Generative AI in Marketing: Foundations, Trends, and Future Research Propositions

Abstract

This study intends to conduct a bibliometric analysis of the literature on generative artificial intelligence (GenAI) in marketing. Moreover, it expounds the research foundations and emerging patterns associated with GenAI in marketing and formulates prospective research propositions. This study utilizes bibliometric analysis and a literature review to evaluate the scholarly contributions of publications, authors with the highest productivity, publications with significant impact, institutions, and nations. Three hundred and seventy‐one Scopus and Web of Science database documents were retrieved and consolidated by eliminating duplicates. The analysis employed various techniques, including coword analysis, thematic representation, cocitations, coupling by clustering, and international collaborations. The research uses the Bibliometrix R package to merge the dataset and conduct the bibliometric analysis. The last 2 years, 2023 and 2024, stand out as the most productive years with a notable quantity of publications, reaching 107 in 2023 and 71 in 2024. The most influential papers revolve around advertising content, sentiment analysis, and text mining. The institution with the most influence in this field is the University of Colorado Boulder, and the country is the United States. Bibliographic coupling analysis proposed the presence of four thematic clusters: opinion and text mining, big data analytics, artificial intelligence in marketing, and user‐generated content. The investigation is an enlightening resource for scholars researching GenAI within the marketing domain. It will benefit researchers to familiarize themselves with previous studies and current research in this field. It also offers valuable information on this area’s most promising articles, journals, and authors. Furthermore, it provides valuable insights into potential avenues for future investigations in this domain. Consequently, the findings of this study will be advantageous for aspiring scholars in this field to establish the direction of their research endeavors. This study primarily examines performance and an academic representation of GenAI’s role in marketing. It serves as the initial study to present GenAI’s current research positions and future directions in marketing through bibliometric analysis.