Artificial intelligence and the governance of overtourism in tourism cities

This conceptual paper discusses how artificial intelligence (AI) can reshape the governance of overtourism in tourism cities by shifting destination management from reactive control towards anticipatory and adaptive governance. Existing overtourism responses, including visitor caps, spatial redistribution, regulation, and awareness campaigns, often intervene only after tourism pressure has become socially and politically visible. In response, the paper reconceptualises overtourism as a dynamic social signal embedded in digital traces of tourist mobility, platform activity, and public sentiment. It argues that AI can enhance early detection, predictive management, smart flow redistribution, and iterative policy adjustment through real-time analytics and decision-support systems. At the same time, the paper critically acknowledges that AI is not a neutral or sufficient solution, as its effectiveness depends on data quality, institutional capacity, governance frameworks, and ethical oversight. Overall, the study positions AI as a governance enabler that can strengthen resilience, responsiveness, and sustainability in increasingly platform-mediated urban tourism systems.