AI-driven sustainability: the interplay of generative capabilities, resource optimization, and institutional support

Purpose This study examines how generative artificial intelligence capabilities (GAIC) influence sustainable performance (SP) in the Spanish hotel industry. Drawing on the resource-based view (RBV) and the AI4GoodTourism framework, it analyzes the mediating role of resource optimization (RO) and the moderating role of institutional support (IS) in this relationship. Design/methodology/approach A moderated mediation model was tested using partial least squares structural equation modeling. Data were collected through a survey of 367 hotel firms in Spain. Both direct and indirect effects of GAIC on SP were assessed, considering RO as a mediator and IS as a conditional moderator. Findings GAIC exerts a strong positive influence on SP directly and indirectly via RO. IS strengthens the impact of RO on SP, amplifying the indirect effect of GAIC on SP through RO. The findings demonstrate the dual role of internal resource efficiency and external IS in driving sustainability outcomes in hotels. Practical implications Hotel managers and policymakers should promote generative AI adoption alongside supportive institutional frameworks. Aligning technological capabilities with RO strategies and policy incentives can enhance hotels’ operational efficiency, reduce environmental impacts, and achieve SP. Originality/value This study pioneers the integration of the RBV and AI4GoodTourism by conceptualizing GAIC as a driver of sustainability. It provides insights into how AI capabilities promote resource efficiency and sustainable outcomes, offering theoretical and practical contributions to the hospitality industry.