Is AEO or GEO different to SEO? This article covers how the difference in technologies impact the tactics and priorities.
There's a debate happening right now in the SEO community that I find genuinely interesting.
One side says AEO (Answer Engine Optimisation) is just SEO with a new label: same techniques, same fundamentals and a new buzzword.
The other side says it's a fundamentally different discipline with new rules and a new playbook.
I think both sides are partly right. And both sides are partly dangerous.
(plus, people are getting too animated about this topic)
My bias upfront:
So my views in this article have been informed by real work and supplemented with research. And it's probably worth mentioning leads from LLMs such as ChatGPT, Gemini, Claude and Perplexity are our #2 pipeline source so we eat our own dog food.
My position: SEO and AEO share the same foundations. Most of the work overlaps. But the underlying technology is measurably different, and those differences change optimal tactics. That combination is essentially my thesis: same foundations, different weighting. Ignoring them is leaving competitive advantage on the table.
This article lays out where they're the same, where they diverge, and why that divergence matters more than most people think.
Before I make the case for where they're different, I want to be honest about where they're identical.
Both SEO and AEO operate across the same three buckets of activity:
Technical: Site speed, crawlability, structured data, schema markup, indexability. Whether you're optimising for Google's crawler or an LLM's retrieval pipeline, your site needs to be technically sound. A broken site is invisible to both systems.
On-page: Clear headings, good content structure, keyword targeting, answering search intent. Both systems need well-structured, relevant content.
Off-page: External signals of authority and trust. Both systems use signals from outside your own site to assess credibility. The mechanism differs (more on that later), but the category is the same.
This is the 80% that makes people say "it's all the same." And at the category level, they're right.
Here's where i actually agree with the "just do good SEO" crowd more than they'd expect.
The foundations that make both SEO and AEO work are identical: Good product marketing fundamentals such as positioning, a well-defined ICP, clear differentiators and the ability to clearly communicate your product's features, capabilities and benefits.
These things are absolutely critical. You cannot succeed at either SEO or AEO without them.
From my past life of consulting and offering demand gen services, this is where most companies are operating and get stuck. They're still trying to get the basics right such as clear messaging and targeting, see low/no results with channel execution and blame the channel. "Ads don't work!" - but they do work - you couldn't get them to work for your company.
When you're at this stage, SEO and AEO look identical because the improvements come from the same place: better fundamentals. If your positioning is weak, fixing it improves both your Google rankings and your AI visibility. If your content doesn't answer real questions, neither system will reward it.
In my opinion this is why so many people see convergence. For most companies the real problem isn't the SEO vs AEO distinction, it's that the product marketing isn't sharp enough yet.
So yes, statements such as "do good SEO" and "write content for your ICP" are technically true but they're also useless from a strategy perspective. Winning strategies aren't built upon platitudes or convergent thinking.
Technology shifts create distribution shifts. Here's a parallel that i think makes this clearer.
When TikTok broke out, Instagram was the dominant short-form content platform. Instagram distributed content primarily based on your follower graph. You posted something, your followers saw it. Growth meant growing your follower count first, then your content reached more people.
TikTok changed the upstream algorithm. The For You page prioritised content quality and relevance to each individual user, regardless of whether they followed the creator. A brand new account with zero followers could go viral on its first post if the content was good enough.
The data backs this up. Research from Socialinsider (2025) showed TikTok averaging roughly 6,268 impressions per post compared to Instagram's 2,635. The distribution mechanics were fundamentally different.
Same broad category: social media, short-form video. Same foundations: good content, clear messaging, understanding your audience. But the upstream technology change created entirely new downstream distribution opportunities.
Brands who said "TikTok is just another short-form platform" got crushed by creators who understood the algorithmic differences and optimised for them. The ones who recognised that the For You page rewarded different signals (completion rate, shares, re-watches) than Instagram's follow-based feed (follower count, engagement from existing audience) built massive reach faster. Instagram incentivised growing a brand which resulted in conventional influencers, TikTok incentivised virality and created an entire market of creators - the UGC creator economy was born.
The same dynamic is playing out in search right now. We have new platforms within a familiar category (search), built upon different technologies.
Google scores documents and returns a ranked list that buyers have to click and self-serve information. LLMs retrieve semantically relevant passages and synthesise a single answer from multiple sources, personalised to the user.
These are different systems with different priorities. And even if 80% of the work is the same, the 20% that differs is where the edge lives. When everyone has access to the same tools and the latest Claude Code skills stored as .md files, the edge is exactly where i want to be operating.
I'll get into the technical details here. It's boring (as a marketer) but it's important we understand how these systems work if we want to optimise for them.
For the last 20 years years, web search has been defined by: ranking documents.
Google takes a query, computes a relevance score for every document it knows about, and returns the top results in a ranked list. Whether you're looking at PageRank from 1998, BM25, RankBrain from 2015, or BERT from 2019, the underlying structure has stayed similar: query in, ranked list of documents out.
