What AI SEO is
AI SEO is the work of making your business easy for AI assistants such as ChatGPT, Perplexity, Claude, Gemini and Google's AI answers to find, trust and name when someone asks them a question. Regular SEO tries to get your page a high place in a list of links. AI SEO tries to get your business mentioned, or your page cited, inside the answer the assistant writes. Most of the underlying work is the same: readable pages, specific content and other people vouching for you. What changes is the goal, the way pages get used and the way you measure success.
A classic search engine takes a query, scores pages and shows a ranked list, and a person picks a link. An AI assistant takes a question, finds sources, reads parts of them and writes a reply. It may name a few businesses and cite a few pages, and the person may never click anything. So traditional SEO measures success in rankings and clicks, and AI SEO measures it in whether you are named and how you are described.
You will see the same idea under several names, so here they are in plain words. LLM stands for large language model, the kind of software behind ChatGPT and similar assistants, and LLM SEO means optimizing for those systems. Generative engine optimization, or GEO, means making your content easy for AI systems that write answers to use. Answer engine optimization, or AEO, is the same idea aimed at direct answers. AI search optimization is another common label. They overlap heavily, and our page on GEO vs SEO sorts out the fine differences where they exist.
How AI SEO works: what happens to a question now
To see what AI SEO can and cannot change, follow one question from the person asking it to the business that gets chosen.
First, a person asks a question in full sentences, often with their situation attached. "Plumber near me" becomes "my water heater is leaking and I rent, who should I call." Second, the assistant decides whether it can answer from what it already learned in training or needs to look things up. Many assistants do both, depending on the question. Third, when it looks things up, it runs a search, reads the pages that come back and pulls passages from them. Fourth, it writes a short answer that names a handful of businesses and sometimes links its sources. The person then checks those few names, often by searching for them directly.
The third step is the one that matters for your business. The sources an assistant reads are still web pages, reviews, forum threads and articles that someone wrote and published. Assistants that search the live web tend to read pages that ordinary search already surfaces. So whatever decides which pages rank still decides which pages an assistant ever sees, and AI SEO sits on top of that base rather than replacing it. Our page on how LLMs choose sources goes deeper on that step.
The assistant's choice in step four leans heavily on outside voices. Claude, in one of our own tests, described a company's own description of itself as a lead, not an endorsement. That is the pattern across assistants: they prefer the business that several independent sources describe in the same way, for that exact job.
What AI SEO shares with regular SEO, which is most of it
A lot of marketing around AI SEO suggests a clean break from everything before. There is no clean break. A large share of the work is the same work.
Pages that can be read. If a crawler cannot fetch your page, or your content only appears after heavy scripts run, neither a search engine nor an assistant will see it. Fixing that helps everywhere.
Content that is specific. Vague pages lose in both worlds. A page that says exactly what you sell, who it is for, what it costs to run and what can go wrong is useful to a searcher and quotable by an assistant.
Trust signals. Google has long talked about experience, expertise, authority and trust, which its guidelines call E-E-A-T. Assistants do not publish a score, but they lean on sources that look reliable and are confirmed elsewhere.
Mentions elsewhere. Links from other sites help ranking. Mentions on other sites help an assistant decide you are real and relevant. The same earned attention feeds both.
A sound site. Clean structure, working internal links and fast pages remove friction for any system trying to understand you.
If you have invested in this work over the years, you have not wasted it. The first move in AI SEO is usually to check that the basics are in place, not to throw them out.
What changes from regular SEO
Here is where the two come apart, and where new effort is worth spending.
The unit of success
Traditional SEO asks, "Where do I rank for this keyword?" AI SEO asks, "When someone asks this question, am I named, and what does the answer say about me?" The second is about a sentence, not a position. A written answer names three or four businesses and stops, so there is no eighth place that still gets seen. Fewer slots means a bigger gap between being named and not.
How the page is used
A search engine sends a person to your whole page. An assistant often lifts one passage. That means the first sentence under each heading carries more weight, and a paragraph that only makes sense after three earlier paragraphs is hard to quote.
Where the evidence lives
In traditional SEO, links are the main outside signal. For AI answers, reviews, forum threads, local press and niche guides carry a lot of the load.
How you measure
Rank trackers do not tell you whether an assistant named you. You need to ask real questions, repeatedly, and record the wording of the answers. That is a different habit from reading a rank report.
How much answers vary
A ranking is fairly stable day to day. An assistant's answer can change between two askings of the same question. That makes single screenshots weak evidence and repeated measurement valuable.
One page, read two ways
A concrete example makes the difference easier to see. Imagine a page about choosing a standby generator for a home.
A traditional SEO pass asks whether the page targets a clear phrase, whether the title and headings match what people search, whether the page is fast and whether other sites link to it. It tries to move the page up a list.
