Linguistic Strategies in AI-Generated Marketing Content: A Policy Framework for Global Brands
DOI:
https://doi.org/10.71435/688503Keywords:
AI-Generated Marketing , Linguistic Strategies, Language Policy, Ethical Transparency, Language Policy FrameworkAbstract
Purpose: Artificial intelligence (AI) is transforming marketing communication by enabling personalized, adaptive, and multilingual content generation. However, the increasing use of AI also raises concerns regarding cultural appropriateness, linguistic bias, authenticity, transparency, and consumer trust. This study examines linguistic strategies in AI-generated marketing communication and develops a language policy framework for global brands.
Subjects and Methods: A qualitative descriptive design was employed in Vientiane, Lao PDR. Data were obtained from purposively selected AI-generated advertisements, social media campaigns, and branded content, complemented by interviews with marketing practitioners. Data were analyzed through iterative thematic coding and discourse-oriented interpretation, focusing on personalization, sentiment adaptation, cultural localization, multilingual communication, and ethical practices.
Results: Three themes emerged: personalization and sentiment adaptation, cultural and linguistic localization, and ethical transparency and consumer trust. AI enables rapid message variation and adaptive emotional communication, but human oversight remains necessary to interpret contextual meanings and preserve authenticity. Multilingual generation also requires cultural adaptation beyond direct translation, particularly regarding tone, idioms, politeness, and cultural references. Ethical communication requires transparency, responsible data management, bias monitoring, and human accountability.
Conclusions: The study proposes a Language Policy Framework integrating transparency, cultural and linguistic adaptability, ethical AI deployment, multilingual consistency, and consumer-centric communication. The framework positions human oversight as an essential component of responsible AI-generated marketing communication.
Downloads
References
AlAfnan, M. A. (2025). Artificial intelligence and language: Bridging Arabic and English with technology. Journal of Ecohumanism, 4(1), 240-256.
Al-Badawi, M. (2024). The role of linguistic variation in multicultural marketing: a case study of foreign brands in Jordan. In Frontiers of Human Centricity in the Artificial Intelligence-Driven Society 5.0 (pp. 791-796). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-73545-5_68
Ali, L., Ali, F., Abdalla, M. J., & Alotaibi, S. (2025). Beyond the hype: Evaluating the impact of generative AI on brand authenticity, image, and consumer behavior in the restaurant industry. International Journal of Hospitality Management, 131, 104318. https://doi.org/10.1016/j.ijhm.2025.104318
Amin, M. R. M., Asbi, A., Sivakumaran, V. M., Kim, J., & Septiarini, E. (2025). Artificial intelligence (AI) adoption in marketing strategies: Navigating the present and shaping the future business landscape. Social Sciences & Humanities Open, 12, 102048. https://doi.org/10.1016/j.ssaho.2025.102048
Brüns, J. D., & Meißner, M. (2024). Do you create your content yourself? Using generative artificial intelligence for social media content creation diminishes perceived brand authenticity. Journal of Retailing and Consumer Services, 79, 103790. https://doi.org/10.1016/j.jretconser.2024.103790
Catullo, D., & Santorelli, M. (2024). The transformative role of linguistic ai in shaping business models. In Creşterea economică în condiţiile globalizării (pp. 165-176). https://doi.org/10.36004/nier.cecg.I.2024.18.16
Chan, H.-L., & Choi, T.-M. (2025). Using generative artificial intelligence (GenAI) in marketing: Development and practices. Journal of Business Research, 191, 115276. https://doi.org/10.1016/j.jbusres.2025.115276
Chen, C., Zhang, D., Zhu, L., & Zhang, F. (2025). Exploring consumer responses to AI-generated visual marketing content: A dual-process theory perspective. International Journal of Consumer Studies, 49(5), e70121. https://doi.org/10.1111/ijcs.70121
Chow, M. Y. C., Ho, P. S. S., Armutcu, B., Tan, A., & Butt, M.-K. (2025). Role of culture in how AI affects the brand experience: Comparison of Belt and Road countries. Asia-Pacific Journal of Business Administration, 18(1), 213–236. https://doi.org/10.1108/APJBA-09-2024-0510
Du Plessis, C. (2025). Ethical requirements for generative AI in brand content creation: A qualitative comparative analysis. Frontiers in Communication, 10, 1523077. https://doi.org/10.3389/fcomm.2025.1523077
Faruk, M., Rahman, M. M., Mustafa, R., & Roy, I. (2025). Updates in the evolution of AI-driven digital marketing practices: a literature review with bibliometric analysis. International Journal of Technology Marketing, 19(3), 292-318. https://doi.org/10.1504/IJTMKT.2025.147357
Ford, J., Jain, V., Wadhwani, K., & Gupta, D. G. (2023). AI advertising: An overview and guidelines. Journal of Business Research, 166, 114124. https://doi.org/10.1016/j.jbusres.2023.114124
Gaczek, P., Leszczyński, G., Wei, Y., & Sun, H. (2026). The bright side of AI in marketing decisions: Collaboration with algorithms prevents managers from violating ethical norms. Journal of Business Ethics, 204(4), 771–794. https://doi.org/10.1007/s10551-025-06083-w
Gorjanc, M. (2025). Trust in the age of artificial intelligence: A framework for privacy protection in personalised marketing. Journal of Innovative Business and Management, 17(1). https://doi.org/10.32015/JIBM.2025.17.1.9
Grigsby, J. L., Michelsen, M., & Zamudio, C. (2025). Service ads in the era of generative AI: Disclosures, trust, and intangibility. Journal of Retailing and Consumer Services, 84, 104231. https://doi.org/10.1016/j.jretconser.2025.104231
Gummesson, E. (2005). Qualitative research in marketing: Road‐map for a wilderness of complexityand unpredictability. European journal of marketing, 39(3-4), 309-327. https://doi.org/10.1108/03090560510581791
Gupta, S., Sharma, L., & Mathew, R. (2025). Balancing personalization and privacy in AI-enabled marketing consumer trust, regulatory impact, and strategic implications: A qualitative study using NVivo. Advances in Consumer Research, 2(5), 46–57.
