Challenges of talent retention and the role of robotic process automation in the covid-19 era: an analysis of organizational strategies and efficiency enhancement
DOI:
https://doi.org/10.37497/rev.artif.intell.educ.v4i00.9Keywords:
Talent management, Post- Pandemic era, Artificial intelligence (AI), Machine Learning (ML), Virtual-world, HR Strategy, Robotic Process AutomationAbstract
Objective: The objective of this paper is to investigate the challenges of talent retention within organizations during the COVID-19 pandemic, propose effective solutions, and highlight the significance of Robotic Process Automation (RPA) in addressing the issue of Non-Utilized Talent, a key facet of waste within the Lean framework.
Method: To achieve this objective, an in-depth analysis of the contemporary organizational landscape was conducted. This analysis included the examination of trends in talent management, the impact of global integration on hiring and development practices, and the role of technology in reshaping human connections. Furthermore, a study of cultural shifts and technological adaptation during the pandemic was undertaken to provide contextual insights.
Results: The investigation revealed that as robots increasingly supplant human labor, organizations are compelled to carefully select and nurture their human resources. Amid the COVID-19 pandemic, unique challenges emerged, influencing talent retention strategies. The paper identifies these challenges and presents a range of innovative solutions tailored to the current circumstances. Moreover, the integration of Robotic Process Automation (RPA) was found to play a crucial role in optimizing resource allocation and mitigating Non-Utilized Talent, thereby fostering operational efficiency.
Conclusions: In light of the findings, this paper underscores the indispensability of strategic talent retention in the face of evolving work dynamics. The interplay of technology and humanism in the virtual realm emerged as a driving force in fostering genuine connections, both within and outside organizational boundaries. By embracing tailored solutions and harnessing the potential of RPA, organizations can navigate the complex landscape of talent retention and resource optimization. This study contributes to the discourse on contemporary talent management, offering insights that can guide organizations toward resilience, efficiency, and success in an era of profound transformation.
References
Brunila, A., & Baedecke Yllner, E. (2013). Talent Management: Retaining and managing technical specialists in a technical career. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva123183.
Claus, L. (2019). HR disruption—Time already to reinvent talent management. BRQ Business Research Quarterly, 22(3), 207-215. DOI: https://doi.org/10.1016/j.brq.2019.04.002
Frankiewicz, B., & Chamorro-Premuzic, T. (2020). The post-pandemic rules of talent management. Harvard Business Review, 1-6.
Gowda, K. (2023). Artificial Intelligence in the Modern Economy: Transformations, Applications, and Future Prospects. Review of Artificial Intelligence in Education, 4(00), e08. Retrieved from https://educationai-review.org/revista/article/view/8 DOI: https://doi.org/10.37497/rev.artif.intell.educ.v4i00.8
Gradim, B., & Teixeira, L. (2022). Robotic Process Automation as an enabler of Industry 4.0 to eliminate the eighth waste: a study on better usage of human talent. Procedia Computer Science, 204, 643-651. DOI: https://doi.org/10.1016/j.procs.2022.08.078
Huang, G.Z.D., Roy, M.H., Ahmed, Z.U., Heng, J.S.T. and Lim, J.H.M. (2002),“Benchmarking the human capital strategies of MNCs in Singapore”, Benchmarking: An International Journal, Vol. 9 No. 4, pp. 357-373. DOI: https://doi.org/10.1108/14635770210442699
H. Uygun And R. Gujrati, "Role of Artificial Intelligence & Machine Learning in Social Media," International Journal of Mechanical Engineering , vol.7, no.5, pp.494-498, 2022
Joerres, J., 2016. Globalization, robots, and the future of work: an interview with Jeffrey Joerres. Harvard Bus. Rev. 94 (10), 74---79.
Kristof‐Brown, A. L., Zimmerman, R. D., & Johnson, E. C. (2005). Consequences OF INDIVIDUALS'FIT at work: A meta‐analysis OF person–job, person–organization, person– group, and person–supervisor fit. Personnel psychology, 58(2), 281-342. DOI: https://doi.org/10.1111/j.1744-6570.2005.00672.x
Panova, E. A., Oparina, N. N., & Bondareva, L. V. (2022). Talent Management: Tasks and Challenges for a Digital Tomorrow. In Proceedings of the International Scientific Conference “Smart Nations: Global Trends In The Digital Economy” (pp. 288-294). Springer, Cham. DOI: https://doi.org/10.1007/978-3-030-94870-2_37
Pillai, Rajasshrie, and Brijesh Sivathanu. 2020. “Adoption of Artificial Intelligence (AI) for Talent Acquisition in IT/ITeS Organizations.” Benchmarking: An International Journal 27 (9): 2599–2629. DOI: https://doi.org/10.1108/BIJ-04-2020-0186
Tambuskar, S. (2022). Challenges and Benefits of 7 ways Artificial Intelligence in Education Sector. Review of Artificial Intelligence in Education, 3(00), e03. https://doi.org/10.37497/rev.artif.intell.education.v3i00.3 DOI: https://doi.org/10.37497/rev.artif.intell.education.v3i00.3
Translated by Content Engine, L. L. C. (2022, Oct 21). Workplace trends: 4 challenges for talent management in 2023. CE Noticias Financieras Retrieved from https://www.proquest.com/wire-feeds/workplace-trends-4-challenges-talent- management/docview/2727434621/se-2
Uygun, H. and Gujrati, R. (2020) ‘Digital innovation: changing the face of business’, Int. J. Forensic Engineering, Vol. 4, No. 4, pp.332–342. DOI: https://doi.org/10.1504/IJFE.2020.115036
Wadhwa, S., & Wadhwa, K. (2022). Fitting in organizations: is it crucial for employee management? Academy of Marketing Studies Journal, 26(2), 1-4.
Wadhwa, S., Gujrati, R., & Uygun, H. (2022). Talent Management amidst the Covid-19 Pandemic with the Role of AI in the Health Industry. International Management Review, 18.
Wiradendi Wolor, C. (2020). Implementation talent management to improve organization’s performance in Indonesia to fight industrial revolution 4.0. International journal of scientific & technology research.
Zhang, C. (2022). Current Status and Outlook of Higher Education Digital Transformation in China. Review of Artificial Intelligence in Education, 3(00), e02. https://doi.org/10.37497/rev.artif.intell.education.v3i00.2 DOI: https://doi.org/10.37497/rev.artif.intell.education.v3i00.2
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