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 deci-sion-support tools raises questions about how the transparency of such information shapes farm-level adaptation. This study examines the relationships among AI trans-parency, climate awareness, decision confidence, agritourism diversification intention, and perceived farm resilience within a perception-based analytical framework in cli-mate-sensitive rural systems. Data were collected through in-person fieldwork con-ducted 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 perceived adaptive pathway under climate stress. The findings highlight AI transparency as a critical informational precondition for adaptive decision-making and resilience building as perceived and evaluated by farm operators, with implica-tions for farmer-centric digital tools and rural climate adaptation policy within com-parable climate-sensitive agricultural contexts.