Artificial intelligence (AI) is revolutionizing the tourism industry by enabling personalized and data-driven solutions that enhance the user experience. AI-based tour planners, offering real-time assistance and tailored recommendations, are becoming essential tools for modern travelers. However, limited research has explored the specific factors influencing user acceptance of these applications, particularly through the lens of user-generated feedback. This study addresses this gap by extending the Technology Acceptance Model (TAM). Using a dataset of 2,825 Google Play reviews of AI-powered tour planning applications, this research employs advanced text-mining techniques to identify key adoption drivers and barriers. The findings reveal that perceived usefulness, personalization, and real-time adaptability are critical enablers of user acceptance, while technical issues such as software glitches and compatibility challenges hinder adoption. These insights contribute to the theoretical refinement of TAM and provide practical recommendations for developers to enhance the design and functionality of AI-driven tour planning applications. The study underscores the transformative potential of AI in redefining travel experiences and highlights the need for further research on cultural, ethical, and longitudinal aspects of AI adoption in tourism.
