[go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

A Critical Review of Artificial Intelligence in People Management

  • Chapter
  • First Online:
HRM 5.0

  • 374 Accesses

Abstract

Artificial Intelligence (AI) seems omnipotent and ubiquitous in the workplace, but managers and employees have mixed views about its merits in practice. In this chapter, the opportunities and constraints of AI-driven management policy and practices are critically discussed, through an in-depth review of both conceptual research and empirical study, drawing on three theoretical perspectives (i.e., job replacement, psychological contract, and demands-resources theories). Following the theories-informed analyses, four meaningful discoveries are revealed. These are: (i) a manager’s experiences, attitude, and understanding of AI are highly influential, which in turn may affect the design and implementation of AI-driven management policies; (ii) the utility of AI-driven management policies does not necessarily guarantee productivity and should not be treated as an elixir to fix poor employee performance; (iii) managers are liable to learn AI and understand its characteristics prior to the implementation of AI-driven management policies; where applicable, a dry-run or pilot practice should be arranged in advance; and (iv) managers should remain cautious of AI’s influence in their managerial practices, as AI has the potential to become a job-demand or job-resource, affecting their employees either psychologically or behaviorally. In conclusion, the current chapter aims to offer new unique insights to AI-driven management literature, hence advancing knowledge in the field of AI policymaking and managerial practices. Limitations and suggestions for future studies are also discussed.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  • Aldosari, S. A. (2020). The future of higher education in the light of artificial intelligence transformations. International Journal of Higher Education, 9(3), 145–151.

    Article  Google Scholar 

  • Ali, M. M., Chang, K., & Vaduva, A. (2023). Does AI bring more benefits or threats to the workplace. Business Time, 30(Winter), 66–67.

    Google Scholar 

  • Bakker, A. B., & Demerouti, E. (2007). The job demands-resources model: State of the art. Journal of Managerial Psychology, 22(3), 309–328.

    Article  Google Scholar 

  • Behl, A., Pereira, V., Varma, A., & Tarba, S. (2022). Guest editors’ overview essay: Exploring the dark side of electronic-human resource management: Towards a new PROMPT model. International Journal of Manpower, 43(1), 1–11.

    Article  Google Scholar 

  • Brown, J., Ling, T., & Gurdeniz, E. (2017). Managing next generation of AI in banking. Oliver Wyman - Marsh & McLenna.

    Google Scholar 

  • Brunette, E. S., Flemmer, R., & Flemmer, C. (2009). A review of artificial intelligence. The 4th International Conference on Autonomous Robots and Agents, Wellington, New Zealand, February 10–12, 2009. Web-link. (Accessed: 13 August 2023).

    Google Scholar 

  • Celse, J., & Chang, K. (2023). Athletic participation brings more job opportunities, truth or false? International Journal of Human Resource Management. Ahead-of-print. Web-link.

    Google Scholar 

  • Celse, J., Chang, K., Max, S., & Quinton, S. (2016). The reduction of employee lying behavior: Inspiration from a study of envy in part-time employees. Journal of Strategy and Management, 9(2), 118–137.

    Article  Google Scholar 

  • Chang, K. S. (2011). Membership stability and performance: A study of baseball clubs and laboratory groups. International Journal of Human Resource Management, 22(2), 457–480.

    Article  Google Scholar 

  • Chang, K. (2019). Has the era of artificial intelligence (AI)-driven management arrived yet: The case of Fudan University Student Canteen. (In Chinese). Fudan Development Institute (FDDI). Fudan University.

    Google Scholar 

  • Chang, K. (2020). Artificial Intelligence in personnel management: The development of APM model. The Bottom Line, 33(4), 377–388.

    Article  Google Scholar 

  • Chang, K. (2023). Does the future workplace really entail more technology and fewer humans? People Management, 1809818. Web-link. (Accessed: 1 October 2023).

    Google Scholar 

  • Chang, K., & Cheng, K.T. (2023). AI-driven employee recruitment: Insights from a consultancy project. Under reviewed by Journal of Strategy and Management (R1).

    Google Scholar 

  • Cheng, K. T., Chang, K., & Tai, H. W. (2022). AI boosts performance but affects employees’ emotion. Information Resources Management Journal, 35(1), 1–18.

    Article  Google Scholar 

  • Chatterjee, S., Chaudhuri, R., & Vrontis, D. (2022). AI and digitalization in relationship management: Impact of adopting AI-embedded CRM system. Journal of Business Research, 150(11), 437–450.

