A General Survey of the Use Cases of Artificial Intelligence in Human Resource
DOI:
https://doi.org/10.54691/qpm14j29Keywords:
Human Resources Management; Artificial Intelligence; Human Resource Life Cycle; Scoping Review.Abstract
Background: such a thorough understanding of this study could best be achieved through conducting in-depth case studies on organizations that have successfully implemented AI in their HR functions, exploring the benefits, challenges, and impact on their workforce, organization, and even the whole of society and a systematic review of existing literature on AI in HR, synthesizing the results of multiple studies to conclude the overall effectiveness, benefits, and challenges associated with AI applications in HR. This study aims to bring out a comprehensive panorama of AI applications in the six sectors of HRM and the impacts of AI implementation in HR on the transformation of business HR practices and its role transformation due to the advent of AI, as well as to promote technological change and ethical policy norms, and legal improvements in this area. Method: We have selected the relevant literature through a scoping study, and we have categorized it according to the six components of the Human Resource Life Cycle. Conclusion: The literature already covers all six of the human resource life cycle's elements as well as its implications for technology and ethical issues. Future studies may concentrate on how AI affects relationships between dimensions and how it affects results that are particular to human resources. Although AI should still be seen as a solution to many of the problems that face human resources management in businesses, practitioners must acknowledge the limits associated with the implementation of AI in HRM.
Downloads
References
[1] Johnson, P., HRM in changing organizational contexts, in Human resource management : a critical approach, G.C. David and G. Wood, Editors. 2009, Taylor & Francis: London ; New York. p. 19-37.
[2] Taylor, F.W., The principles of scientific management. 1911, New York, London,: Harper & Brothers. 2 p. l., 7 -77 p.
[3] Ahammad, T., Personnel Management to Human Resource Management (HRM): How HRM Functions? Journal of modern accounting and auditing, 2017. 13.
[4] Kaufman, B.E., The Development of HRM in Historical and International Perspective, in The Oxford Handbook of Human Resource Management, P. Boxall, J. Purcell, and P.M. Wright, Editors. 2008, Oxford University Press. p. 19-47.
[5] Wright, P.M. and G.C. McMahan, Theoretical Perspectives for Strategic Human Resource Management. Journal of Management, 1992. 18(2): p. 295-320.
[6] Gurlek, M., Tech Development through HRM: Driving Innovation with Knowledge-Based Cultures. 1 ed. 2020: Bingley: Emerald Publishing Limited.
[7] McCarthy, J., et al., A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence, August 31, 1955. The AI Magazine, 2006. 27(4): p. 12-14.
[8] Gélinas, D., A. Sadreddin, and R. Vahidov, Artificial Intelligence in Human Resources Management: A Review and Research Agenda. Pacific Asia Journal of the Association for Information Systems, 2022. 14(6): p. 1-42.
[9] Ekka, S., HR ANALYTICS: WHY IT MATTERS. Journal of Contemporary Issues in Business and Government, 2021.
[10] Tambe, P., P. Cappelli, and V. Yakubovich, Artificial Intelligence in Human Resources Management: Challenges and a Path Forward. California Management Review, 2019. 61(4): p. 15-42.
[11] Ashish, M., P. Vijay, and B. Pawan, HRM in the global information technology (IT) industry: Towards multivergent configurations in strategic business partnerships. Human Resource Management Review, 2021. 31(3): p. 100743.
[12] Wheeler, A. and M. Buckley, The Current State of HRM with Automation, Artificial Intelligence, and Machine Learning. 2021. 45-67.
[13] Lengnick-Hall, M.L. and S. Moritz, The impact of e-HR on the human resource management function. Journal of Labor Research, 2003. 24(3): p. 365-379.
[14] Bhave, D.P., L.H. Teo, and R.S. Dalal, Privacy at Work: A Review and a Research Agenda for a Contested Terrain. Journal of Management, 2020. 46(1): p. 127-164.
[15] Paré, G., et al., Synthesizing information systems knowledge: A typology of literature reviews. Information & Management, 2015. 52(2): p. 183-199.
[16] Bulla, D.N. and P.M.D. Scott. Manpower Requirements Forecasting: A Case Example. 1987.
