AI Search Optimization: AEO, GEO and LLM SEO Explained

For most of search history the job was simple to describe, even if it was hard to do: rank. Now there is a second job stacked on top of it, which is getting quoted. A meaningful share of searches now end inside an answer, whether that answer is a Google AI Overview, a ChatGPT reply, or a Perplexity summary with six little citation chips underneath. The click still exists. It just has competition.

This guide covers what genuinely changes when a machine reads your page before a human does, and what stays exactly the same. The short version: almost everything in our SEO strategy guide still applies. What changes is packaging, entity clarity, and how heavily you lean on one traffic source.

What AI search actually is

It helps to be precise, because the category gets described as one thing when it is really three.

Answer layers inside traditional search. AI Overviews sit above the classic results on Google. They are generated, but they are grounded in pages Google has already crawled and ranked. Bing does the same thing in a slightly different wrapper.

Assistants that search. ChatGPT with browsing, Perplexity, Gemini and Copilot run their own retrieval, read a handful of pages, and synthesise. The user sees prose plus links. These products are search engines with a different interface and a much smaller results set.

Models answering from memory. When no search happens, the model answers from what it absorbed during training. There is no citation, no crawl, and no way to influence it this quarter. This is where brand mentions across the wider web quietly do the work.

Those three surfaces reward slightly different things, which is why the acronyms multiplied.

AI search vs traditional search

	Traditional search	AI search
Result set	Ten blue links per query	One answer, three to eight sources
Query style	Short keywords	Long, conversational, often multi-part
What wins	The best page for the query	The most extractable, verifiable passage
Traffic shape	Position one takes the bulk	Fewer clicks, higher intent when they come
Measurement	Rank, clicks, impressions	Citation share, brand mentions, referrals

The most important row is the second one. People type differently when they expect a conversation. Instead of "eor india cost" they write "how much does it actually cost to hire one engineer in India through an EOR versus setting up a subsidiary". Long queries have almost no search volume individually, which means keyword tools underrepresent them badly. Aggregate they are enormous.

That has a practical consequence for content planning. Pages built around one exact-match keyword tend to underperform on these surfaces. Pages built around a question and its obvious follow-ups tend to win. Our content strategy guide goes deeper on structuring clusters that way.

AEO: answer engine optimization

AEO is the oldest of the three ideas, and it predates generative AI by years. Anyone who ever optimised for a featured snippet has done AEO. The goal is to be the source used for a direct answer.

The mechanics are unglamorous and they work:

• Answer in the first two sentences. Put the direct answer immediately under the heading that asks the question, then expand. Extraction systems reward proximity between question and answer.
• Use the question as the heading. Not "Pricing considerations" but "How much does an EOR cost in India?" Machines match phrasing.
• Keep answer paragraphs to 40 to 60 words. Long enough to be complete, short enough to lift whole.
• Give numbers, dates and units. "Roughly 12 to 15 percent of gross salary, as of mid 2026" beats "varies depending on provider".
• Use lists and tables for comparisons and steps. Structured formats get reused far more often than prose walls.

GEO: generative engine optimization

GEO is the newer discipline, and it is aimed at the assistants. The distinction that matters is that generative surfaces synthesise from several sources at once, so you are not trying to beat nine other results. You are trying to be one of the five things the model reads and trusts.

What appears to move the needle:

• Being present in the source pool. Assistants lean heavily on a small set of trusted domains plus whatever the retrieval query surfaces. If you do not rank in the top 20 for the underlying query, you are usually not in the room.
• Original data. Models gravitate to specific claims they cannot get elsewhere. A survey of 400 companies, a pricing benchmark, a set of processing times. This is also the highest-yield input for digital PR, which makes it double duty work.
• Clear attribution language. Sentences that name the source inside them ("According to Wisemonk's 2026 India hiring benchmark, ...") survive summarisation. Anonymous claims get absorbed without credit.
• Consistency across the web. If three sites describe your pricing three different ways, a model has no reason to trust any of them.
• Recency signals. Visible last-updated dates and current-year figures. Assistants downweight content that reads stale.

LLM SEO and how models describe your brand

LLM SEO is the loosest term of the three. Most people use it to mean influencing what a model says about you when no live search happens, which is largely a function of how the open web talks about your category.

You cannot edit a model's weights, but you can change what it reads next time. Three levers actually work:

1. Get mentioned in the places that get scraped. Industry publications, comparison sites, G2 and Capterra style directories, Reddit and Quora threads, YouTube transcripts, Wikipedia adjacent references. Volume of independent mentions correlates with a model volunteering your name.
2. Own a clear category sentence. Pick one description of what you do and repeat it everywhere, verbatim, for a year. Models learn patterns, and inconsistency is noise.
3. Publish the comparison content yourself. "X vs Y" and "best tools for Z" pages get read constantly by retrieval systems. If you never publish an honest comparison, someone else defines you.

AI Overviews

AI Overviews deserve their own treatment because they sit directly on top of the traffic you already have. A few things worth knowing:

They appear most often on informational and definitional queries, and much less on transactional ones. If your money pages target "buy", "pricing" or branded terms, exposure is lower than the panic suggests. If your traffic is top of funnel explainers, exposure is high.

