The integration of artificial intelligence (AI) is rapidly reshaping work design, employee roles, and performance management across industries, including hospitality [1]. While AI adoption offers benefits like enhanced efficiency, personalization, and operational optimization, it also presents psychosocial challenges that can impact employee stress, job security perceptions, and overall well-being [2,3]. This study is a bibliometric review to examine the evolving scholarly discourse on the relationship between AI adoption and work stress, with a specific focus on the hospitality industry.

Using Dimensions.AI and the PRISMA framework, we retrieved literature from UGC-CARE Group II indexed sources, including the Scopus and Web of Science databases, covering publications from 2009 to 2026. A final dataset of 154 peer-reviewed articles was subjected to bibliometric mapping using VOSviewer (version 1.6.20). This mapping identified publication trends, citation structures, keyword co-occurrence networks, and dominant research clusters within the AI–work stress [96] domain. Recognizing the limited number of hospitality-specific studies, the bibliometric analysis incorporated cross-industry research to establish broader theoretical pathways linking AI implementation to employee stress outcomes.

This study fills a significant research vacuum on the effects of AI on job stress in the hospitality industry and adds to the expanding multidisciplinary understanding of AI-enabled work environments by analysing large-scale bibliometric mapping. The results offer practical implications for hospitality firms looking to strike a balance between technology adoption, employee well-being, and sustainable workforce management, as well as a structured basis for further empirical research..