AI Content Localization in Marketing Communications in Afghanistan: A Qualitative Analysis of ChatGPT-Generated Advertisements

Authors

  • Abdul Basir Mesbah Editor in Chief of Pol-e Sorkh Media, Germany

DOI:

https://doi.org/10.61231/0csx7a03

Keywords:

ChatGPT, Linguistic Localization, Cultural Localization , Marketing Communication., AI

Abstract

AI chatbots play an effective role in content production for organizations and in the development of marketing communications. Given their speed in producing and analyzing content, many companies now use AI chatbots in creating commercial content. However, the compatibility and alignment of content generated by AI tools with the prevailing cultures and values of societies is another issue that has a deep relationship with technology localization. Within the framework of the concept of “technology localization,” this study qualitatively analyzed five commercial advertisements in different cultural contexts of Afghanistan, generated by ChatGPT, in terms of cultural and linguistic bias. The research findings, while indicating the effectiveness of AI chatbots in producing marketing communication content, identified linguistic and cultural biases in the content examined. The results show that the use of foreign words, particularly English vocabulary, the production of relatively shallow and superficial content, as well as the use of certain words that are implicitly more distant from the prevailing culture of Afghanistan, are among the linguistic and cultural biases of AI. This article supports the localization of AI in the industries and marketing communications of Afghanistan and considers the presence of human resources in the formation of content through AI tools a fundamental necessity.

References

Agbozo, G. E. (2022). Localization at users' sites is not enough: GhanaPostGPS and power reticulations in the postcolony. Technical Communication, 69(2), 7–17. https://doi.org/10.55177/tc041879

AlKhamissi, B., ElNokrashy, M., AlKhamissi, M., & Diab, M. (2024). Investigating Cultural Alignment of Large Language Models. Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 12404–12422.

Aljasem, S., Ahmad, W., Ibesh, R., & Halife, H. (2025, September). Technology transfer and localization as a strategy for sustainable recovery and industrial growth in Syria. Paper presented at the II. Al-Bab International Social Sciences Congress, Syria.

Bag, S., Gupta, S., Kumar, A., & Sivarajah, U. (2021). An integrated artificial intelligence framework for knowledge creation and B2B marketing rational decision making for improving firm performance. Industrial Marketing Management, 92, 178–189. https://doi.org/10.1016/j.indmarman.2020.12.001

De Young, R. (2011, October 10). Localization: A brief definition. School of Natural Resources and Environment, University of Michigan. https://doi.org/10.13140/RG.2.1.3937.9367

Huang, M.-H., & Rust, R. T. (2021). A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 49(1), 30–50. https://doi.org/10.1007/s11747-020-00749-9

Li, D., Kreuzbauer, R., Chiu, C.-Y., & Keh, H. T. (2020). Culturally polite communication: Enhancing the effectiveness of the localization strategy. Journal of Cross-Cultural Psychology, 51(1), 49–69. https://doi.org/10.1177/0022022119893464

Malthouse, E. C., & Copulsky, J. (2023). Artificial intelligence ecosystems for marketing communications. International Journal of Advertising, 42(1), 128–140. https://doi.org/10.1080/02650487.2022.2122249

Mogaji, E., Dwivedi, Y. K., Raman, R., & Nguyen, P. (2022). Examining artificial intelligence (AI) technologies in marketing via a global lens: Current trends and future research opportunities. International Journal of Research in Marketing, 39(2), 469–493. https://doi.org/10.1016/j.ijresmar.2021.11.002

Mora Cortez, R., Gilliland, D. I., & Johnston, W. J. (2020). Revisiting the theory of business-to-business advertising. Industrial Marketing Management, 89, 642–656. https://doi.org/10.1016/j.indmarman.2019.03.012

Moradi, M., & Dass, M. (2022). Applications of artificial intelligence in B2B marketing: Challenges and future directions. Industrial Marketing Management, 107, 197–213. https://doi.org/10.1016/j.indmarman.2022.09.023

Tao, Y., Viberg, O., Baker, R. S., & Kizilcec, R. F. (2024). Cultural bias and cultural alignment of large language models. PNAS Nexus, 3(9), pgae346. https://doi.org/10.1093/pnasnexus/pgae346

Yang, Y., Li, C., & Jin, Y. (2026). Artificial Intelligence Localization: Conception and Measurement from a Communication Perspective. Journal of Hospitality & Tourism Research. Advance online publication. https://doi.org/10.1177/10963480261446992

Downloads

Published

2026-09-28

How to Cite

AI Content Localization in Marketing Communications in Afghanistan: A Qualitative Analysis of ChatGPT-Generated Advertisements. (2026). Multidisciplinary Journal of Education , Economic and Culture , 4(2), 329-340. https://doi.org/10.61231/0csx7a03

Similar Articles

11-20 of 23

You may also start an advanced similarity search for this article.