiency, and sustainable destination development. However, existing research on GenAI-enabled aerotainment has primarily focused on airport-centred applications, such as passenger services, airport–visitor interactions, and airport–destination connectivity. This study aims to substantially extend this perspective by reconceptualizing GenAI-enabled aerotainment as a destination-wide governance capability within smart tourism cities. It develops a conceptual framework integrating airports, urban mobility systems, tourism stakeholders, destination management organizations, and public governance structures into adaptive, data-informed tourism ecosystems. The study also introduces the Urban Tourism Destination Pyramid as a conceptual model for analysing different levels of smart tourism maturity.
Design/methodology/approach - The study adopts a conceptual and prospective research design based on an integrative synthesis of literature addressing smart cities, smart tourism destinations, aerotainment, destination governance, digital twins, predictive analytics, and artificial intelligence. Rather than empirically testing causal relationships, the research develops a theoretically grounded framework through the conceptual integration of established knowledge across these fields. The analysis identifies three complementary mechanisms through which GenAI can extend the conventional airport-centred understanding of aerotainment: predictive intelligence, adaptive personalization, and intelligent ecosystem coordination. These mechanisms are used to conceptualize how GenAI may support destination-wide decision-making, stakeholder interoperability, visitor-flow management, and adaptive tourism governance. Málaga is employed as an illustrative case to demonstrate how digital governance initiatives, technological infrastructure, and tourism policies can align with the proposed framework.
Originality/value - The study contributes to the emerging literature on GenAI-enabled aerotainment by substantially expanding its analytical scope from airport-centred applications to destination-wide governance. It integrates smart tourism city theory, systems thinking, and destination management to identify new mechanisms through which GenAI may influence tourism ecosystems. The Urban Tourism Destination Pyramid provides an additional conceptual tool for assessing smart tourism maturity. Future research should empirically validate the proposed relationships and examine their applicability across different tourism destinations and governance contexts.
Practical implications - The framework provides strategic guidance for destination management organizations, airports, tourism businesses, and public authorities seeking to integrate GenAI into smart tourism strategies. AI-supported personalization, predictive visitor-flow management, stakeholder coordination, and data-driven governance may strengthen destination capabilities and improve ecosystem responsiveness. However, effective implementation requires responsible approaches to data governance, interoperability, transparency, privacy protection, and sustainability. The framework therefore encourages stakeholders to view GenAI not simply as a technological tool, but as a potential capability for coordinating and governing increasingly interconnected smart tourism destinations.
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