NEW PERSPECTIVE OF HUMAN RESOURCES MANAGEMENT: EXPLORING THE HUMAN-MACHINE WORKFORCE KNOWLEDGE AS ORGANIZATION'S CAPITAL FOR FUTURE DEVELOPMENT

Authors

  • Biljana Lukić Đorđević Independent Researcher, Serbia

Keywords:

human-machine workforce, knowledge development, workflow reinvention, Human Resources Management, Artificial Intelligence

Abstract

As organization’s function focused, among other activities, on acquisition, development and care of employees, aiming to apply their skills and knowledge to fulfil organization’s business goals, the Human Resources Management function is constantly evolving. With its evolution from previous “personnel management” to “human resources management” and, due to criticism of considering people as other organization’s resources to modern term “people management”, the Human Resources Management function in its essence is dedicated to working with people in an organization. Modern Human Resources Management has passed through significant challenges for the past several years, including the business operations under disruptions and social distancing during the pandemic crisis in 2020, technology development which introduced remote work and now rapid Artificial Intelligence development. The recent usage of the generative Artificial Intelligence, robots and agents by organizations in various industries started as tools for different repetitive tasks, fast data collection and analysis several years ago, and gradually they became agents capable of independent work, be it constant human-like communication with customers regardless of the language or time zone they work in, autonomous transportation vehicles, robots in production and construction processes, Artificial Intelligence agents trained to independently create documents, design, programming and many other works. The widespread application of the Artificial Intelligence caused employees’ concerns for their own future jobs. There are experts and consultants in business development suggesting that, since some of the presently existing jobs will disappear and new ones will emerge in the following years, instead of losing their jobs due to the Artificial Intelligence, the future workforce will consist of people even closely working with Artificial Intelligence hence requiring organizations to reinvent their operational models and workflow in order to embrace the new hybrid human-machine workforce. The purpose and main interest of research and discussion in this paper is to review the related literature and research of experts considering that the next Human Resources Management perspective is relation between humans and the Artificial Intelligence agents as co-workers at the workplace, workflow reinvention, new work roles creation, and all of that impacting mutual knowledge development as organizations’ capital for the future development. The qualitative methodology used in this paper is based on the research of surveys conducted by large business consulting companies, data collecting and analysis, with results and conclusions showing the positive impact of engaging the Artificial Intelligence in organizations from the business results point of view and its usage for employees knowledge development, but also its impact on number of people losing their jobs, and areas where exclusive usage of the Artificial Intelligence has its disadvantages, so the people performing certain works are still indispensable. As recommendation, future research may be conducted to explore the long-term benefits of usage of the Artificial Intelligence agents instead of people and together with them, as well as the risks related to young people having difficulties to be employed at junior positions greatly affected by the Artificial Intelligence and also examination of risks for organizations’ security and data protection.

References

Armstrong, M., & Taylor, S. (2017). Armstrong’s Handbook of Human Resource Management Practice (14th ed.). Kogan Page.

Beauchene, V, Duranton, S., Martin, D., Lyon, V., & Walters, J. (2026, June 03). AI at Work: Strategy Matters More Than Tools. In BCG Global. https://www.bcg.com/publications/2026/ai-at-work-why-strategy-matters-more-than-tools

Bratton, J. (2021). Work and organizational behaviour. Palgrave Macmillan, 387.

Brynjolfsson, E., Chandar, B., & Chen, R. (2025). Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence. Stanford Digital Economy Lab. https://digitaleconomy.stanford.edu/publications/canaries-in-the-coal-mine/

Cavalier, J. (2026). Applying AI in Learning and Development. American Society for Training and Development.

Cress, L. (2026, July 22). OpenAI says its AI went rogue and launched “unprecedented” cyber-attack. https://www.bbc.com/news/articles/c3ek3gvdnj3o

Dhar, J., Ellmer, K., Jameson, P., Martin, D., Lukic, V., & Sivakumar, V. (2026, May 19). Your AI Change Is Actually a People Change. In BCG Global. https://www.bcg.com/publications/2026/why-ai-change-is-actually-a-people-change

Elk, S. (2026, June 26). The Learning System: How Agentic AI Can Compound Its Own Advantage. Forbes. https://www.forbes.com/sites/selk/2026/06/26/the-learning-system-how-agentic-ai-can-compound-its-own-advantage/

Ellyatt, H. (2025). From the “Big Stay” to a “no-hire, no-fire” freeze, labor markets are seeing sizable shifts. In CNBC. https://www.cnbc.com/2025/08/25/the-big-stay-and-a-no-hire-no-fire-freeze-change-to-labor-markets.html

Fergusson, L. (2022). Learning by… Knowledge and skills acquisition through work-based learning and research. Journal of Work-Applied Management, 14(2). https://doi.org/10.1108/jwam-12-2021-0065

Krivkovich, A., Klinger, D., Maor, D., & Guggenberger, P. (2026, February 19). The State of Organizations 2026: Three tectonic forces that are reshaping organizations. In McKinsey & Company. https://www.mckinsey.com/capabilities/people-and-organizational-performance/our-insights/the-state-of-organizations

Marchegiani, L. (2021). Digital Transformation and Knowledge Management. Routledge, 51.

Marchiotto, A. (2024). Adopting AI for Business Transformation. BPB Publications.

McMahon, L. (2026, June 29). Ford rehires human engineers after AI fails to match quality checks. https://www.bbc.com/news/articles/cgrkd41n2v9o

Mitrović, G. (2026, May 21). Sïmon Saneback: „AI ne demokratizuje informacije, već sposobnosti – i to menja sve“. WebMind. https://web-mind.rs/intervjui/simon-saneback-ai-ne-demokratizuje-informacije-vec-sposobnosti-i-to-menja-sve/

Mit Sloan Management Review. (2020). A manager’s guide to the new world of work: the most effective techniques and strategies for managing people, teams, and organizations in these technocentric times. The Mit Press.

Na, S. R. (2024). Application of artificial intelligence in employee training and development. Mathematical Modeling and Algorithm Application, 1(1), 26–28. https://doi.org/10.54097/gg5eemnb

Sukharevsky, A., Kerr, D., Klemens Hjartar, Lari Hämäläinen, Bout, S., & Leo, V. Di. (2025). Seizing the agentic AI advantage. In McKinsey & Company. https://www.mckinsey.com/capabilities/quantumblack/our-insights/seizing-the-agentic-ai-advantage

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Published

2026-08-18

How to Cite

Lukić Đorđević, B. (2026). NEW PERSPECTIVE OF HUMAN RESOURCES MANAGEMENT: EXPLORING THE HUMAN-MACHINE WORKFORCE KNOWLEDGE AS ORGANIZATION’S CAPITAL FOR FUTURE DEVELOPMENT. KNOWLEDGE - International Journal , 77(6), 635–640. Retrieved from https://ojs.ikm.mk/index.php/kij/article/view/8524