Abstract

Conversational artificial intelligence (AI) has become a central feature of digital consumer interactions, yet its effectiveness depends largely on user trust. Unlike traditional interfaces, conversational AI operates as an interactive and adaptive agent, reshaping trust formation in AI-mediated exchanges. This study proposes a conceptual framework explaining how conversational AI influences consumer trust through perceived competence, social presence, transparency, and perceived autonomy. The framework distinguishes between cognitive and affective trust and examines their effects on purchase intention and willingness to disclose personal information. A survey-based research design and Structural Equation Modeling (SEM) are proposed to empirically test the relationships. This study contributes to consumer trust and AI literature by positioning conversational AI as an active trust-building agent and offers practical insights for designing trustworthy AI systems.