    Article  Google Scholar 

  • Clarivate. (2023). Web of science platform: WoS and summary of coverage. Web-link. (Accessed: 7 August 2023).

    Google Scholar 

  • Czarnowski, I., & Pszxzolkowski, P. (2020). A novel framework for decision support system in Human Resource Management. Procedia Computer Science, 176, 1548–1556.

    Article  Google Scholar 

  • Ernst & Young. (2018). The new age: Artificial intelligence for human resource opportunities and functions. Ernst & Young LLP.

    Google Scholar 

  • Farndale, E., McDonnell, A., Scholarios, D., & Wilkinson, A. (2019). Human resource management journal: A look to the past, present, and future of the journal and HRM scholarship. Human Resource Management Journal, 30(1), 1–12.

    Article  Google Scholar 

  • Froese, F. J. (2020). Companies’ adoption of artificial intelligence (AI) in employee recruitment. Georg-August University.

    Google Scholar 

  • George, C. (2010). Psychological contract: Managing and developing professional groups. Open University Press.

    Google Scholar 

  • Goleman, D. (1998). Working with emotional intelligence. Bantam Books.

    Google Scholar 

  • Grace, K., Salvatier, J., Dafoe, A., Zhang, B., & Evans, O. (2018). When will AI exceed human performance? Evidence from AI experts. Oxford University.

    Book  Google Scholar 

  • Henkel, A. P., Bromuri, S., Iren, D., & Urovi, V. (2020). Half human, half machine—Augmenting service employees with AI for interpersonal emotion regulation. Journal of Service Management, 31(2), 247–265.

    Article  Google Scholar 

  • Huang, M. H., & Rust, R. T. (2018). AI in service. Journal of Service Research, 21(2), 155–172.

    Article  Google Scholar 

  • Itegboje, J., & Chang, K. (2021). Agency workers and their equivocal roles: Wandering employees. Labor History, 62(2), 115–133.

    Article  Google Scholar 

  • Jaiswal, A., & Arun, C. J. (2021). Potential of artificial intelligence for transformation of the education system in India. International Journal of Education and Development Using Information and Communication Technology (IJEDICT), 17(1), 142–158.

    Google Scholar 

  • Jaiswal, A., Arun, C. J., & Varma, A. (2022). Rebooting employees: Upskilling for artificial intelligence in multinational corporations. International Journal of Human Resource Management, 33(6), 1179–1208.

    Article  Google Scholar 

  • Jeske, D., & Calvard, T. (2020). Big data: Lessons for employers and employees. Employee Relations, 42(1), 248–261.

    Article  Google Scholar 

  • Johnson, B. A. M., Coggburn, J. D., & Llorens, J. J. (2022). Artificial intelligence and public HRM: Questions for research and practice. Public Personnel Management, 51(4), 538–562.

    Article  Google Scholar 

  • Kaban, A. (2023). An examination of the studies on learning analytics: A bibliometric mapping analysis. International Journal of Technology in Education and Science, 7(2), 211–229.

    Article  Google Scholar 

  • Kaminski, M. E. (2023). Regulating the risks of AI. Boston University Law Review, 103(5), 1347–1411.

    Google Scholar 

  • Kara, H. (2018). Research ethics in the real world: Euro-Western and Indigenous perspectives. Policy Press. ISBN: 978-1447344759.

    Google Scholar 

  • Köllen, T., Kakkuri-Knuuttila, M.-L., & Bendl, R. (2018). An indisputable “holy trinity”? On the moral value of equality, diversity, and inclusion. Equality, Diversity and Inclusion, 37(5), 438–449.

    Article  Google Scholar 

  • Kong, H., Yuan, Y., Baruch, Y., Bu, N., Jiang, X., & Wang, K. (2021). Influences of artificial intelligence (AI) awareness on career competency and job burnout. International Journal of Contemporary Hospitality Management, 33(2), 717–734.

    Article  Google Scholar 

  • Langer, M., Konig, C. J., Back, C., & Hemsing, V. (2023). Trust in artificial intelligence: Comparing trust processes between human and automated trustees in light of unfair bias. Journal of Business and Psychology, 38(2023), 493–508.

    Article  Google Scholar 

  • Lazarus, R. S. (1991). Emotion and adaptation. New York: Oxford University Press. ISBN: 978-0195092660.

    Google Scholar 

  • Lima, Y., Strauch, J. C. M., Esteves, M. G. P., de Souza, J. M., Chaves, M. B., & Gomes, D. T. (2021). Exploring the future impact of automation in Brazil. Employee Relations, 43(5), 1052–1066.

