Engaged to a Robot? The Role of AI in Service

By Ming-Hui Huang, Roland T. Rust. Journal of services research, 2020

873 citations recorded by the source corpus.

This article develops a strategic framework for using artificial intelligence (AI) to engage customers for different service benefits. This framework lays out guidelines of how to use different AIs to engage customers based on considerations of nature of service task, service offering, service strategy, and service process. AI develops from mechanical, to thinking, and to feeling. As AI advances to a higher intelligence level, more human service employees and human intelligence (HI) at the intelligence levels lower than that level should be used less. Thus, at the current level of AI development, mechanical service should be performed mostly by mechanical AI, thinking service by both thinking AI and HI, and feeling service mostly by HI. Mechanical AI should be used for standardization when service is routine and transactional, for cost leadership, and mostly at the service delivery stage. Thinking AI should be used for personalization when service is data-rich and utilitarian, for quality leadership, and mostly at the service creation stage. Feeling AI should be used for relationalization when service is relational and high touch, for relationship leadership, and mostly at the service interaction stage. We illustrate various AI applications for the three major AI benefits, providing managerial guidelines for service providers to leverage the advantages of AI as well as future research implications for service researchers to investigate AI in service from modeling, consumer, and policy perspectives.

Subfields: Artificial Intelligence, Marketing

View Paper: https://www.semanticscholar.org/paper/420e771cfbd7d31aa33f29a5ba1c5540c0f5f7fd

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Marketing

Citations in the corpus

Preference for robot service or human service in hotels? Impacts of the COVID-19 pandemic (2020, neutral): “activated by human staff’s operation according to the order in a queue (Chiang and Trimi, 2020; Huang and Rust, 2020).”
A strategic framework for artificial intelligence in marketing (2020, methodology): “Huang and Rust (2020) show that feeling AI can be used to engage customers in service interaction.”
Machine learning and AI in marketing – Connecting computing power to human insights (2020, neutral): “AI has been and will continue to dramatically transform marketing (Huang & Rust, 2018; Huang & Rust, 2020; Rust, 2020).”