What is Answer Engine Optimization (AEO)?

AEO is the practice of increasing your brand's visibility, mentions and citations within AI-generated answers.

• AEO is about increasing the likelihood that your brand is understood, retrieved, cited and mentioned inside AI-generated answers.
• It overlaps heavily with SEO. Strong content, technical accessibility, topical authority and links still matter, but AEO puts more emphasis on entities, third-party mentions and answer-level visibility.
• AEO is not a guaranteed ranking system. There is no fixed #1 position in ChatGPT, and different prompts can produce different answers.
• The commercial opportunity is bigger than AI referral traffic alone. AI systems can influence which vendors enter a buyer's consideration set before that buyer ever visits a website.
• The strongest strategy is not publishing more generic AI content. First-hand expertise, original evidence, clear entities and credible mentions across the web create a stronger information advantage.
• For most B2B companies, AEO should sit inside one broader organic strategy across AI Search and traditional search rather than operate as a completely separate discipline.

What does AEO mean?

AEO stands for Answer Engine Optimization.

AEO is the practice of increasing your brand's visibility, mentions and citations within AI-generated answers.

In other words, you optimize your website, content and presence across the web so that platforms such as ChatGPT, Gemini, Perplexity and Google’s AI search experiences can better understand your company and expertise.

For a B2B company, the goal is quite practical. When your potential customers use AI to research a problem, compare solutions or find companies, you want to be part of the answer.

What are you actually optimizing with AEO?

AEO isn't simply about adding questions and answers to your website. From our experience, the work sits across several areas that marketers will already recognize:

• Content — answering the questions your ICP actually asks.
• Topical authority — covering the subjects you want your company to be associated with.
• First-hand information — adding expertise, opinions, case studies, data and experience that don't exist everywhere else.
• Brand and entities — making it clear who your company is, what you do and what you're an expert in.
• Off-site authority — earning relevant mentions and citations from sources other than your own website.
• Technical foundations — making sure search engines and AI crawlers can discover and understand your content.

This is also why we don't see AEO as an entirely new marketing discipline. A lot of it overlaps with SEO, content, digital PR and brand building. What's changing is where that information is being discovered and used.

Can you actually influence what ChatGPT and other AI engines say?

Yes, but influence doesn't mean that you can directly control what an AI system says. It means you can shape the information and signals those systems use when forming an answer—through your website, third-party mentions, customer evidence, expert content and other authoritative sources.

There is no fixed number-one position in ChatGPT. Two people can ask almost the same question and receive different answers depending on the prompt, conversation context, information retrieved and the AI system being used.

What you can influence is whether these systems:

• understand what your company does;
• associate your brand with the right topics and categories;
• find evidence that supports your expertise;
• retrieve or cite your content;
• encounter your company on other authoritative sources;
• and ultimately mention your brand for questions that matter to your business.

We've seen enough from our own AI Search work to believe that this visibility isn't completely random. But we also don't believe anyone can honestly promise to “rank your company #1 in ChatGPT.”

A better way to describe what we're doing is:

We systematically increase the likelihood that AI search engines understand, retrieve, cite and mention a brand for commercially relevant questions.

That distinction matters. AEO can be influenced and measured, but it can't be controlled in the same way as changing an ad campaign or bidding on a keyword.

What does AEO look like in practice for a B2B company?

Imagine a B2B SaaS company that sells workforce planning software to companies with 500+ employees. Traditionally, its marketing team might optimize a landing page for a keyword such as “workforce planning software.”

But an AI search can be much more specific. A potential customer might ask:

“We're a 1,500-person European company currently doing workforce planning in Excel. We need better forecasting and integration with our HR systems. What software should we consider?”

The company now wants to appear not only for one keyword, but across the different questions and situations that lead someone towards its product. That could include:

• alternatives to Excel for workforce planning;
• workforce forecasting software;
• headcount planning tools;
• comparisons with Workday or Anaplan;
• implementation and integration questions;
• costs and ROI;
• recommendations for companies of a specific size or industry.

