The rules of search have changed more in the past year than in the previous decade. Ranking #1 in Google is no longer the sole goal, but rather a step in a more complex user journey.
Your buyers are now researching, comparing vendors, and making purchase decisions across multiple platforms, including AI answer engines such as ChatGPT, user forums, and Google. More than ever before, they may decide on a vendor without ever visiting their website.
That shift not only changed how we look at organic visibility, but also spawned various new acronyms: AEO, GEO, GSO, LLM SEO. Currently, each one means different things to different people because the "SEO" space is moving faster than the taxonomy.
We don't want to contribute to the confusion, so we will define the terminology and how we understand it before we dive in. We treat AEO (answer engine optimisation) and GEO (generative engine optimisation) as the same thing. The distinction some practitioners draw between them is semantic, not strategic. We will explain why below.
What matters for B2B marketers is simpler than the acronym debate suggests. Search now happens across three surfaces:
- Google and its AI features: AI Mode and AI Overviews.
- AI answer engines like ChatGPT and Perplexity.
- User-generated content on platforms like G2 and Reddit.
- Social media platforms, especially LinkedIn.
Each surface has different optimisation inputs. All three are active in the same buying journey. Your organic B2B strategy should cover all of them.
What changed in search
The classic path was linear: buyer searches a keyword → Google returns results → buyer clicks a blue link → visits your website.
The zero-click discovery path looks different: buyer uses an AI tool → encounters your brand in a LinkedIn or Reddit discussion → recognises the brand → searches for it directly.
Classic path
Zero-click path
Google remains the dominant entry point. 91% of global searches still start there, and 71% of B2B buyers begin their research with a Google search.
But what happens inside that search is changing fast. In B2B tech categories, AI Overviews now trigger on 82% of queries, meaning the buyer gets a synthesised answer before they ever click a link. And 85% of AI Overview citations come from content published in the last two years - with 44% from 2025 alone. Recency is now a ranking signal for AI visibility in a way it never was for traditional SEO.
This is the structural shift that makes SEO alone insufficient. It's not that traditional SEO has stopped working. It's just that the discovery journey now begins across surfaces that a traditional SEO program was not designed to address.
How brands get found: then, now, and next
Three disciplines. Two are established. One is emerging fast.
- SEO - Search Engine Optimisation - is the foundation. The goal: appear in Google's ranked results as a blue link. The mechanism: high-quality original content, technical health, crawlability, and backlinks. Maturity: established.
- AEO - Answer Engine Optimisation - gets your content pulled as a direct answer into Google's AI Overviews, AI Mode, and voice assistants. It's essentially a successor to SERP features. In AEO, the AI reads your content and surfaces the answer without the user clicking anywhere.
- GEO - Generative Engine Optimisation - positions your brand as a trusted, comprehensive source so standalone AI chatbots like ChatGPT, Perplexity, and Gemini synthesise and cite your content in longer, conversational responses. GEO is less about extraction, and more about authority and citation.
The difference between SEO, AEO and GEO is real. But the strategies to succeed in all of them share a common foundation. Structured, authoritative, well-formatted content that demonstrates genuine topical depth is the starting point.
But succeeding in AEO and GEO also demands new inputs: entity clarity, distributed citation authority, reduced JavaScript dependency, semantic structure, and fresh original content that AI systems have not already synthesised from a hundred other sources.
This is why at VertoDigital we run SEO and AEO as one program under the SEO and AI Search umbrella, with a methodology built for both surfaces.
What is SEO?
Traditional SEO is the practice of ranking pages in Google.
Factors that influence SEO: keyword relevance, domain authority, technical health, and content that matches what users search.
The buyer who enters a high-intent query into Google has already decided they want a solution. Users still search for terms like "best [category] software for enterprise," or "[vendor] vs [vendor]," "[category] pricing". Those moments are still incredibly valuable for your pipeline, and they still happen overwhelmingly on Google.
SEO loses ground earlier in the journey, when the buyer is forming their understanding of a problem, comparing categories, evaluating options in conversation. That journey is increasingly starting in an answer engine.
Which is precisely where AEO comes in.
What is AEO?
AEO is optimising content to be cited, referenced, or synthesised by AI-powered answer engines.
SEO gets your page ranked so a buyer clicks through to your website. AEO gets your brand mentioned inside the AI-generated answer the buyer reads before they click anything. Just like traditional search, AI answers have positions you can rank for.
Being surfaced at the top of an AI Overview versus below the expand button can be a meaningful difference. But unlike the ten blue links, there are fewer positions you can rank for. There is no page two, but most often a direct continuation to AI Mode.
