GENERATIVE AI IN MARKETING COMMUNICATIONS: IMPLICATIONS FOR BRAND DISTINCTIVENESS, CONSUMER TRUST, AND REGULATORY DISCLOSURE.

This review examines how generative artificial intelligence (AI) is reshaping brand communications, with a particular focus on distinctive brand assets (DBAs), authenticity, and persuasive outcomes. Following the PRISMA-ScR guidelines and a PCC framework, primary empirical studies published between 2018 and 2025 were searched for across the Web of Science Core Collection, PsycINFO and the ACM Digital Library. A total of fourteen records met the eligibility criteria and were included in this study. Three key findings emerged across the reviewed studied. Firstly, the credibility, value and intentions of AI-involvement disclosure are typically diminished by manipulation/inauthenticity inferences, with the impact being moderated by audience traits and context. In addition to this, performance is fit-dependent. AI excels with agentic appeals and voice-category congruency, but underperforms in authenticity-intensive categories such as luxury. Consequently, synthetic spokesperson entities can function as DBAs when they are designed to be authentic, credible and trustworthy. There are several gaps in the evidence, including scarce field outcomes, limited measurement of distinctiveness and recognition, narrow disclosure manipulations, a Western and category bias, and a lack of preregistered replications. Overall, generative AI can enhance distinctiveness and performance when designed for congruence and transparency. However, unmanaged disclosure and misfit can erode brand authenticity and persuasion.