AI Search & AEO FAQs — AEO Updates
Plain-English answers to the questions people ask about AI search, Answer Engine Optimisation, citations, visibility and evidence.
Frequently asked questions
What is Answer Engine Optimisation?
Answer Engine Optimisation, or AEO, is the practice of making useful information easy for AI-powered search and answer systems to find, understand and represent accurately. It focuses on the quality of the answer a person receives, not only the position of a link in a conventional search result.
Does AEO replace SEO?
No. AEO builds on many of the same foundations as SEO, including crawlability, useful content, clear structure and trusted references. The difference is that AEO also asks whether a brand or source is represented accurately when an AI system synthesises an answer, comparison or recommendation.
Explore the State of AEO 2026 · Read the sources and methodology
How do AI systems decide which sources to cite?
There is no single public formula. Different systems use different retrieval, ranking and synthesis methods. In practice, a source is more useful when it is accessible, specific, well structured, current where freshness matters, and supported by credible evidence or independent corroboration.
Can a brand improve how it appears in AI answers?
A brand can improve the information environment an answer system encounters. That means publishing clear source material, resolving factual inconsistencies, making important claims easy to verify, and earning credible third-party corroboration. No one can guarantee an individual answer or recommendation.
Why might a relevant brand be absent from an AI answer?
Absence can have several causes. A system may not retrieve the brand, may not have enough reliable information to include it, may prefer another source for the specific prompt, or may frame the category differently from the brand’s own positioning. The first task is to distinguish eligibility for inclusion from preference once included.
Read the eligibility versus preference diagnostic · Browse related analysis
How should a team measure AI visibility?
AI visibility is the frequency and quality with which a brand or source appears in relevant AI answers. Measure it with a stable, documented prompt set that reflects real research and decision moments. Test across the relevant systems at a regular interval, preserve the full responses and citations, and separate inclusion, recommendation position, factual accuracy and source attribution rather than collapsing them into one score.
Read AEO Updates research · Explore the methodology · Browse the AEO Providers Directory
Which metrics matter beyond AI referral traffic?
Referral visits are useful, but they do not show every answer in which a brand appears. Teams should also examine inclusion rate, citations or linked sources, top-recommendation rate, share of voice within a defined prompt set, factual accuracy and the quality of any downstream referral engagement.
Do schema, robots.txt and llms.txt guarantee AI visibility?
No. These tools can help clarify a site’s structure and access policy, but they do not guarantee crawling, indexing, citation or inclusion in an AI answer. They work best as part of a broader foundation of useful information, internal links, source quality and technical accessibility.
Are paid AI placements the same as organic recommendations?
No. Paid placements and organic answer content are distinct systems, even when they appear near the same decision moment. A useful measurement programme keeps paid exposure, organic representation, citations and referral outcomes separate so that one is not mistaken for evidence of the other.
Follow the ChatGPT Ads Watch · Read the AI Search Chronology
What is changing for publishers as AI search grows?
Publishers are testing new approaches to licensing, retrieval, attribution and direct product experiences as answer systems reshape how audiences discover reporting. The practical question is not simply whether content is used by AI, but how evidence, access, referral value and commercial terms are governed.
Read the publisher-response analysis · Browse publisher and platform coverage
What does AEO Updates cover?
AEO Updates covers the systems changing how brands and publishers are retrieved, represented and recommended. That includes platform changes, source-led research, evidence frameworks, AI search measurement and the commercial implications of the answer layer.
How does AEO Updates handle evidence?
AEO Updates distinguishes observed evidence, interpretation and hypothesis. Research coverage links material claims to primary documentation or original reporting where available, identifies limitations, and discloses relevant affiliations or publication updates.
Read the sources and methodology · Read the editorial policy