AI-Enabled Service Quality and Guest Loyalty Intentions in Malaysian Luxury Hotels: An Exploratory Study of Guest Satisfaction

Artificial intelligence (AI) is becoming increasingly visible across the hotel guest journey, yet evidence remains limited on how guests evaluate AI-enabled service quality in luxury hospitality and whether satisfaction explains its relationship with loyalty intentions. This study examines the relationships among AI-enabled service quality, guest satisfaction and guest loyalty intentions in Malaysian luxury hotels. Drawing on SERVQUAL, Expectation–Confirmation Theory and Relationship Marketing Theory, three direct hypotheses and one exploratory mediation relationship were examined using cross-sectional survey data from 115 adults who had stayed at a luxury hotel in Malaysia within the previous 12 months and used at least one AI-enabled hotel service. Data were analysed using descriptive statistics, Spearman’s rank-order correlations and regression-based analyses. AI-enabled service quality positively predicted guest satisfaction (? = 0.561, p < 0.001) and loyalty intentions (? = 0.751, p < 0.001), while satisfaction positively predicted loyalty when examined independently (? = 0.405, p < 0.001). However, satisfaction was not significant after AI-enabled service quality was included in the loyalty model (? = ?0.024, p = 0.755), and the estimated indirect effect was negligible (ab = ?0.015). The findings suggest that, within this exploratory sample, loyalty intentions were associated more strongly with guests’ direct evaluations of AI-enabled service quality than with an indirect satisfaction pathway. The study extends service-quality research into an under-researched Southeast Asian luxury-hotel context and highlights the importance of reliable, responsive, secure and appropriately personalised AI services. Conclusions are tempered by the cross-sectional, purposive design and the marginal reliability of the short satisfaction and loyalty scales.