Getting Indexed by AI Assistants: What Actually Matters (and What's Hype)

If you run a business, you've probably heard some version of this lately:

"SEO is dead. You need to optimize for AI now."

Suddenly there are "LLM SEO" offers everywhere, promising to get you "indexed by ChatGPT" or "recommended by AI search."

Some of this is real shift. A lot of it is hype.

Generative AI tools like ChatGPT, Google's AI Overviews, Perplexity, and others are changing how people search. Instead of ten blue links, users increasingly see a synthesized answer with a few cited sources. Industry surveys are already showing that AI answers can reduce click-through to normal search results for many queries.

So yes, this matters.

But here's the key point: there is no magic "submit to all LLMs" button. The fundamentals that make you visible in traditional search—clear positioning, helpful content, clean tech, and real authority—are very close to the fundamentals that make you discoverable by AI systems too.

This post walks through what "getting indexed by AI" actually means, what's changing (and what's not), and what's worth doing right now if you're a business owner—not an SEO hobbyist.

What "getting indexed by AI LLMs" actually means

First, let's demystify the phrase.

When people say "indexed by AI," they usually mean one (or more) of these:

1. Training data for large language models (LLMs) Models like GPT are trained on huge corpora of text, including public web content. OpenAI and others now publish the user agents their crawlers use (like GPTBot) and explain how you can allow or block them via robots.txt.

2. AI search layers (Google AI Overviews, Bing Copilot, Perplexity, etc.) These tools sit on top of search indexes. They use generative models to summarize results and, in many cases, cite sources with live links back to websites.

3. Assistants that browse live web pages on demand Tools like ChatGPT with browsing, Perplexity, and others can fetch pages in real time via normal HTTP. They still rely on your site being crawlable and understandable, just like search engines.

Notice what's not on that list:

• There's no central "LLM index" you submit your business to.
• There's no special meta tag that guarantees "ChatGPT will recommend us."

You can control whether some AI crawlers use your content (via robots.txt). You cannot micromanage every training set or every AI product's behavior.

So the real question becomes:

"How do we make our website the kind of asset search engines and AI models want to use and cite?"

How AI tools decide what to show or cite

Different AI systems work differently, but most of them care about a mix of:

1. Relevance and clarity

Traditional SEO is about ranking for specific queries. LLM optimization is more about being the most useful, clearly written explanation of a topic for a given intent. The key differences between traditional SEO and LLM optimization come down to how content is evaluated.

If your content:

• Directly answers common buyer questions
• Uses plain language and clear structure
• Stays focused on a specific problem and outcome

…you're much more likely to be the snippet an AI pulls from or cites.

2. Authority and trust

AI systems don't want to hallucinate, but they still do. To reduce that, newer approaches and benchmarks explicitly try to encourage models to generate answers with citations to trusted sources.

"Trusted" in this context usually signals:

• Sites that already perform well in traditional search
• Content that's consistent with other reputable sources
• Pages with clear ownership (real business, contact info, etc.)

Google's own guidance on generative AI content makes it clear: what they care about is helpfulness, experience, expertise, authoritativeness, and trustworthiness, not whether a human or a model typed the words.

3. Technical accessibility

LLMs can't use content they can't see.

If your site:

• Blocks important crawlers in robots.txt
• Hides key content behind complex JavaScript rendering
• Uses weird URL structures or session walls for basic information

…then both search engines and AI agents will struggle.

On the flip side, if your site is:

• Fast
• Mobile-friendly
• Crawlable with clean HTML
• Marked up with sensible headings and, where appropriate, schema

…you're giving yourself a better shot at being surfaced—by Google, by AI Overviews, and by AI assistants that browse or recall.

Concrete steps to make your business more discoverable in the AI era

Here's the simple, no-BS version of "AI search optimization" for a small or mid-sized business.

1. Decide how you feel about AI crawlers (on purpose)

Today, some AI companies give you explicit control via robots.txt. For example, OpenAI documents how to allow or disallow their crawlers (GPTBot, OAI-SearchBot, etc.), and they state that these bots respect robots directives.

You technically have three options:

• Allow AI crawlers to use your public content (more chance to be in training data / cited).
• Block AI crawlers explicitly if you don't want your content used that way.
• Do nothing, effectively allowing them by default.

There's no one-size-fits-all answer, but make it an intentional choice, not an accident.

2. Make your "entity" ridiculously clear

LLMs and search engines both need to understand who you are and what you do.

At a minimum:

• Have a clear, specific home page headline that says what you do and for whom.
• Create a strong About / Company page with:
  • Legal/business name
  • Location(s)
  • Services
  • Team or founder details
• Use consistent language across your site and profiles (Google Business Profile, LinkedIn, etc.).

This isn't just for Google. LLM optimization guides point out that AI systems lean heavily on consistent, contextual signals about entities—what you are, what you're known for, and where you're located.

