AI-Driven Neuro-Personalization in Tourism: Enhancing Customer Experience, Travel Satisfaction and Service Adaptation through Real-Time EEG Analytics

Abstract

Artificial intelligence is transforming tourism businesses from standardized service delivery toward increasingly personalized customer experiences. However, most AI-enabled tourism services rely on historical preferences and behavioral data and remain unable to respond to travelers’ changing cognitive and emotional states during the actual service experience. This study examines how AI-driven neuro-personalization can enhance tourism service delivery by integrating real-time electroencephalogram (EEG) signals into adaptive travel itineraries. Using a randomized experimental design involving 100 travelers, the study compares AI-adapted and static itinerary conditions and examines the effects of neural engagement, stress and real-time itinerary adaptation on travel satisfaction. The findings demonstrate that EEG-measured engagement positively influences travel satisfaction, whereas neural indicators of stress negatively affect satisfaction. More importantly, AI-driven itinerary adaptation significantly enhances satisfaction while reducing traveler stress and cognitive load. The findings position neuro-responsive personalization as an emerging tourism business capability through which firms can dynamically align service offerings with customers’ real-time experiential states. The study contributes to smart tourism and customer experience management by extending AI personalization beyond predictive recommendation toward adaptive service delivery. For tourism businesses, travel platforms, hotels, wellness providers and destination managers, the findings demonstrate how real-time neuro-behavioral analytics can support differentiated service experiences, customer satisfaction and more responsive tourism value creation.

Keywords: AI-enabled tourism; customer experience; neuro-personalization; smart tourism; service adaptation; travel satisfaction; EEG analytics