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Cited by 10Digital Marketing and Social MediaAI in Service InteractionsMarketing and Advertising Strategies

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

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Prasanna, Akshara, Kushwaha, Bijay Prasad·2025·Human Behavior and Emerging Technologies
DOI 10.1155/hbe2/5542513
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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.

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  • Marketing scholarship has examined Generative Artificial Intelligence (GenAI) primarily through firm-side strategy.

    “Marketing scholarship has examined Generative Artificial Intelligence (GenAI) primarily through firm-side strategy(Prasanna and Kushwaha, 2025;Riandhi et al., 2025;Grewal et al., 2025;Kumar et al., 2026)”

    From Shopping by algorithm: How agentic AI deploys human heuristics as a surrogate consumer (2026) · cites this paper as Prasanna and Kushwaha, 2025

    The Background describes GenAI’s use in firms’ marketing strategies, supporting the firm-side aspect. But the Introduction characterizes previous research as primarily focused on technical advancements and applications, and the Conclusion lists themes including text mining, speech recognition, and user-generated content. The paper does not establish that marketing scholarship has examined GenAI primarily through firm-side strategy. (LLM, conf=0.83)

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Cited by

Sorted by citations

Authors
Prasanna, A., & Kushwaha, B. P.
Affiliations
Vellore Institute of Technology University (IN)
Corresponding author
Kushwaha, Bijay Prasad
ORCID
Venue
Human Behavior and Emerging Technologies
Publisher
Wiley
Published
2025-01
Volume
2025
Issue
1
ISSN
2578-1863 (ISSN-L)
DOI
10.1155/hbe2/5542513
OpenAlex
W4412408993
Cited by
10
References
9
Citations by year
2026: 9 · 2025: 1
FWCI
17.42
Type
journal article
Language
en
Open access
Licence
Locations
  • Human Behavior and Emerging Technologies (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Social Sciences › Sociology and Political Science › Digital Marketing and Social Media
  • Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
  • Social Sciences › Business, Management and Accounting › Marketing › Marketing and Advertising Strategies
Keywords
generative AI, marketing, sentiment analysis, text mining, big data analytics, user-generated content, research trends, research gaps

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