AI SEO Agency for Category Leaders

AI SEO is search engine optimization extended to the AI-powered surfaces buyers now use alongside Google: ChatGPT, Gemini, Google AI Overviews and AI Mode, and Perplexity. It covers the classic work (technical foundations, content, authority) plus the newer engineering problems those systems introduce: retrievable passage structure, entity resolution, and presence in the third-party sources AI answers cite. Buyers also reach this discipline under the names generative engine optimization (GEO), answer engine optimization (AEO) and AI search optimization.

Some of what's sold as AI SEO is just SEO rebranded, and you're right to be suspicious of it. The honest version: a real overlap exists, because AI systems retrieve from the same indexed web Google ranks, so the foundations carry over. What's genuinely new is the shape of the problem: answers assembled from passages rather than lists of pages, corroboration weighed across third-party sources, and a measurement job (who gets named, cited and recommended, per query, per surface) that classic rank tracking never had to do.

Our rule: we tell you which parts of the program are proven SEO fundamentals and which are newer, evidence-in-progress work. Our research program tests the newer parts in the open instead of asking you to take them on faith.

An AI SEO agency runs one program across both surfaces of modern search. On the Google side: technical SEO, architecture, commercial content and authority: the demand-capture work described on our Organic Search page. On the AI side: visibility baselines against competitors, passage and structure engineering, entity clarity, and campaigns for presence in the sources AI systems cite. The two halves share foundations, budget and measurement, which is why splitting them across separate vendors mostly buys duplicated work and divided accountability.

AI SEO works in four steps, and each one is measured before the next one gets budget.

• Map the demand. List the commercial questions your buyers actually ask, in their words, and sample them across Google and the AI surfaces. That list becomes the query universe every later number is measured against.
• Make the site retrievable. Important pages have to be crawlable by search engines and AI agents, indexed, and written so a single passage answers a single question without leaning on the rest of the page.
• Build corroboration. AI systems weigh what other sources say about you. Consistent entity signals, plus accurate presence on the review sites, publishers and comparison pages that get cited in your category, are what turn a mention into a recommendation.
• Measure recommendation share. Track whether you are retrieved, mentioned, cited and recommended against named competitors, then tie the movement to branded demand, traffic and pipeline.

Traditional SEO and AI SEO share their foundations and part ways on what gets optimized and what a win looks like.

AI SEO does not replace SEO. It extends the same search infrastructure into systems that retrieve passages, resolve entities and assemble one answer from several sources. How far the two surfaces diverge depends on the category, which is why we measure both instead of assuming either.

AI SEO, GEO, AEO and LLMO are close enough that buyers use the terms interchangeably. The differences are in emphasis:

• AI SEO is the umbrella term for optimizing across Google and AI search as one program.
• GEO (generative engine optimization) focuses on visibility inside the answers ChatGPT, Gemini, AI Mode and Perplexity generate. It is covered in the GEO agency services section below.
• AEO (answer engine optimization) focuses on structuring content so a system can lift a direct answer from a single passage. It is covered in the AEO agency services section below.
• LLMO (large language model optimization) frames the same work around the models themselves, including how they describe your brand when nobody asks about you by name.
• AIO is ambiguous. Some vendors mean AI optimization in general, others mean Google AI Overviews specifically. Ask which one before you sign.

We use AI SEO for the combined program because the work spans Google rankings, AI retrieval, entity understanding, source authority and recommendation measurement. Splitting it by acronym mostly splits the budget. For a deeper comparison, read our guide to GEO vs SEO.

Our AI search agency services make a brand visible, accurately described and recommended across ChatGPT, Gemini, Google AI Overviews and AI Mode, and Perplexity. AI search optimization, also called AI search engine optimization, spans retrievable content structure, entity and schema signals, presence in the third-party sources AI systems cite, and ongoing measurement of how often and how favorably the brand appears in real answers. It builds on traditional SEO rather than replacing it, because AI systems draw on the same indexed web.

You optimize for ChatGPT and AI Overviews by engineering the four inputs those systems demonstrably respond to: content structured so passages can be retrieved and quoted; entity signals that resolve the brand unambiguously; corroborating coverage in the third-party sources each surface repeatedly cites; and a crawlable, indexable technical foundation. Then you sample real queries on a schedule and let the measurements tell you which interventions moved the answer.

