International Journal of Management

Artificial Intelligence has transformed market segmentation by enabling large-scale processing of behavioral, demographic, psychographic, and cultural data. However, traditional segmentation models often treat global markets homogenously, failing to account for cultural variation in beliefs, identity, purchasing attitudes, and communication norms. This study introduces an AI-powered cross-cultural segmentation framework that integrates machine learning, natural language processing, and cultural analytics to derive culturally sensitive consumer clusters across regions. Using social media datasets from five global markets and interviews with AI marketing experts, the analysis reveals that cultural values significantly shape consumer responses to advertising even when observable behaviors appear similar. A multi-layered segmentation model is proposed to optimize communication across culturally diverse audiences.