The way we search for information has changed—fast. Gone are the days of “surfing the web” by clicking through sites and scrolling through pages to find information. Today, answers are instant, either pulled to the top of the search engine results page (SERP) or generated on the spot by AI large language models (LLMs). Tools like ChatGPT, Gemini, Grok, and Claude are changing the game and rewriting the rules of search.
Search keeps evolving, reshaping how we find and trust information. For marketers and content creators, this shift raises a big question: How do I create content that ranks in both AI models and traditional search engines?
At Booyah, we’ve already started seeing the difference from our content marketing and search engine optimizations. Content that’s structured clearly, answers questions directly, and builds authority tends to perform better in rankings and in how it’s surfaced by AI tools.
This new landscape calls for a different approach to creating content and optimizing a website for search. It’s not just about keywords or backlinks anymore. Content needs to be structured in a way that allows it to result in AI overview rankings and LLM response. Content needs real depth and authority behind it. Relevance is another ranking factor that matters more than ever and not just to Google, but to the models that are starting to shape how people find and trust information.
It’s a challenge but for those willing to adapt, it’s also a huge opportunity.
What are Large Language Models?
Large language models like ChatGPT, Gemini, Grok, and Claude, are trained on huge volumes of text to understand how we use language. They don’t search the web the way Google does. Instead, they generate answers through what they’ve already learned fromf language patterns or, in some cases, what they pull from live search integrations.
How AI Selects and Prioritizes Content
Search is evolving, and so is the role of content. It’s no longer just about climbing the rankings. Now, your content also needs to be clear and credible enough to be pulled into AI-generated answers. Whether it’s a chatbot or a search result, structure and authority play a bigger role in how—and if—your content gets seen.
When language models generate a response, they tend to prioritize content that meets a few key criteria:
- Relevance – Does the content directly answer the query?
- Authority – Is the source well-established, widely cited, or trusted?
- Clarity & Structure – Is the content well-organized, easy to parse, and formatted clearly?
- Freshness – If the AI has live search access, newer content may be preferred.
These same qualities matter to search engines too. So, understanding and implementing these ranking factors into your content optimizations will be beneficial for both AI-generated responses and traditional search engine rankings.
Structuring Content for AI and Search Engines
One of the most effective ways to optimize content is by structuring it in a way that both humans and AI can easily digest. Here are some techniques:
1. Use Clear, Question-Focused Formatting
AI models often pull direct answers to user queries, so structuring content in an FAQ format or with clear headings makes it easier for AI to find relevant information. We’ve found that when we rework content to follow this structure, even without adding new sections, it becomes more likely to appear in featured snippets and AI-generated answers.
Instead of writing dense paragraphs, use concise, scannable sections with descriptive headings like:
Good Example: “How Can You Optimize Content for ChatGPT?”
- Use natural language and conversational tone
- Answer common search queries concisely
- Include authoritative references
Bad Example: “Our content strategy should include optimization for AI-driven search tools such as ChatGPT and Gemini, which require structured content to enhance visibility…” (Too long and unclear for AI parsing.)
2. Implement Schema Markup
Structured data (such as FAQ, How-To, and Article schema) is a technical SEO tactic that helps search engines and AI understand content context. If your content is marked up correctly, it’s more likely to be pulled into featured snippets and AI responses.
3. Optimize for Conversational Queries
People interact with LLMs using natural language. Instead of targeting rigid, keyword-stuffed phrases into your on-page SEO like “best SEO strategy 2025,” optimize for conversational search queries such as “What are the best SEO strategies for AI in 2025?”
Building Authority and Relevance for LLM Optimization
To ensure AI models consider your content as authoritative, follow these strategies:
1. Create Deep, Well-Sourced Content
AI models prioritize comprehensive, well-researched information. Aim to create content that:
- Answers common industry questions thoroughly
- Includes data, statistics, and case studies
- Uses citations from trusted sources
2. Earn High-Quality Backlinks & Mentions
AI models recognize authoritative sources based on off-page SEO factors like backlinks and citations. If your content is referenced in well-known industry publications, AI systems are more likely to pull from it when generating responses.
3. Establish Brand and Entity Recognition
Google’s Knowledge Graph and AI systems favor established entities. Ensure your brand is recognized across multiple sources by:
- Creating a well-maintained Google Business Profile
- Using structured data to define your organization
- Being featured in industry directories and trusted websites
Final Thoughts: The Future of SEO and AI
As AI continues to shape the way users find information, SEO isn’t dying—it’s evolving. Marketers who adapt to the new search landscape by creating well-structured, authoritative, and AI-friendly content will reap the benefits of increased visibility.
By following these strategies, you can ensure that your content ranks in Google and appears in AI-powered responses, giving your brand a competitive edge in the world of AI-driven search.
Are you ready to optimize your content for the AI era? Let’s get started!
