Key Take-Aways
- Traditional SEO
- The Rise of AI Engines
- Key Differences Between AI-Driven and Traditional SEO
- How to Adapt Your SEO Strategy for AI
- Common Challenges and How to Overcome Them
- Frequently Asked Questions
- Related Resources
Traditional SEO
Ever since the birth of the World Wide Web, there have been attempts to catalog and index the content. The earliest search engines were kind-a stupid. They basically sniffed around, following links and indexing any web pages they found. The original engines didn’t have complicated “algorithms” for returning search results. Basically, when a query was entered, they looked for the pages that had that exact query the most times. The big SEO technique of the day was “keyword stuffing“. That started to change in the late 1990’s when Google was born.
Google used (and still uses) a propriety search algorithm to rank pages based on a number of factors. No one knows exactly what all of those factors are but SEO’s can make educated guesses based on the search results the see. We know for example when a web page is linked to, the “link text” that is used in the hyperlink is a good indicator to Google as to what that page is about. The content of the page also needs to contain that phrase, once or twice in the content of the post.
For years, this was the standard SEO tactic; Write some content around a particular key phrase (usually 500+ words). Include that phrase within the content – in a natural way so that the text makes sense. Then link to that article, using the key phrase in the hyperlink. The more competitive a phrase was, the more links you would need to build linking to it. There were more on-page things like the title tags, the Meta description and other more subtle things, but in a nutshell, that was the main tactic.
It’s important to remember that “traditional SEO” is not gone, in fact there are a lot of things in common between SEO and AI Engine Optimization (AEO).
The Rise of AI Engines
AI engines like ChatGPT take a very different approach. AI is an LLM (Large Language Model). These engines have been trained on pretty much all of the existing web data. They have spidered the entire internet and “learned” not only all of the data that exists but also how people speak. That means that if you enter a query like:
“How much protein should a 45-year-old active man consume daily for muscle maintenance?”
Google will have to search it’s index for pages that it knows contains some or all of those phrases and will return what it thinks are the closest matches.
AI engines actually understand the question and can pull on it’s existing knowledge base to formulate a unique answer to the question. In many cases the engine will just return the information requested not a particular website.
AI also remembers past conversations you’ve had with it. If you previously mentioned having a kidney issue for instance, the returned information may include a warning about relying too much on protein as it may aggravate that problem further. Also, AI understands things about your location and can provide relevant information like local recommendations etc.
Key Differences Between AI-Driven and Traditional SEO
| Aspect | Traditional SEO | AI-Driven SEO |
|---|---|---|
| Keyword Focus | Relies on exact keyword targeting | Emphasizes intent and context over exact keywords |
| Content Creation | Optimized for search engines | Natural, conversational, and user-friendly content |
| Backlinks | High authority backlinks are key ranking factors | Quality backlinks still matter, but context matters more |
| Ranking Signals | Static ranking signals (on-page, links, etc.) | Dynamic signals based on real-time data and user behavior |
| Schema Markup | Useful but optional | Critical for AI to understand and present content |
| Search Personalization | Minimal personalization | Highly personalized based on user history |
How to Adapt Your SEO Strategy for AI
Here are some actionable steps you can take to help get your web pages listed in the AI Search Results.
- Focus on User Intent
Do keyword research that focuses on what the user is looking for and create content that addresses that search.
- Create Conversational Content
AI’s are conversational so your content should be as well.
- Use Schema Markup
Schema is code that appears in the HTML of your website. It’s not visible to the human eye but AI bots and Search Engines can see it. Schema provides a fast way for AI to understand what is on your page.
- Optimize for Entities
AI bots can better understand and categorize your content when you link to related resources that provide additional context. For example, if you’re writing about renewable energy, you could link to a solar power company or a wind energy organization to strengthen the connection between key topics.
- Leverage Topic Clusters
Create core topic pages then develop related content and link to those core pages. For example a if your website is about Widgets, create a Topic called “Widgets” then create related page or posts about “Blue Widgets”, “Red Widgets” etc. Link your related posts back up to the main “Widgets” page. This is called a “Hub and Spoke” content.
