Artificial intelligence in tourism management: theoretical underpinnings, empirical tests and the SmartTourAI framework

Abstract

Purpose – The aim of the article is to analyze the potential applications of artificial intelligence (AI) in the tourism sector and to develop a strategic model for AI integration in this industry, called SmartTour. The article focuses on understanding and illustrating specific areas of AI application in tourism while addressing the existing research gap in this field. Additionally, the article presents practical recommendations for managers and decision-makers in the tourism sector, aimed at maximizing the potential of AI to enhance the competitiveness and innovativeness of tourism enterprises. Design/methodology/approach – To develop the SmartTour model, cross-validation and methodological triangulation. The study was based on case analyses of enterprises already utilizing AI, expert interviews and quantitative data analysis, which allowed for a comprehensive understanding of the researched phenomenon. In depth semi-structured interviews were conducted with managers of tourism enterprises and customers. Qualitative data were analyzed using NVivo software, while quantitative data were collected from a sample of 200 respondents. The surveys included both closed and open-ended questions, and the data were subjected to statistical analysis using SPSS software. The research sample was purposively selected. Findings – The study revealed that the Polish tourism sector utilizes AI for process automation, offer personalization and data analysis, enhancing efficiency and competitiveness. The developed SmartTour model integrates AI technologies, such as machine learning, to optimize services and customer experiences. Despite challenges like financial constraints and data security concerns, most companies plan further investments in AI. Originality/value – The article presents a new perspective on the application of AI in tourism management and proposes a specific model, SmartTour, which has not yet been empirically studied in the context of tourism. It also offers an analysis of the impact of AI on customer satisfaction, contributing to the existing literature that predominantly focuses on theoretical concepts. The research findings provide practical insights for managers, affirming the relevance and originality of the study. While AI in tourism is a growing area of research, the article’s focus on developing a comprehensive business model tailored to tourism enterprises is both original and significant.