Abstract
Research background: This article discusses how artificial intelligence (AI) is affecting workers' personal and professional lives, because of many technological disruptions driven by the recent pandemic that are redefining global labor markets.
Purpose of the article: The objective of this paper is to develop a systematic review of the relevant literature to identify the effects of technological change, especially the adoption of AI in organizations, on employees’ skills (professional dimension) and well-being (personal dimension).
Methods: To implement the research scope, the authors relied on Khan's five-step methodology, which included a PRISMA flowchart with embedded keywords for selecting the appropriate quantitative data for the study. Firstly, 639 scientific papers published between March 2020 to March 2023 (the end of the COVID-19 pandemic according to the WHO) from Scopus and Web of Science (WoS) databases were selected. After applying the relevant procedures and techniques, 103 articles were retained, which focused on the professional dimension, while 35 papers were focused on the personal component.
Findings & value added: Evidence has been presented highlighting the difficulties associated with the ongoing requirement for upskilling or reskilling as an adaptive reaction to technological changes. The efforts to counterbalance the skill mismatch impacted employees' well-being in the challenging pandemic times. Although the emphasis on digital skills is widely accepted, our investigation shows that the topic is still not properly developed. The paper's most significant contributions are found in a thorough analysis of how AI affects workers' skills and well-being, highlighting the most representative aspects researched by academic literature due to the recent paradigm changes generated by the COVID-19 pandemic and continuous technological disruptions.
Publisher
Instytut Badan Gospodarczych / Institute of Economic Research
Subject
Economics, Econometrics and Finance (miscellaneous),Development,History,Business and International Management
Reference157 articles.
1. Abdullah, K. H., & Sofyan, D. (2023). Machine learning in safety and health research: A scientometric analysis. International Journal of Information Science & Management, 21(1), 17–35.
2. Abina, A., Batkovič, T., Cestnik, B., Kikaj, A., Kovačič Lukman, R., Kurbus, M., & Zidanšek, A. (2022). Decision support concept for improvement of sustainability-related competences. Sustainability, 14(14), 8539.
3. Abuselidze, G., & Mamaladze, L. (2021). The impact of artificial intelligence on employment before and during pandemic: A comparative analysis. Journal of Physics: Conference Series, 1840, 012040.
4. Akanksha, J., Arun, J. C., & Arup, V. (2021). Rebooting employees: Upskilling for artificial intelligence in multinational corporations. International Journal of Human Resource Management, 33(6), 1179–1208.
5. Al-Jubari, I., Mosbah, A., & Salem, S. F. (2022). Employee well-being during COVID-19 pandemic: The role of adaptability, work-family conflict, and organizational response. Sage Open, 12(3), 1096142.
Cited by
28 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献