How to optimize content for AI and LLMs: A practical guide to GEO

If you want your content to show up in AI-generated answers, it needs to be written and structured in a way that large language models (LLMs) can take in. That’s where Generative Engine Optimization (GEO) comes in: an emerging discipline shaped by content strategists, SEO experts, and AI researchers exploring how large language models use and reuse digital content.

This is the second post in our GEO series. We covered the fundamentals of what GEO is and how it differs from traditional SEO in part 1. In this guide, we move from concept to execution, offering practical techniques you can use today to make your brand’s expertise more discoverable and usable in tools like ChatGPT, Claude, and Perplexity. 

So how do you make your content stand out in AI-generated results? It starts with knowing what to optimize first.

The best content types to optimize for GEO

Where should you start with Generative Engine Optimization (GEO)? While almost all digital content can benefit from optimization, some content types are especially well-suited. 

LLMs tend to reproduce content formats that show up frequently in training, like definitions, comparisons, and FAQs. These are reliably quoted or paraphrased, making them great candidates for early GEO efforts. Glossaries and product pages also perform well, especially when structured with definitions or clear benefits. 

There’s even a place for evergreen content in your optimization efforts, especially if you’re a credible and knowledgeable source of niche information. Evergreen content is material that continues to be relevant long after it is published.

Overwhelmed? Prioritize working with what you already have, starting with the topics where you’re seen as an authority. You’ll maximize impact while learning GEO fundamentals along the way. Let’s explore some of those fundamentals now.

Core GEO techniques you can start using today

Many optimization techniques are based on early testing and observation. These are by no means official standards, but they’ve already proven helpful for teams getting started with GEO. 

To make your content more LLM-friendly and quotable, you don’t need to reinvent how you write. 

GEO is about being more intentional about how you structure and phrase things. The biggest advice? Aim to be as clear as possible in what you say. Use plain language, define jargon, and structure ideas so they can stand on their own, even outside of their original context.

These small shifts in how you write can make a big difference in how AI models can retrieve and reuse your words accurately. Human readers will appreciate them too. 

Advanced GEO tactics to maximize AI discoverability

Once you’ve nailed the basics of writing more clearly, you can get a bit more advanced in your efforts, focusing even more on structure and context.

Give machines context

• Use schema markup to add structure: While LLMs don’t read schema directly, structured data can still influence how your content is surfaced by search and retrieval systems. If your CMS supports custom fields or metadata, use them to capture elements like alt text, content types, or topic tags.
  
• Target an accessible reading level: 8th to 10th grade (equivalent to ages 13-16, or lower secondary education) is a safe zone for both humans and models. Many regulated industries like healthcare or insurance have actual readability requirements, so it’s more than just best practice. Even big ideas can be expressed plainly with the help of tools like Hemingway, Grammarly, or Kontent.ai’s native AI author assistance. 

I always try to think as a first-time reader of the piece. When you have expertise in a topic, it’s easy to slip into using terminology that feels normal to you. But would a first-time reader really understand all that jargon? And is it even necessary? This mindset shift helps me keep the reading level accessible and make sure that even complex ideas are presented in a simple way.

Lucie Simonova

Creative Writer, Kontent.ai

Write with reuse in mind

• Create self-contained definitions: When introducing potentially difficult terminology, don’t assume readers have any background knowledge. Define the concept clearly in a single paragraph that could stand on its own. This is called a canonical explanation.
  
  LLMs are more likely to generate accurate answers when they encounter clear, self-contained summaries, especially when those resemble high-quality examples in their training or grounding context.
  
  Let’s look at a example for the term headless CMS: “A headless CMS is a system that lets you manage content in one place and send it anywhere using an API. Unlike traditional CMS platforms, it doesn’t control how the content looks, giving developers full freedom to design websites, apps, or other front-ends separately."
• Think like a prompt. Add Q&A-style blocks that answer common questions (e.g., “What is usage-based pricing?”) in 2–3 crisp sentences.
• Make internal links more descriptive: Instead of “click here,” try something like Explore the feature breakdown. It’s better for readers, and it gives AI more semantic clarity.

Once your written content is in good shape, don’t forget about your visuals. They may not be accounted for in the same way, but they will always be an important part of your success.

Optimizing visuals and images for LLMs

LLMs can’t ‘see’ images, but they do take into account the text around them, like captions, alt text, and structured data. That surrounding context helps convey the meaning of an image. Want your visuals to work harder in AI environments? Here’s some advice:

• Make visuals machine-readable: Use descriptive alt text (e.g., “Bar chart comparing monthly user growth across three pricing tiers”) to give models meaningful context. Alt text, short for alternative text, lives in the HTML and provides a concise explanation of what the image conveys.
  
