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Bots with Feelings: Should AI Agents Express Positive Emotion in Customer Service?

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  • Elizabeth Han

    (Desautels Faculty of Management, McGill University, Montréal, Quebec H3A 1G5, Canada)

  • Dezhi Yin

    (Muma College of Business, University of South Florida, Tampa, Florida 33620)

  • Han Zhang

    (Scheller College of Business, Georgia Institute of Technology, Atlanta, Georgia 30308)

Abstract

Customer service employees are generally advised to express positive emotion during their interactions with customers. The rise and maturity of artificial intelligence (AI)–powered conversational agents, also known as chatbots, beg the question: should AI agents be equipped with the ability to express positive emotion during customer service interactions? This research explores how, when, and why an AI agent’s expression of positive emotion affects customers’ service evaluations. We argue that AI-expressed positive emotion can influence customers via dual pathways: an affective pathway of emotional contagion and a cognitive pathway of expectation–disconfirmation. We propose that positive emotion expressed by an AI agent (versus a human employee) is less effective in facilitating service evaluations because of a heightened level of expectation–disconfirmation. We further introduce a novel individual difference variable, customers’ relationship norm orientation, which affects their expectations toward the AI agent and moderates the cognitive pathway. Results from three laboratory experiments substantiate our claims. By revealing a distinctive impact of positive emotion expressed by an AI agent compared with a human employee, these findings deepen our understanding of customers’ reactions to emotional AIs, and they offer valuable insights for the deployment of AIs in customer service.

Suggested Citation

  • Elizabeth Han & Dezhi Yin & Han Zhang, 2023. "Bots with Feelings: Should AI Agents Express Positive Emotion in Customer Service?," Information Systems Research, INFORMS, vol. 34(3), pages 1296-1311, September.
    • Handle: RePEc:inm:orisre:v:34:y:2023:i:3:p:1296-1311
    DOI: 10.1287/isre.2022.1179
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    References listed on IDEAS

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