The effects of artificial intelligence on human resource activities and the roles of the human resource triad: opportunities and challenges.

Introduction: This study analyzes the existing academic literature to identify the effects of artificial intelligence (AI) on human resource (HR) activities, highlighting both opportunities and associated challenges, and on the roles of employees, line managers, and HR professionals, collectively referred to as the HR triad. Methods: We employed the scoping review method to capture and synthesize relevant academic literature in the AI-human resource management (HRM) field, examining 27 years of research (43 peer-reviewed articles are included). Results: Based on the results, we propose an integrative framework that outlines the five primary effects of AI on HR activities: task automation, optimized HR data use, augmentation of human capabilities, work context redesign, and transformation of the social and relational aspects of work. We also detail the opportunities and challenges associated with each of these effects and the changes in the roles of the HR triad. Discussion: This research contributes to the ongoing debate on AI-augmented HRM by discussing the theoretical contributions and managerial implications of our findings, along with avenues for future research. By considering the most recent studies on the topic, this scoping review sheds light on the effects of AI on the roles of the HR triad, enabling these key stakeholders to better prepare for this technological change. The findings can inform future academic research, organizations using or considering the application of AI in HRM, and policymakers. This is particularly timely, given the growing adoption of AI in HRM activities.

One down, fifty to go: managers' perceptions of their workload and how they cope with it to maintain their psychological health.

Background: Like many other countries, healthcare services in Canada face numerous organizational changes with the main objective of doing more with less. The approach taken within different healthcare networks has brought about a reform in healthcare facilities in Quebec, leading to several mergers and eliminating over 1,000 managerial positions. As a result, this has placed a progressively heavier workload on the shoulders of the remaining managers. Research on mental health in the workplace has mainly focused with the workforce and generally neglects managers. However, studies have shown that workload is a risk factor for managers. Therefore, the objectives of our study are to (1) better understand the elements that make up a manager's workload and the factors that influence it and (2) identify the coping strategies used by managers to deal with their workloads. Methods: Employing a qualitative approach, we analyzed 61 semistructured interviews through an abductive method, utilizing diverse frameworks for data analysis. The participants came from the same Quebec healthcare establishment. Results: Our findings align with the notion that workload is a multifaceted phenomenon that warrants a holistic analysis. The workload mapping framework we propose for healthcare network managers enables pinpointing those factors that contribute to the burden of their workload. Ultimately, this workload can detrimentally impact the psychological wellbeing of employees. Conclusion: In conclusion, this study takes a comprehensive look at workload by using a holistic approach, enabling a more comprehensive understanding of this phenomenon. It also allows for the identification of coping strategies used by managers to deal with their workloads. Finally, our results can provide valuable guidance for the interventions aimed at addressing workload issues among healthcare network managers in Quebec by utilizing the specific elements we have identified.