2025 SEO Strategy: How to Optimize for AI Search LLMs

Search engine optimization (SEO) used to be all about ranking. If your website appeared first, or even on the first page, of a relevant Google search result, you were able to drive traffic to your platform. With Google’s introduction of artificial intelligence (AI) answers to searches, this is no longer the case. Knowing how to rank in AI overviews is a must for brands that want to remain visible in the crowded online sphere.

At Socium, we’re carefully monitoring these changes and adapting our organic SEO and paid search approaches accordingly. Below, we present our findings, offering insights into how to appear in Google AI search results. We also discuss how to optimize content for ChatGPT search, which, for many users, is fast becoming a replacement for traditional search engines.

Why Traditional SEO Tactics No Longer Guarantee Visibility

Now, when internet users input a search into Google, they don’t just get a list of web pages. At the top of the page, they’re shown an AI overview answering their query. While the answers include links to sources as citations, there’s no guarantee that people will click on them. Already, it’s estimated that some 70% of B2B searches have AI answers, and companies are losing traffic as a result¹.

How to Show Up in AI Search Results

Our research at Socium has made one thing clear: Successful AI search engine optimization requires well-written, informative content structured in a way that large language models (LLMs) understand. That content must also serve a purpose, as AI results generally favor pages that directly answer a question or fulfill a specific intent, such as making a purchase.

So far, our testing shows that an AI visibility strategy for brands will benefit from the following:

• Frequently asked questions content: FAQs are often cited in Google’s AI overview as well as by LLM-based tools like Perplexity, Claude, and ChatGPT.
• Product pages: More recently, product pages have been showing up in search engine AI overviews and LLM citations, sometimes with purchase links included.
• Long-form blogs: Longer-form content targeting informational, long-tail keywords performs well, especially when it’s human-written and clearly answers a question.

Content architecture is also crucial for appearing in AI SEO or LLM results. Traditional SEO relies on search engine crawlers (bots that look at components like link structures and metadata to analyze information). In contrast, LLMs don’t just trawl through data, they ingest it and analyze it, considering relationships between ideas, words, and sentences². Clear content architecture that logically conveys ideas is critical.

Model Context Protocol: The New Schema for LLMs

To optimize website structure for LLM and AI search, we’ve found Model Context Protocol SEO to be especially useful. MCP standardizes how applications provide context to LLMs³.

For websites, MCP can help AI better understand site structure, content types, and page relationships. With MCP, you can define key areas of the site, say, product pages versus blog posts. This allows AI models to display content more accurately in search experiences that rely on summaries and recommendations.

Even if your content management system (CMS) doesn’t support dynamic endpoints, a static MCP file can be added to your site. Anthropic, the company behind tools like Claude, compares MCP to a USB-C port for AI: It provides a standardized means of connecting AI models to various data sets and tools, just like a USB-C port provides a standardized means of connecting your laptop to various devices and accessories⁴.

We are currently testing MCPs with clients to better understand how to leverage them to increase visibility and influence search results. With LLMs like Claude already recognizing MCPs, we suspect they will only become more significant, and active testing enables us to determine how to maximize their potential.

AI Visibility Starts with Content Built for Machines

Our findings suggest that LLM content optimization relies on content that is written by humans, for humans, but structured for machines. Structured content for AI discovery exhibits a few key characteristics. We suggest using the following:

• Create a clear structure: Present ideas in clear content blocks of concise paragraphs. Using semantic clues like “in summary” can help LLMs identify content relevance².
• Include headings: Break up text with heading structures (H1, H2, H3, etc.). Ideally, these headings will match natural questions.
• Give a direct reply: Provide a key takeaway at the top of the content, ideally answering a direct question in the first sentence.

How to Optimize Content for ChatGPT and Other AI Models

Our testing has further revealed that ChatGPT and similar AI models tend to favor uniqueness. Proprietary insights that are current and not recycled from hundreds of other sources are more likely to attract attention. Using visible dates and meta tags is one way to signal that content is current⁵.

Structuring data using schema markups is also valuable for helping AI learn not only the relevance but also the context of content. This increases the chances of content featuring in search results, such as snippets⁶. Quotes can also help boost credibility, another signal of relevance for AI.

Finally, it’s necessary to keep in mind that the technical aspects of search are constantly evolving, which makes continuous measurement and testing pivotal. For example, set benchmarks for how often you want your brand to appear in AI answers and check progress over time⁷. At Socium, we continually use methods like these to determine what works and what doesn’t.

FAQs and Question-Based Modules Are No Longer Optional

Based on our testing, FAQs are among the most cited pages in AI and LLM searches, indicating that FAQs are no longer a nice-to-have but a must-have. These findings are supported by external research that suggests 82.5% of AI overview citations link to deep content pages, which are at least two clicks away from the homepage, like FAQs⁸.

With a company’s homepage no longer being the primary driver of traffic that it once was, we’ve been focusing on FAQs on high-intent pages to secure citations for our clients. Link-back strategies from FAQs further enable us to highlight deeper content, thereby expanding options for citability by LLMs and Google’s AI summary results.

Final Thoughts for CMOs Navigating Generative Search

Traditional SEO approaches alone are insufficient for achieving successful AI search engine optimization. To remain relevant in AI and LLM search results, it’s necessary to consider not only technical SEO but also content architecture and LLM context engineering. Our Socium team actively tries out new approaches to enterprise SEO for generative search, developing the frameworks our clients need to remain relevant. Learn more.

Sources:

1. Whitwam, R. (May 20, 2025). Zero-click Searches: Google’s AI Tools Are the Culmination of Its Hubris. Ars Technica. Retrieved May 27, 2025, from https://arstechnica.com/google/2025/05/zero-click-searches-googles-ai-tools-are-the-culmination-of-its-hubris/
2. Shelby, C. (April 28, 2025). How LLMs Interpret Content: How To Structure Information For AI Search. Search Engine Journal. Retrieved May 27, 2027, from https://www.searchenginejournal.com/how-llms-interpret-content-structure-information-for-ai-search/544308/
3. Get started with the Model Context Protocol (MCP). ModelContextProtocol.io. Retrieved May 27, 2025, from https://modelcontextprotocol.io/introduction
4. Model Context Protocol (MCP). Anthropic. Retrieved May 27, 2025, from https://docs.anthropic.com/en/docs/agents-and-tools/mcp
5. White, J. (January 29, 2025). AI Optimization: How to Optimize Your Content for AI Search and Agents. Search Engine Land. Retrieved May 27, 2025, from https://searchengineland.com/ai-optimization-how-to-optimize-your-content-for-ai-search-and-agents-451287
6. Melton, W. (April 29, 2025). How to Optimize Your Website and Content to Rank in AI Search Results. XPonent21. Retrieved May 27, 2027, from https://xponent21.com/insights/optimize-content-rank-in-ai-search-results/
7. Smith, E. Optimizing for AI Search and Discovery. Reforge. Retrieved May 27, 2025, from https://www.reforge.com/guides/optimizing-for-ai-search-and-discovery
8. Goodwin, D. (March 19, 2025). 82% of Google AI Overviews Citations Come from Deep Pages: Report. Search Engine Land. Retrieved May 27, 2025, from https://searchengineland.com/google-ai-overviews-citations-deep-pages-453414