The study examines, within the framework of smart tourism, “double AI” (AI-on-AI) systems. The aim is to present how leaders in the tourism sector (SMEs, municipalities, destinations) can use these new frameworks to increase risk resilience. The research is grounded in the theoretical frameworks of resilience and AI technology, utilising both qualitative (case studies) and quantitative (surveys) methods. According to the literature, AI enables personalised services and enhanced efficiency in tourism while also presenting new challenges related to data protection and employment. The study complements this by presenting international and Hungarian examples, as well as three comparative case studies. The results encompass, on the one hand, the primary components and impacts of AI systems on resilience, and, on the other hand, the key quantitative indicators from the surveys. This mixed-method approach supports corporate leaders’ decisionmaking from several perspectives.
Katits et al. (Tue,) studied this question.