Machine Talk: How Verbal Embodiment in Conversational AI Shapes Consumer–Brand Relationships

Abstract This research shows that AI-based conversational interfaces can have a profound impact on consumer–brand relationships. We develop conceptual model of verbal embodiment in technology-mediated communication integrates three key properties human-to-human dialogue—(1) turn-taking (i.e., alternating contributions by the two parties), (2) turn initiation act initiating next sequence), and (3) grounding between turns acknowledging other party’s contribution restating or rephrasing it). These fundamental systematically shape consumers’ perception an interface, their brand interface represents, behavior connection with brand. Converging evidence from four studies these dialogue enhance perceived humanness which promotes more intimate relationships favorable behavioral outcomes (greater recommendation acceptance, willingness to pay price premium, advocacy, loyalty). Moreover, we show effects are reduced contexts requiring less mutual understanding consumer highlights how principles be harnessed design interactions increasingly AI-driven marketplace.