AI-Powered Personalization: Transforming the Tourist Experience

Abstract

The role of hyper-personalization in the tourism industry based on AI technology is explored in this paper, where AI technology employs machine learning, NLP, and generative models to offer hyper-personalized travel experiences to increase traveler satisfaction, bookings, and sustainability. It then talks about the impact of hyper-personalization based on systematic literature reviews and case studies like recommendation systems of Booking.com that show the impact of hyperpersonalization that leads to more bookings (20-30%), and other adverse consequences including bias, privacy, and digital divides. The main results are technical, that is, the collaborative filtering and predictive analytics, which are powered by the platforms, and the policy requirements to the GDPR-compliant regulation, and implications to the fair access, particularly in developing markets, which advance Viksit Bharat. Limitations are the gap of Western world data and short-term research studies, which may be considered as the subject of future research on multi-region RCTs, explainable AI hybrids, and IoT-based sustainability trials. Lastly, sustainable tourism systems will be the key to responsible AI implementation, which will integrate innovation and ethics to re-engineer global travel by 2030.