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This paper aims to specifically focus on the challenges that human resource management (HRM) leaders and departments in contemporary organisations face due to close interaction between artificial intelligence (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.

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.

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 AI-enabled robot colleagues need to be carefully communicated and managed by HRM staff to maintain the collaborative spirit, as well as future performance evaluations of employees. The authors found that organisational support mechanisms such as 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.

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 focusses on the teamwork dimension, where human workers and AI-powered machines (robots) work together and offer insights and suggestions for such teams' smooth functioning.

Drawing on work from home (WFH), job demand-control and street-level bureaucracy literature streams, this paper specifically focuses on the emerging trend of WFH for public sector employees in a developing country context of Egypt.

The empirical sample comprises focus group discussions with a total of 40 public sector employees in Egypt. Thematic analysis was subsequently used on focus group discussion transcripts to bring out main themes linked to this topic.

Our findings show that employee (marginal discretion power, pharaonism, corruption), citizen (unfamiliarity with digital services) and country (lack of proper info-structure, overstaffing in the public sector)- level challenges hinder and/or slow down the potential for WFH in Egyptian public sector.

A major implication of our paper relates to highlighting the criticality of e-governance and WFH for public sector employees, as well as highlighting multilevel challenges associated with those. At the same time, socio-economic and political consequences of offering such options need to be considered in a country like Egypt where most public organisations are overstaffed, and those employees lack modern day employability skills. Hence, there needs to be an open debate in countries such as Egypt on the consequences of e-governance and WFH and whether it may facilitate delivering citizen services digitally. Also, high power distance culture plays a role in this context, and any change cannot be successful unless that specific aspect is confronted.

This study contributes to the emerging WFH literature by being one of the pioneering studies to offer a multilevel (micro, meso and macro) assessment of this phenomenon in the under-researched fragile developing country’s context.