Answer Engine Optimisation vs SEO: What Is the Difference?
- Jun 5
- 7 min read
Before comparing the two, it helps to be precise about what each one optimises for.
SEO (search engine optimisation) is the practice of making web pages rank higher in search engine results, with the output being a position on a results page. When a user searches for a term, a ranked list of links appears, and the goal is to be near the top of that list, which has historically correlated with traffic.
What Each Discipline Is Actually Trying to Do
Answer Engine Optimisation targets a different output entirely. Rather than a position on a results page, it targets inclusion in a synthesised answer. LLMs (large language models) such as ChatGPT, Gemini and Claude do not return a list of links by default but a single, constructed response, and AEO is the practice of structuring your content, authority signals and digital footprint so that your brand appears in, or is cited by, those responses.
If you want the full definition and mechanics of AEO, see our article on What Is Answer Engine Optimisation?. The comparison here assumes you already know what each term means.
The Difference in Ranking Logic
SEO and AEO operate on fundamentally different ranking logic. Understanding that difference is the clearest way to see why they require separate thinking.
How search engines rank pages
Traditional search engines use crawled indexes. A bot visits your page, reads it, assesses its signals (technical structure, backlinks, keyword relevance, domain authority, page experience metrics) and assigns a ranking position for specific queries. The ranking is explicit: position one, position two, position ten.
The signals that influence that ranking have evolved considerably since the early 2000s, but the underlying mechanism has not changed: a query comes in, the engine retrieves and ranks indexed pages from its crawled index, and the user sees a list.
How answer engines select sources
LLMs do not retrieve pages from an index in the same way. They generate responses based on patterns learned during training, often supplemented by real-time retrieval from the web. The selection logic is less transparent and harder to reverse-engineer, but the available evidence points to a consistent set of signals: domain authority, citation density from third-party sources, content structure, topical consistency and brand presence across the open web.
Research published in 2026 found that brands are 6.5 times more likely to be cited in AI answers through third-party sources than through their own domains. High-authority domains are cited at roughly three times the rate of lower-authority domains for the same query. The overlap between ChatGPT citations and Google's top-10 organic results is around 12%, meaning the two systems pull from largely different pools.
That last figure is worth sitting with. If you assume that ranking well on Google automatically means appearing in LLM answers, the data suggests otherwise. The correlation exists but it is far from deterministic.
Five Concrete Differences
1. The output is different
Where SEO produces a ranking position, AEO produces a citation or inclusion in a synthesised response. These are structurally different outcomes that require different tooling to track: a ranking position is visible in Google Search Console, while a citation in an LLM response requires separate monitoring infrastructure, as the search console does not show it.
2. The user behaviour is different
When a user performs a traditional search and sees links, they decide which to click. When a user queries an LLM, the answer is delivered directly. Pew Research Center, in a July 2025 study tracking the real browsing behaviour of 900 US adults, found that users who encountered a Google AI summary were far less likely to click on a traditional link: only 8% did, compared to 15% on pages without an AI summary. The session frequently ended without any website visit at all.
This is the structural shift driving AEO relevance: the answer increasingly arrives in place of the click, with the user getting what they needed before any page is visited.
3. The content requirements are different
SEO content is typically optimised around keyword presence, content depth, internal linking and topical coverage within a domain. AEO content needs to be extractable: structured so that a model can pull a clear, accurate answer from it without ambiguity. That means short declarative statements, explicit definitions, well-labelled sections and answer blocks that stand alone without context.
The specific passages that get cited tend to be concise, factually dense and structurally clean, and a long article will not help if the model cannot locate the answer within it.
4. The authority signals are different
SEO authority is primarily built through backlinks, and the number and quality of domains linking to your pages remains one of the strongest signals in traditional search ranking. AEO authority is built more through brand presence across the web as a whole: citations in third-party publications, mentions in industry media, reviews on platforms like Trustpilot or G2, and consistency of brand information across all public-facing sources.
Both disciplines value E-E-A-T (experience, expertise, authoritativeness, trustworthiness) in principle. But in practice, LLMs evaluate it differently: not through on-page author bios, but through how the broader web talks about you.
5. The measurement is different
SEO measurement is a well-established practice, with ranking positions, click-through rates, organic sessions and conversion attribution all supported by mature tooling. AEO measurement is newer and requires different instruments: tracking how often your brand appears in LLM-generated answers, what sentiment those answers carry, whether your brand is cited or merely mentioned, and how that compares to competitors across different LLMs.
None of this is a vanity exercise: AEO Monitoring is the practice of measuring these signals systematically, and it produces different data than anything currently inside your analytics stack.
