Development of a Consumer Trust Formation Model for Generative Artificial Intelligence Based Marketing Content

Abstract

The rapid advancement of Generative Artificial Intelligence (GenAI) has transformed the way organizations create and distribute marketing content. Although GenAI offers significant advantages in terms of efficiency and personalization, its adoption also introduces new challenges regarding the formation of consumer trust in AI generated marketing content. This study aims to develop a conceptual model of consumer trust formation toward GenAI based marketing content using a Constructivist Grounded Theory approach. A qualitative research design was employed involving consumers who had prior experience interacting with marketing content generated through GenAI technologies. Data were collected through semi structured interviews and analyzed concurrently using initial coding, focused coding, the constant comparative method, and iterative conceptual category development until theoretical saturation was achieved. The findings reveal that consumer trust does not emerge instantaneously but develops through a gradual process beginning with awareness of AI utilization, followed by the evaluation of information credibility, validation through multiple information sources, and assessment of the transparency and integrity demonstrated by organizations in delivering marketing messages. Based on these findings, this study proposes a conceptual model that explains the underlying mechanism of consumer trust formation in GenAI based marketing content. The proposed model contributes to the advancement of digital marketing theory by providing a process oriented understanding of trust development from the consumer experience perspective. It also offers practical implications for organizations seeking to design more transparent, credible, and trust oriented marketing communication strategies through the effective use of Generative Artificial Intelligence.