SEO vs AEO vs GEO vs LLMO
Published by Krister Ross · Updated May 2026
Four acronyms describe how brands get found in 2026, and they are easy to confuse. Here is what each one actually means, how they differ, and how to decide where to put your effort.
In short
SEO ranks links in traditional search. AEO is the work of becoming the brand AI assistants recommend in their answers. GEO is the work of being cited as a source inside generated answers. LLMO is the umbrella term for shaping how language models perceive your brand, and it contains both AEO and GEO. They are layers of the same problem, not competing choices, and in 2026 most brands need all four working together.
Read the complete AI visibility guide for the full picture.
The four disciplines side by side
The same brand can win or lose on each of these independently. The differences are easiest to see in one view.
| SEO | AEO | GEO | LLMO | |
|---|---|---|---|---|
| Focus | Ranking links in search results | Being recommended in AI answers | Being cited as a source in answers | How models perceive your brand |
| Platforms | Google, Bing | ChatGPT, Gemini, Perplexity | AI Overview, Perplexity, ChatGPT | All major language models |
| Success metric | Position and organic clicks | Recommendation rate and share of model | Citation rate and sources used | Accuracy and sentiment of the model view |
| Key lever | Content, links, technical health | Entity authority and structured answers | Citable, verifiable source content | A coherent, consistent brand identity |
| Timeframe | Months to compound | Weeks to months | Weeks to months | Ongoing, builds over time |
SEO ranks links in search
Search engine optimization is the oldest of the four. For two decades it has decided who appears when someone types a query into Google or Bing. The goal is a high position in a list of links, so the right page earns the click.
SEO rests on three fundamentals that have not changed: content that matches what people are looking for, technical health so the page can be crawled and rendered, and authority earned through links and reputation. These fundamentals still hold value, and they feed everything that comes after.
SEO works best when the buyer still clicks through to a website to compare and decide. For high-consideration purchases, local search and branded queries, that behaviour is far from gone, which is why SEO remains foundational rather than obsolete.
Platforms
Google, Bing
Success metric
Position and organic clicks
Key lever
Content, links, technical health
Timeframe
Months to compound
AEO earns the recommendation in AI answers
Answer Engine Optimization is the work of becoming the brand an AI assistant names when a customer asks for a recommendation. When someone asks ChatGPT or Gemini which tool, supplier or service they should choose, AEO decides whether your brand is in that short answer.
The mechanism is different from SEO. The assistant does not return a ranked list, it returns a judgement built from everything it has learned about the options. AEO works by building entity authority, a clear and verifiable identity, and structured content that answers the real questions buyers ask.
AEO matters most where the customer now resolves the decision inside the conversation and never reaches a list of links. That share of buying journeys is growing quickly, which is why AEO has become the highest-leverage new discipline.
Platforms
ChatGPT, Gemini, Perplexity
Success metric
Recommendation rate and share of model
Key lever
Entity authority and structured answers
Timeframe
Weeks to months
GEO gets you cited as a source
Generative Engine Optimization is the work of being used as a source inside a generated answer, the link or attribution that appears when an AI assistant or AI Overview backs up what it says. Where AEO is about being recommended, GEO is about being the reference the model leans on.
GEO rewards content that is genuinely citable, clear claims, verifiable facts, original data and a structure the model can lift cleanly into its answer. Being cited builds trust both with the reader who follows the link and with the model that learns to treat your domain as reliable.
GEO is most valuable for brands that publish substance, research, guides, documentation and primary information that others want to reference. A strong citation footprint reinforces AEO, because the brand a model cites is often the brand it goes on to recommend.
Platforms
AI Overview, Perplexity, ChatGPT
Success metric
Citation rate and sources used
Key lever
Citable, verifiable source content
Timeframe
Weeks to months
LLMO is the umbrella over all of it
Large Language Model Optimization is the broadest term of the four. It covers all the work of shaping how language models perceive your brand, what they know about you, how accurately they describe you, and whether they speak about you positively. AEO and GEO both sit inside LLMO.
Thinking in terms of LLMO keeps the goal honest. Being recommended and being cited are outcomes, but they rest on the model holding a correct, complete and favourable picture of who you are. If the model misunderstands your brand, no single tactic fixes it.
In practice LLMO is the layer where datadriven optimization happens. You measure how every major model perceives and mentions the brand, find the gaps and mistakes, and close them with the entity, content and citation work that AEO and GEO describe.
Platforms
All major language models
Success metric
Accuracy and sentiment of the model view
Key lever
A coherent, consistent brand identity
Timeframe
Ongoing, builds over time
What does your business need
A few guided questions point you to where the effort belongs first.
If buyers still compare options on websites before deciding, SEO remains foundational and should not be neglected.
If customers increasingly ask an assistant for a recommendation, AEO is the highest-leverage place to invest next.
If you publish research, guides or primary data, GEO turns that substance into citations that compound trust.
If models describe your brand inaccurately or barely know you exist, start with LLMO to fix the underlying picture.
If you are unsure, a visibility check shows what AI says about you today and which gap to close first.
In 2026 all four work together
These disciplines are layers of one problem, not a menu to choose from. SEO keeps your owned pages findable and healthy. GEO turns that content into citations the models trust. AEO converts that trust into recommendations. LLMO keeps the whole picture accurate and favourable.
A brand that treats them as competing tactics tends to win one and lose the rest. A brand that treats them as one system, built on a clear identity and substantive content, compounds across all four. The fundamentals overlap heavily, which is why the work pays off in more than one channel at once.
Frequently asked questions
The questions we hear most about these four disciplines.
SEO optimises for ranking links in traditional search so a page earns the click. AEO optimises for being the brand an AI assistant recommends inside its answer. They share fundamentals like clear content and authority, but the goal differs: ranking a link versus being the recommendation.
GEO, or Generative Engine Optimization, is the work of being cited as a source inside generated answers. Where AEO is about being recommended, GEO is about being the reference an AI assistant or AI Overview links to when it backs up what it says.
LLMO, or Large Language Model Optimization, is the umbrella term for shaping how language models perceive your brand, how accurately they describe you and whether they speak about you favourably. Both AEO and GEO sit inside LLMO.
Most brands in 2026 need all four working together, but the starting point depends on you. If buyers still compare on websites, SEO stays foundational. If they ask assistants for recommendations, AEO has the highest leverage. A visibility check shows which gap to close first.
No. SEO is no longer the only discipline that decides who gets found, but its fundamentals of clear content, technical health and authority feed AEO and GEO directly. SEO is now the foundation that the AI-era disciplines build on rather than a standalone answer.