How hotel AI adoption shapes employee performance? A study based on the transactional theory of stress and coping

Purpose The purpose of this study was to construct a mediated moderating model, based on transactional theory of stress and coping, examining how hotel artificial intelligence (AI) adoption affects employee service performance (in-role and extra-role service performance), with AI crafting as the mediator and appraisals toward AI (challenge appraisals and hindrance appraisals) as the moderators Design/methodology/approach This study used a sample of 334 frontline hotel service employees collected in a three-wave time-lagged design, using path analyses to test the conceptual model. Findings Results indicated that when challenge appraisals toward AI is high, hotel AI adoption and challenge appraisals toward AI interaction have a positive impact on AI crafting. However, when hindrance appraisals toward AI is high, hotel AI adoption and hindrance appraisals toward AI interaction have a negative impact on AI crafting; the interaction between hotel AI adoption and appraisals toward AI on employee service performance (in-role and extra-role service performance) was mediated by employee AI crafting. Practical implications Organizations should develop comprehensive AI adoption strategies that consider both opportunities and risks. Encouraging employee AI job crafting through training programs and knowledge sharing can enhance service performance. Managers should assess and actively shape employees’ cognitive appraisals of AI, promoting challenge rather than hindrance perceptions. Creating an inclusive organizational culture and open communication channels is crucial for fostering positive employee attitudes toward AI adoption. Originality/value This study contributes to the literature on AI adoption and employee service performance by examining when and how hotel AI adoption influences employee service performance.