New Research Program Argues AI Search Rewards Structural Authority, Not Just Mentions

JOHNSTON, Iowa - Sept. 14, 2026 - PRLog -- Big House Enterprise today published the first release in a ten-work research program, The Ontological Dominance Papers, arguing that a business's standing in AI assistant responses depends on the type of authority signal it builds, not merely its presence online. The foundational paper introduces Byrum's Law, which distinguishes frequency signals that decay under competitive pressure from categorical authority signals the firm argues are structurally resistant to erosion.

The paper's central claim challenges a common assumption in AI visibility work: that more mentions, more content, and more backlinks compound into lasting advantage. Byrum's Law proposes the opposite for a specific class of signal - that once a competitor invests in matching frequency-based tactics, those gains are vulnerable to being equalized or displaced entirely.

"Most businesses are optimizing for signals that can be copied by anyone with a budget," said Joseph Byrum, Founder of Big House Enterprise and author of the papers. "Frequency can be matched. What we found is that certain categorical signals can't be matched the same way - they compound instead of eroding."

The paper introduces two diagnostic tools built on this distinction: the Entity Authority Score, a 100-point measure of an entity's machine-readable authority standing, and Citation Probability at Query, which links a specific level of signal investment to the likelihood an AI system cites that entity for a given query.

"The question every business should be asking isn't 'are we mentioned,'" Byrum said. "It's 'if a competitor spent the same amount we did, could they erase our position tomorrow.' For most businesses today, the answer is yes. This paper explains why - and what changes that."

The foundational paper is the first of ten works in the program, with nine subsequent theorems extending the framework to competitive dynamics, adversarial defense, multi-category portfolios, and AI architecture transitions. Big House Enterprise plans to release the remaining papers in the program over the coming weeks.

Read The Ontological Dominance Papers and more on the Big House Enterprise website: https://bighouseenterprise.com