Optimizing for AI Crawlers & LLMs: The New Rules of SEO

Search engine optimization (SEO) has always evolved—but what we're witnessing now isn't just evolution. It's a transformation. A reshaping of how content is discovered, interpreted, and surfaced online. In 2025, traditional SEO techniques are no longer enough. We've officially entered the era of AI-first SEO.

That means you're not just optimizing for human users or even classic search engine crawlers. You're optimizing for Large Language Models (LLMs) like ChatGPT, Claude, and Perplexity, and the AI crawlers that feed them. These models rely on machine understanding, not just link-following, to populate answers and summaries in their results. They digest your content semantically, strip away fluff, and extract meaningful facts, structure, and trust indicators.

If you're still writing for keyword match or relying on old-school backlinks, your content may be left out of the digital conversation entirely. So how do you evolve? Let's dive into the new rules of AI-first SEO and how to implement them in your strategy today.

Let's get one thing straight: Google still matters—but its monopoly is fading. For the first time since March 2015, Google's market share dipped below 90% in October 2024. This drop was no fluke. It marked a pivotal shift in how users interact with digital information.

People are no longer asking Google for answers. They're asking AI assistants like ChatGPT. This transition to conversational search visibility has fundamentally changed how content is consumed. In this new world, click-through is no longer guaranteed. Many answers are zero-click citations, pulled directly from your content and presented as summaries in chat interfaces.

A New Breed of Bot: LLM Crawlers by the Numbers

AI crawlers are no longer niche. They're dominating web traffic—and their numbers prove it:

These bots are everywhere. They're scanning your blog posts, documentation, product pages—even your FAQ sections. But they're not crawling to rank your pages. They're crawling to extract structured knowledge, power retrieval systems, and populate LLM-based responses.

What is RAG and Why Should You Care?

Retrieval-Augmented Generation (RAG) is a method that LLMs use to provide better answers. Instead of guessing from internal memory, the model retrieves external, relevant passages and incorporates them into the response.

This changes everything.

To appear in RAG-based responses, your content must be:

Use Semantic HTML and Lightweight Markup

AI crawlers prioritize structure over aesthetics. They're parsing HTML directly—so every tag matters.

Lightweight, semantic HTML ensures bots can crawl quickly and extract meaning without rendering obstacles.

Adapt to 23-Word Queries

In the LLM world, queries aren't short or vague. They're specific and often long-form. Recent data shows:

Users are typing full questions like:

The Fall of Organic Clicks

In December 2023, AI Overviews (formerly SGE) appeared on 84% of queries. By July 2024, they dropped to 7%—but here's the catch:

E-E-A-T Remains Essential in the AI Era

LLMs are trained to prioritize credible, consistent sources. That means your site needs to show:

Here's what the data shows about content that gets picked up by AI systems:

Use this comprehensive checklist to audit and optimize your content for AI crawlers:

Introducing Large Language Model Optimization (LLMO)

You've heard of SEO. Meet its AI-native successor: LLMO. It's the practice of designing and structuring content specifically to serve LLMs and RAG-based interfaces.

AI-first SEO is a multidisciplinary approach combining traditional technical SEO, structured data, brand entity building, and content design principles built for machine interpretation.

The rules of search and visibility have fundamentally changed. Classic ranking signals like keywords and backlinks still matter—but they're just one part of the equation. The new reality of AI-first SEO means writing for bots that don't just crawl—they read, interpret, and summarize.