AI Overviews Are Here. Here’s What That Means for SEO

SEO is not a new concept, and odds are, if you’re reading this article, you’re already familiar with how search engine optimization works at a foundational level.

But just because the fundamental idea behind SEO has largely remained consistent over the years doesn’t mean it’s standing still. In fact, SEO is evolving faster than most businesses realize.

The SEO You Know

Before the launch of AI-powered search tools, SEOs mainly focused on three pillars of optimization: on-page efforts like keyword usage and content structure, off-page signals such as backlinks and brand mentions, and technical areas like site speed, crawlability, and indexation.

Leveraging various tools and optimization strategies, these pillars helped shape how pages ranked and how traffic flowed from search results to websites. Together, they form the foundation of search visibility by helping search engines understand what a page is about, how trustworthy it is, and whether it deserves to be shown to users.

And these core SEO principles are not going away.

Traditional SEO tactics will remain crucial to establishing relevance, building authority, and ensuring search engines can properly access and understand your site. However, AI-driven search experiences are adding a new layer to the equation, reshaping not only how search results look but also how brands gain visibility and compete for top-of-page positioning.

Which brings us to where we are right now. SEO will continue to form the basis for how we optimize websites and content. AI SEO, however, is becoming essential for how that content is interpreted, reused, and surfaced inside AI-generated answers. It’s not a matter of replacing one with the other; it’s learning how to combine both to protect visibility and stay competitive in search.

The Shift from Clicks to Answers

AI-driven changes are not coming; they are already here. On the user end, you’re probably already noticing these changes in how search results are displayed. From a business standpoint, you may already be experiencing a sudden and pronounced drop in clicks and organic traffic.

And the numbers support what many marketers are seeing in their analytics.

A recent study found that AI Overviews in Google search results lowered click-through rates (CTR) by an average of 34.5%. Meanwhile, the prevalence of Google AI Overviews in search results continues to grow rapidly, showing up in over 60% of informational searches.

People haven’t stopped searching. But they are increasingly getting their answers without having to click through to a website.

Ranking Pages vs Shaping Answers

Traditional SEO and AI SEO have the same foundation, but they’re built for different outcomes. Traditional SEO focuses on getting pages to rank. AI SEO focuses on making information easy to retrieve, reuse, and cite inside AI-generated answers.

As we navigate this new reality, we’re not adding another pillar to our existing SEO framework. We’re adapting SEO to a search environment where answers matter more than clicks.

The goal is no longer to rank a page and hope a user clicks through. The new objective is to make your information clear, trustworthy, and structured so that AI systems can confidently use it in their answers.

So how do you actually do that?

How AI Search Thinks Differently

While clicks might be down, people are still turning to Google, ChatGPT, and other AI-powered tools to get answers to their everyday questions. What’s changing is how the “best” answer is determined.

With traditional search, crawlers would scan your web pages to understand what your content said and whether it matched a specific query. If it did, your page might appear in the search results.

Modern AI-driven search engines are doing something similar, but they’re taking a different path.

Rather than matching a single question to a single page, AI systems break a query into multiple sub-questions and gather information for each before recombining them into a complete response in an AI Overview. This gives users a richer, more complete answer, but it also means that simply optimizing for keywords is no longer enough.

The more clearly your content can satisfy these underlying questions, the more likely it is to be surfaced, referenced, or cited within an AI-generated answer. And next, we’ll give some tips on how you can structure your content to match that logic and increase your chances of being pulled into AI answers.

1. Prompt Graph Coverage

Traditional SEO treats a query as a single unit that maps to one page. To optimize for this type of search, you would focus your content on a specific keyword (or keyword cluster) most likely to match the search intent and rank on the results page; AI-driven search engines do something very different.

AI systems break a query into a network of sub-questions, retrieve information for each one, and then recombine those answers into a single response. Google has been explicit about AI Overviews using multi-step reasoning to handle complex queries. So, the best way to increase your chances of being cited by AI engines is by modeling that process yourself.

Instead of writing one page for “best notary services,” you anticipate the questions the AI will need to answer and create clear, self-contained sections that resolve each sub-question. In this example, you might include:

• What documents can a notary handle in BC?
• What’s the difference between a notary and a lawyer?
• What does notarization cost?
• What do I need to bring to my appointment?
• Can a notary help with real estate transactions?

Each of those needs its own clearly labeled, self-contained section that fully resolves that sub-question.

