AI SEO agency: understand the category, then choose the right work

AI-search visibility is the work of making your business clear, credible and citable when customers ask an answer engine for advice. The answer engine might be Google AI Overviews, Google AI Mode, ChatGPT, Perplexity, Gemini or Copilot. The terms around it are messy: AEO, GEO, LLM SEO, answer-engine optimisation, generative-engine optimisation and AI-search optimisation all overlap. The useful question is simpler: when a buyer asks the machine who to consider, does your business appear, and is the answer accurate?

This page is the category and agency-intent page. It explains what AI-search optimisation is, what it is not, how it connects to SEO, and when you should move from education to measurement. If you already want the productised audit that checks where you appear today across named prompts and engines, use the GEO / AI-visibility audit. The audit page is the service. This page is the explanation and decision point.

The distinction matters. If every page tries to target every phrase, the site competes with itself and the reader gets a muddled offer. Here, “AI-search visibility” and “AI SEO agency” describe the broad category: the work of being understood and cited by answer engines. “GEO / AI-visibility audit” describes the measured audit service: prompts, engines, gaps and a fix list. They are connected, but they are not the same title or the same intent.

What is AI-search optimisation?

AI-search optimisation is the practical work that helps answer engines understand, trust and cite your business. It starts with ordinary SEO: crawlable pages, indexable content, clear titles, structured data where it is genuinely useful, and helpful pages that answer real questions. Then it adds answer-shaped content: concise explanations near the top of the page, question-led headings, cited claims, FAQ pairs and consistent entity signals across the places an AI system may consult.

AEO usually means answer engine optimisation: shaping content so it answers the question directly. GEO usually means generative engine optimisation: shaping content so generative systems cite it in their answers. LLM SEO is a looser market phrase for visibility in tools built on large language models. We use the labels only when they help a buyer find the right page. The work itself is not a vocabulary contest.

There is also a technical boundary worth stating. Existing site content cites Google’s own guidance that there are no special additional requirements for appearing in AI Overviews or AI Mode: pages need to be indexed and eligible for standard Google Search with a snippet. That makes SEO the foundation, not a competing channel. If your page cannot be crawled, indexed or understood in ordinary search, an AI-search package will not save it.

How do you rank in AI search?

There is no single “AI search ranking” to optimise for. Google AI Overviews, ChatGPT, Perplexity, Gemini and Copilot do not all use the same retrieval system or cite the same sources. Our GEO page already carries the useful evidence: an AuthorityTech-reported analysis of 680 million citations found only about 11% of domains cited by ChatGPT were also cited by Perplexity. Treat that figure as directional rather than universal, but the lesson is sound: a tactic that helps one engine may not help another.

For Google AI Overviews, standard SEO is central. The existing GEO page cites Ahrefs’ July 2025 analysis of 1.9 million citations across 1 million AI Overviews, which found 76.1% of AI Overview citations came from pages already in Google’s top 10. That leaves some room for pages outside the top 10, but the foundation is still strong organic visibility.

For ChatGPT and Perplexity, the page has to be understandable and corroborated. Existing site content describes ChatGPT as favouring encyclopedic, well-sourced content and sources that appear consistently across trusted platforms, while Perplexity leans harder on recency and community-validated sources such as trade press, niche directories and discussion forums. We reuse that framing with the same caveat: these are operating patterns, not a public ranking formula.

The practical answer to “how do I rank in AI search?” is therefore not “add one magic file.” It is:

1. Make the page technically eligible: crawlable, indexable, fast enough, and not blocked.
2. Make the answer explicit: put a direct answer in the opening section and structure the page around real questions.
3. Cite claims properly: named sources, dates and caveats where the evidence is early or sector-specific.
4. Build entity consistency: the same business name, services, locations and proof across your site and trusted third-party profiles.
5. Measure real prompts: check whether answer engines cite you for the questions buyers actually ask.

Who this is for

This is for a business that can feel demand shifting but needs a sober route through the hype. You may have heard “AI SEO agency,” “AEO agency,” “GEO agency” or “LLM SEO” and be trying to work out whether they are separate services. Usually they are not. They are overlapping ways to describe being cited in AI-generated answers.

It is most useful for professional services, B2B suppliers, e-commerce categories with research-heavy buying journeys, and any business where customers shortlist before they buy. If someone asks an AI assistant “who should we use for X?”, “what is the best way to solve Y?” or “which suppliers should we compare?”, you want your expertise to be available as a source.

It may be a poor fit if your immediate problem is local map visibility or product-data readiness. Existing GEO content notes that local-service searches had low AI Overview exposure in a cited SeoProfy snapshot, and for many trades the better first move is Google Business Profile, reviews and local SEO. If your issue is shopping-agent readiness for product discovery and checkout, our agentic commerce page is the better fit.

What you get

The first deliverable is clarity. We map the terms and the buying questions so you know whether you need SEO foundations, answer-shaped content, the productised GEO audit, or product-data work. That matters because the wrong service can look impressive and still do nothing useful.

