Understanding service performance of frontline employees from employee–AI interaction perspective

Purpose Despite the increasing trend of integrating artificial intelligence (AI) into organizational workforces, there remains a lack of understanding regarding how employee–AI interaction shapes employee service performance. The objective of this study is to investigate the impacts of employee–AI interaction fluency on in-role and out-of-role employee service performance in different delivery service (smart helmet services vs in-vehicle AI services) contexts. Design/methodology/approach Drawing on mind perception theory and self-efficacy theory, a research model that reflected the impacts of employee–AI interaction fluency on employee service performance was developed. This research model was then tested through two empirical studies using data collected from frontline employees in the delivery service industry. Findings The present study found that employee–AI interaction fluency acts both directly on employee service performance as well as indirectly via mind perceptions. Specifically, in the smart helmet service context, employee–AI interaction fluency affects in-role employee service performance via both perceived empathy and competence. By contrast, this impact shifts to out-of-role employee service performance in the in-vehicle AI service context, where perceived competence fully mediates the relationship between interaction fluency and service performance. In addition, the impact of employee–AI interaction fluency on perceived competence will be diminished among frontline employees with high levels of self-efficacy. Practical implications This study offers valuable insights for AI device developers and managers aiming to improve both in-role and extra-role employee service performance through the lens of employee–AI interactions. In contexts with a high degree of employee–AI collaboration, such as smart helmet services, it is crucial to emphasize the empathy and competence of AI to boost in-role employee service performance. In contrast, in contexts with a lower level of employee–AI partnership, like in-vehicle AI services, the focus should be primarily on enhancing the competence of AI. Originality/value The present paper reveals the critical role of employee–AI interaction fluency in shaping both in-role and out-of-role employee service performance in the smart helmet and in-vehicle AI service contexts. Moreover, this study also validated the significant negative moderating role of self-efficacy in the relationship between interaction fluency and employee service performance.