Humans as teammates: The signal of human–AI teaming enhances consumer acceptance of chatbots

Abstract

Human–artificial intelligence (AI) teaming is a service system in which AI agents work interdependently toward a common goal alongside human agents. Although many consumer services rely on chatbots working with humans, little is known about the influence of human–AI teaming on consumers’ perceptions and use of chatbots in online service encounters. Using signaling theory, the present research examines whether and how human–AI teaming (vs. independent AI) increases consumer acceptance of chatbots. Through six scenario-based studies and an interview, we found that human–AI teaming can use human capabilities to endorse the effectiveness and authenticity of AI, leading to increased chatbot acceptance. However, this effect was not observed when AI capability was clear or the human service experience was negative. We contribute to information systems research by showing the mechanism and boundary conditions underlying the effect of human–AI teaming on chatbot acceptance. We also provide practical insights for managers emphasizing how human teammates in AI–consumer conversations can increase consumer acceptance of AI.