Do AI Overviews Benefit Search Engines? An Ecosystem Perspective

TL;DR

This paper examines how AI Overviews impact search engine ecosystems, proposing game-theoretic models and mechanisms to balance user experience, creator incentives, and long-term profitability.

Contribution

It introduces a game-theoretic framework for creator competition with effort costs and designs incentive mechanisms to sustain search engine profits.

Findings

AI Overviews can harm long-term search engine profit.

Citation and monetary reward mechanisms can mitigate profit loss.

Proposed interventions improve long-term profitability in realistic scenarios.

Abstract

The integration of AI Overviews into search engines enhances user experience but diverts traffic from content creators, potentially discouraging high-quality content creation and causing user attrition that undermines long-term search engine profit. To address this issue, we propose a game-theoretic model of creator competition with costly effort, characterize equilibrium behavior, and design two incentive mechanisms: a citation mechanism that references sources within an AI Overview, and a compensation mechanism that offers monetary rewards to creators. For both cases, we provide structural insights and near-optimal profit-maximizing mechanisms. Evaluations on real click data show that although AI Overviews harm long-term search engine profit, interventions based on our proposed mechanisms can increase long-term profit across a range of realistic scenarios, pointing toward a more sustainable trajectory for AI-enhanced search ecosystems.