Once a corner of the internet gets filled with more than 60% AI junk, the platforms start hiding almost everything in that niche.
The research identifies a 'saturation threshold' where algorithms detect a decline in narrative variety and automatically deprioritize content. This means massive AI-driven marketing campaigns can become invisible almost instantly once they cross a specific volume limit.
Algorithmic Deprioritization Patterns in AI-Generated Content Distribution: The Marketing Agent Decay Model (MAD-M™) as a Predictive Framework
SSRN · 6213138
This research identifies the 60% saturation threshold that triggers accelerated visibility decay in AI-generated content across digital discovery layers. By extending the Marketing Agent Decay Model (MAD-M™), the paper provides a predictive framework for managing Narrative Entropy™ and algorithmic deprioritization in generative search (GEO). This paper examines the systematic reduction in content visibility across major digital platforms when AI-generated content is detected or exhibits AI-chara