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Open Access

REVIEW

A Systematic Literature Review on the Impact of Generative AI in Digital Marketing: Advancements, Opportunities, and Challenges

Arifur Rahman1, MD Azam Khan1, Farhad Uddin Mahmud1, Kanchon Kumar Bishnu2, Ashifur Rahman3, M. F. Mridha4,*, Md. Jakir Hossen5,*
1 School of Business, International American University, Los Angeles, CA, USA
2 Department of Computer Science, California State University, Los Angeles, CA, USA
3 Department of Computer Science and Engineering, Bangladesh University of Business and Technology, Dhaka, Bangladesh
4 Department of Computer Science and Engineering, American International University-Bangladesh, Dhaka, Bangladesh
5 Center for Advanced Analytics (CAA), Faculty of Engineering and Technology (FET), Multimedia University, Melaka, Malaysia
* Corresponding Author: M. F. Mridha. Email: email; Md. Jakir Hossen. Email: email

Computers, Materials & Continua https://doi.org/10.32604/cmc.2026.071029

Received 30 July 2025; Accepted 21 October 2025; Published online 13 March 2026

Abstract

Generative Artificial Intelligence (AI) is reshaping digital marketing by creating automated content, personalizing campaigns, and offering new ways to engage consumers. This systematic review examines research on generative AI, highlighting both its technological progress and the ethical, technical, and organizational hurdles that could limit its use. We used a PRISMA-based method to search major databases (ACM Digital Library, IEEE Xplore, and Scopus) for peer-reviewed studies published from 2018 to 2025. Our findings reveal major gains in text creation, image generation, and multimodal campaigns, which can lower costs and spark creative thinking. Still, data privacy, bias in models, and laws around compliance show the need for clear and responsible adoption. By bringing in ideas from Innovation Diffusion Theory and the Technology Acceptance Model, this review shows how organizational culture and perceived value interact with ethical frameworks to shape how generative AI tools take hold. We provide insights for marketers who want to apply generative AI in a responsible way and set a path for future research aimed at protecting consumer trust.

Keywords

Generative AI; digital marketing; content generation; personalization; ethical AI; technology adoption; innovation diffusion theory; transformer models

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