Ask a language model about your industry and it will answer confidently, naming companies, describing what they do, and making implicit judgements about who is worth mentioning. It did not consult a ranking to do that. It answered from an internal picture assembled from everything it has absorbed about your space, and your brand either features in that picture accurately, features in it wrongly, or does not feature at all.
That is a different problem from ranking a page, and it needs a different way of thinking. LLM SEO is not about winning position one for a query. It is about shaping what the models understand to be true about you, so that when your category comes up, you are described correctly and credibly. Slower, less controllable, and increasingly the thing that decides whether you are considered at all.
What LLM SEO actually means
Traditional SEO optimises a page against a query: match the intent, earn the authority, win the position. LLM SEO works a layer beneath that. It is concerned with the model's representation of your brand as an entity, what you are, what you do, who you serve, and whether you are credible, formed from a huge body of text rather than from any page you control.
The practical consequence is that you cannot optimise your way to a good representation with one great page. What shapes the picture is the accumulated weight of everything that exists about you across the web, and how consistent it is. That makes LLM SEO closer to reputation management than to page optimisation, and it rewards a very different set of habits.
Be an entity, not just a website
Models think in entities and relationships: this company does that, serves those customers, belongs in this category, is associated with these people and products. Being understood well means being a clearly defined entity with consistent connections, not just a collection of pages that happen to rank.
That means describing your business the same way everywhere it appears, being unambiguous about your category and what you actually do, and making sure the associations you want are visible in more than one credible place. A brand that describes itself differently on every profile, page, and listing gives models a blurry, contradictory picture, and blurry entities get left out of confident answers.
Consistency is the strongest lever
If there is one practical lever in LLM SEO, it is consistency of information. When the same clear facts about your business appear repeatedly across many credible sources, models absorb that as settled. When sources disagree, or when your own site says something different from your profiles and third-party listings, the model has to pick, and it may pick wrong or hedge you out of the answer entirely.
This is unglamorous work: aligning how you are described across your site, directories, profiles, and press, keeping details current, and correcting stale descriptions that no longer match what you do. It is the closest thing to a direct input you have, and most brands have never audited it once.
Credibility still decides who gets repeated
Models are built to avoid saying things that are wrong, so they lean on sources and entities that appear reliable. Being mentioned and described by credible places, industry publications, respected sites, genuine coverage, carries far more weight in shaping your representation than anything you publish about yourself.
This is why the durable strategy for AI visibility looks a lot like the durable strategy for everything else: do work worth referencing and be present where your industry is discussed. Self-description is a weak signal; being independently described the same way by people with standing is a strong one.
Make yourself readable to machines
The technical layer still matters, because retrieval-based AI systems reach your content through much the same plumbing search engines use. If crawlers cannot access your pages, if your structure is confusing, or if key facts are locked inside images and scripts, you are harder to read and easier to skip. Clean structure and honest structured data help machines resolve what your pages are about.
You may also see advice about llms.txt, a proposed file for pointing AI systems at your most useful content. It is cheap to add and harmless, but adoption is early and it is not a lever that carries a strategy. Treat it as tidiness, not tactics, and put the effort into the content and consistency that actually move the picture.
Watch how you are described
You cannot manage what you never look at, and most brands have no idea what models say about them. The starting point is simply asking: put the questions your buyers would ask to the major AI systems and read what comes back. Are you mentioned? Is the description accurate? Is it current, or is it repeating something that stopped being true two years ago?
Doing that regularly turns a vague worry into a tractable problem, because wrong or missing information usually traces back to a source you can influence. That monitoring loop is central to how we approach AI visibility, since the gap between how you describe yourself and how models describe you is the most useful map of what to fix.
How we approach it
We start by finding out what the models currently say about a brand and where that picture came from. Then we work on the inputs: making descriptions consistent everywhere the brand appears, strengthening the entity and its associations, earning credible third-party mentions, and keeping the technical foundation clean so retrieval systems can read the site properly.
That approach is what we bring across more than 500 brands in the US, UK, and Canada. As a global company with our headquarters in Delaware and teams in London and Gurugram, the aim is consistent: a brand that AI systems understand accurately and mention confidently, rather than one that quietly gets described wrong or left out.
Where this leaves you
LLM SEO is not a replacement for search optimisation but a layer above it, concerned with what models believe about you rather than where a page ranks. Be a clearly defined entity, describe yourself consistently everywhere, earn credible mentions from places that carry weight, stay readable to machines, and monitor what the models actually say. None of it is a trick, and all of it compounds, which is fortunate, because as more buying journeys start with a question to an AI rather than a search box, being understood correctly stops being optional. If you want to know how AI currently describes your brand, tell us your category and we will show you what is out there and what is worth fixing.
Frequently Asked Questions
What is LLM SEO?
LLM SEO is the work of shaping how large language models understand and represent your brand, rather than only how search engines rank your pages. Traditional SEO optimises a page for a query; LLM SEO optimises the model's underlying picture of who you are, what you do, and whether you are credible. That picture comes from what exists about you across the web, not from any single page you control, which makes it a broader and slower discipline than page-level optimisation.
How is LLM SEO different from answer engine optimization?
They are close relatives working at different layers. Answer engine optimization focuses on being the source quoted when an AI answers a specific question, which is largely about clarity and retrievable content. LLM SEO is about the model's general understanding of your brand, the associations it has formed and repeats even without looking anything up. One is about winning a citation in the moment; the other is about being represented accurately whenever your category comes up.
Can you influence what an AI model says about your brand?
Not directly, and anyone promising control is overselling. You influence it the same way reputation works: by what exists about you across the web and how consistent it is. Models learn from a broad body of text, so consistent, accurate information about your brand in credible places shapes what they absorb, while contradictory or absent information leaves them to guess or rely on stale sources. It is influence over time, not a setting you can change.
What is an llms.txt file?
It is a proposed convention, similar in spirit to robots.txt, where a site publishes a plain file summarising what it offers and pointing to its most useful content for AI systems. Adoption is still early and it is not a guaranteed ranking factor in any system. It is cheap to add and can help machines find your important content, but treat it as a small, optional tidy-up rather than a strategy. The substance still comes from clear content and real credibility.
Does traditional SEO still matter for AI visibility?
Very much so. AI systems that retrieve live information lean heavily on the same signals search engines use, so crawlability, clean structure, and authority still determine whether you are reachable and trusted. Traditional SEO is the foundation, not a competing discipline. LLM SEO adds a layer on top of it, concerned with consistency of information and how your brand is described across the web, but it does not replace the fundamentals that get you found in the first place.
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