If you're "Acme" in one place, "Acme Digital" in another, and "Acme Web Services LLC" somewhere else, you're creating ambiguity for machines and humans.

3. Publish useful, specific content (not generic SEO fluff)

The kind of content LLMs like to use and cite tends to look a lot like the kind of content humans like to read:

• Clear answers to specific questions
• Concrete examples, numbers, and scenarios
• Straight talk instead of jargon

Think less "10,000-word skyscraper" and more:

• "How much does a B2B brochure site really cost in 2025?"
• "What a healthy web project kickoff actually looks like"
• "How to audit your website's lead flow in 30 minutes"

Several LLM optimization articles make the same point: models favor content that demonstrates context, depth, and credibility, not just keyword stuffing.

If your content is thin and interchangeable with every other site in your niche, LLMs have no reason to pick you as the example.

4. Keep your technical SEO "good enough"

You don't need to chase every technical fad, but you do need a clean baseline:

• Crawlable navigation (text links, not just fancy JS widgets)
• Descriptive title tags and meta descriptions
• Logical URL structure
• Fast load times
• Proper HTTPS and no weird redirect chains

Traditional SEO is still foundational. Most AI search optimization advice assumes you already have a reasonable technical base and then adds a layer of LLM-focused thinking on top.

If your basics are broken, you don't have an "AI problem." You have a website problem.

5. Build real-world authority

AI systems watch many of the same signals humans and search engines do:

• Are you mentioned on other reputable sites?
• Do people cite your content, data, or frameworks?
• Are you visible in your niche beyond your own domain?

That can look like:

• Guest posts or interviews on relevant sites
• Partnerships, sponsor pages, case studies
• Being listed in high-quality directories or associations

Again, this is normal brand building and SEO work. The difference is that now you're not just trying to rank—you're trying to educate the models about who you are so they can recall or cite you when relevant.

Myths to ignore about "AI indexing"

Let's kill a few ideas before they waste your time or money.

Myth 1: "There's a secret LLM index we can put you into."

There isn't.

Different companies train and run their models in different ways:

• Some license data from publishers and providers
• Some crawl the public web
• Some combine both with user-submitted content

There is no single form you fill out that says "please include my business in all AI answers." Be skeptical of anyone selling that.

Myth 2: "You need to write for robots, not humans now."

No.

If anything, the rise of LLMs makes clear, human-first writing more important, not less. AI systems are better at understanding natural language than old-school keyword matching. They reward good explanations, not robotic paragraphs stuffed with synonyms.

Google's guidance is explicit: they care about helpful content, not whether a human or a model wrote it, and they continue to evaluate pages based on usefulness and quality signals.

If a piece of content isn't good enough for a human you want as a customer, it's not good enough for an AI assistant either.

Myth 3: "Traditional SEO is dead; it's all about LLM optimization now."

This is like saying "phones made email irrelevant." Obviously not true.

Search engines still crawl, index, and rank pages. For many queries, you still get classic results—just with AI features layered on top. Most serious practitioners now argue that traditional SEO and LLM optimization complement each other. You need both to stay visible.

If someone tells you to ignore fundamentals and chase pure "AI SEO," they're selling, not advising.

Myth 4: "If you just use the right schema or meta tag, ChatGPT will recommend you."

Structured data (schema) can help machines understand your content. It's worth doing when appropriate. But there is no magical schema or meta tag that says "featuring this company in AI answers is mandatory."

The levers that really move the needle are:

• Being genuinely helpful and clear
• Being technically accessible
• Being recognized as an authority

No shortcut replaces those.

How I think about "AI discoverability" for clients

When I'm planning content and strategy with clients, I don't create a separate "AI SEO" checklist.

Instead, I fold it into how we already think about websites as business assets:

1. Get the basics right

   • Clean, fast, mobile-friendly site
   • Crawlable structure and sensible on-page SEO

2. Be intentional about AI crawlers

   • Decide whether to allow or block them via robots.txt
   • Document that decision so you don't forget what you did a year from now

3. Write for humans with questions, not algorithms with checklists

   • Focus on the real questions ideal customers ask
   • Answer them better (and more honestly) than your competitors

4. Make your entity and expertise obvious

   • Clear brand, services, and location
   • Real-world signals that you know what you're talking about

5. Measure what matters

   • Track leads, conversion rate, and CPA
   • Watch how traffic and discovery change as AI features evolve

Will AI search change how people find businesses? Yes—already is.

Will there be more noise, more buzzwords, and more agencies selling shiny new acronyms? Absolutely.

But if your website is already built around clarity, usefulness, and business outcomes, you're in a far better position than most. The game isn't "tricking an LLM into saying your name." It's making your business the obvious, trustworthy answer—so whether a human or an AI is doing the recommending, you get the call.

If you want help making your website genuinely AI-ready—not through gimmicks, but by tightening the fundamentals—let's talk.