Introduction

As conversational AI applications like ChatGPT continue to change consumers search behavior, new terminologies and strategies have emerged in the world of search engine optimization. This guide will help you understand the various terms and concepts related to AI SEO, ensuring your business stays ahead in this evolving field.

What is AI SEO?

AI SEO consists of tracking your current AI visibility and optimizing your digital presence to improve your visibility.

First you must understand how your brand shows up for different queries across various AI Applications. After you understand your current AI visibility you can determine the strategy needed to improve your AI visibility.

This includes adapting content to perform well in:

• Large language models like ChatGPT
• AI search engines and discovery platforms
• Voice assistants and AI-powered tools
• Generative AI applications

We like the term AI SEO, because it realizes that at their core, AI SEO is not completely different from traditional SEO. We outline some of the main differences between the two here.

The main downside to the AI SEO term is it has been attached to many AI content writers, which is a super messy and competitive space. If this term loses out to one of the below terms, this will be why.

AI SEO Terminology Guide: Understanding the Different Names

To be clear at Kai, we think these new terms all essentially mean the same thing. We believe "AI SEO” is the best universally understood term but as we are still early in the market, people are making up names for what this specific subset of SEO should be called.

In the below section I’ll go through the different names in the ecosystem and why or why not we think it makes sense.

LLMO (Large Language Model Optimization)

LLMO means Large Language Model Optimization. The idea with this term is that the core technology behind most conversational AI Applications is an LLM, Large Language Model.

LLMO includes:

• Optimizing content for large language models
• Ensuring content is properly represented in AI training data
• Creating clear information hierarchy
• Maintaining factual accuracy and authoritative sourcing

Our thoughts:

We argue that it’s extremely hard to optimize for being included in the AI training data. It’s important to understand the difference between when AI is using training data vs web search results.

An LLMs’ training data is kind of a black box on how that training data is acquired and what is included.

Certain tools like Kai can provide insight into when top AI models scrape your website and what pages on your website they scrape when they visit.

But at the end of the day only the LLM creator knows which data they actually use to train the models.

Additionally, a lot of core LLMs have a knowledge cutoff of months or years in the past, which makes this not something where you can’t see results of your efforts quick enough to.

AEO / AIEO / AIO (AI Engine Optimization)

AEO / AIEO / AIO means AI Engine Optimization. The idea behind this naming is because it more clearly mimics the “SEO” keyword that is very well known by Marketers around the world.

AI Engine Optimization includes:

• Optimizing for AI-powered search and discovery systems
• Implementing advanced search optimization techniques
• Following Natural Language Processing (NLP) principles
• Creating conversational content structure

Our thoughts:

If we had to pick a term instead of AI SEO, this is what we would pick. It’s close enough to be understood by marketers.

What we are doing in this category, whatever you want to call it, is trying to create good content, in a way that AI Applications will prefer it to the other content that it has to choose from.

You might say that no one really says AI Engine, and we’d agree.

GEO / GAIO (Generative Engine Optimization / Generative Artificial Intelligence Optimization)

GEO / GAIO means Generative Engine Optimization or Generative Artificial Intelligence Optimization. The idea around this is that there are various types of AI, Generative AI is the larger category that includes text generation models (LLMs), image generation models (DALLE), and video generation models (Sora).

GEO / GAIO includes:

• Optimizing for AI generative tools and platforms
• Making content accessible to AI content generation tools
• Implementing proper attribution and citation structures
• Developing strategies for maintaining brand presence in AI-generated content

Our thoughts:

In our opinion this is the worst name. We mentioned before that it’s a term that’s meant in a broad way and not super focused on what most marketers care about, showing up in Conversational AI Applications.

GEO is a term that already has competing meanings, which makes it even less ideal and if you think GAIO is going to gain us respect as an industry I need you to GAIO TF out of here.

SEO for AI

This is another term that in our opinion is synonymous with AI SEO. In some writing situations it even makes more sense to use this term. We switch between these two often.

Conclusion

While the one final name for what we consider to be AI SEO is yet to be determined as a community. We are making a stand, AI SEO or SEO for AI are the two best options.

But it’s not important what you call it, it’s more important that you’re executing on it. And the best way to start is by having a solid understanding of how AI currently talks about your brand.

Next Steps

• Assess your current AI visibility (request a free brand report below)
• Implement basic optimization strategies
• Monitor performance across platforms
• Develop a comprehensive AI SEO strategy
• Stay informed about emerging trends and technologies

The field of AI SEO continues to evolve rapidly, making it essential to maintain flexible, adaptable optimization strategies while focusing on creating high-quality, authoritative content that serves both human users and AI systems effectively.

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