Impact of AI Search Summaries on Website Traffic: Evidence from Google AI Overviews and Wikipedia
This provides early causal evidence that generative-answer features in search engines can reallocate attention away from informational publishers, with implications for content monetization and policy.
The study estimated the causal impact of Google's AI Overview (AIO) on Wikipedia traffic, finding that exposure to AIO reduces daily traffic to English articles by approximately 15%, with larger declines for Culture articles compared to STEM.
Search engines increasingly display LLM-generated answers shown above organic links, shifting search from link lists to answer-first summaries. Publishers contend these summaries substitute for source pages and cannibalize traffic, while platforms argue they are complementary by directing users through included links. We estimate the causal impact of Google's AI Overview (AIO) on Wikipedia traffic by leveraging the feature's staggered geographic rollout and Wikipedia's multilingual structure. Using a difference-in-differences design, we compare English Wikipedia articles exposed to AIO to the same underlying articles in language editions (Hindi, Indonesian, Japanese, and Portuguese) that were not exposed to AIO during the observation period. Across 161,382 matched article-language pairs, AIO exposure reduces daily traffic to English articles by approximately 15%. Effects are heterogeneous: relative declines are largest for Culture articles and substantially smaller for STEM, consistent with stronger substitution when short synthesized answers satisfy informational intent. These findings provide early causal evidence that generative-answer features in search engines can materially reallocate attention away from informational publishers, with implications for content monetization, search platform design, and policy.