Common Challenges and How to Overcome Them
If your website has been around for a while and you have been optimizing it only for SEO then you’ll probably need to make some adjustments to help boost your AI rankings.
If you’ve only focused on key phrases then the conversational nature of AI may not translate well for you. It’s a good idea to go back to your older pages and update their content – write in a more conversational but authoritative tone. Both search engines and AI like fresh content. Updating old pages can in itself be a boost.
Other technical issues may also need to be addressed. How is your site speed? Speed is crucial for AI engines. Also ALL websites need to be mobile optimized today. Make sure to test your web pages on multiple browsers and in multiple platforms (desktop, phones, tablets etc.).
Conclusion
One of the oldest adages in the SEO world is “Content is still King!”. That is still true today but now your content needs to be more conversational.
Frequently Asked Questions
Traditional SEO focuses on optimizing content to rank in search engines like Google by targeting specific keywords, getting backlinks, and optimizing on-page elements like title tags. On the other hand, AI-driven SEO is about intent and context. AI engines don’t just search for keywords—they understand the meaning behind a query and provide a more direct, personalized response. This means your content needs to be more conversational and contextually rich to perform well with AI.
Yup! Keywords still matter, but they’re not the sole focus anymore. Instead of stuffing exact-match keywords, you need to focus on keyword intent. For example, someone searching “best running shoes” might be looking to buy or compare options. AI engines analyze the intent behind those words to provide better results. So, optimize for the purpose of the search by creating content that provides the answer or solution users need.
Conversational content is writing that feels natural and flows like a conversation. Imagine you’re explaining a concept to a friend—use simple, engaging language that people can relate to. AI models like Google’s BERT and ChatGPT prioritize this kind of content because it’s easier for them to understand and deliver in search results. A good example is answering common questions or structuring your content around FAQs.
Schema markup is like a cheat sheet for AI bots. It’s hidden code that tells search engines what your content is about. For example, if you have a recipe page, schema can specify the ingredients, cooking time, and calories. AI engines love this because it helps them understand the structure of your content faster, which increases the chances of it being featured in rich snippets or AI-generated answers.
Here are some simple tips:
Write conversationally and answer common user questions.
Use structured data (schema) to help AI understand your page.
Focus on topic clusters—group related content together and link them to a main topic page.
Optimize for entities by linking to authoritative pages that provide context.
When you do this, you make it easier for AI to categorize and rank your content accurately.
Entities are specific, recognizable “things” like people, places, or concepts. Think of “Elon Musk” or “solar power.” AI search engines focus on these entities instead of just keywords. By linking to related entities within your content, you help AI understand the connections between topics. For example, if you’re writing about renewable energy, linking to information on wind power or solar panels gives the AI extra context and boosts your page’s relevance.
Topic clusters are a strategy where you create a main page (pillar content) and link supporting pages (cluster content) back to it. For example, if your main topic is “Widgets,” you can create pages like “Blue Widgets” and “Red Widgets” and link them back to the main “Widgets” page. This helps search engines and AI engines see your website as an authority on the topic because everything is interconnected.
Absolutely! AI engines love fresh, updated content. If you have older blog posts optimized for traditional SEO, go back and update them with conversational language, relevant links, and schema markup. This not only improves their chances of ranking in AI-driven search but also makes them more valuable to users. AI engines prioritize content that’s recent and useful.
Yes, but with a twist. In traditional SEO, the quantity and authority of backlinks were key factors. In AEO, context and quality matter more. If your backlinks come from sites relevant to your topic, they provide extra context for AI engines. So, focus on getting backlinks from credible and topic-related sources rather than just chasing large numbers.
The biggest challenge is changing how you think about keywords. If you’ve relied on keyword stuffing or exact-match phrases, you’ll need to shift to focusing on user intent and natural language. Also, check your site speed, mobile-friendliness, and structured data, as these are key technical factors AI engines consider. It’s not about abandoning traditional SEO—it’s about enhancing it to meet modern AI standards.