2. LLM Seeding

Search engines rank pages, whereas language models learn from trusted sources. To gain visibility in this environment, you must present as a reliable reference source.

Research consistently shows that AI systems place more trust in neutral, earned sources such as documentation, community forums, and reference-style content than in brand-owned marketing pages. That doesn’t mean it’s time to pull the plug on your SEO, because remember, you still want your pages to rank. But it does mean you need to look beyond your website to position high-quality, factual content where AI models are likely to encounter and learn about your brand. This could include posting in places like:

• Public FAQs
• Community Q&A platforms
• Documentation-style resources
• Public reports or guides

The goal of AI SEO isn’t ranking a URL. The objective is to become a canonical source for a concept wherever models learn their base knowledge.

3. Passage-Level Retrieval Optimization

Classic SEO primarily operates at the page level, ranking entire pages (URLs) based on relevancy and trust signals. AI search retrieves information at the passage level.

What gets cited or reused in the AI overview is typically a specific paragraph, list, or table, not an entire page. That means every major section of your content should be able to stand on its own, independent of the rest of the page, while scoring well on structure, metadata, and semantics.

Each heading should introduce a complete idea, and each section should cover that micro-topic fully without requiring the reader or the model to scroll elsewhere to understand it. In other words, treat every H2 and H3 as a mini-answer you’d feel confident quoting on its own.

4. Citation-Ready Evidence Packaging

AI systems are designed to justify their answers. When they can’t ground a claim in verifiable information, these models will often invent details and facts to support their replies.

To avoid AI hallucinations and increase your chances of being cited, it’s crucial to structure your content in a way that makes the truth easy to find, understand, and reuse. Structured content and clear formatting were already important to your SEO, but now, to support AI SEO, you want evidence packaged in a way AI can lift cleanly, such as:

• Tables, checklists, and side-by-side comparisons
• Clear definitions and quick “what it means” summaries
• Strong claims backed by concrete evidence

The biggest takeaway here is that it’s no longer enough to be right; you need to prove your point and structure your argument in a way that makes your proof easy to reprocess.

5. Neutrality Engineering

AI systems are heavily biased toward neutral, non-promotional content. Overtly salesy language may have worked for traditional SEO purposes, but it is likely to work against you for AI SEO. What’s more, Google is cracking down on spammy or thin content that adds no real value or new perspective.

This doesn’t mean you can’t market your services or promote your brand; you just need to separate the two.

Keep your sales speak separate from your supporting evidence. On pages where you are trying to earn AI Overview citations, focus on facts, comparisons, and third-party validation. Save opinion and positioning for pages or sections that are not competing to be cited as neutral evidence, and always make sure specifics, not broad marketing statements, support your claims.

6. Mentions vs Citation Optimization

There are two ways your brand can show up in an AI search overview:

• Mentions (your name appears in the answer)
• Citations (your site or content is used as proof)

Many brands get neither. Some earn one or the other. Very few get both.

Citation is the highest-value state or ultimate goal. It’s the difference between being loosely referenced in a summary and being treated as a credible source that helps shape the answer itself. But citations are also difficult to earn.

While not quite at the top of the ladder, a mention can still be extremely valuable. It puts your business on the shortlist when someone asks an AI tool for “the best options” in a category.

If you want to climb the visibility ladder from not mentioned to mentioned to cited, you need content that’s tight, factual, and designed for reuse: clear headings, self-contained answers, and proof that supports the claim.

That means:

• A clear purpose and tight scope
• Structured formatting that’s easy to scan (and easy to lift)
• Evidence that supports the claim, not just opinion
• Consistency across your site and the broader web

Ranking still matters, but it’s no longer the only goal. The new question is: Does AI trust your content enough to use it as proof?

Final Thoughts

Traditional SEO is not dead; in fact, it may be more important than ever. But it’s no longer the whole funnel.

AI-driven search has changed how answers are built, how trust is assigned, and how visibility is earned. Brands that treat AI SEO as a curiosity layered on top of SEO risk being left out of the answers their audiences are consuming.

The opportunity isn’t to abandon SEO. It’s to evolve it.

Traditional SEO still helps you get discovered. AI SEO helps determine whether your content gets reused, cited, and surfaced inside the answers themselves. And in a world where more searches end without a click, that distinction matters.

Because now, you’re not just competing to rank. You’re competing to become part of the answer.