The impact of AI-based conversational agent on the firms’ operational performance: Empirical evidence from a call center
Zhenyuan Zhang, Binbin Li, Luning Liu
Abstract
Artificial intelligence (AI) based conversational agent is widely used in the service industry. Although some studies have investigated the impact of AI on customers, little research has documented the concrete effects of AI-based conversational agents on firms’ operational performance. To fill this gap, the main goal of this paper is to investigate the impacts of AI-based conversational agent on firms’ operational performance. In addition, the moderating effect of time blocks is also investigated. We address questions using the event study method and a proprietary data set from a telecom firm in China. Results show that the introduction of an AI-based conversational agent increases the average call length and has no significant influence on call numbers. Moreover, there is a heterogeneous effect among different time blocks. Our findings provide important implications for the operational management of call center.