Keywords
Abstract
The convergence of artificial intelligence and big data is fundamentally transforming how companies design, execute, and evaluate international marketing strategies.
This paper reviews and synthesizes peer-reviewed research and industry data published between 2019 and 2024 to explore how AI-driven capabilities, including predictive analytics, natural language processing, machine learning-based segmentation, and programmatic advertising, are reshaping key marketing decisions in global markets. This paper pays particular attention to cross-cultural applications, differences in AI application between developed and developing economies, and the ethical and regulatory challenges faced by multinational corporations in integrating these technologies.
The findings show that AI and big data significantly improve market access prediction, customer targeting accuracy, and ROI of marketing campaigns, while also raising concerns about algorithmic bias, data privacy, and unequal market access.
This paper concludes that companies hoping to compete in international markets must view AI and big data literacy as a strategic capability rather than a technological function, and must combine technology investment with marketing governance that balances cultural sensitivity and ethical considerations.
References
Apriani, A., Sani, I., Kurniawati, L., Prayoga, R., & Panggabean, H. L. (2024). Comparative study of artificial intelligence (AI) utilisation in digital marketing strategies between developed and developing countries: A systematic literature review. Ilomata International Journal of Management, 5(3), 1034–1051. https://doi.org/10.52728/ijjm.v5i3.1534
Basu, R. (2023). Marketing analytics: The bridge between customer psychology and marketing decision-making. Psychology & Marketing, 40(12), 2829–2847. https://doi.org/10.1002/mar.21908
Connell, C., Marciniak, R., & Drylie Carey, L. (2023). The effect of cross-cultural dimensions on the manifestation of customer engagement behaviours. Journal of International Marketing, 31(1), 22–41. https://doi.org/10.1177/1069031X221130690
Dhavaleshwar, C. (2024). AI personalization and engagement in social media marketing. International Journal of Marketing Research Innovation, 8(1), 1–12.https://www.researchgate.net/publication/386981505_Innovative_Marketing_In_The_Digital_Age_The_Power_Of_AI_Personalization_And_Social_Media
Jain, R., & Kumar, A. (2024). Artificial intelligence in marketing: Two decades review. Management and Labour Studies, OnlineFirst. https://doi.org/10.1177/09711023241272308
Jarek, K., & Mazurek, G. (2019). Marketing and artificial intelligence. Central European Business Review, 8(2), 46–55. https://doi.org/10.18267/j.cebr.213
Kasem, M. S., Hamada, M., & Taj-Eddin, I. (2024). Customer profiling, segmentation, and sales prediction using AI in direct marketing. Neural Computing and Applications, 36(9), 4995–5005. https://doi.org/10.1007/s00521-024-09445-7
Kim, J., Lee, H., & Yoon, Y. (2025). From big data to cultural intelligence: An AI-powered framework and machine learning validation for global marketing. Journal of Theoretical and Applied Electronic Commerce Research, 20(4), 288. https://doi.org/10.3390/jtaer20040288
Labib, E. (2024). Artificial intelligence in marketing: Exploring current and future trends. Cogent Business & Management, 11(1), 2348728. https://doi.org/10.1080/23311975.2024.2348728
Lopez, S. (2023). Optimizing marketing ROI with predictive analytics: Harnessing big data and AI for data-driven decision making. Journal of Artificial Intelligence Research, 3(2), 9–36.https://www.researchgate.net/publication/387897347_
Ejiroghene Amanda Onohwakpo (2025). Predictive analytics for international market entry: A multi-country analysis of success factors. Global Journal of Artificial Intelligence and Technology Development, 1(3), 1–14.https://www.researchgate.net/publication/395441953_Predictive_Analytics_for_International_Market_Entry_A_Multi-Country_Analysis_of_Success_Factors
Okeleke, P. A., Ajiga, D., Folorunsho, S. O., & Ezeigweneme, C. (2024). Predictive analytics for market trends using AI: A study in consumer behavior. International Journal of Engineering Research Updates, 7(1), 036–049. https://doi.org/10.53430/ijeru.2024.7.1.0031.
Statista. (2024). Digital advertisingworldwide market forecast 2024–2029. Statista GmbH. https://www.statista.com
Theodorakopoulos, L. (2024). Leveraging big data analytics for understanding consumer behavior in digital marketing: A systematic review. Human Behavior and Emerging Technologies, 2024, Article 3641502. https://doi.org/10.1155/2024/3641502
Vlačić, B., Corbo, L., Costa e Silva, S., & Dabić, M. (2021). The evolving role of artificial intelligence in marketing: A review and research agenda. Journal of Business Research, 128, 187–203. https://doi.org/10.1016/j.jbusres.2021.01.055
Ziakis, C., & Vlachopoulou, M. (2023). Artificial intelligence in digital marketing: Systematic literature review. Information, 14(10), 557. https://doi.org/10.3390/info14100557