  Kontent.ai has a handy feature to make generating alt text a no-brainer:
  
  “Our content editors particularly like the Describe with AI feature. They use it with every image they upload as a starting point. This is really a quality of life improvement for content editors.” – Owen McCabe, Junior Product Owner, Newcastle Strategic Solutions

• Create context for images: Reference them in your text (“As shown in the chart below…”) and describe their insights in words, rather than relying on visuals alone.
• Again, use markup when possible: Schema types like ImageObject or Infographic help AI models understand and index your visuals more effectively. Since LLMs can’t interpret images directly, make sure any insights shown in visuals are also expressed in text nearby. 

Remember: Any insight shown visually must also be expressed in text if you want AI to reference it.

Visuals are one part of the equation, but to fully unlock GEO’s potential, it also helps to integrate your efforts with a solid SEO foundation.

How to plan for both GEO and SEO strategies

SEO brings people to your content; GEO helps ensure that AI can accurately reuse it. Together, GEO and SEO increase your discoverability across both traditional search and AI-driven experiences. 

For both, you still need a good user experience and high performance to be considered an expert, quotable source. Signals like authorship and citations are important to people; they also help retrieval systems and alignment models rank and frame your content as authoritative.

Make your strategy work for everyone by keeping these principles in mind:

1. Plan for both SEO & GEO from the start
   When outlining or briefing what to create, consider both human search intent (SEO) and machine comprehension (GEO). This saves time later and ensures your content is discoverable and usable across both channels.
2. Use modular content architecture
   Structure your content so that key takeaways can be easily lifted (GEO) while the full page still satisfies in-depth human queries (SEO). Think: summaries, FAQs, call-outs, and clearly marked sections. Writing modular content in a CMS designed for it makes this much easier. Modular content not only is efficient, but it also supports GEO by enabling consistent reuse of well-structured blocks across articles, help docs, or product pages.
3. Embed GEO and SEO strategies in your editorial workflow
   Small process shifts, like baking in GEO checks during editing, or defining reusable modules in briefs, can help optimization feel like intentional practice rather than an afterthought.
4. Audit performance in both directions
   Monitor traditional SEO metrics (rank, CTR, bounce) alongside prompt testing with tools like ChatGPT or Perplexity. This helps you identify whether your content is both visible and quotable and where it might be falling short in either dimension.

The shared goal of GEO and SEO is to produce content that serves human readers who want detailed information and AI models who use quotable, accurate answers.

Build trust for both search engines and AI

To stand out in search results and AI-generated responses, your content must earn trust. True optimization techniques aren’t about gaming a system or manipulating results. When you focus on delivering high-quality, relevant insights—that genuinely reflect your expertise and offer real value to readers—you’re thinking the right way. 

Optimization efforts, when done well, aim to bring the best answers to light.

One recommendation stands out: Align your work with the E-E-A-T framework (from Google’s quality rater guidelines), so that your content demonstrates: 

• Experience through personal insights or case studies
• Expertise with accurate and well-researched information
• Authoritativeness through citations or endorsements
• Trustworthiness via transparency and clarity

Models are increasingly tuned to reward content that feels human, verified, and complete. E-E-A-T isn’t optional anymore. If your content lacks clear authorship or trustworthy sourcing, it’s less likely to be surfaced by search engines or AI tools.

Roxana Pirlogea

Head of Demand Generation, Kontent.ai

Content following the principles of E-E-A-T creates positive signals for traditional SEO. It also help large language models recognize your information as reliable.

Clarify context and protect the meaning of content

As large language models reuse content across different prompts and interfaces, it’s important to be aware of the risks of lifted content: your insights could appear without full context or even attribution. Sometimes the AI-synthesized answers don’t even make sense. 

Helping AI use your content effectively is powerful. Helping users trace ideas back to their source is essential. To reduce the risks of decontextualized reuse, do what you can to help models and readers assess your work responsibly. 

• Add disclaimers for sensitive or regulated content (e.g., “This is not legal advice” or “For informational purposes only”).
• Be clear about usage rights (e.g., Creative Commons tags or usage statements), important if you want your content cited but not copied wholesale.
• Use contextual CTAs (e.g., “Read the full guide” or “See the original source for full context”) that guides everyone back to the source of truth.

What other ways can you help your content earn trust from both users and models? A solid distribution strategy makes a difference. Let’s check out how.

Content distribution and engagement

Strategic distribution ensures your content goes farther. Share it across high-impact channels like newsletters, social platforms (LinkedIn, Reddit), and relevant communities (Slack groups, Discord communities, forums) to generate engagement signals. 

Clicks, shares, and comments signal engagement, which is always a good thing. For example, posting a thought leadership article in a niche industry Slack channel can spark conversations that lead to increased mentions across platforms.

Tip: Track referral patterns from AI platforms like Perplexity, which now includes citations in their responses.