The sources cited are usually, but not always, pages already ranking on page one. Getting cited without ranking happens, and it tends to happen on pages with a very clean answer to a very specific sub-question.

Impressions typically hold while clicks fall. That combination in Search Console is the clearest fingerprint that an Overview has landed on one of your query clusters. Segment by query type before you conclude anything, because a sitewide average will hide it.

The defensive move is not to fight the Overview. It is to shift some of your content investment toward queries where an Overview cannot substitute for the page: comparisons, calculators, templates, pricing, case studies, anything where the user needs your actual thing.

Optimising for specific engines

ChatGPT

Retrieval is powered by a search index, so classic rankings matter as a qualifying step. Two crawlers to know: OAI-SearchBot handles retrieval for live answers, and GPTBot handles training collection. They are separate user agents in robots.txt, so you can allow one and disallow the other. Blocking the retrieval bot removes you from citations, which is rarely what a marketing team wants. Answers skew toward well-structured pages with obvious headings, and toward brands with strong presence on review and community sites.

Perplexity

The most citation-hungry of the group, and the most generous with links. It reads more sources per answer than the others, which makes it the easiest place to earn a first citation. It also weights freshness heavily. If you update a guide and want a quick read on whether the update registered, Perplexity usually reflects it first. Its crawler is PerplexityBot.

Claude

Claude's web search cites sources inline and tends to favour primary documentation, official pages and technical depth over listicles. Long-form content that holds a coherent argument survives its summarisation better than content assembled from subheadings. ClaudeBot is the crawler to keep in mind.

Gemini

Closest to Google's own ranking behaviour, unsurprisingly, and it shares grounding infrastructure with AI Overviews. Practically, optimising for Google organic and optimising for Gemini are close to the same project. Structured data, entity clarity in your Knowledge Graph footprint, and a healthy technical foundation carry over directly. Our technical SEO guide covers the crawl and rendering side that all of this depends on.

Earning AI citations

Citations are not distributed randomly. Looking at what actually gets cited, a few patterns repeat:

• Statistics pages. A single page collecting well-sourced numbers on a topic gets cited relentlessly, because it is the fastest path to a defensible claim.
• Definitions with edge cases. Not just what a term means, but when it does not apply.
• Process documentation. Numbered steps with realistic timelines and requirements.
• Comparison tables. Structured, hedge-free, with the tradeoffs stated plainly.
• First-hand experience. "We processed 1,200 of these last year and here is what went wrong" cannot be synthesised from other sources, so it survives.

The pattern underneath all five is verifiability. Machines that have to stand behind an answer prefer sources that make the answer checkable.

Structured data for AI

Schema markup will not force a citation, but it removes ambiguity, and ambiguity is what causes a model to attribute your data to someone else. Worth implementing, roughly in priority order:

• Organization with sameAs links to your profiles, plus logo, founding date and location. This is your entity anchor.
• Article or BlogPosting with author, datePublished and dateModified that reflect reality.
• FAQPage on pages that genuinely answer discrete questions.
• Product or Service with real pricing where you can disclose it.
• LocalBusiness if you have physical presence, which connects to the work in our local SEO guide.
• Author markup with credentials, tied to a real author page.

Keep it consistent with what the page says. Markup that contradicts visible content is worse than no markup.

Brand mentions as the new backlink

Here is the shift that most teams have not internalised yet. Language models do not need a hyperlink to learn that you exist. An unlinked mention in a trade publication teaches a model exactly as much as a linked one, and for the generative surfaces it may count for more.

That changes what a PR win looks like. A paragraph in an industry newsletter with no link used to be a consolation prize. Now it feeds the corpus. If you are tracking only referring domains, you are measuring half your authority. Track mentions, sentiment and the phrasing used to describe you, alongside links.

Where this is heading

Three predictions I would put money on, and one I would not.

Confident: informational query volume will keep drifting away from ten blue links, and transactional volume will not. Confident: measurement will get worse before it gets better, because assistants leak far less referrer data than search engines do. Confident: brand becomes a bigger share of the outcome, because when there is one answer instead of ten links, being the named default matters more than being the tenth result.

Not confident: that any of the current acronyms survive. AEO, GEO and LLM SEO describe overlapping work that will probably fold back into "SEO" once the novelty wears off. Optimise for the mechanics, not the vocabulary.

Best practices, condensed

1. Answer the question in the first 60 words under every heading that asks one.
2. Write headings as the questions people actually type.
3. Put a real, visible last-updated date on every guide and keep it honest.
4. Publish original data at least twice a year, even small studies.
5. Keep entity descriptions identical across your site, profiles and press.
6. Allow retrieval crawlers unless you have a specific reason not to.
7. Ship Organization, Article and FAQPage schema, and keep it truthful.
8. Track brand mentions, not only backlinks.
9. Shift some content investment toward pages an answer cannot replace.
10. Check monthly what the major assistants say when asked to recommend a provider in your category.

None of that is exotic. It is the same craft, aimed at a reader who happens to be a machine that will paraphrase you in front of your next customer.