How AI-Generated Content Undermines the Epistemic Resilience of Brands

Abstract

The rapid diffusion of generative artificial intelligence has turned brand communication into a site of large-scale, largely unsupervised production of text, images, and videos. This article examines how AI-generated content undermines the epistemic resilience of brands as their capacity to sustain reliable, trusted, and internally consistent knowledge about themselves within a contested information environment. Drawing on recent empirical and theoretical literature, the article identifies five interacting mechanisms of erosion: the AI penalty and disclosure paradox in audience perception; authenticity discounting in influencer and social content; hallucination and the self-reinforcing "AI slop loop" in generative search; model collapse as a long-term contamination of the shared information commons; and the homogenization of brand voice under algorithmic optimization. The article argues that these mechanisms operate cumulatively rather than in isolation, converting short-term efficiency gains into long-term reputational and epistemic liabilities. It concludes with a governance framework built on provenance, human epistemic authority, and transparent disclosure practices that brands and researchers alike can use to preserve trust in AI-mediated communication.