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So now that we understand how AI sees brands from my previous article “Best AI SEO Strategies for 2026: Rank in ChatGPT, Perplexity, and Google AI Overviews,” now let’s get into the practical stuff.
This is where the real change begins. Because AI doesn’t reward the most content. It rewards the most organized content.
Now, what is organized content?
It is the content that is easy to interpret, connect, verify, and quote.
Here’s what we used to do pre AI SEO era, we built websites like brochures.
It was a must to have a homepage, a few service pages, or product pages, a blog, some contact info.
And frankly, that really worked when Google was the only gatekeeper. But now with LLMs in the ring, it is a different ball game. Now, we have to think differently and that’s where I see most marketing agencies are missing out.
I still see IT and marketing agencies pitching brochure-style sites to clients. The change has to start at the strategy and thinking level.
Because in this new search era, where LLM platforms like ChatGPT, Perplexity, and Grok are driving traffic to websites and even acting as auto lead vetting and nurturing engines, your website can’t be a brochure anymore.
It has to behave like a database. It should be a network of information that helps AI understand relationships, depth, and authority in your topic.
I will break this down for you in detail in this article. So keep reading.
Everything on your website should map to a clear data model. This means AI should be able to understand four simple things without guessing.
Let me break this down with examples from some of the audits we have done for our clients to help get a clearer picture.
Most websites don’t make this clear. They speak to everyone and end up speaking to no one.
One of our clients who run a service marketplace, their website pages never defined who the platform actually served.
There were no dedicated user segments.
– No “For homeowners”
– No “For businesses”
– Not even a “For professionals” page explaining who could join the platform
So, in the audit we did, I found that LLMs had no idea which audience these pages were meant for. It couldn’t build entity relationships like:
I helped them understand that LLMs need clear segments to understand context.
Because the audience is part of your entity graph.
If you are doing something like this, then it's time to change and define audience types in your structure, like:
A clean data model starts with clear human segments.
This is where most websites completely fail. I have seen businesses with unclear service or product models, which makes it harder for LLMs to understand.
In one of our healthcare tourism client projects, we saw hundreds of service pages. But all of them were mixed between:
There was no separation between categories. No parent-child hierarchy. And most importantly, there was no clarity on what is a service vs what is supporting content.
For LLMs, this is chaos. We suggested the following model and it really worked for them:
Main categories:
– Hair transplant, dental implants, cosmetic surgery, weight loss
Subcategories:
– Hair restoration methods, dental crown types, fat reduction options
Keyword rich landing pages:
– Hair transplant in Turkey
– Dental implants in Spain
– Tummy tuck in Mexico
Supporting content:
– Pricing
– Recovery
– Success stories
– Doctor qualifications
This help AI platforms understand:
Location is a massive part of AI/LLMs understanding. As I mentioned in the service marketplace project we worked on, the business targeted;
But the site had:
AI cannot trust a location page if it has no local depth.
To AI, a “Service in Melbourne” page with no providers, no reviews, no pricing, and no local context is not a location page.
It’s just text.
We suggested a proper breakdown:
With this we created thousands of real location-entity connections.
Now this is the foundation of programmatic SEO. But most brands skip this step and generate thin, useless pages. Take note as AI ignores those instantly.
This is the most underrated part of the data model.
AI learns from formats, not just words.
In one of the client projects – we noticed that they had great products and categories.
But no structured formats like:
Everything was written like a paragraph. So LLMs treated it like generic text.
We also noticed Article Schema on service pages. So we instantly know that LLMs are going to classify them as blogs, not medical services.
Take a note
“Wrong schema equals wrong interpretation.”
Your data model should include structured content formats like:
When AI sees consistent formats, it starts associating your brand with:
This is what increases your retrievability changes by AI platforms like ChatGPT and others.
Because AI is not trying to “rank” your content. It’s trying to understand it.
And it can only understand it if your website behaves like a structured database.
Most websites today are not designed for this. They’re designed for human scrolling, not LLMs evaluation.
But the brands that fix this early will dominate AI search for years.
If you need help identifying the gaps and fixing/updating your site for AI retrievability, drop me an email at contact@sanjayb.com or just book a consultation with me.
