AEO vs SEO vs GEO: What's the Difference?
Key Takeaways
- AEO, GEO, and LLMO are mostly different names for the same kind of AI visibility work.
- The real difference is between ranking your own pages in search and getting your brand mentioned in AI-generated answers.
- Good SEO still matters. Crawlability, useful content, and mentions from trusted third-party sources can help with AI visibility too.
- Traditional SEO metrics like keyword rankings and traffic do not fully show how visible your brand is in AI answers.
- For Indian brands, language, location, and local sources can change the answers people get.
What do AEO, GEO, SEO, and LLMO actually mean?
SEO (search engine optimization) helps your pages rank in traditional search results.
AEO (answer engine optimization) focuses on getting your brand mentioned, described, or recommended in AI-generated answers.
GEO (generative engine optimization) focuses on making your content and brand more likely to appear in answers from generative AI systems.
LLMO (large language model optimization) is a less common term for similar work, with more focus on how large language models understand and use your brand.
Look at those three terms again. They're mostly talking about the same kind of work, just from slightly different angles.
No industry standard clearly separates them, so the label often comes down to how a provider chooses to position its services.
So, don't choose a provider based on whether they call it AEO, GEO, or LLMO. Instead, ask what they actually measure, which AI engines they cover, and what they can do with the findings. Ours is set out in full in our measurement methodology. Those answers will tell you much more than the acronym itself.
If the labels don't really differ, what's the actual distinction that matters?
The real difference is that SEO is about ranking your own pages, while AI visibility is about getting your brand into the sources AI uses to build an answer.
| SEO / Ranking | AI Visibility | |
|---|---|---|
| What you're optimising | Your own website and pages | Your website plus third-party sources |
| Where you compete | Search results | AI-generated answers |
| What success looks like | Ranking higher in search results | Being mentioned or recommended by AI |
| What users see | A list of search results | A direct answer or shortlist |
| What you can control | Mostly your own website | Much less, because many sources are outside your control |
| How you measure it | Rankings, clicks, and traffic | Mentions, citations, and which sources AI uses |
That's the real shift. It's not about learning another acronym. It's about where the work happens and what you can control.
What carries over from SEO, and what doesn't?
A lot of what works for SEO still matters for AI visibility. If you've already invested in SEO, you're not starting from scratch.
What still applies
Crawlability and indexation. AI systems need to be able to read your pages. The technical basics are largely the same, with AI crawler access added.
Content that answers questions. Pages structured around real questions, with direct answers, were good SEO practice and are good retrieval practice too.
Authority and citation from other sites. Being referenced by credible sources helped rankings, and it helps retrieval in the same way.
Structured data. It can help systems understand your content, but don't expect it to drive AI visibility. Google has stated that structured data isn't required for AI search features, and testing has found limited measurable impact on AI citation rates. Treat it as good technical hygiene, not a major lever.
Pages that rank well tend to get retrieved too. Ranking and retrieval share signals, so strong SEO is a genuine head start.
What doesn't carry over
Keyword research. AI questions are often more detailed than search queries. Search volume doesn't always show what people ask AI, especially in India.
Position as the metric. There is no "position one." Your brand is either mentioned or it isn't.
Traffic as the proof. AI recommendations often don't lead to clicks, so traffic alone can't measure AI visibility.
The owned-asset assumption. This is the big one. SEO focuses on your pages. AI visibility also means working on third-party sources you don't control.
Single-observation reporting. AI answers can change between runs, so one check isn't enough.
What do you need to do differently for AI visibility?
Prompt set construction. Choose the questions you want to track based on what customers actually ask, not just keyword data. The prompt set becomes the basis for measuring visibility.
Citation tracing. Track which sources AI uses to answer questions in your category. This shows where your brand needs to build a presence.
Third-party source work. Work on aggregators, directories, review platforms, community discussions, and local publications that AI systems use. This is more targeted than general digital PR.
Repeated sampling. Run the same questions multiple times because AI answers can vary. Use a measurement methodology instead of relying on one check.
Entity consistency. Keep your company information consistent across your website, LinkedIn, directories, registries, and listings. Conflicting information can make it harder for AI to understand your brand.
What's different about AI visibility work for Indian brands?
Three things matter more in India, and most AI visibility tools don't measure them well.
Language. Your customers may search in English, Hindi, or Hinglish. Each can bring up different sources and brands. If you only track English, you're missing part of the market.
Location. The same question can get different answers in Mumbai, Delhi, or Bengaluru because the local sources are different. If you only look at national data, you may miss these differences.
The source ecosystem. The sources AI uses in India can be different from those used in Western markets. Regional publications, local aggregators, Quora, and Reddit India can matter more. So, if you follow a Western-market checklist, you may end up focusing on the wrong sources.
How should you split your budget between SEO and AI visibility?
No fixed ratio works for every business. Start with what's already working for you.
Keep investing in SEO. If your category brings in search traffic, your pages rank for terms that convert, and your customers still use search, SEO should remain a priority. For most Indian businesses, that's still the case.
Add AI visibility work when you see a gap. Take your ten most important buyer questions and run them through the AI tools your customers use. Run each question several times and track whether your brand appears and what gets said. If competitors appear consistently and you don't, you have a gap that rankings alone won't fix.
You can use this prompt-tracking guide to help you structure this testing process.
Don't cut SEO to fund AI visibility. The two share some signals, so weakening your SEO can hurt both.
Start with measurement. First, find out what AI says about your brand and which sources it uses. This gives you a baseline and helps you decide where to focus.
Before choosing a provider, use these nine questions to evaluate AI visibility work to understand what they're actually measuring.
Conclusion
The acronym matters less than what you're actually measuring. If you've already invested in SEO, you're not starting from scratch. The same basics, like crawlability, useful answers, and third-party authority, still matter for AI visibility.
The bigger change is where you need to show up. You're no longer just improving pages you control. You also need to build a presence in the sources AI systems use to create answers.
So, before you spend more money, start by checking where you stand today. Build a baseline, see what's working, and then decide where to focus.
Sources
- Google Search Central, structured data guidance
- IAB, Measuring Visibility in the AI Era, August 2026
- Inner Labs measurement methodology
Frequently Asked Questions
Is SEO dead?
No. AI systems still use much of the same web that search engines index, so pages that rank well can also be retrieved. But ranking alone isn't enough. Your page can rank well and still be left out of an AI-generated answer.
Which term should you use internally?
Use whichever term your team understands best. The name matters less than agreeing on what you're measuring. If your team already uses AI visibility, keep using it.
Can your SEO agency do this?
Some can, but ask specific questions before assuming they do. Ask which prompts they track, how they choose them, your share of voice against competitors, and which sources AI engines use. You should get clear answers to all of these.
Is GEO more technical than AEO?
Some providers say it is, but there is no industry standard that supports this difference. Treat it as a provider's positioning rather than a fact.
Do you need separate tools?
Usually, yes, alongside your SEO tools. SEO tools measure rankings and traffic, but they don't show whether your brand appears in an AI answer or which sources it used.
How do you know if AI visibility matters for your category?
Test it. Pick ten important questions, run them several times in a fresh session, and see what comes up. If competitors appear consistently and you don't, that's a gap worth fixing. If no brands appear, refine your prompts before deciding that AI visibility doesn't matter for your category.
About the author
Founder, The Inner Labs
Yohann John is the founder of The Inner Labs, an AI discovery and answer engine optimization platform for brands across India and the GCC. He works with retail, fintech, real estate and hospitality brands on how AI assistants describe and recommend them.
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