Applications of Generative Artificial Intelligence in Marketing: A Research Review and Future Prospects

Main Article Content

Kangcheng Mei
School of Economics, Beijing Technology and Business University, Beijing 102445, China

DOI: https://doi.org/10.70267/fer.v3n6.83102

Keywords

generative artificial intelligence, marketing, consumer response, disclosure paradox, human-AI collaboration

Abstract

Generative artificial intelligence (GenAI) is turning marketing content into an abundant resource with near-zero marginal cost, but related research is highly fragmented. This paper thematically integrates Chinese- and English-language literature published from 2019 to 2026. The findings show that gains from GenAI marketing are “stratified along the funnel”: evidence of improvements at the attention and interaction stages is sufficient, whereas the effect on final conversion is weak; consumers’ evaluations of content are decoupled from evaluations of the “artificial intelligence (AI) source” label, and disclosure of the AI source significantly suppresses transactions; only 13% of the literature examines moderating variables. Accordingly, this paper proposes a five-stage integrated framework of “technical characteristics → marketing applications → psychological mechanisms → consumer responses → moderating boundaries” and a future research agenda.

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Nov 5, 2026
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Mei, K. (2026). Applications of Generative Artificial Intelligence in Marketing: A Research Review and Future Prospects. Financial Economics Research, 3(6), 83-102. https://doi.org/10.70267/fer.v3n6.83102