Branding Without Belonging: How AI-Generated Content Marketing Erases the Cultural Context of Heritage Foods

Abstract

Baked goods transport cultural memory through rituals and migrations, but when AI tools convert that heritage into marketing content, the cultural depth that differentiates these products disappears. This research is informed by the author's experience operating a baking business where this tension shaped brand decisions daily. This study combines a literature synthesis with a comparative prompt experiment across ChatGPT 5.2, Google Gemini 3, and Claude 4.5 to test whether LLMs suppress cultural depth in a commercial context. For six baked goods, each model was queried under three contexts: Commercial, Open-Ended, and Cultural Preservation. Responses were scored using a rubric for depth of cultural and marketing context to distinguish mentions from explanations. Commercial prompts scored 83 percent lower in depth than Preservation prompts. Across models, the focus narrowed to ingredients, price, and convenience, with little attention to history, ritual use, or brand voice. Preservation prompts revealed specific origins, symbolism, and lived practices, indicating that knowledge is present but only becomes apparent under the right framing. These findings carry implications for content marketing and brand positioning. As businesses rely on AI to generate product content, culturally informed prompts are essential for entrepreneurs seeking to preserve brand authenticity while scaling heritage-baked goods.