Let’s talk about content.
You might find this surprising, but I actually started my career as a content writer and strategist.
It’s been more than 15 years now, and I still see most brands treating content like a school assignment.
That approach worked when the goal was to “rank a page.” But now the goal is different.
Now the goal is information gain.
And the biggest shift I’m noticing is that LLMs don’t want consumption content. They want participation content that lets the user take action, compare, validate, check, calculate, or decide.
In short, LLMs want content with:
Let me dive in and share a bit more details on what LLMs really want:
AI systems can identify when a page feels human and trustworthy. A big issue I saw in our client projects especially the dental clinics, hospitals, restaurants, and law firms – their pages were full of scraped reviews and misleading numbers.
Nothing on the page felt real.
And trust me when I say this, AI can instantly detect this.
If your content looks manufactured or disconnected from real user activity, it will get ignored.
What real signals look like?
Real content comes from real behavior, and that’s what AI trusts.
Generic content dies in AI search. Client projects I mentioned above were from the US, Canada, UK and Australia, and all of them had similar issues. Their pages were filled with vague advice but no data.
– No pricing.
– No success rates.
– No comparisons.
– No factual tables.
So even though the content was long, it had zero information gain.
Real data includes:
AI loves data because it can validate it, cross-check it, and use it in answers.
This is where most brands are falling behind. I see brands creating static content and expect engagement.
But AI prefers content that helps the user interact.
So, you need elements on the site to make people interact. You can integrate widgets, price calculators, comparisons tables with check/uncheck options like tools, quizzes, checklists, etc.
In one of the client website audits, the brand had great products but no way for users or AI to compare them.
So, we suggested a comparison functionality like the example I shared above to help them build:
It also gave AI clean chunks of information that can be reused in answers.
User-generated content has become a core trust factor for AI. One of the worst issues I found in the above client projects was fake or duplicated reviews.
Some reviews were copied from Google and pasted on the website, and AI spotted that instantly.
Real user feedback tells AI that:
This is why platforms with real community activity get cited more often.
If your site has no user signals, you’re depending entirely on what you write. That’s risky.
This is the most underrated part of content design. AI prefers content that feels lived, not manufactured.
This can include:
LLMs love experience-backed content because it proves you know what you’re talking about.
Because AI extracts information, not paragraphs.
It looks for specific answers:
If your content has these participation elements answered, you stand out. If not, you blend into the noise of generic AI-generated blogs that get ignored.
This is what information gain means. And this is what makes your content retrievable.
This is where database structure really unlocks results. Because once your content is organized, you can scale in a meaningful way.
For example:
If you have 10 core services and 20 cities you serve. That is not 10 or 20 pages. That is 200 pages of specific intent
Like:
Users ask very specific questions. AI responds with very specific answers.
So, you need very specific pages.
Programmatic SEO lets you satisfy thousands of intent combinations without writing thousands of blogs.
But only if those pages have:
This is rarely talked about. Internal links are not just SEO navigation elements anymore.
They are a knowledge graph signal for AI.
One of our lawyer clients had a website with thousands of orphan pages. Google indexed them but AI did not know how they related to anything else.
We cleaned the structure:
Suddenly, the website had context
AI platforms could understand:
That is how entity authority is built. Not just through links, but through connections.
Schema markup is not decoration. It is vocabulary for machines.
You need to speak AI’s language so it can speak yours.
Key schemas that matter now:
Good schema tells AI:
AI does not guess, it uses signals. So, give it the right ones.
Here is a simple checklist for you – this is the interactive content moment 🙂
Open your notepad and write the answers for the following questions:
If you are able to answer all of them clearly, the next step is to check if it is applied on our website structure.
Keep in mind that rankings are old SEO and retrievability is new SEO. And retrievability comes from structure.
Ranking is one thing. Getting quoted by AI is another.
When you see a ChatGPT answer that starts with “According to…” or “Based on data from…”, that’s not random.
It means that the website earned enough trust, clarity, and structure for the AI to use it as a source.
That’s the next level of visibility being cited.