An AI SEO pass asks different questions of the same page. If someone asks an assistant what size generator a three-bedroom house needs, is there a sentence on this page that answers it plainly, with the conditions attached? If an assistant lifts only the third paragraph, does that paragraph still make sense? Does the page say who wrote it and why they know? Do outside sources, such as installer forums or a local utility guide, agree with it?
Neither pass is wrong. The first gets the page found. The second gets part of the page used. The practical edit is small: add a one-sentence answer at the top of the section, name the conditions in the same sentence, and keep the long explanation underneath for the person who wants it. That one habit serves a person scanning results and an assistant looking for something to quote.
Who AI picks, and why the biggest brand often loses
Because assistants lean on independent sources, the business that gets named is often not the one with the largest ad budget or the most famous name. It is the one that the most outside sources vouch for, for that specific job.
We saw this ourselves in a small field test of local searches, written up in why AI recommends local businesses over chains. In several categories the assistants named local businesses over national chains, and the sources they leaned on were third-party: review sites, local forums, local blogs and press. The write-up states its limits plainly, so treat it as an observation worth testing in your own market, not a law. The direction is still useful. A smaller business with real reviews and real mentions has a path into the answer that does not depend on outspending anyone.
This is also why the strongest single lever in AI SEO is independent opinion. A business with a polished site and no outside voices is doing half the job.
Will AI replace SEO?
No. Search is changing, and some of the work SEO people do is changing with it. That is a different statement from "search is dying," and mixing the two up leads to expensive decisions in both directions.
People still have questions and still need to find businesses, products and facts. Systems that answer those questions, whether Google's own or an independent assistant, need material to build answers from, and that material is overwhelmingly pages, reviews, forum posts and articles that someone wrote and published. Somebody has to make sure it exists, can be read by a machine and is trustworthy. That job is, at its core, what SEO has always been. The skill of being easy to find is still needed. The skill of being easy to recommend is added to it.
What is genuinely changing
More questions get answered on the results page, so some people get a quick fact or definition without visiting a site. Recommendations come as shorter lists, so the gap between named and not named is bigger. And success is harder to see in a rank report, so new measurement habits are needed. Notice what these have in common. They change how results are shown and measured. They do not change the need for good source material.
Why "SEO is dead" keeps coming back
People have announced the end of SEO for well over a decade, with mobile, voice search, featured answers and social media. Each time the work changed shape and kept going. The claim survives because it is true in a narrow sense every time: specific tricks do die. Stuffing a page with keywords stopped working, and so did buying hundreds of links. It is easy to jump from "that trick is dead" to "the whole field is dead." The claim also sells things, because a headline that says everything changed makes a good pitch for a new service. A fair test for any claim here is to ask where it assumes answers come from. If the answer is "from nowhere, the AI just knows," be wary.
Who feels the change most
Information-only sites feel it first, because short factual questions can be fully answered without a visit, and the response is depth and original material an answer cannot replace. Local businesses may see a shift in who gets chosen, since a person asking for a recommendation gets a short list. Online stores see shoppers putting "best for" and comparison questions to assistants. Businesses with strong brands are less exposed to the click shift, since people already search for them by name, but they still need to be described accurately. If you are not sure which group you are in, compare your impressions and clicks in Google Search Console over the last year. A widening gap may point to answers satisfying readers before they click.
What nobody knows yet
Nobody knows exactly how large a share of searches will move to assistants, or how fast. Early figures often come from people with something to sell. Nobody knows how ads and answers will settle next to each other, or which assistants will dominate in two years, so measuring several is safer than betting on one. And nobody can promise that a given business will be named. Work that makes your business clearly described, well reviewed and widely mentioned is useful under almost any outcome, which is the best reason to start with it.
How to do AI SEO, in order
There is no universal ratio between the old work and the new, but this order suits most small and mid-sized businesses. None of it requires abandoning what already works.
1. Keep the shared base going. Pages, structure, speed and links remain the foundation. If you stop the traditional work, you weaken the pool of pages assistants draw from.
2. Check that AI crawlers can read your site. A single line in your robots.txt file or a security setting can block them without anyone noticing. It is a ten-minute check, and everything else depends on it.
3. Rewrite your key pages answer-first. Take the ten pages that matter most and make the first sentence under each heading a direct answer to the question the heading asks. This is editing, not rebuilding, and it tends to help ordinary search too.
4. Build the outside evidence. Ask real customers for specific reviews, get listed in the directories and niche guides your field uses, and earn local or trade press. This is slow and it counts in both channels.
5. Measure the AI side separately. Write about twenty real buyer questions, ask them in two or three assistants each month, and keep the questions unchanged so you can see a trend. Record who is named and what is said, not only whether you appear.
6. Keep reading your ordinary search data. Impressions, clicks and queries in Google Search Console still show demand and the words customers use.
If you would rather hand this to someone, our guide to choosing an AI SEO agency covers what a fair engagement should include and the warning signs to watch for.