    Article  Google Scholar 

  • Lucena, F. J. H., Aznar-Diaz, I., Reche, M. P. C., & Romero-Rodriguez, J. M. R. (2019). Artificial intelligence in higher education: A bibliometric study on its impact in the scientific literature. Education Sciences, 9(1), 51–70.

    Article  Google Scholar 

  • Ma, Y., & Siau, K. L. (2018). Artificial Intelligence Impacts on Higher Education. MWAIS 2018 Proceedings. 42. Web-link. (Accessed: 1 October 2023).

    Google Scholar 

  • Malik, A., Budhwar, P., Srikanth, N. R., & Varma, A. (2019). May the bots be with you! Opportunities and challenges of artificial intelligence for rethinking human resource management practices. Paper Accepted for presentation at the Annual Conference, British Academy of Management 2019.

    Google Scholar 

  • Marr, B. (2023). Why every company needs a chief AI officer. Forbes: Innovation & Enterprise Tech. Forbes Media. Web-link.

    Google Scholar 

  • Mullins, L. J. (2016). Management and organizational behavior (11th ed.). Pearson.

    Google Scholar 

  • Niederman, F. (2021). Project management: Openings for disruption from AI and advanced analytics. Information Technology and People, 34(6), 1570–1599.

    Article  Google Scholar 

  • Pan, Y., Froese, F., Liu, N., et al. (2021). The adoption of artificial intelligence in employee recruitment: The influence of contextual factors. International Journal of Human Resource Management, 33(6), 1125–1147.

    Article  Google Scholar 

  • Ortony, A., Clore, G. L., & Collins, A. (1988). The cognitive structure of emotions. Cambridge University Press.

    Book  Google Scholar 

  • Qi, L., & Yao, K. (2021). Artificial intelligence enterprise HRM system based on FPGA high performance computer hardware. Microprocessors and Microsystems, 82(4), 103876.

    Article  Google Scholar 

  • Rot, M. A. H., Moskowitz, D. S., Pinard, G., & Young, S. N. (2006). Social behavior and mood in everyday life: Effects of tryptophan in quarrelsome individuals. Journal of Psychiatry Neuroscience, 31(4), 253–262.

    Google Scholar 

  • Rousseau, D. M. (1989). Psychological and implied contracts in organizations. Employee Responsibilities and Rights Journal, 2(2), 121–139.

    Article  Google Scholar 

  • Russell, S., & Norvig, P. (2009). Artificial intelligence: A modern approach (3rd ed.). Prentice Hall Press.

    Google Scholar 

  • SAS. (2018). Artificial Intelligence: What it is and why it matters. SAS. Web-link. (Accessed: 14 October 2023).

    Google Scholar 

  • Silverman, D. (2019). Interpreting qualitative data. London: Sage. ISBN: 978-1526467249.

    Google Scholar 

  • Sivathanu, B., & Pillai, R. (2018). Smart HR 4.0—how industry 4.0 is disrupting HR. Human Resource Management International Digest, 26(4), 7–11.

    Google Scholar 

  • Smith, A., & Anderson, J. (2014). AI, robotics, and the future of jobs. Pew Research Center.

    Google Scholar 

  • Votto, A. M., Valecha, R., Najafirad, P., & Rao, H. R. (2021). Artificial intelligence in tactical HRM: A systematic literature review. International Journal of Information Management and Data Insights, 1(2), 100047.

    Google Scholar 

  • Wang, A. M., Wang, T. L., & Huang, C. J. (2017). Big Data on human resource management: Model, theory and application. Tsinghua University Press.

    Google Scholar 

  • Wisskirchen, G., Biacabe, B. T., Bormann, U., Muntz, A., et al. (2017). Artificial intelligence and robotics and their impact on the workplace. IBA Global Employment Institute.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University of East London, London, England

    Kirk Chang & Stephanie Sandland

  2. National Tsinghua University, Hsinchu, Taiwan

    Kuotai Cheng

Authors
  1. Kirk Chang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kuotai Cheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Stephanie Sandland
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kirk Chang .

Editor information

Editors and Affiliations

  1. University of East London, London, UK

    Toyin Ajibade Adisa

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Chang, K., Cheng, K., Sandland, S. (2024). A Critical Review of Artificial Intelligence in People Management. In: Adisa, T.A. (eds) HRM 5.0. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-031-58912-6_3

Download citation

Publish with us

Policies and ethics