Information Architecture was never just about navigation.

For years, SEO professionals have talked about site structure, navigation, categories, internal linking, URLs and content hierarchies.

We have advised businesses to organize their websites logically because it makes websites easier for users to navigate and easier for search engines to crawl and understand.

But the emergence of AI Search is giving Information Architecture a much bigger role.

Today, a website is not only being accessed by a person who clicks from page to page.

Its information may also be discovered, interpreted, connected and retrieved by increasingly sophisticated search and AI systems.

And that changes the way SEOs should think about Information Architecture.

The question is no longer simply:

“Can a user find the information on my website?”

It is increasingly:

“Can a search engine or AI system understand how the information on my website is organised, related and connected?”

That is where Information Architecture and AI Search intersect.

What exactly is Information Architecture?

Information Architecture (IA) is the practice of organizing, structuring, labelling and connecting information so that it can be found and understood.

On a website, this includes things such as:

• Site hierarchy
• Navigation
• Categories and taxonomies
• Content relationships
• Internal linking
• URL structure
• Headings and page structure
• Content organisation
• Breadcrumbs
• User pathways
• Findability

Traditionally, much of the discussion around IA has been centered on user experience.

A visitor should be able to understand:

• Where am I?
• What information is available here?
• What should I look at next?
• How do I get back to the previous level?
• Where can I find the answer to my question?

These are still extremely important questions.

But there is another participant in the ecosystem now:

AI.

The website is becoming an information system

For a long time, many businesses treated their website as a collection of individual pages.

• A Home page.
• An About Us page.
• A few service pages.
• Some product pages.
• A blog.
• A Contact page.

From a traditional website-development perspective, that may be enough.

From an SEO perspective, however, these pages have always needed to work together.

And in the age of AI Search, that interconnectedness becomes even more significant.

Think about the difference between these two websites.

Website A

• It has 100 articles.
• Each article targets a different keyword.
• The articles are largely independent of one another.
• There are very few internal links.
• The categories are vague.
• The navigation is based mainly on the company’s internal terminology.

There is little indication of how the topics relate to each other.

Website B

• It has 100 articles too.
• But the content is organized around clearly defined topics.
• There are comprehensive pillar pages.
• Supporting articles connect to those pillars.
• Related concepts are linked contextually.
• Categories have meaning.
• URLs follow a logical structure.
• Important pages are accessible through internal links.
• The website demonstrates relationships between concepts.

Both websites may have 100 pages.

But they don’t have the same information architecture.

And they certainly don’t communicate the same amount of meaning.

SEO has always been about more than individual pages

One of the mistakes I see in SEO is thinking about every page independently.

We often ask:

• What keyword should this page rank for?
• What should the title tag be?
• What should the H1 be?
• How many times should the keyword appear?

These questions have their place.

But a search engine does not encounter your website as a collection of isolated pages.

• It discovers pages through links.
• It processes the content on those pages.
• It observes relationships between pages.
• It tries to understand what the website is about.

Google itself states that links help its systems find new pages and understand the relevance of pages and recommends linking to important content from relevant pages using meaningful anchor text.

So internal linking is not merely a navigation mechanism.

It is part of the information architecture of a website.

Now add AI Search to the equation

AI Search changes the nature of the search experience.

Instead of simply returning a list of documents for a query, AI-powered search systems can retrieve information from multiple sources and use it to construct a response.

Google’s current documentation describes AI Overviews and AI Mode as using techniques including query fan-out and retrieval to find supporting information across the web. Google also says its generative AI search features are rooted in its existing Search systems and that foundational SEO practices continue to apply.

This has an important implication for SEOs.

The ability of a website to communicate relationships between pieces of information matters.

Imagine a website about solar energy.

It has a main page about:

Solar Energy Solutions

Under that, it has pages about:

• Residential Solar
• Commercial Solar
• Solar Panels
• Solar Inverters
• Battery Storage
• Solar Installation
• Solar Maintenance
• Solar Financing

It also has supporting articles about:

• How solar panels work
• Monocrystalline vs polycrystalline panels
• How much electricity a solar system generates
• Solar battery storage
• Solar panel maintenance
• Solar ROI
• Government incentives

If these pages are properly connected, the website isn’t merely publishing articles.

It is building an information environment.

The relationships between those pages help communicate:

Solar Energy → Solar Systems → Components → Applications → Installation → Maintenance → Economics

That is Information Architecture.

And that is also highly relevant to modern SEO.

From keywords to concepts

This is perhaps the most important change SEOs need to make.

Traditional SEO often started with:

Keyword → Page

Modern SEO increasingly needs to think in terms of:

Topic → Concepts → Entities → Relationships → Content → Pages

And Information Architecture is the mechanism that helps turn those relationships into a navigable website.