What a sensible first year looks like
In the first month, check crawler access, take a baseline of twenty questions across two or three assistants, look at your Search Console numbers and rewrite your five most important pages. By the third month, you have a steady rhythm of useful new pages aimed at specific jobs and you have asked your best customers for specific reviews. Repeat the baseline and note what changed. By the sixth month, you have earned a few mentions on sites you do not own, completed your listings and started to see which of your pages assistants actually quote. By the twelfth month, you have a year of dated measurements and can decide with evidence where to spend next.
How long each one takes
Traditional SEO usually takes months before a new page settles into a stable position. AI answers move on different clocks depending on the assistant. Some look up the live web and can reflect a change within weeks. Others lean on what they already know and move slowly. Keep the two clocks separate in your head. A flat month in AI answers does not mean ordinary search is failing, and a good month in ordinary search does not prove the AI work is paying off.
How to read an AI answer about your business
Once you start asking assistants your buyers' questions, the answers carry more information than a yes or no. Reading them well is most of the skill in AI SEO, and it costs nothing but attention.
Named or cited. Being named means the assistant wrote your business into the reply. Being cited means it linked to one of your pages as a source. They are different results. A business can be named because review sites praise it while none of its own pages are cited, which points at thin pages. A page can be cited for a fact while the business is never recommended, which points at weak outside evidence.
How you are described. Being named as the budget option, the one with slow shipping or the one that only serves part of a region counts as present in any tally. Only the wording shows it. Copy the full sentence, not a tick in a column.
Who else is named. The other businesses in the answer are your real competition for that question, and they are often not the ones you benchmark against. Look at what they have that you do not. Often it is a single clear page that answers the exact question, or a set of reviews that describe the same strength in the same words.
Which sources it leaned on. Some assistants list their sources. Others need a follow-up question. Either way, note the review sites, forums, guides and articles behind the answer. If you are missing from all of them, no change to your own site will fix that alone.
What it gets wrong. An old address, a discontinued product or a policy you changed usually traces back to a stale source: an old directory entry, an outdated review or a forgotten page on your own site. The fix is correcting the source, starting with the pages you control, not arguing with the assistant.
Ask each question more than once, on different days, and in a logged-out window as well as your own account, since a logged-in assistant may adapt to your history. One answer is a sample. Several answers over a month are a reading you can act on.
Which side matters more for your type of business
The right balance depends on how your customers decide.
Local service businesses. People ask for a recommendation, such as a good plumber nearby, and assistants answer with a short list. Reviews, a complete maps profile and local mentions carry a lot of weight. We cover this in AI SEO for local business.
Online stores. Shoppers ask for comparisons and "best for" answers. Product data, reviews and comparison content matter alongside ordinary category page work. See AI search optimization for ecommerce.
Professional services and B2B. Buyers research longer and ask nuanced questions. Detailed pages, case evidence and being cited by industry sources help most.
Publishers and information sites. You may see the biggest shift in click patterns. Depth and being the origin of facts matter most.
In all of these, the traditional work remains the foundation. The AI work sits on top and rewards specificity.
Mistakes people make with AI SEO
Treating it as either/or. The two share a base. Dropping one to fund the other usually costs more than it saves.
Buying a new service for something an old one already covers. If a supplier's AI SEO proposal is mostly a rename of an existing menu, ask which parts are actually new. Some are, such as tracking answers. Many are not.
Judging it by clicks. An assistant may name you and send nobody to your site that day. A customer may then search your name directly. Judging only by referral clicks understates the effect.
Judging it by one screenshot. Answers vary. One good screenshot is a pleasant moment, not a result, and one bad one is not a verdict either.
Chasing tricks. Hidden text, stuffed question lists and invented credentials fail in both worlds. Systems that read pages carefully tend to notice, and customers certainly do.
Waiting for certainty. Reviews, mentions and clear pages build up over time, so earlier is better. Assistants are still working out what they rely on, and a business that starts building evidence now is not behind in any way that matters.
How RunOctopus does AI SEO
RunOctopus treats the shared base and the AI-specific work as one job, because they depend on the same pages. Our AI, Ollie, and our team research a business, then write, publish and link pages directly on its own website. It works with Shopify, WordPress, WooCommerce and Wix. The business does not have to approve each page first, and we report where ChatGPT, Perplexity, Claude and Gemini name it.
Our All Angles Creatures case study shows both sides of the work on one site. Google clicks over the 28 days to October 10, 2026 were 5,447, up from 3,645 in the 28 days before. On two locked sets of AI questions, the site was the most-cited domain in every answer set, and ChatGPT named the company on 8 of 8 questions shaped like the site's own comparison guides, but only 4 of 8 generic buyer questions. The other case studies keep their misses in too.
To see what Ollie would plan for your site, paste your address into the free site read. No account and no call.
AI SEO is the work of getting your business named and cited in AI answers. It stands on the same base as regular SEO, then adds answer-first writing, outside evidence and measuring the answers themselves.