Rethinking SEO in the age of AI

For years, SEO followed a fairly predictable playbook: create valuable content, optimize it for search engines, and compete for rankings on Google. But the way people discover information online is changing quickly. Tools like ChatGPT, Perplexity, and Gemini are introducing a new layer between users and search engines, where answers are generated and synthesized rather than simply retrieved.

In a recent episode of the Get Discovered podcast, Joe Walsh, CEO of Prerender.io, sat down with Yoast’s Principal Architect Alain Schlesser to discuss what this shift means for SEO and online discoverability. Their conversation explores how AI answer engines are reshaping the search landscape and why many traditional SEO assumptions no longer fully apply.

Alain shares insights on:

• How AI systems retrieve and surface information
• Why brands must rethink their online positioning, and
• What businesses should start preparing for as AI-driven discovery evolves over the next 12–18 months?

Watch the full conversation between Joe Walsh and Yoast’s Principal Architect, Alain Schlesser, in the Get Discovered podcast below.

The new discovery layer: AI is becoming the gatekeeper

“There’s now a layer in front of search that acts as a gatekeeper before you even hit those search engines.”

That’s how Alain describes one of the biggest structural shifts happening in online discovery today. For years, the flow of search was straightforward: a user typed a search term into a search engine, the engine returned a list of results, and the user decided which link to click.

But AI-powered systems have added a new layer to that process.

From search queries to conversational discovery

Today, many users begin their search journey by asking questions in tools like ChatGPT, Perplexity, or Gemini instead of typing traditional keyword queries. The AI system then determines whether it needs external information and may generate multiple search queries behind the scenes to retrieve relevant sources.

The discovery flow now looks something like this:

Previously:

User → Search engine → Website

Now:

User → AI model → Search engine → Website → AI synthesis → User

Instead of presenting a list of links, the AI model interprets and combines information before generating an answer. Alain explains this process in more detail in the podcast, highlighting how AI systems now act as a filtering layer between users and the web.

Search is fragmenting beyond Google

“We were in a rather comfortable position where we were only dealing with a monopoly search.”

For much of the past two decades, SEO largely meant optimizing for one ecosystem: Google. Even though other search engines existed, Google dominated how people discovered information online.

But that environment is changing.

As Alain explains, AI systems are introducing a new layer of fragmentation in discovery. Different AI platforms rely on different combinations of search engines, indexes, and training data, which means results can vary widely between them.

In practice, that means a brand might appear prominently in one AI system while barely showing up in another. For SEO teams, this marks a shift toward thinking about visibility across multiple AI-driven environments rather than just one search engine.

Do checkout: Why does having insights across multiple LLMs matter for brand visibility?

What hasn’t changed: The fundamentals of SEO

Despite technological changes, Alain emphasizes that the core principles of good SEO remain intact.

“You shouldn’t try to game the search engine. You need to create valuable content that humans actually want to read, and structure it so search engines can understand it.”

At its core, search still aims to deliver the best possible answers to users. Whether the request comes from a person typing a query or an AI model generating one behind the scenes, the goal remains the same: surface useful, reliable information.

That means SEO teams should continue focusing on fundamentals such as:

• high-quality content
• clear structure
• indexable and accessible pages
• content that satisfies the user’s search intent

AI systems may change how information is surfaced, but they still rely on the same underlying signals of quality and relevance.

The “top results or nothing” reality

As the discovery landscape evolves, another important shift emerges in how AI systems interact with search results.

“They don’t see the full search result page. What the LLM typically sees is just the five topmost elements per search query.”

Unlike human users, AI systems typically work with a very small set of retrieved sources before generating an answer. That means if your content doesn’t appear among those top results, it may never reach the AI system at all.

In a world where AI answers rely on the summarization of modern content, only the sources that make it into that small retrieval window influence the final response.

This makes strong search visibility more important than ever. Ranking well isn’t just about earning clicks anymore. It determines whether your content is even considered when AI systems construct an answer.

Why “safe” content strategies are no longer enough

Even if your content reaches those top results, there’s another layer of filtering happening inside the AI model itself.

Large language models compress enormous amounts of information during training. As Alain explains:

What the model keeps are the dominant signal and the outliers. Everything in between is often compressed away as statistical noise.

In the podcast, Alain uses this idea to explain why brands that try to be broadly acceptable or “safe” may struggle to stand out in AI-driven discovery.

The takeaway is clear: in a world where AI systems summarize and compress information, having a clear and distinctive perspective becomes increasingly important.

Why Yoast launched AI visibility tracking

As AI systems reshape how information is discovered and summarized, a new challenge emerges for businesses: understanding how their brand appears in AI-generated answers. That’s the problem Yoast set out to address with Yoast SEO AI +, a feature designed to help businesses monitor how their brand shows up across major AI platforms.

Earlier in this article, we explored how AI systems now sit between users and search engines, retrieve only a small set of results, and synthesize answers through the summarization of modern content. Together, these changes create a new discovery layer that is far less transparent than traditional search.

As Alain explains in the podcast:

“We need more visibility and observability into that AI-based layer to figure out what is going on there. Right now, it’s mostly a black box.”

Unlike traditional search engines, AI systems don’t provide clear rankings, impressions, or click data that explain why a source was selected. Instead, answers are generated from a mix of retrieved content, training data, and model reasoning. For businesses, that makes it much harder to understand whether their brand is visible in AI-driven discovery.

This is where AI visibility tracking becomes valuable. Rather than focusing only on search rankings, teams also need insight into how their brand is represented inside AI responses.

Yoast SEO AI + helps surface that layer by allowing teams to observe how their brand appears across AI systems, such as ChatGPT, Perplexity, and Gemini.

Must read: What is ChatGPT Search (and how does it use Bing data)?

The goal is not simply to track another metric. It’s to help businesses understand how AI systems interpret and represent their brand.

As Alain notes, visibility in AI systems can vary significantly depending on the platform, because each one relies on different combinations of:

• search engines
• indexes
• training datasets

This means a brand might appear frequently in one AI system while barely showing up in another. Without visibility into those differences, it becomes difficult for teams to understand how their content performs in the new discovery landscape.

In that sense, tools like Yoast SEO AI + are less about selling a new SEO feature and more about helping businesses observe a rapidly changing ecosystem where discoverability no longer happens only in search results.

The next evolution: AI agents making decisions

“What we will increasingly see is automated transactions where AI agents navigate websites and initiate actions on behalf of users.”

So far, much of the discussion around AI and search has focused on how answers are generated. But according to Alain, the next phase of this evolution may go further.

Over the next 12–18 months, AI systems may begin moving beyond answering questions and start performing tasks on behalf of users. Instead of guiding someone toward a website to make a decision, AI agents could increasingly compare options, interact with websites, and complete actions automatically.

If that shift happens, the traditional customer journey could change significantly. Alain shares a fascinating perspective on what this might mean for businesses in the coming years in the full podcast conversation.

SEO matters more than ever

AI isn’t replacing SEO. If anything, it’s reinforcing why good SEO matters in the first place. What’s changing is the path between users and content. Instead of navigating search results themselves, users increasingly receive answers that AI systems retrieve, interpret, and synthesize.

That makes strong fundamentals more important than ever. Businesses still need to focus on:

• valuable content
• clear structure
• discoverable and indexable pages
• a distinctive brand identity

But the central question for SEO is evolving. It’s no longer just:

“Can Google find my website?”

It’s now:

“Does the AI have a reason to remember my brand?”

For more insights from Alain Schlesser on how AI is reshaping SEO, watch the full Get Discovered podcast episode.

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