Jan Laurijssen —an HR Evangelist for SD Worx, a seasoned HR consultant and PhD researcher at the University of Antwerp. This blog is produced as a part of the Reshaping Work Fellowship Programme. The opinions and views expressed in this publication are those of the author. They do not purport to reflect the opinions or views of Reshaping Work or organisations that have supported the programme.
Work and the workplace are being transformed by emerging technologies, like artificial intelligence (AI), that give rise to new ways of working. “For better or for worse, AI is already making its way into the workplace” was a clear statement in the OECD’s 2023 Employment Outlook. It’s not surprising that in recent years, the impact of AI on work has attracted a lot of attention, both in the community of researchers as well as practitioners, across disciplines ranging from engineering, law, sociology, economics, and psychology to human resources management (HRM).
Clearly, the impact of AI is making itself felt on the ‘people side of the business’ and it raises the question of whether HR can respond accordingly and promptly to this transformative force. Beyond the familiar range of opportunities to use (generative) AI to automate and optimize HR processes like recruitment or payroll, AI is in fact challenging talent management as we know it. It is algorithmically changing the nature of the employment relationship, while raising the issue of human-centricity in the workplace.
Considering all automation technologies including AI, 27% of workers are in occupations at high-risk of automation, according to the OECD. Yet at the same time, the World Economic Forum argues that throughout the waves of creative destruction over time, the total number of people employed has risen. As of a result of this tension between job creation and destruction many organizations are experiencing a persistent gap between the skills they need and those offered by the labor market. These skills shortages have been exacerbated since COVID-19, reaching record highs.
HRM departments are often at a loss for how to tackle this talent and skills challenge, characterized by uncertainty in both the demand for and supply of talent. At the intersection of planning technology, talent management and people analytics, however, a new HR discipline is emerging: Strategic Workforce Management (SWM). It is a call-to-action for any HR department to reinvent talent and career management, and to acquaint themselves with contemporary tools and evidence-based HR.
AI is not only changing talent management but also transforming the employment relationship and the management of (non-)standard workers. AI-driven decision-making is becoming an element of many employer functions, from recruitment and selection to reward. Simply put, algorithms are supporting evidence for decisions like: to employ or not to employ?
Meijerink adopted the term algorithmic HRM (AHRM) for this, described as: “the use of software algorithms that operate on the basis of digital data to augment HR-related decisions and/or to automate HRM activities”. Such technologies will require essential upskilling for HR staff to apply them most effectively. The term AHRM has three main features: (1) the generation and use of big data; (2) the processing of digital data using software algorithms; and (3) partial or full automation of decision-making in HR. Professionals will need to invest in acquiring an understanding of these algorithmic processes and the associated risks and opportunities. Just because ‘tech can make it happen’ and we are allowed to do something from a legal standpoint, that doesn’t make it a good idea from an ethical point of view. By now, it’s a strategic imperative for HR professionals to scrutinize algorithmic management practices.
Human-centricity, people sustainability and sustainable HRM are emerging concepts in the fields of work, social relations and HRM. Their rise reflects the advent of a new paradigm against the background of twin digital and green transitions, driven by EU reporting requirements on environmental, social and governance (ESG) factors. Ratings on ESG’s provide information about the sustainability performance of a company by assessing its exposure to sustainability risks and/or its impact on people and the environment. Meanwhile, the EU Artificial Intelligence Act, the EU Platform Work Directive and GDPR all contribute the improvement of sustainable and decent work. Not to mention, the Industry 5.0 approach places the wellbeing of the worker at the center of the production process, and uses new technologies to provide prosperity beyond jobs and growth — while respecting the production limits of the planet. All these legislative and regulatory initiatives clearly demand that HR departments pick up to pace of learning and get on board with sustainability.
So, is HRM ready to rise the AI occasion? I’m convinced that many professionals are trying to navigate the AI revolution in HRM to the best of their abilities, but they are having to resort to leading HR models that survived the previous industrial revolution. A mere renaissance of past HR models will, however, fall short against this transformative force. We need nothing less than the reinvention of the HR organizational model if we wish to reconcile artificial and human intelligence in the new world of work.
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References
Cameron, R., Herrmann, H. & Nankervis, A. Mapping the evolution of algorithmic HRM (AHRM): a multidisciplinary synthesis. Humanit Soc Sci Commun 11, 303 (2024).
Dima, J., Gilbert, M. H., Dextras-Gauthier, J., & Giraud, L. (2024). The effects of artificial intelligence on human resource activities and the roles of the human resource triad: opportunities and challenges. Frontiers in Psychology, 15, 1360401.
Du, J. (2024). Unlocking the potential: Literature review on the evolving role of AI in HRM. Frontiers in Management Science, 3(1), 28–33.
Fenech, R., Baguant, P., & Ivanov, D. (2019). The changing role of human resource management in an era of digital transformation. International Journal of Entrepreneurship, 22(2), 166–175.
Fenwick, A., Molnar, G., & Frangos, P. (2024). Revisiting the role of HR in the age of AI: bringing humans and machines closer together in the workplace. Frontiers in Artificial Intelligence, 6, 1272823.
Kluge, A., Wilkens, U., Nitsch, V., & Peifer, C. (2024). Human-centered AI at work: common ground in theories and methods. Frontiers in Artificial Intelligence, 7, 1411795.
Kochan, T. A., & Dyer, L. (1993). Managing transformational change: the role of human resource professionals. International Journal of Human Resource Management, 4(3), 569–590.
Meijerink J, Boons M, Keegan A, Marle J (2021) Algorithmic human resource management: Synthesizing developments and cross-disciplinary insights on digital HRM. Int J Hum Resour Manag 32(12):2545–2562.
OECD (2023), OECD Employment Outlook 2023: Artificial Intelligence and the Labour Market. Paris: OECD Publishing.
Oeij, P.R.A., Lenaerts, K, Dhondt, S., Van Dijk, W., Schartinger, D., Sorko, S.R., Warhurst, C., (2024). A Conceptual Framework for Workforce Skills for Industry 5.0: Implications for Research, Policy and Practice, Journal of Innovation Management, 12(1), 205–233.
Strohmeier, S. (Ed.). (2022). Handbook of research on artificial intelligence in human resource management. Edward Elgar Publishing.
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Reshaping Work Fellowship is supported by Zurich Insurance.
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