Mastering LEO: How To Optimize Your Content for Large Language Models

The increasing popularity and availability of artificial intelligence (AI) tools have created a shift in the behavior of internet users. While people once relied on traditional search engines, they now look to AI-powered chatbots and applications to learn about new topics, research products, or find new places to visit. The dominance of tools like ChatGPT and Google Gemini has, therefore, led to the rise of LLM Engine Optimization (LEO). 

LEO, as its name suggests, is the process of optimizing your content to maintain visibility and relevance in the AI-first digital landscape. But how does large language model optimization happen? What are the strategies you can employ so your content shows up in the results? Connection Model is here to answer these questions and more. 

What Is LLM Engine Optimization (LEO)? 

LEO is the process of optimizing digital content for understanding, indexing, and surfacing by Large Language Models (LLMs). This strategy is also sometimes referred to as generative AI optimization or GEO. 

Traditional search engine optimization (SEO) has the same goal of optimizing digital content, but its focus is on search engines like Google or Bing, as well as native search engines of social media sites or e-commerce platforms. 

LEO, on the other hand, focuses on ChatGPT, Gemini, and other AI tools. SEO focuses on keywords and backlinks, while LEO focuses on semantic clarity, contextual depth, and AI readability to optimize content for the AI websites. 

SEO is no longer as relevant due to AI-driven zero-click search, which enables users to obtain answers without needing to click on any links. AI already provides key summaries that are also easier to digest, thanks to conversational search interfaces. By following LEO practices, companies can adapt to this change and ensure that their brands become part of the search query response. 

Why LEO Matters More Than Ever in 2025 

As you likely know, there has been an increasing use and dependency on AI chatbots and generative AI for information retrieval. Within the next few years, it’s expected that most users will use these AI tools as their default search engines. No longer will people scroll search engine page results (SERPs). Instead, they can simply ask questions in a conversational manner and receive curated answers thanks to AI’s power. 

This surge in zero-click searches means fewer visits to traditional web pages, creating a risk for brands that haven’t adapted. In other words, if your content isn’t optimized for LLMs, it could be left out of the digital conversation entirely. 

Adapting in 2025 and beyond means leveraging LEO strategies to position your brand as an authoritative source in AI knowledge bases. The stakes are high now that LLMs act as gatekeepers of knowledge, and investing in LEO now can help ensure that your brand remains on the surface, always reliable and trusted. 

Key Differences Between SEO and LEO 

While both SEO and LEO are designed to enhance a brand’s website visibility, there are several key differences in how each process achieves this goal. 

SEO 

• SEO targets SERP rankings and clicks. The goal is to rank your webpages at the top of the results so you can increase engagement. 

• The primary factors that drive higher rankings are the use of relevant keywords, backlinks, and technical website elements. 

• Content needs to be optimized for algorithms and website crawlers. 

• SEO relies primarily on text with metadata. 

LEO 

• LEO targets content clarity, context, and inclusion in AI-generated responses. You want your brand to appear in the AI results or conversations within the AI platform. 

• The main factor that drives visibility is semantic SEO. The content needs to be rich in context and align with how LLMs process information. 

• LEO values E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness), fact-checked accuracy, and user intent instead of algorithms. 

• LEO relies on rich, multimodal content that includes text, images, and videos for AI comprehension. 

Core Strategies for Effective LEO 

What are the specific strategies digital marketers and brands can leverage for LEO? 

• Develop Comprehensive Topic Clusters: The interconnected content must revolve around a common theme and provide thorough answers to user queries. This step helps LLMs recognize your content as an authority in the subject. 

• Use Conversational and Educational Tones: This strategy mimics how users interact with AI tools, as well as how these programs respond. Clarity over jargon is essential for accurate interpretation of meaning. 

• Clear Definitions and Contextual Relationships Are Key: Defining key terms within your content helps the AI achieve a better semantic understanding. 

• E-E-A-T Needs to Be a Priority: E-E-A-T strategies are crucial for creating content that AIs recognize as authoritative. As such, your text and media must showcase expertise, cite trustworthy resources, and be factual with minimal bias. 

• Optimize Multimodal Content: Ensure that other types of media, in addition to text content, contribute to semantic understanding. 

• Implement Structured Data and Schema Markup: Similar to SEO, structuring data and implementing Schema markup are still beneficial practices. These strategies include clear labeling of key content components, such as FAQs or reviews, which helps AI parse and surface content in relevant responses. 

• Regularly Audit and Update Content: Like with SEO, LEO requires you to periodically audit your content and make changes as needed. For example, correcting old statistics or references can help make your content more AI-ready. It’s also good practice to evaluate your content or topic clusters as a whole to determine if their language still aligns with current AI model training data. This allows you to refine content to align with the current trends. 

Measuring Success in LEO 

The primary difference in tracking SEO vs. LEO success is that website traffic may not be sufficient for the latter. The more critical factor is the visibility of your content in AI-driven responses. Given this main metric, there are various indicators you can track; however, the most common method is to monitor the frequency of brand mentions in AI-generated responses, as well as in voice search or chatbot outputs. Tools like AI engine optimization graders help make tracking more convenient and comprehensive. 

With AI performance metrics and feedback, you’ll have data that lets you see where your content is performing well and where adjustments are needed, allowing you to take the next steps for fine-tuning your strategy for AI content optimization. 

Future Outlook:  Preparing for the AI-First Search Ecosystem 

AI-first is the undeniable future of search and digital discovery. LLMs are now being integrated into search engines, social media sites, and numerous other platforms, resulting in a significant shift in how people access knowledge. As such, brands must adapt by adopting LEO as part of their broader marketing strategies and overarching search everywhere optimization (SEvO) approach. 

Prioritizing LEO offers a competitive advantage for companies that adopt it early. Not only will your brand remain visible, but you’re also future-proofing your visibility in an environment where AI is becoming the primary gateway into customer journeys. 

AI Content Optimization for Brands 

The digital world of 2025 and beyond has been forever changed by AI search capabilities. For brands to remain visible, their marketers must embrace LLM optimization as a core pillar of their content strategy. With the right approach, your content will appear as answers delivered by AI, allowing you to remain discoverable, relevant, and authoritative in your field. 

Ready to future-proof your digital presence with cutting-edge LLM engine optimization?  Connect with Connection Model today for expert guidance on mastering LEO and capturing the AI-driven customer journey.