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This editorial review presents a bibliometric account of the convergence of the fields of artificial intelligence (AI) and human resource management (HRM) and an overview of the related contributions in this special issue. It also explores the expansive area where research on AI and HRM intersects, a domain experiencing rapid growth and transformation, faster than we envisaged.

This substantive editorial employs a range of bibliometric analytical tools to present a state of knowledge on the topic and also provides an analytical overview of the contributions in this Special Issue.

A thorough examination of scholarly publications spanning two decades illuminates the evolutionary path of themes, key contributors, seminal works and emerging trends within this interdisciplinary sphere. Leveraging co-word analysis, we distill essential themes and insights from an extensive dataset of 654 journal publications curated from the Web of Science database. Our analysis underscores critical research domains, highlighting the nuanced interplay between HRM and AI.

By integrating findings from the bibliometric analysis and the contributions from the papers in the Special Issue, we highlight and speculate where the field is heading and where scholars have crucial? Opportunities to contribute to going forward.

To describe how decision-making in the selection processes of managerial successors in business families is influenced by the use of cutting-edge technologies such as AI.

Systematic literature review of 65 articles indexed in Scopus and in the main specialized journals on family businesses.

The integration of AI and algorithms, specifically in selection procedures, raises major questions and faces legal and ethical issues that affect employee performance, moral commitment and fairness in the processes. These aspects are important to ensure transparency, fairness and accountability as they provide insight into the practices of business families and how succession challenges such as the possibility of using signaling games and addressing gender biases and information asymmetries that have been reported in past research could be complemented by these actions.

The limitations of this research are mainly attributed to the exclusive use of a single database (Scopus), which could limit access to relevant literature; Furthermore, the exclusion of certain articles, despite focusing on prestigious journals on business families, may have overlooked relevant contributions; Furthermore, the 20-year scope of the literature review that ended in February and August 2024 omits subsequent publications that could have enriched the findings of this study.

To the best of the author’s knowledge, this study is the first of its kind to conduct a bibliometric analysis covering the line of successor selection and the process leveraged by new practices such as AI, an aspect that has been little addressed in the literature. In addition, this work traces aspects of decision-making that may affect selection. The research is of great value since it allows to illustrate in a consistent way the relationship between the selection of executive successors and how it is affected by the different decision-making processes in families, which allows to identify research gaps and make strategic decisions regarding the management of successions in BFs. Furthermore, this research provides a framework for future research in this area.

Intelligence transformation has hugely influenced business operation in many industries and countries, such as in the emerging market. Generative Artificial Intelligence (GAI) adoption by organisations is a significant result of transformation. However, the influence of GAI adoption on small and medium-sized enterprises (SMEs) has been given less attention in business and management studies. In particular, managing the relationship of employees in GAI adoption is a focal point during the transformation from an ethical, responsible and sustainable perspective. Drawing on organisational socialisation and technology adoption theories, this chapter develops a process of socialising newcomers and/or existing employees in the development of GAI adoption in their workflow with identification of challenges and strategies to the adapt to the change. This discussion can help managers and other key persons to effectively manage the relationship and interactions between employees and technology (GAI) in a more ethical, responsible and sustainable manner.

The present research study aims to understand the cause-and-effect reasons behind the job-hopping practices followed by Gen Z employees in the industry 5.0 in India. Further, in the tandem of efforts, the research study has examined the direct and indirect relationship among novice behaviour, social alienation and job-hopping in Gen Z in the information technology sector of Industry 5.0 in India.

The 533 Gen Z or millennial employees were chosen from northern India Industry 5.0 following the non-probability purposive sampling technique. The study follows the quantitative research approach, and the data were collected through a survey questionnaire based on standardized measuring instruments. Further, the gathered data were analysed using the structure equation modelling.

The study’s findings confer the significant direct impact of novice behaviour on job-hopping. While measuring the indirect relationship, the partial mediation effect was noticed in the relationship among novice behaviour, social alienation and job-hopping in the Gen Z employees of Industry 5.0 in India.

The present study will be beneficial to the investors to recognize the job-hopping reasons in Industry 5.0. Further, Gen Z employees and academicians will also receive insight into the cause and effect behind job-hopping. Such will minimize the gap between industry and academia and help Gen Z attain stable employment in Industry 5.0.