Main Article Content

Abstract

Artificial Intelligence (AI) has become crucial in digital marketing strategies in the rapidly advancing digital era. Developed and developing countries exhibit significant differences in adopting and implementing this technology, influenced by infrastructure readiness, human resources, and policy support. This study aims to compare the use of AI in digital marketing strategies between developed and developing countries to understand each group's challenges and opportunities. The research employs a Systematic Literature Review (SLR) method by analyzing 50 articles from leading databases such as Scopus, Springer, and IEEE Xplore. The analyzed articles were selected based on inclusion criteria, including relevance to the topic, publication year (2018-2024), and full accessibility. Data were analyzed through thematic synthesis to identify patterns, trends, and gaps in AI adoption between the two groups of countries. NVivo and VOSviewer are used as analytical tools to facilitate data analysis. The findings reveal that developed countries leverage AI for content personalization, predictive analytics, and marketing automation, supported by advanced digital infrastructure. Meanwhile, developing countries still face various obstacles, such as limited infrastructure and digital literacy. The implications of this study highlight the need for more significant investment in technological infrastructure in developing countries and the importance of global collaboration to accelerate equitable AI adoption. This research also provides recommendations for policymakers and business practitioners to optimize AI utilization in digital marketing strategies across different contexts.

Keywords

Artificial Intelligence, Digital Marketing, Developing Countries, Developed Countries

Article Details

How to Cite
Mubarok, M. U., Sari, M. I., Wibowo, Y. G., & Mathew, R. (2024). Comparative Study of Artificial Intelligence (AI) Utilization in Digital Marketing Strategies Between Developed and Developing Countries: A Systematic Literature Review. Ilomata International Journal of Management, 6(1), 156-173. https://doi.org/10.61194/ijjm.v6i1.1534

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