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Conceptualizing the Collaborative Bond Between Employees and Artificial Intelligence in Service
Authors: Khanh B. Q. Le (University of Auckland, New Zealand), Laszlo Sajtos (University of Auckland, New Zealand), Karen V. Fernandez (University of Auckland, New Zealand)
The emergence of artificial intelligence (AI) has started reshaping companies’ service strategy all over the world (Van Doorn et al. 2017; Huang and Rust 2018; Goudey and Bonnin 2016). Higher utilization of machines can help companies increase efficiency (Huang and Rust 2018; Di Pietro, Pantano, and Di Virgilio 2014; Wedel and Kannan 2016; Meuter et al. 2000), which view has underlined the notion of competition between humans (employees) and machines (AI) in service (e.g. Huang and Rust 2018; Van Doorn et al. 2017). However, service industries have long depended on skilled service employees as a point of differentiation (Wünderlich, Wangenheim and Bitner 2013). Hence, shifting the emphasis in service provision from humans to machines is likely to significantly alter customers’ perceptions of their experience with the firm (Chellappa and Sin 2005). In contrast to the ‘competition’ view, this research aims to explore the concept of human-machine bond and relationship (Daugherty and Wilson 2018). This study aims to shed light on the collaborative interaction between employees and computational systems (i.e. AI, robots), which, thus far, has been neglected in the services domain. In particular, this study focuses on employees’ perception towards AI, the types of relationships employees develop with AI, and finally, the performance (efficiency and effectiveness) implication of the employee-machine relationship for the business. Our literature review draws on from studies in both, the service research and computer science domains, and develops a framework for human-AI collaborative service provision. By underlining the collaboration (vs. competition) aspect, this framework can help companies harness the power of human-machine collaboration to develop effective service strategies.