This is where AEO becomes particularly interesting for B2B marketers. AI search allows buyers to describe their actual situation instead of reducing it to a two- or three-word search query. This is partly enabled by mechanisms such as query fan-out, where an AI search experience can break a broader question into multiple related searches before constructing an answer.

If your company repeatedly appears when someone researches those problems, compares possible solutions and asks which vendors they should consider, AI can introduce your brand before that buyer has ever visited your website.

And that, in our opinion, is the real opportunity with AEO. The goal isn't to collect ChatGPT mentions for a dashboard. It's to get your company into the consideration set when the right buyer is researching what to do next.

So why is AEO even important for B2B marketers?

Because AI is starting to sit between the buyer and the companies they eventually evaluate. A buyer no longer has to open ten search results, visit ten websites and create a shortlist from scratch. They can describe their company, problem, requirements and constraints in a conversation and ask an AI system to help narrow down the options.

That doesn't mean Google is disappearing. It means there is now another discovery layer that can influence which companies make it onto the shortlist in the first place.

The difference is easiest to see like this:

For us, that last point is particularly important. AI Search can influence a buying decision without necessarily sending a measurable referral visit to your website. A buyer can learn your name, see you recommended several times and only visit your website later through branded search or a direct visit.

Is there actually evidence that AEO matters?

Yes, although we think the evidence is often presented badly. There are really three separate questions: are people using AI for search and discovery, can that usage create commercial value, and can marketers actually influence which sources or brands appear?

The answer to all three questions is increasingly yes, although there are still important limitations. AI referral traffic remains much smaller than traditional organic search for most websites, and we don't think the available evidence supports claims that “SEO is dead” or that every company should suddenly shift its search budget into AEO.

Our view: AI Search is still a relatively small acquisition channel by direct traffic, but a potentially much larger influence channel during research and consideration.

Are people actually using AI for search and discovery?

Yes. Google has said that AI Overviews increased usage by more than 10% for the types of queries where they appear in major markets such as the US and India, while also reporting that people ask longer and more complex questions in its AI search experiences.

Independent datasets point in the same direction. Ahrefs reported roughly 9.7× year-over-year growth in AI referral traffic across approximately 82,000 websites in one study. At the same time, Semrush found that AI referrals still represented less than 0.15% of total web traffic in its dataset.

Both can be true. AI Search can be growing extremely quickly while still being much smaller than Google. We think B2B marketers should be able to hold those two ideas at the same time instead of choosing between “AI changes everything” and “AI traffic is too small to matter.”

Ahrefs reported the 9.7× year-over-year increase in its analysis of approximately 82,000 websites, while Semrush found that AI referrals accounted for less than 0.15% of total web traffic in its dataset. Google has also reported that AI Overviews increased usage by more than 10% for the types of queries where they appear in major markets such as the US and India, alongside longer and more complex questions in its AI search experiences.

Does AI Search actually generate B2B customers?

There is evidence that it can. Ahrefs reported that only 0.5% of its visitors came from AI Search in one analysis, while those visitors accounted for 12.1% of signups. In its dataset, an AI Search visitor was 23× more likely to convert than a traditional organic-search visitor.

That's interesting because Ahrefs is itself a B2B SaaS company, but we would put a very large asterisk next to the 23× figure. It is one company's dataset. It does not prove that AI traffic converts 23× better for B2B companies in general.

The more defensible conclusion is simpler: AI assistants can generate commercially valuable B2B acquisition, and some of those visitors may arrive unusually far into their research process. Someone can spend ten minutes discussing requirements, alternatives and vendors with an AI before they ever click through to a company website.

Can AEO actually change which content appears in AI-generated answers?

There is experimental evidence that content and source characteristics can affect generative-search visibility. Researchers from Princeton and other institutions introduced Generative Engine Optimization in a 2023 paper and tested different optimization methods across a benchmark they called GEO-bench.

