Why SEO Still Matters in the Age of AI Search and How LLMs Use It to Rank Content

How many times have you heard that “SEO is dead”? We bet it happened a thousand times. And now, with AI rapidly taking over search, it’s easy to fall into the trap of abandoning tried-and-true SEO tactics in favor of shiny new AI initiatives. But the truth is, SEO and AI search aren’t competing forces, they’re deeply interconnected. In fact, SEO still matters today, maybe even more than ever before.

With AI-powered search experiences like Google’s Search Generative Experience (SGE), Perplexity AI, and ChatGPT’s browsing tools transforming how people find information, marketers are understandably questioning if traditional SEO is still relevant. 

This article will demystify how AI search engines actually use SEO signals to discover, rank, and surface credible content. You’ll learn why classic SEO best practices remain foundational in this new era, and how to adapt your strategy to thrive alongside AI-powered search.

The rise of AI-powered search: How it impacts SEO

The search landscape is evolving. Again. Tools like Google’s Search Generative Experience (SGE), Perplexity AI, and ChatGPT’s browsing capabilities are reshaping how users engage with information online. Now, instead of traditional lists of links, users get the previews of more conversational, contextual, and often zero-click search results.

This shift creates new behaviors: fewer clicks, more direct answers, and a preference for dialogue-style information discovery. Because why would someone click on a link and read the entire article or page, if they can instantly see the short answer, right? For marketers, this raises critical questions:

1. If AI provides answers without users visiting your site, does SEO still matter?
2. How do AI models find and rank the content they surface?
3. Should we shift focus from optimizing for search engines to optimizing for AI models?

While these questions are valid, the answer lies in understanding how these AI search engines operate under the hood. Good news is that despite the conversational interfaces and new formats, the underlying AI models still depend heavily on web content that follows SEO best practices. 

This means that the rise of AI search isn’t the end of SEO, it’s more of an evolution that requires marketers to deepen their technical and strategic approach.

How LLMs use SEO to rank content

So, why SEO still matters? It all starts with understanding how Large Language Models (LLMs), which power AI search, learn and fetch content.

The training data behind LLMs

LLMs like ChatGPT, Google Bard, and others are trained on massive datasets that include billions of words from the open web, books, articles, and knowledge bases. Much of this content is indexed by traditional search engines before it’s fed into AI training pipelines. This means the quality, structure, and authority of indexed web content directly impact what LLMs “know” and generate. In other words, first SEO, then LLM.

Content discovery and ranking by AI

When a user asks an AI search engine a question, the model relies on a mixture of:

• Retrieval from indexed web content: AI systems query vast indexes of web pages (similar to traditional search engines) to find relevant documents.
• Knowledge graphs and structured data: AI uses connected data points about entities and facts to enhance answers.
• Semantic understanding: AI models analyze context and intent, moving beyond simple keyword matching.

Here’s the key: the content that these AI systems retrieve and surface must be discoverable, credible, and authoritative, and that’s where classic SEO signals come into play.

Why SEO signals still matter for AI search

While AI-powered search introduces new layers of complexity, many of the classic SEO signals remain critical for your content to get noticed, ranked, and ultimately surfaced by AI models.

Here are the most important SEO factors that AI search engines continue to rely on:

1. Structured content and metadata
2. Authoritative backlinks
3. Semantic SEO and topical relevance
4. Clear page architecture and crawlability
5. Freshness, quality, and accessibility

Structured content and metadata

Structured data like schema.org markup, JSON-LD, and Open Graph tags gives your content a clear, machine-readable “label.” It tells AI exactly what each page or element is: a product, an article, or an event. This clarity helps AI understand and index your content properly, boosting the chances your site will be featured in AI-generated answers or snippets.

Authoritative backlinks

Backlinks are still the digital equivalent of a vote of confidence. When trusted websites link to your content, it signals authority and reliability, strengthening your standing in search engines, which feed AI search results. Cultivating a strong backlink profile remains just as important as ever.

Semantic SEO and topical relevance

Gone are the days when just sprinkling exact-match keywords would do the trick. AI now gets context, synonyms, and related ideas. When you optimize for semantic SEO and cover topics fully using related terms, you make it much easier for AI to match your content to a wide range of user queries, boosting your chances of showing up in AI-powered search results.

Clear page architecture and crawlability

AI can’t read what it can’t find. Making your content easy to crawl with clean URLs, sitemaps, and a clear hierarchy ensures both AI and traditional search engines can discover your pages and understand how they connect. Without this, even your best content might get overlooked.

