Artificial intelligence, and human workers interaction at team level: A conceptual assessment of the challenges, and potential HRM strategies

Purpose – The current paper aims to specifically focus on the challenges that human resource management (HRM) function in contemporary organisations faces due to close interaction between AI (primarily robots) and human workers especially at the team level. It further discusses important potential strategies, which can be useful to overcome these challenges based on a conceptual review of extant research.
Design/methodology/approach – The current paper undertakes a conceptual work where multiple streams of literature are integrated to present a rather holistic yet critical overview of the relationship between AI (particularly robots) and HRM in contemporary organisations.
Findings – We highlight that interaction and collaboration between human workers and robots is visible in a range of industries and organisational functions, where both are working as team members. This gives rise to unique challenges for HRM function in contemporary organisations where they need to address workers’ fear of working with AI, especially in relation to future job loss and difficult dynamics associated with building trust between human workers and AI-enabled robots as team members. Along with these, human workers’ task fulfilment expectations with their AIenabled robot colleagues need to be carefully communicated and managed by HRM staff to maintain the collaborative spirit, as well as future performance evalutations of employees. We found that organisational support mechanisms like facilitating environment, training opportunities, and ensuring a viable technological competence level before organising human workers in teams with robots are important. Finally, we found that one of the toughest challenges for HRM relates to performance evaluation in teams where both humans and AI (including robots) work side by side. We referred to the lack of existing frameworks to guide HRM managers in this concern and stressed the possibility of taking insights from the computer gaming literature, where performance evaluation models have been developed to analyse humans and AI interactions while keeping the context and limitations of both in view.
Originality/value – Our paper is one of the few studies that go beyond a rather general or functional analysis of AI in the HRM context. It specifically focuses on the teamwork dimension, where human workers and AI-powered machines and processes (including robots) work together and offer insights and suggestions for such teams’ smooth functioning.