Hakimi, M., Parsa, N. M., & Turan, M. N. (2026). Consumer trust in AI-generated advertisements: A comparative study of AI and human-created advertising content. COMMUSTY: Journal of Communication Studies and Society, 5(1), 29–48. https://doi.org/10.38043/commusty.v5i1.7734
Hartmann, J., Exner, Y., & Domdey, S. (2025). The power of generative marketing: Can generative AI create superhuman visual marketing content? International Journal of Research in Marketing, 42(1), 13–31. https://doi.org/10.1016/j.ijresmar.2024.09.002
Hidayat, A. S., Mardani, A. D., & Pramulanto, H. (2025). Personalization vs. privacy: Balancing data-driven marketing and consumer trust in the digital economy. YUME: Journal of Management, 8(1), 1191–1201. https://doi.org/10.37531/yum.v8i1.9010
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
Imtiaz, A., Ashfaq, K., Abbas, N., & Nisar, M. F. (2025). Exploring The Academic Nexus: Bibliometric Mapping Of Social Media, Wom, And Destination Image In Ecotourism Research. Journal for Business Education and Management, 5(1), 147-182. https://doi.org/10.5281/zenodo.16988775
Indrawan, D., Yorman, Y., Stiadi, M., Hendayani, N., & Al-Amin, A. A. (2023). Revolutionizing social media marketing through AI and automation: an in-depth analysis of strategies, ethics, and future trends. International Journal of Humanities, Social Sciences and Business (INJOSS), 3(1), 22-45.
Jayashankar, P., Johnston, W. J., & Sheth, J. (2025). Multilingualism as strategy: AI-enabled STP for inclusive market development in emerging economies. Marketing Strategy Journal, 4, 100011. https://doi.org/10.1016/j.msj.2025.100011
Jenks, C. J. (2025). Communicating the cultural other: Trust and bias in generative AI and large language models. Applied Linguistics Review, 16(2), 787–795. https://doi.org/10.1515/applirev-2024-0196
Kamal, M., & Himel, A. S. (2023). Redefining modern marketing: an analysis of AI and NLP’s influence on consumer engagement, strategy, and beyond. Eigenpub Review of Science and Technology, 7(1), 203-223.
Kapoulas, A., & Mitic, M. (2012). Understanding challenges of qualitative research: Rhetorical issues and reality traps. Qualitative Market Research: An International Journal, 15(4), 354-368. https://doi.org/10.1108/13522751211257051
Kelly‐Holmes, H. (2010). Languages and global marketing. The handbook of language and globalization, 475-492. https://doi.org/10.1002/9781444324068
Keser, H. Y. (2025). The role of artificial intelligence in eliminating language and cultural barriers in cross-border e-commerce. In J. Belak & Z. Nedelko (Eds.), 9th FEB International Scientific Conference: Sustainable Management in the Age of ESG and AI: Navigating Challenges and Opportunities (Vol. 9, pp. 277–288). University of Maribor Press. https://doi.org/10.18690/um.epf.5.2025.26
Kirk, C. P., & Givi, J. (2025). The AI-authorship effect: Understanding authenticity, moral disgust, and consumer responses to AI-generated marketing communications. Journal of Business Research, 186, 114984. https://doi.org/10.1016/j.jbusres.2024.114984
Kunizhev, M. A. (2019, October). Genesis and Future Development of Marketing Linguistics in the Era of Economy Digitalisation. In Institute of Scientific Communications Conference (pp. 1053-1061). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-69415-9_117
Lim, W. M. (2025). What is qualitative research? An overview and guidelines. Australasian marketing journal, 33(2), 199-229. https://doi.org/10.1177/14413582241264619
Lu, J. G., Song, L. L., & Zhang, L. D. (2025). Cultural tendencies in generative AI. Nature Human Behaviour, 9, 2360–2369. https://doi.org/10.1038/s41562-025-02242-1
Mariani, M. M., Perez‐Vega, R., & Wirtz, J. (2022). AI in marketing, consumer research and psychology: A systematic literature review and research agenda. Psychology & Marketing, 39(4), 755-776. https://doi.org/10.1002/mar.21619
Markou, V., Serdaris, P., Antoniadis, I., & Spinthiropoulos, K. (2025). Personalization, trust, and identity in AI-based marketing: An empirical study of consumer acceptance in Greece. Administrative Sciences, 15(11), 440. https://doi.org/10.3390/admsci15110440
Mirek-Rogowska, A., Kucza, W., & Gajdka, K. (2024). AI in communication: Theoretical perspectives, ethical implications, and emerging competencies. Communication Today, 15(2), 16-29.