Where They Overlap
The two disciplines are not entirely separate systems, and several signals matter to both.
Domain authority is a shared foundation. High-authority domains rank better in traditional search and get cited more often in LLM answers. The investment in building domain authority pays into both channels simultaneously.
Content quality and structure benefit both. Content that is well-organised, factually grounded and topically consistent tends to perform better in search rankings and is more likely to be extracted by models.
Technical accessibility matters in both. Pages that cannot be crawled or loaded properly will underperform in both traditional and AI-mediated search.
Third-party presence is increasingly relevant to SEO through brand signals and to AEO through citation probability. Getting your brand covered in credible external publications is no longer just a PR activity.
The practical implication: teams that have done solid SEO work have an advantage going into AEO. But they are not interchangeable, and the gap between ranking well and being cited by LLMs can be substantial.
The Query Type Split
One of the more useful ways to think about AEO vs SEO is by query type rather than by channel.
Transactional and navigational queries ("buy X", "login", "near me", "compare pricing") still produce traditional search results with strong click intent, where the user wants to complete an action and SEO investment has a clear, measurable return.
Informational queries are where the picture changes most. Question-based searches, definitional queries and research-stage questions increasingly trigger AI summaries or land directly in LLM conversations. Pew Research found that question-based searches ("who", "what", "why") generated AI summaries 60% of the time in their March 2025 dataset. For longer, natural-language queries of ten or more words, the figure rose to 53%.
If your audience is asking questions about your category, your competitors or your use case, they are increasingly asking LLMs, not just Google. McKinsey's August 2025 consumer survey found that roughly half of consumers already intentionally use AI-powered search, with 44% of those saying it is now their primary and preferred source of information, ahead of traditional search at 31%.
That does not mean SEO is irrelevant for informational content. It means that informational content now needs to be optimised for both traditional search and AI-mediated retrieval as distinct channels with different selection logic.
What This Means for Strategy
The framing of AEO versus SEO as competing priorities misunderstands how they relate: the two disciplines are not substitutes for each other, but address different parts of the visibility picture across the same user journey.
A brand that invests only in SEO is building visibility in a channel where the user journey is changing: AI summaries are intercepting informational queries before a click occurs, and LLMs are shaping brand perception during the research phase, before a user ever reaches a search results page.
A brand that invests only in AEO without the underlying SEO foundation is building on uncertain ground, since domain authority, content depth and technical health remain prerequisites for being cited in LLM responses, and skipping that foundation leaves the surface with nothing to hold it up.
The practical approach is to treat them as parallel channels with shared infrastructure. The content, authority signals and technical work you do for SEO supports AEO readiness. The brand presence you build for AEO (external mentions, third-party coverage, consistent entity information) feeds back into SEO signals.
For more on what that looks like across different content types and query categories, see our article on AI Optimisation for Websites.
Frequently Asked Questions About Answer Engine Optimisation and SEO
Does good SEO automatically mean good AEO performance?
Not reliably. The overlap between brands that rank well on Google and brands that get cited by LLMs exists (domain authority is a shared signal) but it is partial. Research indicates that citation overlap between ChatGPT and Google's top-10 organic results is around 12%. Ranking on the first page of Google does not guarantee inclusion in AI-generated answers.
Can I measure AEO performance the same way I measure SEO?
No. Traditional analytics tools track clicks, sessions and ranking positions. AEO performance requires separate monitoring: tracking how often your brand appears in LLM responses, with what framing, and how that compares across different LLMs and competitor brands. This is what AEO Monitoring covers as a discipline.
Does AEO replace SEO?
No. LLMs are not replacing traditional search entirely; they are adding a parallel layer of discovery. The appropriate response is to invest in both, with the allocation shifting depending on the query types most relevant to your business.
Is AEO only relevant for informational content?
Primarily, yes, at least at this stage. Transactional queries (purchase, comparison, local) still largely produce traditional search results where SEO investment drives return. Informational and research-phase queries are where LLM answers dominate and where AEO has the most immediate impact.
What is the fastest way to understand where my brand stands across both channels?
Start with a structured audit. For traditional search, Google Search Console gives you ranking and click data. For AI visibility, you need to run AEO Monitoring: checking how your brand appears in LLM answers across the platforms your audience uses, what sentiment those answers carry and where you are absent.
Where to Start
If your brand invests in content and search visibility but has not yet looked at how it appears in LLM-generated answers, the starting point is straightforward: find out what is already being said.
AI, TELL ME! runs AEO Monitoring across the LLMs your audience uses, tracking brand mentions, citation frequency and sentiment, giving you a clear baseline before any optimisation work begins.
