What is AI Search? GEO, AEO, LLMO & SEO: AI Optimization Guide

What is AI Search? 

Unlike traditional search, AI search refers to engines like ChatGPT, Gemini, and Perplexity that use Natural Language Processing (NLP) and Machine Learning to deliver more personalized results. This shift has given rise to new strategies like GEO SEO, LLM SEO, and AEO SEO, all focused on optimizing content for AI. If you’re new to this and wondering, what is AI search? Follow along as I break it down, and discover how to get featured in AI search results. 

AI-focused SEO strategies

• Generative Engine Optimization (GEO): GEO is an SEO strategy focused on optimizing content for AI-powered search engines like ChatGPT and Google’s AI Overview (formerly SGE). The goal is to have your content displayed or cited in AI-generated answers—not to be confused with geographic SEO, which targets location-based search.

SEO Pro Tip: Helpful Content

• Large Language Model Optimization (LLMO): LLMO or LLM SEO refers to optimizing your website so that AI engines can better understand, interpret, and retrieve your content. Doing LLMO effectively is often a crucial first step—and a prerequisite—for achieving success with GEO strategies.‍
  

SEO Pro Tip: Robots.txt, Vector Embedding, and Schema Markup

• Answer Engine Optimization (AEO) : Last but not least, AEO SEO is a strategy focused on structuring content to be directly featured in AI-generated answers—often resulting in zero-click searches or responses in voice search results.‍
  

SEO Pro Tip: FAQs & Structured Data

The Role of Helpful Content in AI Search

What is E-E-A-T in SEO? Experience, Expertise, Authoritativeness, and Trustworthiness - a framework used by Google to determine the quality of content, benefits both traditional rankings and AI citations, which is the goal for Generative Engine Optimization (GEO).

Craft unique content that understands user-intent and answers questions clearly and concisely. Helpful content should make the reader say, “This answered my question.” and If it’s helpful to humans, it’s helpful to AI - that’s what modern SEO is all about!

Why Your robots.txt File Matters in LLMO 

One of the most overlooked, yet critical, elements in LLMO is your robots.txt file. This tells search engine crawlers (including AI agents) which parts of your site they are allowed—or not allowed—to access and index. 

If your content isn’t crawlable by AI, it won’t be used in AI answers. Your robots.txt file is a foundational piece of LLM SEO—make sure you’re inviting the right bots in.

What is Vector Embedding for SEO?

Large Language Models (LLMs) use a technique called vector embedding where words, phrases, or even entire pages are converted into numerical values (vectors) and plotted in a multi-dimensional space. This allows AI systems like ChatGPT, Gemini, or Perplexity to recognize the semantic relationships between terms—even if they don’t use the same exact keywords. 

To learn how to generate vector embeddings for SEO in Screaming Frog, follow the brilliant steps laid out here by Mike King from iPullRank! Want more info on Vector Embedding in SEO? Read more about how Google’s New MUVERA Algorithm Improves Search in this post from Search Engine Journal.

Making your site easier for AI and LLMs to understand contextually—not just by keyword, means organizing and internally linking pages based on semantic similarity, not just URL structure or silo.

Zero-Click Search Features: FAQs & More

Most zero-click searches display snippets from content that’s structured as FAQs, lists, or numbered formats. These sections are designed to answer user questions directly, reducing the need to click through for more information. 

When you have clear, well-structured content that is genuinely helpful, it stands a much better chance of being featured in AI-generated answers and search snippets—boosting visibility without relying on traditional clicks.

Structured Data (Schema Markup) for AI Search 

Speaking of FAQs—don’t overlook the power of FAQ schema for LLM optimization. Adding FAQ schema helps increase your content’s visibility in AI-powered search by making it easier for engines to understand and extract relevant information.

Typically written in JSON-LD, schema markup provides structured data that gives search engines (and AI systems) clear context about your page’s purpose and content.

And it’s not just about FAQs—use:

• Article schema for blog posts
• Organization schema for your homepage
• How-To, Product, or Author schema where relevant

GEO, AEO, LLMO: It All Comes Back to SEO

While terms like GEO, LLMO, and AEO might sound new, they’re really just updated language for the same core objective: helping search engines—whether traditional or AI-powered—understand and surface your content.

The truth is, great SEOs are already ranking in AI search because they’ve been doing the right things all along. At the heart of every effective strategy—whether you call it GEO, LLM SEO, or anything else—are the timeless SEO fundamentals:

• Helpful, user-focused content
• Clear structure and schema markup
• Strategic internal linking
• Off-page authority through link building and digital PR

Staying Ahead of the SEO Curve

Right now, there’s a lot of noise around “what is AI search” and it seems like SEO may be a thing of the past - but I’m here to tell you the opposite. SEO isn’t dead, it’s evolving, and the need for experienced SEOs is growing. SEO is no longer just about keywords - but we already knew that. It’s about optimizing for AI, for user-internet and conversions. 

Keep your business ahead of the competition with Digital Valley 360! Call today for a free AI Search audit to see how to get featured in AI search results. Thanks for reading!