For example:

Digital Marketing

could contain:

→ SEO
→ Paid Search
→ Social Media Marketing
→ Content Marketing
→ Email Marketing

SEO could contain:

→ Technical SEO
→ On-page SEO
→ Off-page SEO
→ Local SEO
→ Ecommerce SEO
→ AI Search

AI Search could contain:

→ AI Overviews
→ AI Mode
→ Generative Search
→ RAG
→ Retrieval
→ Semantic Search
→ GEO
→ AEO

Now imagine that the pages within these groups are properly linked to one another.

The website begins to communicate something much more powerful than individual keyword targeting.

It communicates relationships between concepts.

Internal linking is information architecture in action

Internal linking is sometimes treated as an SEO tactic that is primarily about passing authority from one page to another.

That is an incomplete view.

An internal link can also answer a much more important question:

What is this page related to?

Consider this sentence:

“AI Search is changing the way websites need to communicate information.”

If the words AI Search link to an authoritative page explaining AI Search, that link creates a relationship.

Now imagine another page discussing:

“Retrieval-augmented generation and how AI systems retrieve information.”

If it links back to the AI Search page, another relationship is created.

Over time, these links create an information network.

This is why I believe SEOs should stop looking at internal links only as an authority-distribution mechanism.

They should also look at them as a semantic relationship mechanism.

Google’s own guidance recommends using relevant anchor text and linking to related resources because this helps both users and Google make sense of a website and discover other pages.

Your website can have a taxonomy — or a pile of pages

Taxonomy is another important part of Information Architecture.

A good taxonomy answers:

How should this information be grouped?

Suppose an SEO agency has 200 blog posts.

If the categories are:

• SEO
• Marketing
• Digital
• Business
• Technology
• Other

the taxonomy doesn’t communicate much.

But if the content is organized around meaningful subject areas such as:

• Technical SEO
• Content SEO
• Ecommerce SEO
• Local SEO
• AI Search
• Search Analytics
• SEO Strategy

the taxonomy begins to communicate expertise.

The difference is subtle but important.

A taxonomy is not merely a filing system.

It is a representation of how you understand your subject.

And that is precisely why IA becomes interesting in the context of AI.

Information Architecture can become your website’s knowledge map

Think of your website as a knowledge map.

• Every important page represents a piece of information.
• Every internal link represents a relationship.
• Every category represents a grouping.
• Every heading establishes hierarchy.
• Every breadcrumb establishes position.
• Every URL communicates location.
• Every navigation element communicates importance and context.

Together, they form an architecture.

This doesn’t mean that an AI system literally reads your website as a human-readable mind map.

We should be careful about making such claims.

But we can reasonably say that clear structure, crawlability, contextual links and well-organized content make information easier for both people and search systems to discover and interpret. Google explicitly recommends logical site structures, relevant internal links and clear headings for search visibility and sitelinks.

That is the real SEO opportunity.

IA and the rise of RAG

There is another reason Information Architecture deserves more attention from SEOs.

Modern AI systems increasingly use retrieval techniques to obtain relevant information before generating an answer.

Google’s documentation describes retrieval-augmented generation (RAG), or grounding, as a technique used in its generative AI search experiences to retrieve relevant, up-to-date web pages from its Search index.

This doesn’t mean that simply reorganizing a website will guarantee inclusion in an AI answer.

It won’t.

There is no magic “AI-friendly IA” formula.

But it does reinforce a fundamental SEO principle:

Information has to be discoverable before it can be retrieved.

And information that is properly organized and connected is easier for humans and machines to navigate.

IA is not about making a website “AI-friendly”

I would actually caution SEOs against using the phrase “AI-friendly website” too loosely.

There is a growing tendency to create lists of things supposedly required to make a website visible in ChatGPT, Gemini, Perplexity or Google’s AI features.

Some of these recommendations are useful.

Others are simply the latest version of SEO folklore.

Google’s current guidance is quite clear that there are no special additional technical requirements or special schema needed specifically to appear in AI Overviews or AI Mode. The fundamentals still matter – crawlability, indexability, useful content, internal links, structured data where appropriate and good page experience.

So, I wouldn’t recommend rebuilding a website merely because “AI needs it.”

Instead:

Build a website whose information is clear, accessible, logically structured and meaningful.

That is good Information Architecture.

It is good UX.

It is good SEO.

And increasingly, it is good preparation for AI-mediated search.

What should SEOs examine when auditing Information Architecture?

An IA audit should go much deeper than checking whether the main navigation works.

I would look into at least these areas.

1. Site hierarchy

Can you understand the website’s subject hierarchy within a few minutes?

Does the structure reflect the way customers think about the subject?

2. Content hierarchy

Does each major topic have a logical parent?

