The Rise of AI Search: Implications for Information Markets and Human Judgement at Scale

2026-02-13

AI Summary

This study investigates how the rapid proliferation of AI-powered search is reshaping the global information ecosystem, incentives for information production, and human judgment mechanisms. Through 24,000 queries across 243 countries, it presents the first large-scale empirical comparison between AI and traditional search in terms of information coverage, source diversity, and credibility. Findings reveal that Google’s AI Overviews expanded from 7 to 229 countries within a year, with AI-generated responses to COVID-related queries surging by 5,600%. AI search significantly compresses long-tail information sources, reduces response diversity, and more frequently surfaces low-credibility content with right-leaning or neutral political slants. The results uncover embedded geographical inequities, information centralization, and political biases in AI platform policies, systematically elucidating their profound implications for the structure of information markets and public cognition.

Technology Category

• Philosophy and Ethics of AI: Bias, Fairness & Equity
• Search and Optimization: Learning to Search
• Humans and AI: AI for Accessibility

Application Category

• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines
• Economics, Online Markets and Human Computation: Research challenges in human and human-AI computation
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

We executed 24,000 search queries in 243 countries, generating 2.8 million AI and traditional search results in 2024 and 2025. We found a rapid global expansion of AI search and key trends that reflect important, previously hidden, policy decisions by AI companies that impact human exposure to AI search worldwide. From 2024 to 2025, overall exposure to Google AI Overviews (AIO) expanded from 7 to 229 countries, with surprising exclusions like France, Turkey, China and Cuba, which do not receive AI search results, even today. While only 1% of Covid search queries were answered by AI in 2024, over 66% of Covid queries were answered by AI in 2025 -- a 5600% increase signaling a clear policy shift on this critical health topic. Our results also show AI search surfaces significantly fewer long tail information sources, lower response variety, and significantly more low credibility and right- and center-leaning information sources, compared to traditional search, impacting the economic incentives to produce new information, market concentration in information production, and human judgment and decision-making at scale. The social and economic implications of these rapid changes in our information ecosystem necessitate a global debate about corporate and governmental policy related to AI search.

Problem

• AI search
• information markets
• human judgement
• information diversity
• policy implications

Innovation

• AI search
• information ecosystems
• algorithmic policy
• search bias
• global information exposure