Is LLMO (Large Language Model Optimization) the same as GEO? Getting confused by all the acronyms

Let me clarify the acronym landscape.

The terms and their origins:

GEO (Generative Engine Optimization)

• Coined to describe optimizing for generative AI search
• Includes ChatGPT, Perplexity, Claude, Google AI Overview
• Focus: Being cited in AI-generated responses
• Most widely adopted industry term

LLMO (Large Language Model Optimization)

• More technical term
• Specifically about optimizing for LLMs (the AI models)
• Focuses on how LLMs interpret and cite content
• Less common in marketing circles

AEO (Answer Engine Optimization)

• Emphasis on answer engines (Perplexity, etc.)
• Focus on being the answer source
• Sometimes used interchangeably with GEO

SGO (Search Generative Optimization)

• Less common
• Sometimes used for Google SGE specifically
• Narrower focus than GEO

The practical reality:

They all describe the same core concept: optimizing content to be cited in AI-generated responses.

My recommendation:

Use GEO. It’s:

• Most widely recognized
• Broad enough to cover all platforms
• Easy to explain (“like SEO but for generative AI”)

Agency perspective on terminology.

What we settled on:

We use “GEO” with clients because:

• Easy to explain as “SEO’s evolution”
• Matches industry discourse
• Doesn’t require explaining what an LLM is

How we position it:

“SEO gets you ranked. GEO gets you cited in AI responses.”

Simple, memorable, accurate enough.

When we use other terms:

Technical discussions: Might use LLMO when talking about model-specific behavior

Perplexity-specific: Sometimes use AEO since Perplexity is literally an “answer engine”

Google focus: Might reference SGE/SGO when discussing AI Overviews specifically

The lesson:

Match terminology to audience. CMO? Use GEO. CTO? Might appreciate LLMO precision. Content team? Just call it “AI optimization.”

Historical context on emerging terminology.

This happens every time:

Remember when we debated:

• SEM vs SEO vs PPC
• Content marketing vs inbound marketing
• Social media marketing vs social marketing

Industry terms consolidate over time. Right now:

2024: Multiple terms emerging 2025: GEO gaining dominance 2026: GEO becoming standard

The prediction:

GEO will become the standard term. Others will fade or become subsets:

• LLMO: Technical subset of GEO
• AEO: Specific to answer engines
• SGO: Historical term for early Google AI efforts

What to do:

Use GEO. It’s winning the terminology battle. But understand the others in case clients/partners use them.

Technical perspective on why LLMO is more precise.

LLMO specifically addresses:

Large Language Models process content through:

• Tokenization
• Embedding
• Attention mechanisms
• Context windows

Understanding these technical aspects can inform optimization:

• Token efficiency in content
• Semantic clarity for embeddings
• Context-appropriate information density

Why GEO is more practical:

Most marketers don’t need to understand tokenization. They need to:

• Create citable content
• Build authority
• Track visibility

GEO abstracts the technical complexity.

When LLMO precision helps:

If you’re:

• Working with AI engineering teams
• Discussing model-specific behaviors
• Optimizing for specific LLMs

Otherwise, GEO is sufficient.

Content perspective on the terminology.

What our content team needed:

Clear direction on what’s different from traditional SEO.

The framing that worked:

“GEO means we’re writing to be cited, not just ranked.”

This simple framing changed how writers approach content:

• Lead with answers
• Make statements extractable
• Think about what AI would quote

The terminology didn’t matter:

Whether we called it GEO, LLMO, or “AI content optimization” - the behavioral change was the same.

My advice:

Focus less on which acronym to use. Focus more on ensuring your team understands the behavioral shift:

• From: Write to rank
• To: Write to be cited

Call it whatever gets that message across.

Perfect clarity now.

My takeaways:

1. Same concept, different names - GEO, LLMO, AEO all describe AI search optimization
2. GEO is winning - Most widely adopted, use this default
3. Strategies are the same - Regardless of terminology
4. Match audience - Use terms that resonate with who you’re talking to
5. Focus on the shift - “Ranked” to “cited” is the key change

What I’m doing:

• Using GEO as standard term
• Explaining it as “SEO’s evolution for AI”
• Focusing on the behavioral change for team
• Not getting caught up in acronym debates

Thanks for the clarity!