Musonda, N., & Siame, P. (2025). The impact of language on branding: A comprehensive analysis. Linguistic Exploration, 2(1), 37-46.
Nazeer, I., Yousaf, S., & Hussain, K. G. (2023). Exploring The Language Of Facebook Ads: Linguistic Patterns And Their Impact On Customer Engagement. Journal of Positive School Psychology, 7(6).
Nie, Y., Liu, Z., & Jiang, Y. (2025). Exploring the impact of generative AI-driven advertising on Generation Z’s consumer behavior in China: A grounded theory approach. American Journal of Applied Psychology, 14(4), 113–128. https://doi.org/10.11648/j.ajap.20251404.11
Niros, A., Niros, M. I., Baltas, G., Giovanis, A. N., & Painesis, G. (2025). Chatbot marketing efforts in the era of artificial intelligence: The moderating role of individualism. International Marketing Review, 42(4), 788–816. https://doi.org/10.1108/IMR-10-2024-0443
Paschen, J., Kietzmann, J., & Kietzmann, T. C. (2019). Artificial intelligence (AI) and its implications for market knowledge in B2B marketing. Journal of business & industrial marketing, 34(7), 1410-1419. https://doi.org/10.1108/JBIM-10-2018-0295
Pizzi, G., Matta, S., Caboni, F., & Stewart, D. W. (2025). Immersive and generative technology: New tools for marketing, new tools for consumer response. Psychology & Marketing, 42, 3236–3250. https://doi.org/10.1002/mar.70036
Prasanna, A., & Kushwaha, B. P. (2025). Generative AI in marketing: Foundations, trends, and future research propositions. Human Behavior and Emerging Technologies, 5542513. https://doi.org/10.1155/hbe2/5542513
Qiu, X., Wang, Y., Zeng, Y., & Cong, R. (2025). Artificial intelligence disclosure in cause-related marketing: A persuasion knowledge perspective. Journal of Theoretical and Applied Electronic Commerce Research, 20(3), 193. https://doi.org/10.3390/jtaer20030193
Ratta, A. A., Muneer, S., & ul Hassan, H. (2024). The impact of AI generated advertising content on consumer buying behavior and consumer engagement. Bulletin of Business and Economics (BBE), 13(2), 1152-1157. https://doi.org/10.61506/01.00476
Roy, S. K., Tehrani, A. N., Pandit, A., Apostolidis, C., & Ray, S. (2025). AI-capable relationship marketing: Shaping the future of customer relationships. Journal of Business Research, 192, 115309. https://doi.org/10.1016/j.jbusres.2025.115309
Sandelowski, M. (2000). Whatever happened to qualitative description?. Research in nursing & health, 23(4), 334-340. https://doi.org/10.1002/1098-240X(200008)23:4%3C334::AID-NUR9%3E3.0.CO;2-G
Şenyapar, H. N. D. (2024). The future of marketing: The transformative power of artificial intelligence. International Journal of Management and Administration, 8(15), 1-19.
Singh, P., & Prakash, A. (2024). Influence of conversational AI on consumer engagement with brands: A bibliometric analysis. IUP Journal of Brand Management, 21(4), 5-29.
Srivastava, A., & Srivastava, S. (2024). Decoding the Landscape of Customer Engagement: Marketing Intelligence Backed With AI and Neuro-Linguistics Hack. In Improving Service Quality and Customer Engagement With Marketing Intelligence (pp. 211-227). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3693-6813-8.ch009
Teepapal, T. (2025). AI-driven personalization: Unraveling consumer perceptions in social media engagement. Computers in Human Behavior, 165, 108549. https://doi.org/10.1016/j.chb.2024.108549
van Esch, P., Cui, Y. (G.), & Heilgenberg, K. (2024). Using artificial intelligence (AI) to implement diversity, equity and inclusion (DEI) into marketing materials: The “CONSIDER” framework. Journal of Interactive Marketing, 59(3), 1–17. https://doi.org/10.1177/14413582241244504
Wojtaszek, A. (2025). Lost in localisation? International advertising in the age of AI: Discursive challenges and digital solutions. Asia Pacific Translation and Intercultural Studies, 12(3), 249–261. https://doi.org/10.1080/23306343.2025.2596479
Zotzmann, K., & O’Regan, J. P. (2016). Critical discourse analysis and identity. In The Routledge handbook of language and identity (pp. 113-127). London: Routledge. https://doi.org/10.4324/9781315669816
.jpg)
