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AEO (Answer Engine Optimization, in the paper “Agentic Engine Optimization”) is the discipline of ensuring brands are included and favorably positioned within AI-generated responses. A Stanford GSB paper by Bliey & Chatwin (SSRN, Jul 2026) frames the field; the terms GEO (Generative Engine Optimization), AEO, GAIO, and LLMO are used largely interchangeably in the industry. Key arguments from the paper (Jul 2026):
  • AI-mediated search grew from under 10% of search interactions in 2023 to roughly 30% by early 2026 (citing First Page Sage), fragmenting search across general-purpose platforms and specialized assistants.
  • The unit of value is shifting from the click to the synthesis. In agentic search, inclusion depends less on domain authority or paid placement and more on whether a brand survives retrieval, grounding, and cross-source validation inside LLM systems.
  • The “Perfect Click”: a click arriving from an AI recommendation is confirmatory, not exploratory — the decision is substantially made — so one AI-mediated recommendation can be worth more in conversion terms than hundreds of unqualified impressions.
  • Expected rank across the distribution of users becomes the relevant metric, not static rank on a common results page, because outputs are non-deterministic and personalized.
The mechanics the paper builds on — passage-level retrieval, query fan-out, reranking — are covered with measured data in How AI search chooses passages and What is a query fan-out. Source: Answer Engine Optimization: How Agentic AI Reshapes SEO, Miles Bliey & Keira Chatwin, Stanford GSB (SSRN), Jul 2026.