TRUST, AUTHENTICITY AND ARTIFICIAL INTELLIGENCE IN TOURISM: A QUALITATIVE EXPLORATION OF TRAVELLERS’ EXPERIENCES WITH AI-POWERED TRAVEL TECHNOLOGIES

Background: Artificial intelligence (AI) is increasingly transforming tourism by influencing destination discovery, travel planning, personalisation, and real-time decision-making. However, as AI-generated recommendations become more embedded in travel experiences, questions remain regarding how travellers construct trust and perceive authenticity when interacting with intelligent technologies. Existing research has primarily focused on technology adoption, behavioural intention, and trust formation, with limited attention to the lived experiences through which travellers negotiate trust, uncertainty, and authenticity. Purpose and Research Gap: This study addresses this gap by exploring how travellers experience, interpret, and negotiate trust and authenticity in interactions with AI-powered travel technologies. Drawing on trust in automation theory and tourism authenticity theory, the study examines how travellers develop, question, and adjust reliance on AI while evaluating whether AI-mediated experiences remain meaningful and genuine. Methodology: An interpretivist qualitative research design was adopted. Data were collected through semi-structured interviews with 30 travellers who had used AI-powered travel technologies, including generative AI tools, recommendation systems, and virtual travel assistants. Participants were recruited through purposive online recruitment channels, including travel-related online communities, social media platforms, and personal networks of travellers with prior experience using AI-powered travel technologies, and were interviewed between March–May 2026. The data were analysed using reflexive thematic analysis following Braun and Clarke’s approach, resulting in four major themes. Findings: Travellers developed conditional, calibrated trust rather than complete acceptance or rejection of AI. Participants relied on AI for efficiency, personalisation, and information organisation, but maintained verification practices for high-risk decisions. Four themes emerged: (1) trust as a conditional and calibrated process, (2) authenticity as a negotiated travel experience, (3) the interrelationship between trust and authenticity, and (4) selective reliance and human–AI collaboration. Participants perceived AI as supporting authenticity when it facilitated personal discovery and meaningful engagement, whereas excessive reliance could reduce spontaneity and personal agency. Novelty and Contribution: The novelty of this study lies in examining trust calibration and authenticity negotiation together as interconnected processes in travellers lived encounters with AI-powered travel technologies. The study contributes to tourism research by repositioning AI-mediated tourism as an experiential and interpretive phenomenon rather than solely a technology-adoption issue. It integrates trust in automation and tourism authenticity perspectives to show that travellers assess both the reliability of AI information and its capacity to support meaningful travel experiences. Practically, it offers guidance for tourism organisations and AI developers seeking to design transparent, credible, and human-centred AI services.