Common mistakes in the GEO strategy

GEO is still relatively new. However, there are already mistakes to avoid (and lessons learned from SEO “hacks” of the past). The following mistakes and manipulations, shown in the table below, can hurt readability across the board, weakening your credibility overall. 

GEO bad habits can waste effort and limit the value of your content. Fortunately, you don’t need to solve these challenges manually. The right tools can help you avoid common mistakes and build GEO into your workflow more efficiently.

Reminder: GEO works best when tailored to the content format. Not every guide needs to read like an FAQ. Clarity and audience fit come first.

Tools that can help improve your GEO

Are there any required tools for GEO? Not really. A whole new tech stack isn’t going to make or break your success, but a few smart tools can make the process much easier. 

First, use AI itself to do some of the heavy lifting here: LLM interfaces like ChatGPT, Claude, and Perplexity to simulate user prompts and see how your content holds up in AI environments.

Readability checkers like Hemingway Editor and Grammarly help you keep language clear and accessible, something both humans and models appreciate. When it comes to structure, schema markup generators (like RankMath or Merkle’s tool) simplify adding structured data to FAQs, glossaries, and articles.

And finally, your CMS plays a critical role. A modular, content-first approach in a CMS like Kontent.ai helps teams create consistent, structured, and semantically rich content, making it easier for AI to understand and reuse across contexts. More on this topic to come in part 3.

The biggest piece of advice for getting started? Focus on tools that fit naturally into your existing operations. The point isn’t to add complexity; it’s to build GEO habits into what you’re already doing.

How to test and validate if your content is AI ready

What is AI-readiness? AI-readiness means your content can be reused accurately by AI models, even when pulled out of its original context. That’s why clear language and well-structured ideas matter more than ever.

Want to check if your content is AI-ready? Start by looking at how it answers questions: does it get to the point in the first sentence or two? Then, scan your structure: are your main takeaways easy to isolate through headings or bullet points? Finally, check your metadata. Titles and subheads should reflect how your audience actually phrases their questions. 

To validate your own review, also take your content to the engines themselves! We recommend prompt testing your top performing pieces monthly to identify optimization opportunities.

Want deeper insight into what you should keep tabs on to ensure your efforts aren’t for nothing? Check out our recommended approach to running a GEO audit.

How to run a monthly GEO visibility audit

Set aside time each month to review how well your content performs in LLM-driven experiences, not just search engines. Below is a simple five-step auditing workflow to assess your GEO visibility:

1. Select 10–15 pieces to test, prioritizing FAQ pages, glossaries, or posts with high search traffic.
2. Simulate real prompts in tools like ChatGPT, Claude, and Perplexity, asking questions your content is meant to answer.
3. Check for citations, summaries, or reuse of your content, either direct quotes or recognizable paraphrasing.
4. Track referrals and mentions, including AI platform citations, brand-specific phrases, or new backlinks.
5. Note which formats, structures, or phrasing styles appear most often, then use that insight to inform your next round of edits.

When you’re feeling good about the quality of your optimized content, it’s logical to wonder how to exactly measure if your GEO efforts are working. That’s where tracking visibility and reuse comes in.

Measuring GEO success: What to track

There’s no single dashboard that shows how AI models use your content just yet, but you can track meaningful signals that indicate visibility and reuse. 

While not a formal standard, many teams are beginning to treat prompt testing as a key metric for GEO performance. Right now, it may be your most direct signal. 

Traffic and engagement metrics are also key for measuring GEO:

• Look for referrals from AI platforms like Perplexity, which include citations.
• Monitor mentions of unique phrasing with Google Alerts or brand monitoring tools.
• Track organic traffic, dwell time, and backlinks, all strong signs that what you are saying is resonating and being referenced.

Even if attribution is imperfect, repeated citations and lifted phrases are strong indicators that your work is both discoverable and quotable.

We treat prompt testing as the clearest early signal for GEO. If AI tools cite or summarize our content, we know it’s working. We also watch for referral links, repeated phrasing, and traffic bumps tied to branded queries.

Martin Brazda

Senior Performance Marketing Specialist, Kontent.ai

Pro tip: Content leads or SEO managers can own this process; it pairs nicely with monthly performance reviews. 

Prioritize AI in your content strategy now

We’re in the middle of a major shift in how content gets discovered and reused. Whether you call it Generative Engine Optimization (GEO), Answer Engine Optimization (AEO), or something else entirely, the goal is the same: to create clear, credible, and machine-readable outputs. 

Because AI tools are now key distribution channels.

To stay ahead, it’s time to consider building a repeatable GEO approach, whether that means evolving briefs, updating workflows, or simply aligning your team around structure and intent. The upside is you don’t need to start from scratch or go it alone. With the right tools, including CMS platforms embracing the agentic future, you can scale your GEO efforts without adding friction. 

We’ll cover exactly how in part 3.