Abstract
Abstract The hospitality industry is adapting to new business realities amid rising consumer expectations, increased experiential offerings, shifting travel patterns, and emerging geopolitical challenges. This study focused on how the hospitality industry can leverage artificial intelligence to provide the expected customer experience, service quality, and personalization. All these factors positively impacted customer satisfaction, perceived service quality, and loyalty. Using structural equation modelling on data from 276 respondents, this study found that perceived value was the strongest and most consistent predictor of customer satisfaction (β = 0.65), and that service expectancy was, in turn, the strongest predictor of perceived value (β = 0.60) and of perceived risk (β = 0.25). Response time significantly shaped both perceived value (β = − 0.10) and perceived risk (β = 0.39). By contrast, service quality and customer experience showed no significant direct effect on perceived value, risk, or satisfaction, and perceived risk itself did not significantly predict satisfaction—findings that depart from several Western studies emphasizing the “dark side” of AI and instead suggest that Indian hospitality consumers weigh tangible value and efficiency more heavily than functional service quality or residual risk concerns. Hence, the novelty of this study lies in identifying perceived value and service expectancy rather than service quality alone as the critical levers through which AI integration can improve consumer satisfaction and loyalty in emerging markets such as India.