Malika Soulami ^1,2* Saad Benchekroun ^1,2 Asiya Galiulina ^3,4,5

• ¹ Sidi Mohamed Ben Abdellah University, Fes, Morocco
• ² Laboratoire de Recherche Multidisciplinaire « LAREM », Fes, Morocco
• ³ Université Sultan Moulay Slimane, Béni Mellal, Beni Mellal-Khenifra, Morocco
• ⁴ Laboratoire de Recherche en Economie et Management des Organisations "LAREMO", Béni Mellal, Morocco
• ⁵ École Nationale de Commerce et de Gestion de Béni Mellal, Béni Mellal, Morocco

The adoption of artificial intelligence (AI) in the workplace is changing the way organizations function, and profoundly affecting employees. These organizational changes raise crucial questions about the employee's future and well-being. Our study aims to explore the intersection between artificial intelligence and employee well-being through a bibliometric review and a contextual analysis. Methodology: Carried out in May 2024, our study is divided into two phases. The first phase, dedicated to bibliometric review, was conducted using the PRISMA method, and explored the Scopus and Web of Science databases for the period from 2015 to 2024. A total of 92 articles were selected for quantitative analysis using VOSviewer software. The second phase is based on an indepth systematic analysis of 25 articles selected from those previously identified. These articles were selected on the basis of their relevance to the research question, and were subjected to in-depth thematic analysis using NVivo software. Results: The bibliometric analysis results reveal a significant increase in publications starting from the year 2020, highlighting advancements in research, primarily in the United States and China. The co-occurrence analysis identifies four main clusters: ethics, work autonomy, employee stress, and mental health, thus illustrating the dynamics created by artificial intelligence in the professional environment. Furthermore, the systematic analysis has brought to light theoretical gaps and underexplored areas, such as the need to conduct empirical studies in non-Western cultural contexts and among diverse target groups, including older adults, individuals of different sexes, people with low education levels, and participants from various sectors, including primary and secondary industries, small manufacturing businesses, call centers, as well as public and private healthcare sectors. Conclusion: Existing literature emphasize the importance for organizations to implement supportive strategies aimed at mitigating the potential adverse effects of AI on employee well-being, while also leveraging its benefits to enhance workplace autonomy and satisfaction and promote AI-enabled innovation through employee creativity and self-efficacy.