Not just smarter—better jobs: How AI transforms work design and employee experience in tourism using SEM and fsQCA

With the rapid advancement of artificial intelligence (AI), the digital transformation of tourism enterprises is accelerating, shifting employee collaboration from traditional interpersonal interaction to human–machine integration. This shift reshapes the nature of work and significantly influences employee attitudes and behaviors. However, existing research has largely focused on isolated task features, overlooking how AI redefines the broader constellation of job characteristics, including task, knowledge, social, and contextual dimensions, that collectively shape employee experiences. Adopting a multidimensional job design perspective, this study investigates how AI usage transforms the full spectrum of job characteristics among tourism employees and identifies effective configurations that foster high performance, job satisfaction, and well-being. Using a mixed-method approach combining SEM and fsQCA, we draw on three-wave survey data collected from two samples of tourism employees. Results show that: (1) AI usage is positively associated with employees’ task, knowledge, social, and contextual job characteristics; (2) job characteristics partially mediate the relationship between AI usage and employee outcomes; and (3) multiple equifinal configurations of AI usage and job characteristics jointly foster high levels of performance, job satisfaction, and well-being, with specific attributes (e.g., autonomy, task identity, feedback, specialization) serving as key differentiators across configurations. By integrating variable-centered and configurational approaches and adopting a cross-national perspective, this study advances theoretical understanding of how AI reshapes work not only through average, linear effects but also through multiple, context-dependent pathways. In doing so, it offers practical guidance for designing AI-enabled jobs that simultaneously support employee performance, well-being, and satisfaction in service-intensive industries.