AI search optimization is the work of making a business findable, quotable and trustworthy to AI search products, so that tools such as ChatGPT and Google AI Overviews name it when someone asks a relevant question. It builds on SEO. The additions are specific: crawler access for each product, pages written so a single claim can be lifted out cleanly, one consistent version of the facts about the business, and credible mentions on other sites.
This is the second of three pillar guides. It covers how the discipline relates to SEO, AEO and GEO, the steps to take now, how to measure with the tools that exist today, and what nobody can honestly promise yet. The first guide covers AI SEO and the use of AI in SEO workflows. The third covers generative engine optimization and how language models retrieve and synthesize content.
What counts as AI search
AI search is any product that answers a question with generated text instead of a list of links, usually with some sources attached. The products behave differently, and lumping them together hides the decisions that matter.
- AI features inside a search engine. Google AI Overviews and AI Mode sit inside Google Search. Google documents that they use a technique it calls query fan-out, issuing multiple related searches across subtopics and data sources, and that supporting links come from pages that are indexed and eligible to show with a snippet.
- Chat assistants with a search mode. ChatGPT and Gemini can answer from what the underlying model learned in training, or fetch live pages, or combine the two, depending on the question and the product settings.
- Answer engines built around retrieval. Perplexity is designed around retrieving sources and citing them next to the answer.
- Assistants answering from memory alone. When no live lookup happens, the answer reflects patterns learned in training. You cannot fix a missing mention there with a page edit today. You influence it by what is published about you across the web over time.
Which surface matters depends on the client. A local service business mostly cares about the first group. A software company selling to researchers may care more about the second and third. Start by asking where the client's buyers actually ask questions, not by optimizing for every product at once.
How does AI search optimization relate to SEO, AEO and GEO?
AI search optimization is the umbrella, SEO is the foundation under it, and AEO and GEO are two overlapping ways of describing the work on top. There is no standards body for these terms, so the definitions below are the working ones I use with agencies. Other practitioners draw the lines differently, which matters when you compare proposals.
| SEO | AEO | GEO | |
|---|---|---|---|
| Goal | Rank and earn organic clicks in classic results | Be quoted or named inside generated answers | Shape the content, entities and outside sources models draw on |
| Unit of success | A ranking position and a visit | A named citation or recommendation for a given question | A mention, with the right facts, across many differently phrased prompts |
| Main levers | Technical health, content relevance, links, local signals | Answer-first page structure, schema, crawler access, consistent facts | Entity clarity, third-party mentions, original information, coverage of related questions |
| Typical deliverable | Technical fixes, content, link and local work | Page rewrites for extraction, FAQ and schema work, citation tracking | Entity and corroboration audit, source mapping, content and outreach plan |
| Measurement | Mature: rankings, clicks, conversions | Early: fixed-prompt citation checks, with high variance | Earliest: sampled mentions and accuracy checks across prompt sets |
| Common failure | Ranking for terms that never convert | Ranking well but having no quotable answer | Inconsistent or thin information about the brand across the web |
A useful way to hold the three together: SEO gets the page into the set of things a system can retrieve. AEO makes a page easy to quote once it is retrieved. GEO deals with the wider picture of what is known and said about the brand, which affects whether the brand appears even when your own page is not the source. For the earlier essay on this distinction, see AI answer engines.
Why a top ranking does not guarantee a citation
A top ranking does not guarantee a citation because ranking and citing are different selections made by different mechanisms. A search engine orders documents. An AI search product has to retrieve candidates, pick passages it can use, and then write an answer, often attributing only some of what it read.
Three consequences follow from that. First, the passage that matters is a few sentences, not the whole page, so a page whose answer is buried or hedged can lose to a lesser page that states the point cleanly. Second, because systems such as Google's issue several related searches for one question, a single page competes on many sub-questions, and breadth of coverage on a topic can matter more than a perfect page on one term. Third, if three pages on one domain give slightly different facts, the system has no clean source to prefer. I covered the extraction problem in more detail in why your best page might never get an AI citation.
Eight steps to take now
The steps below are ordered by how often each one is the blocker and how cheap they are to check. Do them in order.
- Confirm crawler access. Review robots.txt and any bot-blocking rules. OpenAI documents separate crawlers: OAI-SearchBot is used to surface sites in ChatGPT search results, while GPTBot relates to training, and a site can allow one and not the other. Perplexity documents that PerplexityBot is for surfacing and linking sites in search results and is not used to crawl content for foundation models. Decide your policy per crawler on purpose, because a blanket block is a common accident.
- Confirm the content is in the raw HTML. If key text appears only after JavaScript runs, some crawlers will not see it. View the unrendered source of important pages.
- Make every important section answer first. Put the direct answer in the opening sentence, then the explanation. Write headings as the questions a buyer would ask. The test is whether the first sentence still makes sense when quoted alone.
- Fix contradictions. List every fact a buyer might ask about: services, locations, credentials, process, policies. Make sure each is stated the same way on every page and profile you control.
- Use structured data where it fits. Organization, Person, Article and FAQ markup describe facts in a machine-readable form and support other search features. Be accurate about what it does for AI products: Google states there is no special schema.org structured data you need to add to appear in its AI features. Treat markup as a consistency tool, not a lever.
- Add information others cannot copy. Original data, first-hand process detail and named experts give a system something specific to attribute. Research on generative engines points the same way: in the authors' benchmark study of generative engine optimization, adding quotations and statistics produced the largest relative gains on one visibility metric, and repeating target phrases produced little to no improvement. That is one academic test, not a guarantee for any commercial product.
