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Cultural Blind Spots in Marketing AI: Case Studies of Failure

Cultural Blind Spots in Marketing AI: Case Studies of Failure
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Author(s): Aakriti Jain (Christ University, India)and Ila Anand (Christ University, India)
Copyright: 2026
Pages: 30
Source title: AI-Driven Decision-Making for Diversity, Equity, and Inclusion in Marketing
Source Author(s)/Editor(s): Theodore Tarnanidis (International Hellenic University, Greece)
DOI: 10.4018/979-8-3373-6731-6.ch006

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Abstract

Artificial intelligence has been quickly shifting into the pioneer of contemporary marketing. AI powered systems influence how brands communicate with culturally diverse audiences through automated content creation and hyper personalized targeting. These systems, while highly efficient, are proving to have major cultural blind points in which algorithmic decision making fails to detect or interpret cultural, social, and representational subtleties. Such lapses appear as biased outputs, homogenization of identity, and reinforcement of stereotypes, growing into public controversies and reputational crises. This chapter explores cultural blindness in marketing-focused AI systems through four case studies: Amazon's recruitment tool, H&M's culturally insensitive campaign, Dove's beauty representation controversy, and Levi's AI generated diversity models.

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