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1. Introduction
The momentous rise of artificial intelligence (AI) is a global revolution that is expected to persist in the future. Seventy-seven percent of the consumers are knowingly or unknowingly using AI technologies ranging from interactive chatbots and smart wearables to personal digital assistants (Seal, 2019). According to recent projections, the total global revenue for AI software is expected to grow from $9.5 billion in 2019 to as much as $118.6 billion in 2025, a remarkable growth expectation of more than 1,100 percent (Seal, 2019). AI, also termed as machine intelligence, was introduced to develop “thinking machines” that mimic human capabilities and intellectual behavior and are capable of supplanting human intelligence (Jia et al., 2018; Min, 2010). AI has been (and continues to be) promoted as a proficient system that accurately deciphers external data and learns from it to attain explicit objectives through workable modifications to its prior learnings (Kaplan and Haenlein, 2019). Since the late 1970s, AI has demonstrated tremendous potential in improving human decision-making processes and in the ensuing efficiency in various business settings (Jia et al., 2018; Min, 2010; Partridge and Hussain, 1992; Sturman et al., 1996). With AI’s increasing acceptance as a decision-aid tool, it is set to become an integral part of nearly all the functional areas of an organization (Fountaine et al., 2019; Jia et al., 2018; Lawler and Elliot, 1996). Many AI tools (such as genetic algorithms, fuzzy sets and artificial neural networks, to name a few) are now being used in various functional areas of organizations (Arrieta et al., 2020; Holland, 1992; Rajpurohit et al., 2020).
One management area that has begun to leverage AI applications and has presented a diverse set of AI usage implications is Human Resource Management (HRM) (Strohmeier and Piazza, 2015). AI has been successfully applied in various HRM functions such as human resource (HR) performance evaluation (Huang et al., 2006; Moon et al., 2010; Zhang et al., 2012), employee selection (Chien and Chen, 2008; Hooper et al., 1998; Oswald et al., 2020; Shahhosseini and Sebt, 2011), employee turnover (Sexton et al., 2005), prediction of the level of employees’ emotional involvement (Lucia-Casademunt et al., 2013), and employee assignment (Hajiha