Intelligence adoption and operational efficiency in tourism firms: The mediating role of implementation challenges

This study examines the impact of artificial intelligence (AI) adoption on operational efficiency in tourism firms, incorporating implementation challenges as a mediating mechanism. Drawing on Diffusion of Innovations, Service-Dominant Logic, and Dynamic Capabilities theory, the research proposes an explanatory structural model linking chatbot use, service automation, and predictive analytics to operational performance outcomes. Data were collected from 121 tourism SMEs located in Cali, Colombia, and analyzed using partial least squares structural equation modeling (PLS-SEM). The results indicate that AI adoption positively influences operational efficiency both directly and indirectly through implementation challenges, confirming partial mediation. Chatbot use emerges as the strongest driver of AI integration, followed by service automation and predictive analytics. The findings suggest that operational benefits derived from AI depend not only on technological deployment but also on organizations' capacity to manage technical, regulatory, and human barriers. This study contributes empirical evidence from an underrepresented Latin American context and advances understanding of AI as a systemic organizational capability.