AI Transparency and Climate-Adaptive Agritourism: Farm-Level Decision-Making and Rural Resilience

Climate change increases uncertainty in agricultural production and rural livelihoods, encouraging farms to pursue diversification strategies that can buffer climate-related risks. At the same time, the growing use of digital and AI-based climate and decision-support tools raises questions about how the transparency of such information shapes farm-level adaptation. This study examines the relationships among AI transparency, climate awareness, decision confidence, agritourism diversification intention, and perceived farm resilience in climate-sensitive rural systems. Data were collected through in-person fieldwork conducted throughout 2025 among agritourism-oriented farm operators in two Serbian rural clusters: a Western mountain agritourism belt and an Eastern/Southeastern dry-stress zone. Using structural equation modeling, the analysis reveals a coherent pattern of positive associations across all modeled relationships. Higher perceived transparency of AI-based climate information is associated with stronger climate awareness, greater decision confidence, increased intention to diversify toward agritourism, and higher perceived farm resilience. Perceived farm resilience was most strongly related to agritourism diversification intention, underscoring diversification as a key adaptive pathway under climate stress. The findings highlight AI transparency as a critical informational precondition for adaptive decision-making and resilience building, with implications for farmer-centric digital tools and rural climate adaptation policy.