AI systems don’t prefer long blogs or keyword-heavy pages. They prefer content that’s extractable, clean, specific, and easy to quote.
Here are six formats that consistently show up in AI-generated answers.
This is the simplest and most reliable format.
Start by giving the direct answer in one or two sentences, then add context and data below.
AI reads top-down.
If you make it easy to understand the main idea in the first line, it will use your content more often.
We saw this while optimizing content for a SaaS business.
Pages with clear, definition-style openings were cited more frequently in AI summaries than those with long introductions.
Structure your paragraphs like this:
These are small, focused pages built around a single subtopic, claim, or concept.
Instead of writing a 3000-word general guide, break it into smaller, self-contained pages.
Each page should include:
This makes your website look like a structured knowledge graph. LLM systems love it because they can retrieve a single, clear answer without parsing a massive article.
AI systems like recommendations that include reasoning.
“Best” or “Top” lists work well only if you justify them.
Example:
“Tool A is best for small teams because it’s easier to set up.
Tool B suits large organizations due to its workflow automation features.”
That’s the kind of logic AI picks up. It isn’t the word “best,” it’s the reasoning that follows it.
Use compact tables, comparison functionality (interactive element), pricing examples, and verdict-style summaries.
This is what modern AI overviews pull into answers.
This format is almost made for AI retrieval. Question-answer pairs, structured cleanly with FAQ schema.
Make each answer short and specific, two or three sentences max.
Include metrics or constraints wherever possible.
For example:
Q: How often should you update AI-optimized content?
A: Once every 90 days is ideal to maintain freshness, based on crawl and retrieval frequency.
Simple. Clear. Useful.
We implemented this for a tourism site, and within 4 weeks, their FAQs started appearing inside AI Overview panels.
AI systems often answer “how” questions with procedural clarity.
If your page lists steps with clear roles, time, and expected outcomes, it’s gold for citation.
Example:
Each step can be parsed and reused by AI as instruction-level knowledge.
Add How To schema where relevant, and AI can instantly identify the procedural nature of the content.
This one’s underrated.
AI doesn’t just learn from success stories. It learns from contrast, when you show what worked and what didn’t.
If you include both “actions taken” and “what would’ve happened if we didn’t,” it demonstrates real expertise.
Example:
“After implementing structured data, conversions rose 23%.
Without it, AI Overviews continued to skip our content for two months.”
You can check our case studies for more details here: Case Studies
This shows understanding, validation, and consequence, perfect signals for AI trust.
Once you have the right format, the next step is to write in a way AI can extract.
Here’s how:
The more grounded your writing, the more likely it is to be quoted.
Everything AI cites is backed by structured clarity.
That’s why metadata and schema implementation matter more than ever.
Before you publish, check:
This invisible layer tells AI, “This page is reliable and current.”
Without it, even great content can stay unseen.
In one of our project examples I shared above – an online service platform, their “Top Professionals” pages were rewritten using micro-page structure, with local schema and FAQs.
Within three months, those pages were being referenced in AI responses for city-specific service queries.
The content didn’t go viral. It just became useful.
That’s the shift from chasing traffic to becoming part of the answer.
AI SEO isn’t about tricking algorithms. It’s about helping them understand you faster and trust you more.
You don’t need to create more content. You need clearer, more structured, and more useful information.
When your brand becomes the source AI platforms quote, you stop chasing visibility.
You own it.
If you want support with AI SEO audits, content architecture, or rebuilding your site for AI retrievability, feel free to reach out.
This is the work I do every day with my team.
We help brands with:
A full audit of your AI visibility across ChatGPT, Perplexity, Gemini, Copilot, and Google AI Overviews.
Full AI SEO done for you.
We redesign and update the on-page elements of your site into an AI-friendly structure.
We rewrite or optimize your existing content so AI systems can understand and quote it.
Local visibility for AI search.
Direct access to you for strategy, growth, planning, content systems, AI workflows, and marketing leadership.
Light, ongoing monthly monitoring for brands that don’t need full execution.
If you want me to take a look at your setup and show you exactly what needs to change, just message me.
Happy to help
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22 Nov 2025
