Advancements in Artificial Intelligence (AI) technologies' social fluency are being integrated into commercial interactions. As tools such as OpenAI's assistant are integrated into platforms such as Shopify, Klarna, and Visa, understanding consumer responses to AI social features become essential. One such feature is relational talk, an informal and non-obligatory social communication embedded in transactional exchanges. Across four experiments, we find: 1) a negative main effect of AI relational talk on satisfaction, mediated by expectancy violation and perceived interaction awkwardness, and 2) goal-relevant relational talk to attenuate this effect. This paper extends the literature by challenging the assumption that increased social fluency will improve satisfaction, and highlights the complexity of integrating social features into AI systems. It also identifies awkwardness as a key emotional response and barrier to effective human-AI interaction, showing that even in the absence of real social repercussions, perceived awkwardness in AI-led commercial interactions can elicit negative responses.

翻译：人工智能（AI）技术社交流畅性的进步正被整合到商业互动中。随着OpenAI助手等工具被集成到Shopify、Klarna和Visa等平台，理解消费者对AI社交功能的反应变得至关重要。其中一种功能是关系性谈话，即嵌入交易交换中的非正式、非强制性社交沟通。通过四项实验，我们发现：1) AI的关系性谈话对满意度有显著的负面影响，该效应由期望违背和感知互动尴尬感中介；2) 目标相关性关系性谈话可减弱这一效应。本文通过挑战“增加社交流畅性将提升满意度”的假设拓展了相关文献，并强调了将社交功能整合到AI系统中的复杂性。研究还指出尴尬感是有效人机互动的关键情绪反应和障碍，表明即便缺乏真实社交后果，AI主导的商业互动中感知到的尴尬感仍可能引发负面反应。