Linguistic Strategies in AI-Generated Marketing Content: A Policy Framework for GLOBAL Brands

Abstract

Purpose: This study examines linguistic strategies in AI-generated marketing content and proposes a Language Policy Framework for Global Brands to ensure ethical, culturally adaptive, and consumer-centric communication. Subjects and Methods: A qualitative descriptive analysis was employed, reviewing existing literature and industry practices to assess AI-driven personalization, cultural localization, and ethical transparency in marketing communication. Results: AI enhances engagement through personalization and sentiment adaptation, but challenges include linguistic bias, cultural misalignment, and ethical concerns. Transparency and localization improve trust and consumer relationships. Conclusions: A structured Language Policy Framework integrating transparency, cultural sensitivity, and multilingual consistency is essential for responsible AI deployment in global marketing. Future research should explore hybrid AI-human collaboration for optimal brand communication.

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