There are simply fewer positions available in an AI Overview than there are on a Google results page. This makes getting in - and staying in - much more competitive.
It's also worth noting that AI Mode has become increasingly prevalent in recent months, and there is ample speculation within the industry that it will soon become the default way Google works. In the near future, we'll likely see the ten blue links phased out in favour of AI Mode.
What is GEO?
GEO is the practice of creating and optimising content so it can be easily discovered, understood, and used by AI chatbots and generative search engines like ChatGPT, Perplexity, and Gemini.
Where AEO optimises for immediate, concise answers in Google's AI Overview and AI Mode, GEO is about longer, conversational replies. A user asks ChatGPT what they should consider when picking a data pipeline tool - the response summarises the main factors that should guide that decision, and cites its sources. Getting into those sources is GEO.
How a GEO citation happens
Buyer asks ChatGPT
"What should I look for in a data pipeline tool?"
Model synthesises
Pulls the main factors from trusted sources
Answer cites sources
Footnoted or linked references
Your brand appears
One of the cited, trusted sources
The mechanism differs from SEO. We're seeing a gradual shift away from keywords and links, and toward distributed presence - though it's worth noting that keywords, links, and site rankings in the SERPs still inform a significant share of AI answers.
The majority of GEO authority is built through topical depth, distributed presence, and being referenced by sources that AI systems already trust. The more your brand appears across credible third-party content - industry publications, social media platforms like LinkedIn, partner sites, analyst coverage - the more likely an LLM is to include you when a buyer asks a question in your space.
In practice, GEO and AEO run on the same program. The content that once would have earned a featured snippet on Google is the same content that gets cited in a Perplexity response. The technical foundation is identical.
The difference is primarily in where the answer surfaces. Google's AI Overviews can expand significantly into multi-turn, chat-like responses through AI Mode, blurring the line between a short AEO extraction and a longer GEO-style reply.
What stays constant across both is the underlying requirement: structured, authoritative content that an AI system can confidently extract, synthesise, and attribute to a source.
Google crawlers vs AI crawlers
This is the distinction most marketers miss, and it changes how you need to write.
When Google's crawler visits your site, it is building a map of the entire web: structure, metadata, keywords, how pages connect. It's building a granular picture of what each page is about and how well it answers a specific query.
That is why a single strong page on a low-authority domain can outrank a weak page on a high-DA publication.
It reads everything.
AI crawlers work differently. They are selective. They scan for discrete chunks of information they can extract and use to answer future questions. They'll skip past clever brand storytelling to find the facts.
There's also a more fundamental technical barrier that most teams don't account for: JavaScript dependency.
Many modern websites rely heavily on JavaScript to render content. Google's crawler has developed the ability to execute JavaScript over time. Most AI crawlers have not.
What each crawler sees on a JavaScript-dependent page
Google crawler
Executes JavaScript - full page indexed.
AI crawler
Skips JavaScript - that content is invisible.
This means that if your key pages - your service pages, pillar content, product descriptions - depend on JavaScript to load their content, large portions of your website may simply be invisible to LLMs. It never gets indexed, synthesised, or cited. It doesn't matter how good the content is.
This is something we see consistently when auditing client websites. Reducing JavaScript dependency and using schema markup is one of the highest-leverage technical changes a B2B site can make for AI visibility.
Another distinction is that search engine crawlers care about your site structure and how pages relate to each other. AI crawlers hunt for clear, factual, self-contained answers they can lift and synthesise.
Even if your page reads beautifully as a flowing argument, it can still be invisible in AI answers, because it never isolates a direct answer to a specific question. So, even if your content ranks well on Google, it can still perform poorly in LLMs.
This is where content chunking becomes the foundational unit for AEO. AI systems do not read a page from start to finish. They scan for discrete, self-contained units of information: a definition, a comparison, a direct answer to a specific question. Each chunk needs to make sense in isolation, without the surrounding context of the page it lives on.
Atomic chunks take this further. Each section of content should answer exactly one question, completely, in as few words as possible.
One idea. One answer. One extractable unit.
In practice, atomic chunks most commonly take the form of headings that pose a clear question, followed by a tight, direct response. That way, answers and definitions can stand alone, making extraction easy for LLMs.
It is worth noting that answer-first content structure and self-contained answers are not new ideas. They were already the best practice for capturing featured snippets and People Also Ask results long before LLMs arrived.
What has changed is the scale and the surface: the same structural discipline that once earned you a snippet now determines whether you get cited across every AI platform your buyers use.