Some interventions increased visibility in their experiments by up to 40%, although the effectiveness differed by topic and optimization method. That does not mean adding a statistic to your landing page will make modern ChatGPT recommend your company 40% more often.

What the research does support is the more modest—and more useful—conclusion that visibility in generative answers isn't necessarily random. The information you publish and the characteristics of the sources containing that information can affect whether it gets surfaced.

What does Google itself say about optimizing for AI Search?

Interestingly, Google doesn't prescribe a completely separate “AEO playbook.” Its guidance for appearing in AI Overviews and AI Mode largely points website owners back toward familiar search fundamentals: useful and original content, crawlability, page experience, structured data that matches visible content, strong media and accurate business information.

We think that's an important reality check. AEO isn't a magical technical layer that suddenly replaces everything marketers already know about organic search. Much of the work combines SEO, content, brand authority, entity building, digital PR and first-hand expertise—but applies those inputs to a new way of discovering and synthesizing information. Our broader AI Search guide explains how these systems fit into the wider search landscape.

So is AEO actually legit?

In our opinion, yes. The behaviour exists, it can be measured, there is evidence that AI systems influence discovery and acquisition, and there is evidence that visibility can be influenced.

What we don't think is established is the neat industry playbook being sold around it. Nobody has a universal formula that guarantees citations in ChatGPT, Gemini, Perplexity and Google AI. These systems work differently, change quickly and can produce different answers to very similar questions.

That's why we're comfortable saying AEO is real, while being much more skeptical when someone claims they have cracked the algorithm for ranking in ChatGPT.

AEO vs. GEO vs. AI Search: what the hell is the difference?

This is where we think the industry has made something relatively simple unnecessarily confusing.

AEO, or Answer Engine Optimization, historically describes optimizing information so that an answer engine can understand and surface an answer. The idea predates the current generative-AI boom and has been associated with featured snippets, voice assistants and other direct-answer experiences.

GEO, or Generative Engine Optimization, became more prominent after researchers introduced the term in the 2023 GEO paper. It is generally used more specifically for optimization aimed at generative systems that synthesize information into an answer.

And then there are terms such as LLMO, AI SEO and AI Search Optimization, which describe overlapping versions of essentially the same marketing problem.

Do marketers really need separate AEO and GEO strategies?

We don't think so.

You can absolutely draw a theoretical distinction between an answer being extracted and an answer being generated. But from a B2B marketing perspective, the practical work overlaps enormously: publish useful information, demonstrate expertise, build topical and brand authority, make entities clear, earn credible mentions elsewhere and make your information accessible to machines.

Our opinion: the distinction between AEO and GEO is technically defensible but mostly unnecessary for marketers.

We currently use AEO because it is a term people understand and search for. If we had to choose the clearest description of the discipline itself, we'd probably choose AI Search Optimization. It says what we're actually trying to improve without creating another acronym for every variation of an AI-generated answer. If you want the deeper terminology distinction, our GEO Agency page explains how we think about Generative Engine Optimization commercially.

What's the difference between SEO and AEO?

SEO and AEO overlap heavily, but the output you're optimizing for is different. Traditional SEO primarily tries to earn visibility for pages in search results. AEO also tries to make your information and brand usable inside the answer itself.

We therefore don't see AEO as a replacement for SEO. For most B2B companies, the sensible strategy is to build one strong organic foundation that can perform across traditional search and AI Search. For companies looking for external support, our AEO Agency page explains how we structure that work in practice.

Why simply publishing more AI-generated content isn't an AEO strategy

Generative AI has made producing acceptable informational content extremely cheap. That also means another generic article explaining “10 benefits of workforce planning” creates very little information advantage when thousands of companies can produce something similar in minutes.

This is why we think first-hand information becomes more important, not less. That can mean proprietary data, customer examples, named expert commentary, original research, screenshots, experiments, benchmarks, strong opinions or simply explaining what you have learned from doing the work repeatedly.

