From ideation to execution: unleashing the power of generative AI in modern digital marketing and customer engagement - a systematic literature review and case study

Salih, Sayeed and Husain, Omayma and Almohamedh, Refan Mohamed and Tajelsier, Hayfaa and Hassan Abdalla Hashim, Aisha and Elshafie, Hashim and Motwakel, Abdelwahed (2026) From ideation to execution: unleashing the power of generative AI in modern digital marketing and customer engagement - a systematic literature review and case study. Array, 29 (NA). pp. 1-25. E-ISSN 2590-0056

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Abstract

Generative Artificial Intelligence (GAI) is revolutionizing digital marketing by auto-content creation, personalized customer experience, and data-driven decisions. This study conducts a systematic literature review and case study analysis to explore GAI applications, benefits, and challenges in modern digital marketing. Drawing on an extensive analysis of academic journals and industry publications, the current research examines leading GAI software such as ChatGPT, DALL-E, MidJourney, Jasper.ai, and Synthesia based on how they aid in content creation, visual design, and video production. The research also provides real-world case studies in multiple industries, such as retail and fashion, food and beverages, and travel and tourism. The case findings illustrated how GAI augments marketing automation, facilitates customer engagement, and amplifies brand engagement, resulting in greater customer satisfaction, higher conversion rates, and better campaign performance. Although it has several benefits, the adoption of GAI is hampered by several critical barriers, such as data privacy, ethical risks, worker resistance, quality control issues, and infrastructure constraints. This research pinpoints these essential challenges and offers practical solutions. It provides actionable insights for businesses seeking to leverage GAI for competitive advantage in the evolving digital landscape by bridging the gap between theory and practice. The findings contribute to the growing discourse on AI-driven marketing strategies and lay the foundation for future research on GAI’s long-term impact on consumer engagement and brand loyalty.

Item Type:	Article (Review)
Additional Information:	2523/125796
Uncontrolled Keywords:	Generative AI, Digital Marketing, Customer Engagement, Content Creation, GAI Adoption, AI Personalization, Marketing Automation
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices > TK7885 Computer engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Electrical and Computer Engineering Kulliyyah of Engineering
Depositing User:	Prof. Dr. Aisha Hassan Abdalla Hashim
Date Deposited:	15 Jan 2026 13:31
Last Modified:	15 Jan 2026 16:37
Queue Number:	2026-01-Q1618
URI:	http://irep.iium.edu.my/id/eprint/125796

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