The intent quality justifies the work: in Seer Interactive's case study, ChatGPT referral traffic converted at 15.9% against 1.76% for Google organic on the same site. The channel is small. The buyers in it are not browsing. See how we measure AI recommendations →

High Salience works as an LLM SEO and AI visibility agency for B2B software companies: we measure which brands ChatGPT, Google AI Overviews and AI Mode name for your buyers' questions, then change the sources those answers are built from. LLM SEO covers how a large language model learns about your brand, from its training data and from the pages it retrieves live when a buyer asks; our LLM SEO guide explains both routes. AI visibility is the measurement side: how often you are named, recommended and cited on a fixed set of buyer questions, reported as a range across repeated pulls rather than a single reading.

Our generative engine optimization (GEO) agency services shape how ChatGPT, Gemini, Google AI Overviews and AI Mode, and Perplexity include, cite and recommend your brand in the answers they produce. GEO is the practice of structuring digital content and managing a brand's wider web presence for those systems, and it works on three fronts at once: content machines can retrieve and quote, entity signals machines can resolve, and third-party sources machines already trust.

A GEO agency measures how generative systems currently answer a market's commercial questions, then engineers the inputs those answers are built from. In practice that means benchmarking brand visibility against competitors across the AI surfaces, restructuring content so its passages can be retrieved and quoted, consolidating the entity signals that let machines resolve the brand, and winning accurate presence in the third-party sources those systems cite. The output is not a report about AI. It is movement in the answers your buyers actually see.

Is generative engine optimization a real thing?

Yes, generative engine optimization is real, with an honest caveat. Generative answers are demonstrably influenced by measurable inputs: whether content can be retrieved and extracted, whether the brand resolves as a clear entity, and how often trusted third-party sources corroborate it. Those inputs can be engineered, and the results can be measured by sampling real queries over time. What is not real is guaranteed placement. Any GEO agency promising specific citations in a system it doesn't control is describing a slot machine as a vending machine.

How we measure GEO performance

We measure GEO performance with the same inspectable measurements on every engagement, sampled against a fixed query set:

• Recommendation share: the portion of category answers that name you
• Mention and citation frequency: how often you appear, and how often documents representing you get cited
• Competitive share of answer: your presence measured against named competitors, not in isolation
• Description accuracy and sentiment: whether the systems say what a good salesperson would say
• AI referral traffic and assisted pipeline: the revenue trail, from your own analytics and CRM

Our answer engine optimization (AEO) agency services structure a brand and its information so AI systems (ChatGPT, Gemini, Google AI Mode and AI Overviews, Perplexity) can retrieve it, understand it, corroborate it and cite it when they assemble an answer. Where traditional SEO competes for a position in a list of links, AEO competes for presence inside the answer itself: the shortlist, the definition, the recommendation a buyer receives without ever seeing a results page.

SEO earns rankings on the classic results page; AEO earns citation and recommendation inside AI-generated answers. The two are not rivals. Answer engines draw heavily on the same indexed, crawlable, authoritative web that Google ranks, so strong SEO is usually a precondition for strong AEO. The difference is the unit of competition: SEO optimizes pages, AEO optimizes passages, entities and the third-party sources answer engines treat as evidence. For a fuller side-by-side, read our AEO vs SEO guide.

Answer engine optimization services at High Salience run in five steps, from mapping answer demand to remeasuring the answers and attributing what moved.

The case for a single AI SEO agency is consolidation: Google rankings and AI answers run as one program, not two.

Separate SEO and GEO agencies will happily sell you the same foundations twice: an SEO retainer for the rankings and a GEO retainer for the answers, each agency optimizing the same pages, chasing the same sources and reporting into different decks. Because both surfaces draw on one indexed web, the split buys duplicated technical work, divided accountability and two vendors pointing at each other when a number moves the wrong way. A single AI SEO program removes the seam: one query universe, one authority strategy, one measurement system, one throat to choke.

The split can still make sense at enterprise scale, where an in-house team owns classic SEO and buys AI-surface specialization on top. We work both ways, and we published a comparison of how the agencies in this market actually position, price and disclose so you can judge the vendors for yourself: see how the AI search agency market compares →

Our AI SEO statistics come from research that runs 100 commercial questions per software category through ChatGPT with web search, codes every answer against a fixed rulebook, and pulls Google's top ten for each question as a control. Twenty-one categories are published so far, each with its dataset. Three findings that shape how we run AI SEO:

Every number above links to its teardown and dataset. The full series lives on our AI search research hub.

These are the AI SEO questions buyers ask us most often, answered plainly.

Does AI SEO replace traditional SEO?

AI SEO contains traditional SEO rather than replacing it. The rankings still carry most commercial intent, and the AI systems assembling answers retrieve from the same indexed web those rankings live on. AI SEO keeps the classic work (technical foundations, content, authority) and extends it with retrieval structure, entity clarity and source presence. Dropping traditional SEO to chase AI answers would starve the layer the answers are built from.

