Search engines don’t just match keywords anymore. They’re trying to figure out what people mean in addition to what they type. That shift has everything to do with how artificial intelligence, especially semantic search, is changing the way we think about content.
At the center of that shift are AI tools like ChatGPT, Gemini, and Claude. These are all examples of large language models (LLMs). As they become part of how search works, sometimes even replacing traditional results, marketers need to rethink how they create and structure content.
There was a time when search engines worked like simple word-match machines. If you typed “best pizza,” they’d pull up pages with those exact words. That sounds helpful, but in practice, it missed the point of what users were often trying to say.
With semantic search, engines now try to understand context, intent, and the relationships between words. This approach became more common after major Google updates like Hummingbird, which focused on interpreting conversational queries, and RankBrain, which used machine learning to figure out meaning, even when a query was brand-new or oddly phrased.
For example, if someone searches for “how to make pasta without wheat,” the engine understands they’re likely looking for gluten-free options, not just any recipe with pasta and wheat in the same sentence.
This kind of thinking laid the foundation for how LLM SEO now works. It goes deeper than surface matches and starts to consider the why behind a search.
Large language models are trained on massive amounts of text. What they do is try to predict and generate natural language based on that training. However, in the process, they also become good at understanding what people are asking and what kind of information might help.
That means LLMs don’t just return search results. They generate answers. If you’ve used Bing Copilot, Perplexity, or even some features in Google, you’ve already seen this in action. Instead of a list of links, users get summaries, recommendations, or full explanations right on the screen.
This changes how visibility works. A site that used to win by ranking first might not even appear in an LLM’s answer. Now, success might mean being the source that the model pulls from, even if you’re not the top link.
If you’re hearing terms like LLMO or generative engine optimization, they’re part of this new conversation. In short, these approaches ask: What makes content usable by AI models?
The answer depends a lot on structure, clarity, and coverage. LLMs don’t think like traditional ranking systems. They look for sources that are complete, context-rich, and easy to understand when it comes to answering real questions.
If a person asked you a question directly, would your content provide a good, clear response? If yes, you’re on the right path.
Writing for LLMs doesn't mean you have to give up good SEO. But it does mean that you need to improve how you structure and write your content.
Write like someone’s reading, not like a robot’s scanning. Use full questions, casual phrasing, and conversational tone. This aligns with how conversational search works. People are increasingly speaking into their devices or typing long-form queries like “What are the best SEO tools for beginners?”
LLMs (and Google, for that matter) benefit from seeing content organized around topic clusters. Instead of having one blog post about, say, email marketing, it helps to have a main guide supported by related pages, like case studies, tool comparisons, or beginner tips.
When your content is clearly labeled, it’s easier for models to pick up what it’s about. Structured data like FAQ schema or HowTo markup helps define the purpose of a page. That’s especially helpful in featured snippets, AI summaries, or voice search results.
If you want to know how AI sees your content, just ask it. Go into ChatGPT or Claude and type in queries related to your business.
This kind of quick test shows how well your content optimization efforts are working and where you might need to strengthen authority or clarity.
When it comes to LLM SEO, links still help, but brand presence plays a bigger role than it used to. That’s because many models are trained on public content and media, not just web page rankings.
If your brand is frequently mentioned in articles, blog posts, or news coverage, that repetition builds credibility in training data. It becomes part of how the model understands what your company does and when to bring you up.
This is one reason generative engine optimization strategies now often involve PR teams. Getting your business featured on third-party sites can have a surprising impact even if the link itself doesn’t drive traffic.
A study out of ETH Zürich recently showed how models like Bing Copilot and GPT-4 could be manipulated by preference manipulation attacks. Basically, someone could hide instructions inside a web page, even with white font or invisible formatting, and make the LLM recommend their product over others.
In some tests, fake products were twice as likely to be recommended after an attack. And that’s with no real authority or branding behind them.
The point isn’t to find loopholes or game the system. What really matters is knowing that AI still has blind spots, and the best way to stand out is by creating clear, trustworthy content that actually helps people. That’s what wins out in the long run, even when others try to cut corners.
Search is changing, not just in how people use it but in how systems decide what to show. With semantic search becoming standard and LLMs handling more of the decision-making, what works in SEO today might not work tomorrow.
At The Creative Momentum, we work with brands to build content strategies that hold up in this new environment. That means crafting resources people actually want to read, and that AI tools can easily understand, reference, and trust.
If you're thinking about how your business can stay visible as search continues to evolve, let’s have that conversation. We’ll help you shape content that connects with users and keeps pace with the way search engines are growing.