Bots with Feelings: Should AI Agents Express Positive Emotion in Customer Service?
Abstract
The rise of emotional intelligence technology and the recent debate about the possibility of a “sentient” artificial intelligence (AI) urge the need to study the role of emotion during people’s interactions with AIs. In customer service, human employees are increasingly replaced by AI agents, such as chatbots, and often these AI agents are equipped with emotion-expressing capabilities to replicate the positive impact of human-expressed positive emotion. But is it indeed beneficial? This research explores how, when, and why an AI agent’s expression of positive emotion affects customers’ service evaluations. Through controlled experiments in which the subjects interacted with a service agent (AI or human) to resolve a hypothetical service issue, we provide answers to these questions. We show that AI-expressed positive emotion can influence customers affectively (by evoking customers’ positive emotions) and cognitively (by violating customers’ expectations) in opposite directions. Thus, positive emotion expressed by an AI agent (versus a human employee) is less effective in facilitating service evaluations. We further underscore that, depending on customers’ expectations toward their relationship with a service agent, AI-expressed positive emotion may enhance or hurt service evaluations. Overall, our work provides useful guidance on how and when companies can best deploy emotion-expressing AI agents.
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The task of reporting a missing item from an online order and requesting a replacement was chosen because it is one of the most frequent e-commerce customer service requests.
“This task was chosen for our research because it is one of the most frequent e-commerce customer service requests (Han et al., 2023).”
From Explainability in AI: Comparing Human-Like and System-Like Trust Repair Strategies (2026) · cites this paper as Han et al., 2023
The selection of the e-commerce domain for the experiment was driven by the industry's rapid transition toward replacing or supplementing human customer support agents with CAs.
“The selection of this domain for the experiment was driven by the industry's rapid transition toward replacing or supplementing human customer support agents with CAs (Han et al., 2023;Haupt et al., 2023).”
From Explainability in AI: Comparing Human-Like and System-Like Trust Repair Strategies (2026) · cites this paper as Han et al., 2023
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References 74 · Cited by 307
- Authors
- Han, E., Yin, D., & Zhang, H.
- Affiliations
- McGill University (CA)
- University of South Florida (US)
- Georgia Institute of Technology (US)
- Venue
- Information Systems Research
- Published
- 2023-09
- Volume
- 34
- Issue
- 3
- Pages
- 1296-1311
- ISSN
- 1047-7047 (ISSN-L)
- 1526-5536
- OpenAlex
- W4311111985
- Cited by
- 307
- References
- 74
- Citations by year
- 2026: 128 · 2025: 114 · 2024: 51 · 2023: 13 · 2019: 1
- FWCI
- 14.66
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Information Systems Research (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Customer Service Quality and Loyalty
- Social Sciences › Sociology and Political Science › Emotional Labor in Professions
- Keywords
- AI agents, positive emotions, emotional expression, chatbots, customer service, service evaluation, human-AI interaction, customer expectations
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