AI Agents and the Attention Lemons Problem in Two-Sided Ad Markets

TL;DR

This paper presents a theoretical model analyzing how autonomous AI agents in two-sided advertising markets cause externalities that reduce revenues and efficiency, proposing a fee mechanism to mitigate these effects and prevent market collapse.

Contribution

It introduces a formal 'attention lemons' externality model in digital advertising markets and proposes a Pigouvian fee to internalize the externality and improve market outcomes.

Findings

Delegation to AI agents lowers ad prices and revenues.

Toll fees for AI agents outperform blocking strategies.

Market collapse occurs beyond a critical delegation threshold.

Abstract

I develop a theoretical model to examine how the rise of autonomous AI (artificial intelligence) agents disrupts two-sided digital advertising markets. Through this framework, I demonstrate that users' rational, private decisions to delegate browsing to agents create a negative externality, precipitating declines in ad prices, publisher revenues, and overall market efficiency. The model identifies the conditions under which publisher interventions such as blocking AI agents or imposing tolls may mitigate these effects, although they risk fragmenting access and value. I formalize the resulting inefficiency as an ``attention lemons" problem, where synthetic agent traffic dilutes the quality of attention sold to advertisers, generating adverse selection. To address this, I propose a Pigouvian correction mechanism: a per-delegation fee designed to internalize the externality and restore welfare. The model demonstrates that, for an individual publisher, charging AI agents toll fees for access strictly dominates both the `Blocking' and `Null (inaction)' strategies. Finally, I characterize a critical tipping point beyond which unchecked delegation triggers a collapse of the ad-funded digital market.