Are supporting topics connected to broader topics?

Are important pages buried several levels deep?

3. Internal linking

Are important pages linked from relevant pages?

Are links contextual?

Does the anchor text explain the relationship?

Are there orphan pages?

Google recommends that important pages should be reachable through links and specifically notes that every page you care about should have a link from another page on the site.

4. Taxonomy

Do categories represent meaningful topics?

Or were they created simply because the CMS required categories?

5. URL structure

Does the URL structure reinforce the organisation of the website?

A URL should not be considered a ranking trick.

But a logical URL structure can help communicate location and hierarchy.

6. Navigation

Does the navigation reflect user needs?

Or does it merely reproduce the organisation’s internal departments?

This is a surprisingly common problem.

A company may think in terms of:

Solutions → Vertical A → Product X

while its customers think:

What I need → Problem → Solution → Product

Good IA bridges that gap.

7. Content relationships

Ask a simple question:

What other information should a person understand before or after reading this page?

Those relationships should often become internal links.

8. Semantic consistency

Are the same entities and concepts referred to consistently throughout the website?

If a business uses three different terms for the same concept, does the website make the relationship clear?

9. Findability

Can users—and search engines—reach important information without having to guess where it is?

Google’s guidance for AI features specifically stresses making content easily findable through internal links.

10. Content gaps and unnecessary duplication

Does the website have:

too little information?

Or does it have:

multiple pages saying almost the same thing?

AI doesn’t make content duplication a strategy.

In fact, Google’s current guidance warns against creating large numbers of pages around variations of queries simply to influence search or AI responses.

The goal should be meaningful coverage, not maximum page count.

The future SEO audit may need an IA layer

Traditional SEO audits often contain sections such as:

• Technical SEO
• On-page SEO
• Content
• Backlinks
• Core Web Vitals
• Schema
• Indexation

I believe Information Architecture deserves to be treated as a distinct strategic layer.

Because a technically perfect website can still have a poor information architecture.

It can be:

• Crawlable.
• Indexable.
• Fast.
• Mobile-friendly.
• Schema-enabled.

And still be difficult to understand.

That’s a problem.

Not just for users.

But for the systems trying to make sense of the information.

IA, SEO and AI: three different perspectives

Perhaps the easiest way to understand this relationship is to look at the same website from three perspectives.

Perspective	Primary question
User Experience	Can I find and understand what I need?
SEO	Can search engines discover, understand and surface the information?
AI Search	Can information be discovered, interpreted, connected and retrieved in the context of a question?

These aren’t three separate objectives.

They overlap.

And good Information Architecture sits at that intersection.

The website is no longer just a collection of pages

This is where I believe the conversation around IA needs to evolve.

For years, we have optimized pages.

We now need to think more seriously about information systems.

A website should not simply answer:

“What does this page say?”

It should also make it possible to understand:

“What does this website know?”

And then:

“How is that knowledge organized?”

And:

“How are the different pieces of knowledge connected?”

This is a much more strategic way of looking at SEO.

IA could become one of the foundations of AI Search readiness

I would not call Information Architecture a new AI ranking factor.

That would be an oversimplification.

Nor would I suggest that restructuring a website will automatically make it appear in ChatGPT, Gemini, Perplexity or Google AI features.

It won’t.

But the direction of Search is clear.

Search systems are becoming increasingly capable of understanding questions, concepts, context and relationships.

Google’s own guidance for generative AI search continues to emphasise the fundamentals: useful content, clear organization, crawlability, internal linking and technical accessibility.

That makes an old SEO discipline suddenly much more interesting.

Information Architecture.

The SEO takeaway

Perhaps the biggest lesson is this:

Don’t build a website as a collection of pages. Build it as a connected body of information.

Don’t ask only:

What keyword should this page target?

 

 

Ask:

• What topic does this page belong to?
• What concepts does it explain?
• What other concepts is it connected to?
• Which page should be its parent?
• Which pages should it support?
• What should link to it?
• What should it link to?
• Can a user find it?
• Can a search engine discover it?
• Can the information be understood in context?

That is Information Architecture.

And in my view, the rise of AI Search doesn’t make IA new. It makes good IA more important.

The future of SEO may not be about creating more pages.

It may be about creating better-connected information.

Because when search moves from matching words to understanding questions, the relationships between pieces of information become increasingly important.

And that is where Information Architecture meets SEO—and where SEO meets AI Search.

Points to ponder on…

We spent years telling businesses:

“Build your website for your users, not just for search engines.”

Perhaps the next evolution is:

“Build your website so that its information is understandable to users, discoverable by search engines and meaningful when machines need to retrieve and connect that information.”

That isn’t about gaming AI.

It is about building a better web.

And I am sure that is what good SEO has always been about.