AEO vs GEO: why we treat them as one thing
At VertoDigital, we define AEO and GEO by the surface they target: AEO for Google's answer surfaces, GEO for third-party LLMs like ChatGPT and Perplexity. That distinction is useful when talking about measurement and distribution.
Where it stops being useful is when building the program. Whether the surface serving the answer is Google's AI Overview or Perplexity's synthesis engine, the question it's asking about your content is identical: is this a credible, expert source that clearly addresses what the user is asking?
The optimisation inputs are the same - your website and its content. The only meaningful difference is whether the LLM recommends your brand directly in its answer or uses your content as a background source for informational queries.
Both outcomes require similar kinds of work. Which is why at VertoDigital we run GEO and AEO as a single service, not two separate tracks.
Has AEO replaced SEO?
No, AEO hasn't replaced SEO.
Google still accounts for 91% of global search, and 71% of B2B buyers still start their research with a Google search. That organic traffic still converts. Abandoning SEO to chase AEO creates a gap in demand capture at the exact moment a buyer is ready to act.
What is changing is the discovery phase, and to a great extent the whole user journey. By the time buyers reach Google with a high-intent keyword, they may already have an opinion or knowledge shaped by what answer engines told them first. If your brand is absent from that earlier phase, you are not losing clicks. You are losing consideration and overall brand visibility.
The question we've often received in the past 12 months is whether to choose between SEO or AEO. The right answer is that you need both SEO and AEO, with a clear understanding that they serve different roles and come at different stages in the buying journey.
The ultimate goal of your SEO/AEO strategy should be to make sure they are interconnected and build upon one another.
SEO vs AEO and GEO
Here's how the two disciplines compare side by side:
| SEO | AEO / GEO | |
|---|---|---|
| Goal | Appear in Google's ranked results | Be cited as a trusted source by AI answer engines |
| Surfaces | Google/Bing blue-link results | Google AI Overviews, AI Mode, featured snippets, ChatGPT, Perplexity, Claude, Gemini |
| Optimises for | Rankings and clicks | Citations, brand mentions, zero-click visibility |
| Primary input signals | Keywords, backlinks, crawlability, metadata, E-E-A-T | Topical authority, structured content, citation graph, schema markup |
| Content format | Keyword-mapped pages and blogs | Atomic chunks, question-first formatting, distributed thought leadership |
| Success metric | CTR, rankings, SERP impressions | Citation rate, brand mentions in AI answers, AI visibility score |
| Maturity | Established | Growing rapidly: early-mover advantage still available |
How to run SEO and AEO as one engine: practical tactics
At VertoDigital, we focus on SEO and AEO strategies that run as a single engine.
- Same content investment.
- Same technical foundation.
- Same ICP-mapped topic architecture.
- All united under one cohesive, holistic strategy.
Stage 1: fix the technical foundation first
The technical work that makes your site readable for Google is largely the same work that makes it readable for AI crawlers.
Three things matter most:
- Crawlability and Core Web Vitals: if Google can't index your content efficiently, neither can an AI crawler.
- Schema markup and structured data: this is where you move from hoping AI systems understand your content to telling them explicitly what it means, who it is about, and how your brand relates to the topics you cover.
- JavaScript and rendering architecture: content that depends on JavaScript to load may never be consumed by AI crawlers. Auditing your key pages for JS dependency and moving content-critical elements to server-side rendering is a purely technical intervention - but one with direct consequences for LLM visibility. Heading hierarchy is important, but it belongs in content structure, not in the technical foundation.
Stage 2: integrate semantic signals AI crawlers look for
There are two signals that most marketers overlook when it comes to LLM citation.
The first is semantic triples: structuring key facts as Subject → Predicate → Object. You must be direct about your company, your services, and the outcomes you produce. Avoid pronouns, and use your brand name explicitly so AI systems learn the association rather than having to infer it:
"VertoDigital provides B2B SEO and AEO services to help companies rank in Google and get cited by AI search engines."
The sentence above is a semantic triple which states a clear relationship between an entity, an action, and an outcome. That's exactly the kind of statement an LLM can extract, verify against other sources, and confidently reproduce in a response.
The second semantic signal AI crawlers look for is lexical proximity - keeping positive qualifiers close to your brand name.
"Leading B2B SEO agency VertoDigital" works. "VertoDigital, which has been recognised as a leading agency in the B2B space" works less well, because the qualifier and the brand name are too far apart for the association to register cleanly. Within two or three words is the working rule.
Stage 3: build a content strategy focused on real ICP questions, not keywords
Most SEO programs start with a keyword list: find a term with acceptable difficulty and reasonable volume, create content, repeat. That model produces traffic, but it doesn't reliably produce pipeline, because the keywords you can rank for are not always the questions your ICP is asking.
