GEO vs AEO vs LLMO: What's the Difference?
Confused by the alphabet soup of AI optimization terms? Here's what each one means and which actually matters for your strategy.
The Alphabet Soup of AI Optimization
If you've been researching how to optimize for AI, you've probably encountered a confusing array of acronyms: GEO, AEO, LLMO, CAIO, AI SEO. What do they all mean? Are they different strategies or just different names for the same thing?
The short answer: They're mostly the same thing with different origins. The tactics are nearly identical - only the terminology differs.
GEO: Generative Engine Optimization
Origin: Coined by Princeton University researchers in November 2023
Definition: Optimizing content to improve visibility in AI-generated responses from tools like ChatGPT, Claude, and Gemini.
Focus: Generative AI systems that create original responses based on user queries.
GEO is the most academically-grounded term and has gained traction among enterprise platforms and marketing agencies. It emphasizes that we're optimizing for a new type of “engine” - one that generates answers rather than returning links.
AEO: Answer Engine Optimization
Origin: Predates generative AI, originally coined for Google's featured snippets and voice search
Definition: Optimizing content to appear in answer boxes, featured snippets, and AI-generated summaries.
Focus: Getting your content selected as “the answer” to user queries.
AEO is the older term. It was popular before ChatGPT when the goal was getting into Google's featured snippets or voice assistant responses. Today, it's often used interchangeably with GEO, especially for Google AI Overviews.
LLMO: Large Language Model Optimization
Origin: Coined by Jina.ai in December 2022, right after ChatGPT launched
Definition: Optimizing content specifically for visibility in large language model outputs.
Focus: Technical focus on how LLMs process and retrieve information.
LLMO is the most technical term. It specifically targets the underlying technology (LLMs) rather than the user-facing application. It's accurate but sounds too technical for most marketing contexts.
AI SEO: The Umbrella Term
Definition: Using AI in search optimization OR optimizing for AI-powered search.
AI SEO is the broadest term and can mean two things:
- Using AI tools to improve your traditional SEO (AI-assisted keyword research, content optimization)
- Optimizing your content to appear in AI-powered search and assistants
This ambiguity makes it less precise, but it's the most accessible term for newcomers.
How They Compare
| Term | Origin | Best For |
|---|---|---|
| GEO | Academic (2023) | Enterprise, agencies |
| AEO | SEO industry (pre-2020) | Traditional SEOs, Google focus |
| LLMO | Technical (2022) | Developers, technical audiences |
| AI SEO | Marketing (general) | Beginners, general audiences |
Which Term Should You Use?
It doesn't matter. The tactics are the same regardless of what you call it:
- Add statistics and data to your content (+22-41% visibility)
- Include expert quotations (+28-37% visibility)
- Cite authoritative sources
- Structure content with clear headings, FAQs, and tables
- Build E-E-A-T signals (Experience, Expertise, Authority, Trust)
- Get mentioned on authoritative sites
At Infrared, we use “AI visibility” because it's clear and jargon-free. Your brand is either visible to AI assistants or it isn't - that's what matters.
The Bottom Line
Don't get caught up in terminology debates. Focus on the tactics that actually improve your visibility:
- Check your current AI visibility to establish a baseline
- Implement proven GEO tactics on your content
- Monitor your progress and iterate
Whether you call it GEO, AEO, LLMO, or AI SEO - the goal is the same: getting your brand recommended by AI assistants when users ask questions in your space.