Journal Press India^®

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The negative impacts of climate change have created an increasing vulnerability for tourism destinations and increased the need for governance systems that are adaptive, predictive and evidence-based. In this paper, artificial intelligence (AI) and data-driven policy systems are explored for enhancing smart governance for climate-resilient tourism. The study is based on a structured literature and policy review, which highlights the main gaps in the current tourism governance framework, such as a lack of institutional coordination, a lack of integration of climate intelligence, a lack of predictive capacity, and a lack of adequate monitoring mechanisms. To address this, the paper suggests the establishment of a Smart Tourism Governance Framework (STGF), which combines data infrastructure, AI-powered analytics, multi-level governance, and smart policy interventions and sustainability outcomes. The framework emphasises the role of predictive analytics, real-time monitoring, multi-stakeholder cooperation, and adaptive feedback cycles in helping to build more resilient tourism systems. The study has implications for the tourism governance literature in terms of the links it draws between adaptive governance, digital governance, and resilience theory and in terms of the operational implications it offers for policymakers, destination managers, and tourism stakeholders looking to create climate-resilient and future-proof tourist destinations

Keywords

Artificial Intelligence; Smart Governance; Climate-Resilient Tourism; Data-Driven Policy; Sustainable Tourism; Adaptive Governance

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