Then we inspect the foundation. For Google AI Overviews, a page has to be eligible for standard search. That means crawlability, indexing, snippet eligibility, sensible internal links and a page that actually answers the query. We check the same basics a good SEO engagement checks, because AI-search visibility rests on them.

Next, we reshape the content. The existing GEO page cites the Princeton and IIT Delhi GEO study from KDD 2024, which found optimisation methods could lift visibility in AI-generated responses by up to around 40%, with strong levers including well-attributed statistics, authoritative sources, expert quotations and clear readable writing. We do not treat that as a promise for your site. We use it as evidence for the page anatomy: answer first, source claims, structure by questions and avoid keyword stuffing.

Finally, we decide whether to measure. If the question is “where do we appear today?” the right next step is not another explainer page. It is the GEO / AI-visibility audit, which checks named prompts across ChatGPT, Perplexity, Gemini and Google AI Overviews and turns the gaps into a fix list.

How it works: inputs to outputs

The input is your current search footprint: service pages, guides, case studies, profiles, reviews, technical SEO status, Search Console data and the questions buyers ask before they contact you. The output is a prioritised plan for AI-search visibility, with the category jargon translated into work you can actually approve.

First, we define the prompts. We do not start with keywords alone, because people ask AI tools full questions. “AI SEO agency” is a search term. “How do I rank in AI search?” is a question. “Who should I shortlist for Shopify AI-search visibility?” is an agency-intent prompt. We group these by buyer stage, not by buzzword.

Second, we check whether your pages deserve to be cited. That is an editorial and technical question. Are they specific? Do they answer directly? Do they explain who the service is for and who it is not for? Do they cite evidence where they make factual claims? Are they thin compared with the question being asked? A page that only says “we help you show up in AI” is not a source; it is an advert.

Third, we fix the shape. The U12 service anatomy used across this site is deliberate: what it is, who it is for, what you get, how it works, price anchor, proof and next step. That structure helps the reader, but it also makes the page easier for answer engines to parse. We add FAQs where they are useful because FAQ pairs give both people and structured-data systems a clean question and answer.

Fourth, we separate education from audit. This page can explain AEO, GEO and LLM SEO. It should not pretend to be the full measured visibility audit. The audit belongs on the GEO / AI-visibility page because that is where the service promise sits: check the prompts, compare the engines, show the gaps, and prioritise the fixes.

What has actually changed?

The honest answer is “research and shortlisting are changing faster than final purchase.” Existing site content cites a two-stage pattern from UK practitioner guidance: AI engines increasingly influence research and shortlisting, while maps, direct search and ordinary checkout still own much of the booking or buying stage. That is a calmer picture than “Google is dead,” and it is more useful.

The traffic picture is also early. The GEO page states that AI referral traffic is roughly 1% of all web referrals, with ChatGPT making up about 87% of that, citing Conductor as reported by Search Engine Land in 2025. It also cites Similarweb measuring ChatGPT referral conversion at 7.1% in May 2026, and Visibility Labs finding ChatGPT traffic converted 31% higher than non-branded organic search across 94 e-commerce brands in 2025. Those figures are useful because they have caveats attached: small volume, early-stage measurement, and a heavy e-commerce skew.

For shopping queries specifically, existing site coverage cites Visibility Labs analysis reported by Search Engine Land: Google AI Overviews appeared on 14.0% of shopping queries by March 2026, up 5.6 times from 2.1% in November 2025, across 20.9 million shopping keywords. That is not proof that every business needs a full AI-search retainer today. It is evidence that the answer surface is material enough to prepare for.

Price anchor

AI-search work can be a one-off education and content-structure project, part of a broader SEO and content plan, or the front door into the GEO / AI-visibility audit. The right shape depends on how much foundation work already exists and whether you need measurement across engines.

See the current pricing and engagement options.

Proof, without pretending we have magic access

The proof for AI-search optimisation has two layers. The first is third-party evidence: Google’s published position on AI Overview eligibility, the Ahrefs citation analysis already cited on the GEO page, the Princeton and IIT Delhi GEO study, and the published AI-referral and shopping-query figures reused above. Those sources support a cautious conclusion: strong SEO, answer-shaped content and cited claims matter; unsupported shortcuts do not.

The second layer is our own public proof. We will not invent testimonials or claim private results this page cannot show. See the live proof library at /case-studies. Where AI-search case studies are not yet published, we leave the proof slot honest and rely on the work’s inspectable quality: cited pages, clear structure, measured prompts and no fabricated rankings.

What happens next?

If you are still deciding what the category means, start here. We will identify the questions your buyers ask, show where your current content is thin, and tell you whether the right next move is SEO foundations, answer-shaped content, product-data work or a visibility audit.

If you already know you want measurement, go straight to the GEO / AI-visibility audit. That page is deliberately titled differently because it sells the audit service, not the category explanation. The audit checks your current presence across target prompts and engines, then gives you the fix list.

Either way, the work starts from evidence. No guaranteed ChatGPT rankings, no “AI hack” language, no invented proof. Just a clear answer to where your business should be cited, whether it is cited now, and what is worth fixing first.