SEO vs AEO: Why Structure Beats Backlinks in an AI-Driven World

At some point in the last year, SEO quietly split into two conversations.

One group is still arguing about rankings, backlinks, and domain authority.

The other group is asking a different question entirely:

“Why does this article keep getting cited by ChatGPT?”

That second question is where things start to get interesting.

Because what we’re seeing now isn’t the death of SEO — it’s a shift in what matters most.

First, let’s clear up the terminology mess

Depending on who you ask, this new thing is called:

• AI Engine Optimisation (AEO)

• Answer Engine Optimisation

• Generative Engine Optimisation (GEO)

• AI Search Optimisation

If that feels messy and undefined, it’s because it is.

This is a very young field. We’re still arguing about the name, which usually means the rules aren’t settled yet.

But regardless of what we call it, the underlying change is clear:

content is no longer being evaluated only by search engines — it’s being consumed by machines that generate answers.

And those machines care about different things.

Backlinks still matter… just not as much as they used to

This is usually the point where someone gets uncomfortable.

So let’s be precise.

Backlinks are not useless.

Internal linking still matters.

Authority still matters.

But backlinks are no longer the primary signal for visibility inside AI answers.

That makes sense when you think about why Google cared about backlinks in the first place.

Backlinks were votes. They helped Google decide which pages humans trusted.

LLMs don’t need votes in the same way. They need clarity.

They’re not ranking pages on a results list — they’re extracting answers.

What AI actually wants from your content

When an LLM looks at your page, it’s not asking:

“Is this domain authoritative?”

It’s asking:

“Can I confidently use this to answer a specific question?”

Which means the things that matter most now are:

• clear page structure

• short, focused sections

• explicit answers

• predictable formatting

• unambiguous language

In other words: on-page SEO is having a comeback moment.

A real example: low backlinks, high visibility

One of our best-performing pieces inside AI tools is an article about HubSpot pricing.

From a traditional SEO perspective, it’s nothing special:

• very few referring domains

• low URL rating

• not much link equity

Yet it consistently shows up as a cited source when you ask questions like:

“What does HubSpot cost per user?”

“How does HubSpot pricing work in 2025?”

Why?

Because the article is answer-shaped.

It has:

• clear headings

• short sections

• key takeaways up front

• tables with explicit numbers

• updated information

• no fluff

The structure does the heavy lifting.

Compare that to the classic pillar page

Now let’s look at the opposite.

We have a long-form pillar page comparing multiple CRMs in South Africa.

It’s well written.

It ranks.

It’s been updated.

It even has videos.

From an SEO checklist point of view, it ticks a lot of boxes.

But inside AI tools?

It doesn’t exist.

Why?

Because it’s doing too many jobs at once.

It’s broad.

It’s long.

It mixes multiple topics.

It requires interpretation.

Humans might enjoy reading it.

Machines don’t want to interpret. They want to extract.

Specific beats comprehensive

This is one of the hardest mindset shifts for content teams.

For years, we were taught:

“Go deep.”

“Cover everything.”

“Create ultimate guides.”

AI flips that.

The content that wins now tends to be:

• narrowly focused

• very specific

• clearly segmented

• explicitly titled

“HubSpot pricing per user in 2025” beats

“Which CRM should you choose?”

Not because it’s better content — but because it’s easier to use as an answer.

FAQs are no longer an afterthought

One of the strongest signals we’re seeing is the return of the humble FAQ section.

Not long, meandering FAQs.

Short ones.

Clear ones.

Almost boring ones.

Questions like:

• How much does X cost?

• What’s included?

• Who is it for?

• What’s the downside?

These map perfectly to how people prompt AI tools.

And when your content already looks like the answer, it becomes the answer.

Domain authority vs page usefulness

Another subtle shift: page-level usefulness is outweighing domain-level authority.

We’re seeing relatively small sites get cited over massive brands simply because their page answers the question more cleanly.

This would have been almost unthinkable in classic SEO.

But again, LLMs aren’t ranking — they’re assembling.

They don’t need “the best site”.

They need “the clearest answer”.

What AEO really changes (and what it doesn’t)

AEO doesn’t replace SEO fundamentals.

It changes the priority order.

Less emphasis on:

• chasing backlinks at scale

• bloated pillar pages

• writing for volume

More emphasis on:

• structure

• specificity

• freshness

• clarity

• accuracy

And one more thing that’s easy to underestimate…

Bad data scales badly in AI

We had HubSpot reach out to us to correct a small pricing detail in one of our articles.

One number.

One seat price.

Out of dozens.

That’s not a coincidence.

AI systems don’t just consume content — they amplify it.

If your data is wrong, it doesn’t stay wrong quietly on page 3 of Google. It gets repeated confidently.

Which means content hygiene is now a brand risk issue, not just an SEO one.

The uncomfortable takeaway

You can be ranking well on Google and still be invisible in AI.

That’s new.

And it’s why SEO dashboards alone are no longer enough.

The next question becomes:

How do you even measure whether your brand shows up inside AI tools?

Because if discovery is happening there, that’s where share of voice needs to be tracked.

That’s what we’ll tackle next.

Read: How to Measure Your Brand’s Visibility Inside AI (And Why Share of Voice Matters)