Most content plans start with a keyword list. A more effective approach starts with your ICP's buying journey.
What is a VP of Marketing at a 200-person B2B SaaS company asking at each stage of their evaluation? What do they need to understand before they shortlist a vendor? These questions become your content map, and the keywords follow from the questions, not the other way around.
A piece of content that addresses a genuine ICP question builds the citation graph LLMs use. It simultaneously earns SEO rankings and featured snippets for the same topic.
In that same vein, your website shouldn't be the only piece of your content strategy, because LLMs crawl social platforms like Reddit and LinkedIn, industry publications, and other third-party sources.
Stage 4: structure content for AI extraction
Some specific formatting choices move the needle for AEO:
- Question-format headings: AI systems are built to answer questions. A heading that poses the exact question your ICP is asking, followed immediately by a direct answer, is an extractable unit. Avoid vague headings like "Learn more about schema markup" - use "How does schema markup improve AI citations?" instead. Don't overdo it, though: just like SEO, there is such a thing as over-optimising your content.
- Direct answers near the top: after every heading, the first sentence should answer the question directly. Never open with "it depends" or "in today's digital landscape."
- Comparison tables: AI systems understand relationships between options well when they're structured as tables. Any time you're comparing two or more things, use an HTML table.
- FAQ sections: build comprehensive FAQ sections that mirror how your ICP actually phrases questions to AI tools. The average AI prompt is 23 words long - write for that, not for a two-word keyword. FAQ schema markup further improves your chances of getting cited, since it makes it easier for AI engines to extract the answers.
- TL;DR or key takeaway blocks: a short summary near the top gives AI crawlers an immediately extractable overview.
Stage 5: measure all three surfaces - often ignored, really important
A new set of metrics is emerging that will, over time, reshape how we measure organic performance and report on investment. Traditional SEO metrics are not going away - but they will be joined by a parallel measurement layer for AI visibility that most B2B teams do not yet have in place.
Here is how measurement currently breaks down across the funnel:
One of the biggest issues in AEO is the lack of monitoring tools, especially compared to SEO.
- SEO: Google Search Console and Google Analytics give us valuable data about rankings, traffic, CTR, and technical issues. If we want to analyse what the broader search market looks like and what our competitors are doing, we can use keyword tools like Semrush or Ahrefs.
- AEO in LLMs: we can use Google Analytics to monitor the referral traffic we get from LLMs, and we can use tools like Peec or Rankscale to monitor whether our brand is getting cited for specific prompts we're interested in. But unlike Google Search Console, we don't have data for the specific prompts people use to search for our brand. The closest thing we have is Bing Webmaster's AI Performance Report, which only surfaces data for Copilot.
- AEO on Google: the most reliable way to measure a brand's citations in Google's AI Overviews is Semrush's AIO reports. However, in 2026, Search Console began rolling out AI Overview performance reports for some UK websites. Soon, we expect to see that feature rolled out to other sites, as well.
Frequently asked questions
Is AEO the same as GEO?
No, AEO and GEO are not the same, but they are closely related. AEO focuses on getting your content pulled as a short, direct answer into Google's AI Overviews, featured snippets, and voice assistants. GEO focuses on getting your brand cited as a trusted source when LLMs like ChatGPT, Claude, or Perplexity generate longer, conversational responses.
In practice, the same work is needed for both AEO and GEO: authoritative content, clear structure, strong E-E-A-T, schema markup, and distributed citation authority. These inputs serve both surfaces simultaneously.
Does traditional SEO still work?
Yes, traditional SEO still works. Commercial-intent queries still resolve through Google and still convert. The case for SEO as a pipeline channel is unchanged. What SEO does not cover is the earlier, conversational phase of the buying journey, where AEO picks up.
How do I know if my brand is being cited in AI search?
The most systematic way is to use dedicated tools: Rankscale, Peec, or Semrush's AIO reports. For a quick manual check, run your ten highest-value ICP queries in ChatGPT, Perplexity, Google AI Overviews, and Claude, and document which brands appear. It takes under two hours and tells you immediately where you stand - and, often more usefully, which competitors are already establishing citation authority in your industry.
SEO, AEO, and GEO aren't competing strategies - they're one program with three surfaces. Fix the technical foundation, write in atomic, question-first chunks, name your brand explicitly next to the outcomes it produces, and measure all three surfaces of the funnel, not just Google rankings. Start with your highest-traffic pages, restructure them for direct answers, and track citations alongside rankings.
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