Integration of digital technologies and artificial intelligence in tourism project management: conceptual foundations and practical outcomes

Abstract

Digital technologies and artificial intelligence are becoming key drivers of transformation in the tourism industry, altering traditional management models and creating new formats of customer interaction. In modern conditions, tourism companies are compelled to rapidly adapt to dynamic market changes, utilizing algorithmic solutions, automated analysis systems, and analytical platforms to optimize the efficiency of operational and strategic processes. The purpose of this study is to investigate the impact of digital technologies and AI on the management of tourism projects, and to formulate practical recommendations for their application at the planning, implementation, and monitoring stages. Methods. The methodological basis of this work involves the use of a systems approach, comparative analysis of innovative technologies, case studies for implementing intelligent solutions in tourism, modeling of tourist flows, and an analytical assessment of the effectiveness of AI in management decision-making processes. Results. The study found that the use of digital tools and cognitive technologies provides automation of routine operations, increases the accuracy of demand forecasting and allows creating personalized tourism offers based on big data. Intelligent systems contribute to the integration of disparate information, the optimization of resource allocation, and the reduction of project management costs, while improving the quality of communication between participants in the tourism process. The scientific novelty of the study lies in the proposed multi-level financial model that integrates machine learning algorithms, predictive analytics, and KPI metrics to enhance the resilience of tourism enterprises. Conclusions. The study confirmed the strategic importance of digital technologies and AI for enhancing the efficiency of tourism program management; however, the emphasis should be placed not only on implementing existing solutions, but also on finding new approaches to their integration. Promising areas for further research include the development of adaptive management models based on predictive analytics, the creation of decision support systems utilizing machine learning, the implementation of virtual and augmented environments to enhance customer experience, and the analysis of cybersecurity and ethical considerations surrounding the use of AI in tourism. It is expected that the expanded use of intelligent platforms and digital ecosystems will contribute to the creation of more flexible and sustainable business models that can meet the challenges of global competition and the changing needs of tourists.