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🚀 Try our newly launched Conversational Search tool
Ed Braddock 08 Sep 2025
For years, SEO was the playbook for online visibility. It was all about identifying high-performing keywords and battling to get your site onto Google’s first page.
But users’ discovery no longer ends at a bunch of ranked links.
Users are reading AI-generated summaries at the top of Google, or using tools like ChatGPT, Perplexity, or Claude to find information. Instead of scanning links, they expect a direct, plain-language answer to their exact questions.
Semrush already projects that traffic driven by these Large Language Models (LLMs) will surpass traditional search by 2028.
This marks the shift from the traditional SEO era to the era of AI SEO, also known as Generative Engine Optimization (GEO) or Answer Engine Optimization (AEO).
The world of AI search comes with overlapping terms. To avoid confusion, here’s how AI SEO, GEO, and AEO relate, and why we’ll treat AI SEO as the umbrella reference here:
Different terms and what each mean
AI SEO: The umbrella term for optimizing content so it’s discoverable in both traditional search engines (Google, Bing) and AI-driven engines (ChatGPT, Perplexity, Google SGE).
Generative Engine Optimization (GEO): Emphasizes how content is cited, summarized, and reused by generative AI systems.
Answer Engine Optimization (AEO): Focuses on formatting content so it can be lifted directly into answer boxes, FAQs, or AI summaries.
Think of it as SEO meets PR: your content must be technically structured and answerable, but also visible and referenced in the wider public domain. Mentions, backlinks, and citations strengthen authority not only for Google but also for AI systems, which rely on the collective memory of public information.
In this blog, we’ll show you why an AI SEO strategy is essential, and how to make your content optimized for both Google and the new wave of AI search engines.
We’ll also be unpacking these themes in our upcoming seminar on AI-powered search. Sign up here if you’d like to learn more.
There’s a gap most teams are missing: you can rank #1 on Google and still lose in AI search. Traditional SEO only measures visibility to Google’s crawler. It doesn’t check whether AI systems can interpret and reuse your content. And if AI can’t understand your content, it may skip it. Or worse, reference content from a competitor.
A standard SEO audit measures:
All of that still matters, but the blind spot of AI search discoverability can’t be ignored.
This is where on-site tools like Squiz Conversational Search make a difference. Not only can you audit traditional SEO performance, but you can also see how your content is interpreted by an AI-based search system, closing the gap most SEO audits miss.
Imagine a university’s help page is optimized for “psychology scholarships” and ranks high on Google. But the content is long, unstructured, and buried in paragraphs, while their competitor’s FAQ is concise and well-structured.
When students ask ChatGPT “What scholarships are available for psychology students?”, it surfaces the competitor’s FAQ instead.
The result? You’ve “won” on SEO, but you’ve lost the AI discovery battle.
Ignore traditional SEO and you’ll disappear from search results. Ignore AI SEO and your content risks being invisible where users now go for answers.
Organizations now need to think about:
And here’s the business case: the average AI search visitor can be worth 4.4x more than a traditional organic search visitor, based on conversion rate. That means even a modest presence in AI results can deliver greater business value.
AI SEO requires more than traditional ranking factors. To succeed, organizations now need to create content that serves both human searchers and AI systems.
Use these five pillars as your guide to what you should prioritize to be referenced by AI search engines:
AI models prefer structured, consistent formats. Content with:
Certain formats, like FAQs, best-of lists, and concise reviews are especially AI-friendly. LLMs prefer content that can be quickly understood and cited, making structure as important as substance.
What to do:
Use clear hierarchy and consistent formats.
Key takeaway:
AI engines don’t “read” like humans. Structured content makes it easier for AI to reuse your answers.
Example:
An FAQ with schema markup about scholarships is easier for ChatGPT or Google Search Generative Experience (SGE) to summarize accurately than a long, text-heavy article with generic headings.
Long paragraphs full of context but no clear takeaway are often ignored. AI models look for concise, fact-rich statements that can stand alone as an answer.
Ask yourself if a sentence or short paragraph from your page could be used, verbatim, as a reliable response to a user’s question. If not, it’s time to rewrite.
If your content is vague or wrapped in too much narrative, AI won’t cite it. Concise answers are more likely to be cited by AI.
“Psychology students can apply for three main scholarships: A, B, and C” is far more reusable than “Our university has a proud history of supporting students through a variety of funding opportunities.”
Conflicting terminology confuses AI systems. If one page refers to a “student hub” and another to a “student portal”, the model may treat them as separate concepts. Consistent vocabulary and messaging ensure your content is interpreted reliably.
Standardize terminology across pages, microsites, and knowledge bases.
AI tools assess consistency across your whole site, not just isolated pages. Consistent terminology builds authority with AI systems.
A shared style guide and term inventory ensures the site reads as one coherent, authoritative source.
AI systems look beyond single pages. They check if your content cluster covers a topic in depth. Covering a topic in depth with well-linked, related content helps AI assess relevance and authority.
But comprehensive coverage isn’t limited to your own site. External signals, like backlinks, mentions, and references also reinforce your authority, making it more likely that both Google and AI engines will surface your content as the trusted source.
Build interlinked content clusters.
AI evaluates the breadth and depth of related pages, not just a single URL. Content depth signals expertise and trust.
A driver’s license renewal hub that links to fees, timeframes, required documents, and FAQs is more likely to surface than a single standalone page.
Semrush data shows that almost 90% of the pages ChatGPT cites rank outside Google’s top 20 results. In other words, keyword rankings alone aren’t enough. Without tools that track AI visibility too, you risk only seeing half the picture and staying invisible in generative search.
Examples of integrated tooling that shows performance in both traditional search and AI search include:
With Squiz Conversational Search, powered by Funnelback, you can monitor how content performs on both sides: keyword rankings for traditional SEO, and visibility in generative answers for AI SEO.
Use tools that monitor both sides of the equation: traditional SEO metrics like keyword rankings, and AI visibility metrics like citation frequency or attribution accuracy.
SEO and AI search engines behave differently. You can rank well on Google but still be invisible to AI tools. Monitoring both sides prevents blind spots.
A university ranks third on Google for “apply for graduate programs”, yet an AI visibility reporting shows ChatGPT and Google SGE answering with competitor pages that present concise, structured FAQs. Without monitoring both sides, this gap would go unnoticed.
These pillars set the foundation. But to put them into action, you need tools that can identify gaps, improve structure, and deliver AI-ready experiences on your site and beyond. That’s where conversational AI search comes in.
While AI SEO requires content to be structured and answerable, it also needs to work for people. Rigid formats alone won’t hold attention. Readers still expect engaging content, with a mix of text, visuals, and examples that bring information to life.
Think of:
By striking this balance, your content remains authoritative and AI-friendly while still delivering an experience that people want to spend time with.
AI SEO and on-site conversational search are two sides of the same coin. The same practices that make your content discoverable in Google SGE or ChatGPT (clarity, structure, answerability) also make it perform better in your own AI-powered search tool.
By implementing Squiz Conversational Search, powered by Squiz Funnelback, you cover both sides of the search equation. Funnelback lets you audit and optimize traditional SEO performance, while Conversational Search shows how your content is interpreted by AI systems. Together, they ensure you’re ready for both SEO and AI SEO.
You can try our Conversational Search demo today and see how AI-powered answers change the user experience on your own website, in this hands-on demo.
Here’s what that looks like in practice:
The result is stronger visibility in AI search engines externally, and faster, more trusted answers for your users internally.
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