A useful test we increasingly apply to content is:

Could an LLM have written this without knowing anything about our company, customers or experience?

If the answer is yes, the content might still be useful, but it probably isn't doing much to establish why your company should become a source on the subject.

Why third-party mentions matter more than your own website alone

Your website is naturally going to say that your company is good at what it sells. That's useful for explaining your proposition, but it isn't the only information available to an AI system.

AI engines can encounter your company through publications, customer websites, partner pages, directories, reviews, research, communities and other independent sources. For that reason, part of our AEO work increasingly happens outside the client's website: understanding which sources appear around commercially relevant prompts and identifying where credible third-party visibility can realistically be built.

This leads to a question we think is more useful than “How do we optimize this page for ChatGPT?”

What does the web collectively say about our company, and does it consistently associate us with the topics and problems we want to be known for?

How do we measure AEO if there isn't a fixed ranking?

You can't reduce AEO to one ranking position, so we think measurement needs to happen across a defined set of commercially relevant prompts. The exact metrics depend on the company, but we typically care about things such as:

• Brand mentions — how often the company appears in relevant AI answers.
• Citation share — how often the company's pages are used as sources.
• Share of voice — how visibility compares with relevant competitors.
• Prompt coverage — which commercial questions the company does and doesn't appear for.
• Source domains — which third-party websites AI engines repeatedly use when answering those questions.
• AI referral traffic — visits that can be attributed directly to AI platforms.
• Commercial outcomes — leads, signups and pipeline where AI Search can be identified as part of the journey.

None of these metrics is perfect in isolation. Prompt results can vary, attribution is incomplete and AI platforms keep changing. But together they give marketers something much more useful than occasionally opening ChatGPT, typing their favourite prompt and celebrating when their company appears.

What we've learned from working on AI Search for B2B companies

The biggest lesson for us so far is that AEO is much broader than optimizing individual pages. The companies that are easiest for AI systems to understand tend to have a clear proposition, substantial coverage of their area of expertise, evidence supporting their claims and consistent signals about who they are across their own site and the wider web.

We've also become increasingly skeptical of isolated AEO “hacks.” Adding schema can be useful. Making answers easier to extract can be useful. An llms.txt file may have specific uses. But none of those things compensates for a company that has thin content, no real expertise on the page and almost no independent authority around the topics it wants to own.

Our approach has therefore moved towards the bigger picture: what questions does the ICP actually ask, what does the company genuinely know, what evidence can we publish, where does the brand need to be mentioned, and how do we make all of those signals consistent?

What do we think happens next with AEO?

We don't know which acronym will win, and we don't think that matters very much. The more important change is that search is becoming conversational, contextual and increasingly capable of synthesizing information before a buyer reaches a company's website.

That makes organic visibility broader than rankings. B2B marketers will still care about Google rankings, traffic and conversions, but they'll increasingly also need to understand whether their company exists inside the answers buyers receive while researching a market.

The companies that start building that authority now don't need to bet that Google disappears or that every buyer moves to ChatGPT. They only need to believe that AI will play a meaningful role in some part of the B2B research and buying journey. We think the evidence for that is already strong enough.

So what is the actual goal of AEO?

For us, the goal isn't to collect citations or screenshots showing that ChatGPT mentioned your company. Those are useful signals, but they're not the business outcome.

The real goal is much closer to traditional marketing: be present when the right customer is forming an opinion about their problem and deciding which companies or solutions deserve further consideration.

If your ICP increasingly uses AI during that process, you want your expertise to be understood, your content to be usable and your company to have a realistic chance of appearing in those answers.

That's why we take AEO seriously. Not because we think it replaces SEO, and not because we've found a secret way to manipulate ChatGPT, but because the way B2B buyers discover and evaluate companies is changing—and we want the companies we work with to be visible wherever that research happens.

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