Exploring how AI adoption in the workplace affects employees: a bibliometric and systematic review.

Journal: Frontiers in artificial intelligence

Volume: 7

Issue: 

Year of Publication: 

Affiliated Institutions:  Formerly at Laboratory of Studies and Research in Management of Organizations and Territories (ERMOT), Faculty of Legal, Economic, and Social Sciences of Fez, Sidi Mohamed Ben Abdellah University, Fez, Morocco. Laboratory of Research in Economy and Management of Organisations (LAREMO), National School of Business and Management of Beni Mellal, Sultan Moulay Slimane University, Beni Mellal, Morocco.

Abstract summary 

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.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 in-depth 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.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 under-explored 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.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.

Authors & Co-authors:  Soulami Malika M Benchekroun Saad S Galiulina Asiya A

Study Outcome 

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Statistics
Citations :  Ahn J., Kim J., Sung Y. (2022). The effect of gender stereotypes on artificial intelligence recommendations. J. Bus. Res. 141, 50–59. doi: 10.1016/j.jbusres.2021.12.007
Authors :  3
Identifiers
Doi : 1473872
SSN : 2624-8212
Study Population
Male,Female
Mesh Terms
Other Terms
artificial intelligence;bibliometric review;employee well-being;systematic review;workplace stress
Study Design
Study Approach
Quantitative,Systemic Review
Country of Study
Publication Country
Switzerland