Entire industries evolved around that function: SEO, content marketing, link building. All of it optimised for one thing: how to get your page ranked higher on that list.
LLM-based search does something different.
These are structurally different systems. Classic search still resolves to a ranked list of results, even if Google uses systems like passage ranking to understand individual sections of a page. Modern answer engines do more than hit a search endpoint once. OpenAI’s own web-search docs distinguish between simple web search, agentic search where the model manages the search process and decides whether to keep searching, and deep research that can work across hundreds of sources. Google’s Gemini grounding docs describe a similarly multi-step flow: prompt analysis, one or multiple search queries, search-results processing, then a grounded response with citations.
That distinction alone should be enough evidence to anyone saying "it's all the same."
Hence why, we generally view organic search through three primary surface areas:
Let's continue with some practical implications because that's what us marketers can execute against.
Google's ranking system has historically placed enormous weight on backlinks. For years, your backlink profile was arguably the single most important ranking factor. Although, it's worth mentioning this is weighted less now (Gary Illyes, 2023).
The logic makes sense: if lots of other sites link to you, you're probably authoritative. Domain authority, domain rating, referring domains - the entire link building industry exists because these signals matter to Google.
LLMs don't work this way. They don't look at your backlink profile through the same lens.
When an LLM retrieves passages to build an answer, it's scoring how well a passage matches the query semantically. It's not checking how many backlinks the source page has. A page on a DR 15 domain with almost no backlinks that directly and clearly answers the question can get cited over a DR 70 site with thousands of backlinks. We've seen this play out across clients and it's arguably one of the main reasons why time-to-impact in AEO is so much faster than the "wait for 6 months" SEO we all knew.
This doesn't mean backlinks are worthless for AEO. They still help with indexing and crawling, which feeds the retrieval pipeline. But the weight has shifted dramatically. The traditional SEO playbook says invest heavily in link building, whereas for AEO you may want to prioritise answer quality, passage relevance and information consistency (point 3) to improve probability of passage selection during citation time.
Google's own SEO guide says content length alone doesn’t matter for ranking. Long-form pages often won in traditional SEO because they covered more intent, earned more links, and satisfied more searches, not because 5,000 words is inherently better than 500.
The original RAG paper by Lewis et al. (2020) describes retrieval from a dense vector index using a neural retriever, and the related Dense Passage Retrieval paper by Karpukhin et al. found that dense retrievers outperformed BM25 by 9–19 points in top-20 passage retrieval accuracy.
In plain English: answer engines are often retrieving and evaluating chunks or passages, not rewarding a page simply because it exists as the most exhaustive resource on the topic.
That shifts the content question from “How do I make the most comprehensive pillar page?” to “How do I make the cleanest extractable answer?”.
In a 2023 GEO paper Aggarwal et al. found GEO methods could improve visibility by up to 40%, with gains from adding citations, quotations, and statistics. Keyword stuffing showed little benefit and even underperformed baseline in some tests.
(Small plug: Our CITABLE framework was built to structure content that's optimal for LLM retrieval. Use this free tool to score your content)
Google’s web ranking systems don’t directly verify the factual accuracy of every claim (e.g. "used by 2,500 teams") on a page before ranking it. Your page gets ranked based on its own signals.
LLMs work differently. They give higher confidence to information that's consistent across multiple independent sources, a good piece of research on this is Google's AGREE framework. This is partly how they reduce the risk of hallucination. If your claim appears on your website, on Reddit, in industry publications, and in news articles, an LLM is more likely to surface it confidently.
This changes how we think about off-page strategy.
Traditional SEO off-page: get as many do-follow links as possible from high-DA sites. Focus on link juice and anchor text optimisation. Links, links, links!
AEO-aware off-page: ensure consistent, accurate information about your brand appears across as many independent sources as possible. Less about whether the link is do-follow or no-follow. More about whether your claims can be verified across the open web.
This job of 'information consistency' is extremely important, especially if like our B2B SaaS clients your product is evolving every quarter so messaging requires a frequent refresh. Imagine an AE pitching prospects with a sales deck that's 6 months out of date - that's the new consideration this presents.
I can already hear the counter-argument: "Fine, so there are some differences. But if 80% of the work is the same, why does the 20% matter?"
Because in any competitive market, the margin between winning and losing is small.
Think about it like this. When you and your 4 closest competitors all have solid product marketing, good content, and proper technical SEO, what separates you?
The edge lives in the remaining 20%.
It's the same in every competitive domain. The difference between an Olympic gold medallist and someone who doesn't make the podium is often fractions of a second. They all train. They all have world-class coaches. They all eat clean and sleep right. The difference is in the marginal gains that most people consider too small to prioritise.
According to Ahrefs data, In mid-2025, 76% of Google AI overview citations came from pages already ranking in Google's top 10. By early 2026, that number dropped to 38%. In less than a year, the systems diverged significantly. Companies that adjusted their tactics captured visibility that competitors missed entirely.