Freshness, quality, and accessibility

AI loves content that’s fresh, high-quality, and genuinely useful. Regularly updating your pages and making sure they load fast, look great on mobile, and are easy to access signals value to both AI and human visitors, helping your content shine in search results.

In short, SEO is still the foundation that AI search builds on. Even as user interactions with search results evolve, the content AI relies on follows classic SEO principles, just upgraded for the new era of generative and semantic technologies.

5 practical SEO tips for AI-driven search

Adapting your SEO strategy for AI-driven search doesn’t mean starting over; it’s about evolving what’s already working and giving it a smart, AI-ready upgrade. Here’s how to future-proof your content in a world where AI is part of the search experience:

1. Optimize structured metadata and schema markup

Make sure every page has clear, accurate structured data (think schema.org). This helps AI understand your content’s context and improves your chances of appearing in rich results and AI-generated answers.

2. Build and maintain authoritative backlinks

As backlinks are still the digital “trust badges”, keep cultivating links from reputable sources. AI models weigh these signals heavily when deciding which content to surface.

3. Embrace semantic SEO techniques and optimize for generative AI (GEO)

Move beyond exact-match keywords. Cover topics thoroughly, use natural language variations, related terms, and FAQs. This helps AI understand user intent and match your content to a broader range of queries.

Generative Engine Optimization (GEO) takes this a step further for AI-driven search. By structuring your content clearly with headings, labeled sections, and authoritative answers, you make it easier for generative AI engines like ChatGPT or Google SGE to confidently surface your content in answers. Think of GEO as the next evolution of semantic SEO where your content not only ranks but also powers AI-generated responses.

4. Leverage headless CMS for structured, accessible content

Headless content management systems like Storyblok let you model your content semantically and deliver it via APIs. Structured, well-organized content makes it easier for AI crawlers and indexing systems to find, understand, and surface your pages.

5. Monitor AI search results and adapt

Check how your content shows up in AI-powered search experiences like Google SGE or ChatGPT. Use these insights to refine your strategy continuously and stay ahead of the curve.

Technical insights for developers and technical marketers

For developers and technical marketers, content architecture is more important than ever. Here’s how technical teams can power SEO success in an AI-driven world:

Content modeling in headless CMS supports AI search

By defining clear content types, relationships, and metadata in a headless CMS, you create machine-readable content that AI can easily index and understand.

API-driven delivery enables dynamic, omnichannel SEO

Headless CMS platforms deliver content via APIs to websites, apps, voice assistants, and AI interfaces. This ensures your SEO signals are consistent across every channel.

Collaboration between SEOs, marketers, and developers

SEO experts, content strategists, and developers should work hand-in-hand to implement structured content, schema, and technical SEO best practices within headless CMS workflows.

Automate SEO signal generation and monitoring

Take advantage of CMS features or external integrations to automate metadata creation, schema updates, and AI indexing monitoring. This helps keep your SEO healthy as AI search continues to evolve.

Conclusion: AI search is nothing without SEO, and so is your discoverability

Yes, AI is changing a lot, especially how people search for and consume information. But SEO is still a key part of the game. It’s the backbone of modern search. Today, it’s not about keyword stuffing anymore, it’s about clear structure and providing genuinely helpful answers.

Well-organized, easy-to-read content with proper links and logical structure helps both search engines and AI understand what your pages are about. And the tools? Using a headless CMS such as Storyblok gives you flexibility to adapt as AI search continues to evolve.

Focusing on SEO today means you’re ready for the way people will search tomorrow. Your content will stay discoverable, trustworthy, and ready to reach the audience you want, no matter how technology changes.

Frequently asked questions (FAQs)

Is SEO still relevant with AI search?
Absolutely. AI search engines depend on SEO signals like structured metadata, backlinks, and semantic content to discover and rank trustworthy content.

What SEO signals matter most for AI-powered search?
Structured data, authoritative backlinks, clear site architecture, semantic keyword targeting, and high-quality, accessible content are key signals.

How does a headless CMS like Storyblok help with AI SEO?
Headless CMS platforms enable flexible, structured content modeling and API delivery, making your content more accessible and machine-readable for AI crawlers and indexing systems.

What is Generative Engine Optimization (GEO)?
GEO refers to optimizing content specifically for generative AI engines, ensuring it is clear, authoritative, and structured so AI can confidently include it in generated answers.

Will AI search replace traditional SEO?
No. AI search builds on traditional SEO fundamentals. It requires even more precise and structured content to perform well in AI-driven search results.