- Earn corroboration. Mentions on credible third-party sites, directories that buyers and models both read, and consistent profiles help the brand appear as an entity others describe. This takes weeks to months and cannot be rushed.
- Cover the neighboring questions. Because answers draw on multiple sub-questions, publish pages for the related questions a buyer asks before and after the main one, and link them together sensibly.
An AEO audit walks through steps one to five on a real site and ranks the findings by effort and expected impact.
Diagnosing a client who is not mentioned
Start from the symptom, because the first check differs. The table below is the order I would investigate in.
| Symptom | Likely cause | First check |
|---|---|---|
| Not in any AI answer, and weak in classic search | Foundational SEO problems | Indexing status, crawl errors, thin or duplicate pages |
| Ranks well, never named in AI answers | Answer not extractable, or no corroboration | Is there a plain one-sentence answer? Are there third-party mentions? |
| Named, but with wrong facts | Conflicting or outdated information across the web | Compare your pages, profiles and directory listings against each other |
| Named in one product, absent in another | Different crawlers, different sources | Crawler access per product, and which sources each product tends to cite |
| Competitor named instead | Better corroborated or more clearly described | Read the sources the product cites for that question and compare them with your own pages |
Measuring with a prompt panel
You measure it with a fixed panel of prompts that you repeat on a schedule, and you read the results as a trend, not a score. Nothing in the market is as settled as rank tracking, and anyone who presents a single visibility number as exact is simplifying.
A workable panel has these parts:
- Prompts. Ten to thirty real buyer questions per client, grouped by stage: problem awareness, comparison, and selection. Include different phrasings of the same question.
- Repeats. Run each prompt several times on each product, because the same prompt can return different answers. Record how often the brand appears, not only whether it appeared once.
- Fields. For each run, note whether the brand is mentioned, whether your domain is cited, the position in the answer, whether the facts are correct, and which competitors and sources appear.
- Context. Note the product, mode, location and date. Results differ by all of these.
- Baseline. Run the panel before any changes so there is something to compare against.
On the classic side, Google states that traffic from its AI features is included in the overall search traffic in Search Console, within the Web search type of the Performance report. Referrals from other AI products can appear in analytics, but how they are labeled depends on the product and your setup, so check your own data before reporting a number.
What nobody can promise yet
Several things cannot be promised honestly today, and an agency that promises them is taking on risk it cannot control.
- A specific citation, position or date. Products decide independently and change without notice.
- A reliable share-of-voice figure. Sampling and prompt choice change the number.
- Attribution of revenue to a specific AI mention. Referral labeling is inconsistent and many answers produce no click.
- Permanence. A mention gained under one model version can disappear under the next.
What can be promised is the work: a documented audit, a prioritized list of fixes, completed changes, and a repeatable measurement panel with a baseline. That is a fair basis for a scope.
Prioritizing when capacity is tight
Prioritize by what blocks the most downstream work. Crawler access and indexability come first because every other step depends on them. Fixing contradictions comes next because it is cheap and prevents the system from having to choose between your own pages. Answer-first rewrites should start with the five to ten pages that match the questions your client's best buyers ask, not the whole site. Third-party corroboration starts early because it is slow, but it should not delay the on-page work. A short written plan with those four tracks, an owner for each, and a date for the first measurement run is more useful to a client than a long list of recommendations.
Packaging AI search optimization as an agency
Package it as an audit first, then a defined improvement phase, then ongoing monitoring. An audit gives the client a clear picture and gives you a fixed scope before open-ended work begins. The improvement phase covers the page, entity and corroboration changes. Monitoring keeps the panel running and flags changes in the products.
If your team does not have the capacity or the experience for this, the delivery can be handled for you. I run white label work for agencies through an in-house team, under the agency's brand. The details are on the white label services page, and the AEO version in particular is described at white label AEO. To compare the SEO, AEO and GEO audits side by side, see the audit services overview.
Summary
AI search optimization is mostly strong SEO plus a handful of extra checks, an editing pass for quotability, a clean set of facts and patient work on third-party corroboration. Products differ and keep changing, measurement is directional, and outcomes cannot be promised. The agencies that handle this well are the ones that scope it as defined work, measure it with a baseline, and report it with the caveats attached.
FAQ
What is AI search optimization?
AI search optimization is the work of making a business findable and citable by AI search products such as ChatGPT, Gemini, Perplexity and Google AI Overviews. It builds on SEO and adds crawler access, answer-first page structure, consistent facts and credible third-party mentions.
Is AI search optimization the same as AEO or GEO?
They overlap, and the terms have no formal standard. I use AI search optimization as the umbrella, AEO for getting cited inside answers, and GEO for shaping the content, entities and corroboration that language models draw on. Other practitioners draw the lines differently.
Do I need special schema markup to appear in Google AI Overviews?
Google states that no special schema.org structured data is needed to appear in its AI features, and that there are no additional requirements beyond being indexed and eligible to show with a snippet. Structured data can still help consistency and support other search features.
How do I measure AI search visibility?
Use a fixed panel of real buyer prompts, run each several times per product, and record mentions, citations, accuracy and competitors. Repeat on a schedule against a baseline. Read the results as a trend, because the same prompt can produce different answers.
How long does AI search optimization take to work?
No honest timeline exists. Technical and editing changes can be completed in weeks, but whether any product starts citing the brand depends on its own crawling, sources and model updates. Third-party corroboration usually takes months, so promise the work and the measurement, not a date.