Updated October 2026
SEO, AEO, GEO and LLMO describe overlapping parts of the same job, which is getting your brand found and trusted wherever people search. SEO earns visibility in search results. AEO aims to be the direct answer. GEO aims to be cited in AI-written answers. LLMO aims to shape how AI models understand and describe your brand. They share one foundation, and we plan them as one strategy.
Here’s what each term means, where they differ, and what changes in practice.
The four terms side by side.
| Term | Stands for | Where it shows up | What it aims for |
|---|---|---|---|
| SEO | Search engine optimization | Google and Bing results, including AI Overviews | Visibility, clicks and leads from relevant searches |
| AEO | Answer engine optimization | Featured snippets, People Also Ask, voice assistants, AI Overviews | Being the answer shown for a question |
| GEO | Generative engine optimization | ChatGPT, Perplexity, Gemini, Copilot, Google AI Mode | Being cited or mentioned in AI-written answers |
| LLMO | Large language model optimization | Any tool built on a large language model | How models describe your brand, with or without a citation |
AEO grew out of featured snippets and voice search. GEO was coined in a 2023 academic paper that tested how content changes affect citations in generative search. LLMO is the broadest of the three and the least defined.
How GEO differs from LLMO.
The two are often used as synonyms, but there’s a useful difference. GEO usually refers to AI answers that search the web in real time and cite sources, like Perplexity, ChatGPT search or Google AI Mode. Those tools pull from pages they can find and read today, so classic SEO work carries over directly.
LLMO reaches further. It includes what a model already “knows” from its training data, which shapes answers even when no source is cited. You can’t edit that training data, but you can influence it over time through consistent information about your brand, coverage on trusted sites, and a clear reputation in your category.
Google says the fundamentals haven’t changed.
Google’s guidance for its AI features is that there are no extra requirements to appear in AI Overviews or AI Mode. The same practices that help a page in search apply. Pages need to be crawlable, indexed and eligible for a snippet, and content needs to be helpful and people-first.
That matches what our team sees. The brands that show up in AI answers are usually the ones that already had strong, credible content and a well-known name in their space.
Why so many new names?
Our team fields a lot of questions about these terms from clients and partners, usually after a LinkedIn post or a cold email. The reasons behind the new labels are understandable:
- Some people want their names attached to the new vocabulary.
- Some marketers worry about being left behind as AI changes search.
- Agencies and tool vendors feel pressure to package something that sounds new.
Some of the people coining terms are doing real testing and research, and their work is worth following. The risk is in tactics promoted before they’re validated, or advice that ignores what still works in search today.
What actually changes in AI search.
The rigid SEO playbook is outdated. The goal has moved from rankings alone to visibility across a growing set of search and AI experiences.
Plan for visibility, not just clicks.
Many searches now end without a click. AI Overviews, featured snippets and chat tools often answer the question on the spot. Being named and cited in those answers matters as much as ranking below them.
- Earn mentions on trusted, relevant sites through digital PR and partnerships. AI tools lean on sources they consider authoritative.
- Answer questions directly and early on the page, then add depth.
- Use clear headings and semantic HTML so machines can parse the page.
- Use structured data like Organization, Article, Product and LocalBusiness to describe what you are. Don’t count on FAQ or HowTo schema for rich results, since Google now shows those for very few sites.
Create content AI can’t easily repeat.
AI is good at summarizing facts that already exist on a hundred sites. It struggles with judgment, first-hand experience and original data. That’s where to invest:
- Comparisons and buying guides that help with evaluation
- Calculators and tools that offer real utility
- Case studies, original research and customer insights
- Content that answers objections before the sales call
- Your own methods and expert commentary
Basic “what is” and “how to” content still has a role, but AI answers it well. Shift more of your effort toward content that helps buyers compare and decide.
Show up across discovery channels.
People find brands on YouTube, LinkedIn, Reddit, TikTok and in AI chat. AI tools also cite those platforms often.
- YouTube: clear titles, descriptions and transcripts help in YouTube search and in AI tools that read video content.
- Reddit and forums: join relevant conversations with helpful, non-promotional answers.
- LinkedIn: articles and posts from your team build visibility for your people and your brand.
- TikTok and Instagram: if your audience searches there, use the words they use in captions and voiceovers.
Measure what matters now.
Rankings and raw traffic tell less of the story than they used to. Add these to your reporting:
- Referral traffic from AI tools like ChatGPT, Perplexity and Copilot in GA4
- Citations of your pages in AI Overviews and other AI answers, tracked in a tool like Ahrefs
- Regular checks that ask ChatGPT, Gemini and Perplexity the questions your buyers ask, to see whether your brand comes up and how it’s described
- Brand mentions across third-party sites and communities
- Leads and revenue tied back to organic and AI search in your CRM
What not to do.
Some marketers are reviving old black hat tactics with an AI twist:
- Publishing AI-generated content at scale with little review
- Keyword stuffing and hidden text
- Guest posts on irrelevant sites to chase authority
- Doorway pages written to catch specific searches or AI prompts
Google’s spam policies already cover scaled content abuse, and other AI platforms have strong reasons to filter manipulation too. These tactics may work briefly, but recovering from a manual action is slow, and the bigger cost is lost trust with your audience.
Which term should you use?
We call it SEO and AI search, because that describes the goal plainly. We’re not attached to any acronym. “Online marketing” and “internet marketing” eventually settled into “digital marketing,” and the vocabulary here will settle too.
What won’t change is the strategy behind the name. The brands that win create content worth citing, earn visibility across platforms, and offer value AI can’t easily repeat.
Here is the bottom line.
SEO, AEO, GEO and LLMO are four angles on one goal, which is visibility in search and AI, so they work best as one strategy. Build on strong SEO, then adapt your content, authority and measurement for how people search today. See how our AI search and SEO services put this into practice, or read more on whether keywords still matter in SEO.
Sources: AI features and your website, Google Search Central, and GEO: Generative Engine Optimization (Aggarwal et al., 2023). Both checked October 2026.