Artificial Intelligence in Service

Abstract

Artificial intelligence (AI) is increasingly reshaping service by performing various tasks, constituting a major source of innovation, yet threatening human jobs. We develop a theory of AI job replacement to address this double-edged impact. The theory specifies four intelligences required for service tasks—mechanical, analytical, intuitive, and empathetic—and lays out the way firms should decide between humans and machines for accomplishing those tasks. AI is developing in a predictable order, with mechanical mostly preceding analytical, analytical mostly preceding intuitive, and intuitive mostly preceding empathetic intelligence. The theory asserts that AI job replacement occurs fundamentally at the task level, rather than the job level, and for “lower” (easier for AI) intelligence tasks first. AI first replaces some of a service job’s tasks, a transition stage seen as augmentation, and then progresses to replace human labor entirely when it has the ability to take over all of a job’s tasks. The progression of AI task replacement from lower to higher intelligences results in predictable shifts over time in the relative importance of the intelligences for service employees. An important implication from our theory is that analytical skills will become less important, as AI takes over more analytical tasks, giving the “softer” intuitive and empathetic skills even more importance for service employees. Eventually, AI will be capable of performing even the intuitive and empathetic tasks, which enables innovative ways of human–machine integration for providing service but also results in a fundamental threat for human employment.

Designing conceptual articles: four approaches

“…A model paper typically begins from a focal phenomenon or construct that warrants further explanation. For example, Huang and Rust (2018) sought to explain the process and mechanism by which artificial intelligence (AI) will replace humans in service jobs. They employed literature that tackles key variables associated with the target phenomenon: service research illuminates the focal phenomenon, technologyenabled services, and research across multiple disciplines discusses the likely impact of AI on human labor.…”

“…By synthesizing this literature pool, they identified four types of intelligence and then built a theory that could predict the impact of AI on human service labor. This involved a particular kind of formal reasoning, supported by research from multiple disciplines and real-world applications (Huang and Rust 2018). In other words, the authors use method theories and deductive reasoning to explain relationships between key variables, facilitated by theories in use (MacInnis 2011).…”

An Experimental Case Study on Edge Computing Based Cyber-Physical Digital Service Provisioning with Mobile Robotics

“…Whereas the existing studies on role of AI and robotics in service [8], [9] have focused on conceptual level exploration, this work contributes an experimental case study with a trial system in a laboratory setting revealing new insights on challenges related to design and provisioning of cyber-physical digital service with mobile robot and AI components.…”

“…However, the rapid progress in Internet-of-Things (IoT) [3], Cyber-Physical Systems (CPS) [4], automation [5], robotics [6] and Artificial Intelligence (AI) [7] is enabling increasingly complex social and physical tasks to be automated. As presented in [8], the progress in these technologies is reshaping also service provisioning by changing work and tasks allocation in service between human labor and advanced technical systems. These systems are embodied in many different forms and have been collectively defined as service robots in [9].…”

Emotional intelligence or artificial intelligence– an employee perspective

“…In general, AI is used to automate mundane and low-level tasks. Based on the four taxonomies of analytical intelligence (mechanical, analytical, intuitive, and empathetic intelligence) proposed by Huang and Rust (2018), Wirtz et al (2018) propose an intuitive understanding of service delivery based on the complexity of emotional and cognitive tasks (see Figure 2). The authors indicate that complex emotional-social task will tend to be performed by humans, and complex cognitive-analytical task will tend to be executed by robots.…”