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 to buffer climate-related risks. Concurrently, the growing use of digital and AI-based climate 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 within a perception-based analytical framework 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 consistent 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, a higher intention to diversify toward agritourism, and greater 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 evaluated by farm operators, with implications for farmer-centric digital tools and rural climate adaptation policy in comparable climate-sensitive agricultural contexts.