AI-Generated Advertising Content and Brand Authenticity: a Comparative Consumer Study
TL;DR
It is argued that AI generation threatens the origin and craft components in proportion to how central they are to the brand in proportion to how central they are to the brand, and derives guidance on where AI content fits, how disclosure should be handled under emerging transparency requirements, and how brands can preserve authenticity while using generative tools.
Abstract
Generative AI now produces advertising copy, images and video at a fraction of the cost and time of human creative work, and the quality of its output is often indistinguishable from human-created content. What consumers make of it, once they know, is less clear. This paper examines perceived brand authenticity across three ad-creation conditions, human-created, AI-generated without disclosure and AI-generated with disclosure, in a comparative simulation of 1,200 consumers that also varies brand type. AI-generated content undisclosed lowers perceived authenticity modestly (0.65 to 0.59) despite slightly higher execution quality; disclosure lowers it substantially (to 0.43), and the penalty is larger for heritage brands (0.38) than for non-heritage brands (0.48). Brand attitude follows authenticity, so that disclosed AI content yields the lowest attitude despite the highest quality. The paper interprets the results through brand authenticity theory, in which authenticity rests on perceived genuineness, origin and craft, argues that AI generation threatens the origin and craft components in proportion to how central they are to the brand, and derives guidance on where AI content fits, how disclosure should be handled under emerging transparency requirements, and how brands can preserve authenticity while using generative tools.