[17] Phillips-Wren, G., D. Power, and M. Mora, Cognitive bias, decision styles, and risk attitudes in decision making and DSS. Journal of Decision Systems, 2019. 28: p. 63-66.
[18] Stoilkovska, A., J. Ilieva, and S. Gjakovski, EQUAL EMPLOYMENT OPPORTUNITIES IN THE RECRUITMENT AND SELECTION PROCESS OF HUMAN RESOURCES. UTMS Journal of Economics, 2015. 6: p. 281-292.
[19] Pandey, S. and P. Khaskel, Application of AI in Human Resource Management and Gen Y’s Reaction. International Journal of Recent Technology and Engineering (IJRTE), 2019. 8: p. 10325-10331.
[20] Angrave, D., et al., HR and analytics: why HR is set to fail the big data challenge. Human Resource Management Journal, 2016. 26: p. 1-11.
[21] Kraiger, K., Benefits of Training and Development for Individuals and Teams, Organizations, and Society. Annual review of psychology, 2008. 60: p. 451-74.
[22] Vedapradha, R., H. Ravi, and S. Rajan, Artificial Intelligence: A Technological Prototype in Recruitment. Journal of Service Science and Management, 2019. 12: p. 382-390.
[23] Daugherty, P., H. Wilson, and R. Chowdhury, Using Artificial Intelligence to Promote Diversity. 2020. p. 15-22.
[24] VanHaitsma, T.A., et al., Mental Training: Magic Or Physiologic Reality - The Role Of Mental Training In Improving Performance: 762. Medicine and Science in Sports and Exercise, 2023. 55(9S): p. 264-264.
[25] Cappelli, P., P. Tambe, and V. Yakubovich, Artificial Intelligence in Human Resources Management: Challenges and a Path Forward. SSRN Electronic Journal, 2018.
[26] Jia, Q., et al., A conceptual artificial intelligence application framework in human resource management. 2018.
[27] Ågerfalk, P.J., K. Axelsson, and M. Bergquist, Addressing climate change through stakeholder-centric information systems research: A Scandinavian approach for the masses. International Journal of Information Management, 2022. 63: p. 102447.
[28] Mooney, J.G., V. Gurbaxani, and K.L. Kraemer, A process oriented framework for assessing the business value of information technology. SIGMIS Database, 1996. 27(2): p. 68–81.
[29] Kim, G., et al., IT Capabilities, Process-Oriented Dynamic Capabilities, and Firm Financial Performance. J. AIS, 2011. 12.
[30] Abijith, A. and S. Fosso Wamba, Business Value of RFID-Enabled Healthcare Transformation Projects. Business Process Management Journal, 2012. 19.
[31] Guenole, N. and S. Feinzig, The business case for AI in HR: With insights and tips on getting started. IBM Publishing, 2018.
[32] Nam, C.W. World economic outlook for 2020 and 2021. in CESifo Forum. 2020. Institut für Wirtschaftsforschung (Ifo).
[33] Meskó, B., G. Hetényi, and Z. Győrffy, Will artificial intelligence solve the human resource crisis in healthcare? BMC Health Serv Res, 2018. 18(1): p. 545.
[34] Chamorro-Premuzic, T., Attractive people get unfair advantages at work. AI can help. Harvard Business Review, 2019.
[35] Murgai, A., Role of Artificial Intelligence in Transforming Human Resource Management. International Journal of Trend in Scientific Research and Development, 2018. Volume-2: p. 877-881.
[36] Wamba, S.F., et al., Big data analytics and firm performance: Effects of dynamic capabilities. Journal of Business Research, 2017. 70: p. 356-365.
[37] Ross, J., C. Beath, and D. Goodhue, Develop Long-Term Competitiveness Through IT Assets. Sloan Management Review, 1998. 38.
[38] Cappelli, P. and A. Tavis, The performance management revolution. Harvard Business Review, 2016. 94: p. 58-67.
[39] Xu, W. and F. Ouyang, The application of AI technologies in STEM education: a systematic review from 2011 to 2021. International Journal of STEM Education, 2022. 9.
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Scientific Journal of Economics and Management Research
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
How to Cite