Is AI SEO a one-time project or an ongoing program?

AI SEO mixes one-time projects with an ongoing program. The foundations can be projects: a technical fix, a passage restructure, an entity cleanup all ship and stay shipped. The measurement and the source layer are ongoing, because the systems keep changing and competitors keep publishing. Most clients run a scoped program reviewed quarterly against the baseline, and we're direct about which parts have finished paying for themselves.

What's included in an AI SEO audit?

Instead of a generic AI SEO audit, High Salience delivers the Category Salience Brief: your commercial query universe sampled across Google and the AI surfaces, competitor visibility and recommendation share, the sources shaping your category's answers, retrievability and entity gaps on your own domain, and a ranked intervention plan. Verdict first, evidence attached, scoped before any retainer is discussed.

Does AI SEO require changing our whole website?

AI SEO rarely requires changing your whole website. The changes it does require concentrate where the commercial queries point: the pages that carry definitions, comparisons and proof for your category. Those get rewritten so each one answers its questions plainly, with clean entity signals; the rest of the site mostly needs technical hygiene. The intervention plan is ranked by expected payoff so you change the twenty pages that matter instead of the two hundred that don't.

Do keywords still matter in AI SEO?

Keywords still matter in AI SEO. Buyers still type and speak queries, and the keywords in them decide which pages get retrieved in the first place. What changed is what happens next: AI systems resolve those words to entities and pick passages that answer the specific question. Keyword research tells you what to answer; entity and passage work decide whether your answer gets used.

What content performs best in AI search?

Pages perform best in AI search when they answer a buyer's question in a passage that stands on its own: clear definitions, honest comparisons, published pricing, named methodologies, original data and specific use cases. In our research, being well known got brands named, while a clear stated use case is what got them chosen.

How do you measure AI SEO results?

We track AI SEO results as a chain: is the brand retrieved, mentioned, cited and recommended for the queries that matter, and does that movement show up in branded demand, traffic and pipeline? Each step is reported against named competitors on the same query set, with the raw answers attached, so no single score has to be taken on trust.

Which AI engines does High Salience optimize for?

High Salience optimizes for these core surfaces on every engagement: Google AI Overviews and AI Mode, ChatGPT, Gemini and Perplexity. Claude and Copilot are added where they are commercially relevant to your buyers. Coverage is weighted by where your buyers actually are rather than spread evenly for a dashboard. The full tracking approach is documented on our AI search visibility capability page.

Can an agency guarantee ChatGPT recommendations?

An agency cannot guarantee ChatGPT recommendations. These are systems no agency controls, and a guarantee of placement in them is a sales tactic, not a service. What can be guaranteed is the process: a measured baseline, engineered inputs, scheduled remeasurement and full visibility into whether recommendation share is moving. That evidence trail is the honest version of a guarantee.

Do I need GEO if I already rank first in Google?

Ranking first in Google helps, but you may still need GEO: a top ranking does not guarantee inclusion in generative answers. Generative systems retrieve passages and weigh corroborating sources, so a top-ranked page with unextractable structure, weak entity signals or no third-party corroboration can still be skipped. The reverse also holds: well-structured, well-cited brands can appear in answers without holding the top organic position.

Can we do GEO in-house?

Parts of GEO can be done in-house: retrievable content structure and schema are execution work a strong team can own. What is hard to replicate in-house is the measurement infrastructure and the source intelligence: sampling real answers at scale, isolating what moved after a change, and knowing which third-party sources actually get cited in your category. That intelligence layer is where we spend most of our time.

Is AEO the same as featured snippet optimization?

AEO grew out of featured snippet work but has outgrown it. Featured snippets were one answer surface on one engine; AEO now covers the full set of systems that assemble answers, from AI Overviews and AI Mode to ChatGPT, Gemini and Perplexity. The craft carried over: self-contained, extractable answers under question-shaped headings. The measurement and the source layer are new.

Can AEO fix how AI systems describe my brand?

AEO can frequently fix how AI systems describe your brand, because those systems assemble brand descriptions from retrievable sources. When systems describe a brand inaccurately, the cause is usually stale or conflicting information in the documents they draw on. Correcting the entity signals on your domain and the third-party sources machines keep citing changes the raw material the description is built from. It takes recrawl-and-refresh time, and we track the wording as we go.

The cost of our AI SEO services starts at $7,500/month for a strategic engagement. Most category-wide engagements fall between $10,000 and $20,000/month; larger multi-market, multi-product and execution-heavy programs are scoped separately. Every engagement starts with the $750 Category Salience Brief, credited against the engagement: your market's evidence first, the scope priced from it.