AI customer service: Task complexity, problem-solving ability, and usage intention

• Published in: Australasian marketing journal Vol. 28; no. 4; pp. 189 - 199
• Main Authors: Xu, Yingzi, Shieh, Chih-Hui, van Esch, Patrick, Ling, I-Ling
• Format: Journal Article
• Language: English
• Published: London, England Elsevier Ltd 01.11.2020; SAGE Publications
• Subjects: AI customer service; AI definition; Problem-solving ability; Task complexity; Usage intention; Problem-solving ability; Usage intention; Task complexity; AI customer service; AI definition
• ISSN: 1441-3582; 1839-3349
• DOI: 10.1016/j.ausmj.2020.03.005

•For low-complexity tasks, consumers considered the problem-solving ability of AI to be greater than that of human customer service and were more likely to use AI.•For high-complexity tasks, consumers viewed human customer service as superior and were more likely to use it than AI.•Perceived problem-solving ability mediated the effects of customers’ service usage intentions (AI or Human service) with task complexity serving as a boundary condition.•We provide a definition of artificial intelligence (AI) in a customer service context. Artificial intelligence (AI) in the context of customer service, we define as a technology-enabled system for evaluating real-time service scenarios using data collected from digital and/or physical sources in order to provide personalised recommendations, alternatives, and solutions to customers’ enquiries or problems, even very complex ones. We examined, in a banking services context, whether consumers preferred AI or Human online customer service applications using an experimental design across three field-based experiments. The results show that, in the case of low-complexity tasks, consumers considered the problem-solving ability of AI to be greater than that of human customer service and were more likely to use AI while, conversely, for high-complexity tasks, they viewed human customer service as superior and were more likely to use it than AI. Moreover, we found that perceived problem-solving ability mediated the effects of customers’ service usage intentions (i.e., their preference for AI vs. Human) with task complexity serving as a boundary condition. Here we discuss our research and the results and conclude by offering practical suggestions for banks seeking to reach customers and engage with them more effectively by leveraging the distinctive features of AI customer service. 在客户服务的情境中, 我们将人工智能定义为一种技术支持的系统, 用于评估实时服务场景, 使用从数字和/或物理来源收集的数据, 以便为客户的查询或问题 (甚至是非常复杂的问题) 提供个性化的建议,替代方案和解决方案.我们通过三个基于实地调研的实验, 研究了在银行服务环境中, 消费者是否更喜欢人工智能或人类客户服务应用程序.结果表明, 在低复杂性任务中, 消费者认为人工智能的解决问题能力大于人类客服, 更倾向于使用人工智能;反之, 在高复杂性任务中, 消费者认为人类客服更优越, 相较于人工智能更倾向于使用人类客服.我们发现, 消费者感知到的问题解决能力介导了客户服务使用意图的影响 (即, 他们对人工智能和人类的偏好) , 且任务复杂性作为边界条件.通过这篇文章, 我们讨论了我们的研究和成果, 并为银行寻求接触客户并与他们更有效地利用特色的人工智能客户服务提供了有效的建议.