Authors - Shahin Makubhai, Ganesh R Pathak, Pankaj R Chandre, Raju Gurav Abstract - Artificial intelligence (AI)–driven personalization is increasingly embedded in digital customer journeys to enhance relevance and efficiency. However, such systems simultaneously raise concerns related to surveillance, autonomy, and trust, particularly in data-intensive service environments. This study investigates how AI personalization intensity and recommendation quality influence perceived surveillance, perceived autonomy, trust, customer experience, and loyalty within AI-enabled hotel journeys. Using a quantitative approach, survey data were collected from 200 hotel guests who interacted with AI-based personalization features. The proposed model was tested using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that AI personalization in-tensity and recommendation quality significantly increase perceived surveillance and perceived autonomy, while perceived surveillance plays a central role in trust formation. In contrast, customer experience and loyalty are weakly explained by AI personalization alone. The study contributes to ICT research by demonstrating that AI-driven systems primarily shape cognitive and perceptual mechanisms rather than directly driving behavioral outcomes, highlighting the importance of human-centered and ethically designed AI personalization in digital service con-texts.
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