"Just do good SEO" is weak advice for three reasons:
1. It's a massive oversimplification. It collapses a meaningful tactical distinction into a platitude. It's the equivalent of a football coach telling the team to "give it your all."
2. Most companies don't know what "good" looks like. They think they do. But when we run our discoverability diagnosis, we consistently find companies that rank well for their core terms on Google but are weak in ChatGPT and Perplexity for the same queries. "Good SEO" didn't translate to AI visibility. Something else was missing.
3. Edges aren't gained with convergent thinking. If everyone in your market follows the same playbook, that playbook becomes table stakes. It doesn't differentiate you. The competitive edge comes from understanding where the systems differ and doing what your competitors haven't figured out yet.
Convergent thinking produces average results. Understanding the actual technology produces outsized results. The issue is that with convergent thinking comes consensus - and it's very uncomfortable to bet against consensus.
I get why people ask this. B2B marketing has a long history of relabelling the same services with new names to justify higher fees and an unhealthy obsession with creating new categories.
I've reviewed dozens of AEO strategies from agencies and heard from buyers who've spoken with AI visibility software companies. The general vibe is that...it's all the same stuff and nobody can really explain what they do that's all that different. Sprinkle in a lot of regurgitated content and infographics on LinkedIn, it's not hard to imagine why people's grifter senses start to tingle.
So yes, a lot of what's being sold as AEO could be classed a grift.
But that doesn't mean the discipline itself isn't real. Just as divergent thinking can help you gain an edge, being able to discern noise from signal - without throwing the baby out with the bathwater - is also a great skill to have.
It's like saying personal training is a scam because most personal trainers are terrible. Or like a marketer saying ads don't work because they didn't work for them. Bad practitioners don't invalidate the discipline.
If you've read this far and you're wondering what this means in practice, here's where i'd focus:
1. Don't abandon your SEO foundations
Everything you're doing that works for Google is still valuable. AEO builds on top of SEO foundations, it doesn't replace it. Your technical infrastructure, your content quality and the objective of satisfying search intent all still matter. Keep doing it.
2. Start thinking in extractable sections, not just pages
Structure your content so each section independently answers a specific question. Put the answer early in each section (first 100-200 words). Keep sections focused at 120-180 words between headings. Avoid topic drift within a single page. Use the CITABLE framework to help you.
3. Stop treating backlinks as the whole off-page strategy
I'm not saying stop building links. But if you're spending 40% of your budget on link building campaigns, consider redirecting some of that toward ensuring consistent, accurate brand information across independent sources. Get mentioned on Reddit, in industry publications, on comparison sites, in forums where your customers actually hang out.
Do-follow links are a bonus, not the objective. And you could be underestimating Reddit's impact on ChatGPT.
In our analysis of 144k AI citations and decrypted traffic, Reddit appeared in just 0.35% of visible ChatGPT citations while occupying roughly 27% of ChatGPT’s internal search slots during query processing. That’s exactly why a links-only view of off-page misses part of what is actually shaping answers.
4. Audit your AI visibility separately from Google visibility
Do not assume good rankings equal good citation visibility. We see this constantly across new clients we work with. Run the AI visibility audit using the various tools that exist, check whether your brand appears in AI-generated answers for the queries that matter to your business. If it doesn't, your Google rankings could be giving you a false sense of security.
Quick thoughts on this:
5. Get Technical Alpha
"Alpha" is a term used in finance to describe an investment's outperformance of a benchmark. In gaming, it can be simplified to "having an advantage".
You can definitely get lost in the technical weeds but, in my opinion, the teams who understand retrieval mechanics are the ones who'll produce the best AEO results. These will be the marketers who build the AEO playbook that everyone else follows. The ones selling "AI-optimised content" without actually changing anything are going to fade away.
Ask your agency how LLMs retrieve information and how that impacts the strategy execution. If they can't explain it clearly, you may be getting AI-washed.
SEO and AEO share the same foundations. Most of the work is the same. I've said that multiple times in this article because I believe it.
But the underlying retrieval technology is measurably, provably different. And those differences, however small, change the optimal tactics for anyone who wants to compete seriously.
Is AEO a grift? Some of what's being sold under that name, absolutely. But the math is clear, the data is real, and companies who've leaned in are already seeing positive results.
Calling it "just good SEO" is like telling a sprinter that all running is the same. Technically, you're putting one foot in front of the other and running on a track, but the difference between a marathon stride and a 100m sprint matters quite a lot when the race is on.
The companies that understand both systems and optimise for the differences between them will win. The ones that wave it all away as "just SEO" will be confused when their page 1 rankings stop translating into the market share they used to. In the end, regardless of the technologies and channels, getting customers from organic search will remain the goal.
Thanks for reading. Please DM me if you have any questions or feedback - always looking to improve.
References
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