Artificial Intelligence and Sustainable Tourism: Transforming Destination Management and Enhancing Visitor Well-being in the Digital Era

Abstract Artificial intelligence (AI) is transforming tourism through predictive analytics, personalized recommendation systems, conversational agents, intelligent resource management, and data-driven destination planning. Although these technologies offer opportunities to improve tourism services and operational efficiency, their contribution to sustainable tourism depends on environmental outcomes, social inclusion, institutional capacity, and responsible governance. This study examines the relationship between AI, destination management, visitor well-being, and sustainable tourism through an integrative review of secondary literature. The review draws on peer-reviewed systematic reviews, tourism-management research, and policy publications, including the OECD's analysis of AI in tourism and recent studies of AI-enabled tourism services. A qualitative thematic synthesis is used to organize the literature into four themes: AI-enabled destination management; AI and sustainable tourism development; AI and visitor well-being; and challenges associated with responsible AI adoption. The synthesis indicates that AI can support demand forecasting, visitor-flow management, personalized information services, accessibility, and operational planning. However, its contribution to sustainability is constrained by privacy concerns, algorithmic bias, digital exclusion, infrastructure costs, and the possibility that technological efficiency may not translate into lower environmental pressure. The study proposes a conceptual framework in which AI applications influence destination-management and visitor outcomes, while governance, inclusion, institutional capacity, and human oversight shape the realization of sustainable benefits. The paper concludes that AI should complement human expertise and participatory destination governance rather than be treated as an independent solution to tourism sustainability challenges.