How to Rank in AI Search Results: Strategies That Work in 2026

If you did a Google search for Artificial Intelligence, the answer you get today would be wildly different than 10 years ago. AI is everywhere, and it’s influencing the world of SEO as much as everything else. We get asked how to rank in AI search results a lot, both by existing and potential clients. The good news is that it’s providing more opportunities for online visibility, and the other good news is that it’s not impossible to achieve.

AI search results don’t rank or list websites like search engines. Ranking in AI terms equates to visibility: how often your brand is mentioned as a potential solution, or your content gets cited as a source for the answer.

There’s a lot of noise about how AI is changing search. But in reality, it’s been influencing search results for a while. Search engines like Google have been using some form of artificial intelligence and machine learning to influence search results for many years. The difference today is AI’s sophistication, scale, and accessibility.

That being said, cracking how to rank in AI search results is now an action item for brands trying to increase website traffic and brand recognition. So no matter your end goal in terms of online visibility, whether AEO vs GEO vs SEO, the tips and strategies we’re sharing today can help get you there.

Although not every AI model is exactly alike, they’re all trying to accomplish the same thing: give users the best and most accurate answers or recommendations. This is as true for ChatGPT as it is for Google’s AI Overviews. To achieve this, models generally use a combination of LLMs (Large Language Models) or pre-trained knowledge, live web retrieval, and trusted third-party sources to generate responses and recommendations. For example, if two brands published almost identical content, but one has a stronger domain authority and more mentions on other websites, the AI engine will likely lean toward that brand as a source. That being said, solving the overarching puzzle of how to rank in AI search is multi-pronged: content structure and depth, brand authority and recognition, and technical optimizations.

It’s easy to talk about how to rank in AI search results, but what really matters is execution. What do brands need to do to get there? Here are five AI search optimization strategies that work.

SEO has always favored genuinely helpful content, and that hasn’t changed. We’ve always been told to write for the audience, not search engines, and that too hasn’t changed. What has evolved is content formatting. AI models prefer clarity in content, in both language and formatting.

AI-friendly content should focus on:

This tactic leans on the technical side and occurs on the backend of your site. Schema markup is structured data code used for website content that helps AI models interpret what it is, who wrote it, and why it matters. Schema makes it easier for AI to identify, categorize, and use website content.

This foundational tactic for gaining visibility in AI search results is similar to traditional SEO philosophy: content is still king. However, instead of focusing on “more” content, brands should focus on building content “clusters” that stay true to E-E-A-T. Content clusters are groups of related content centered around one core topic. For example, rather than writing just one blog about how to rank in AI search results, we also wrote about related, more specific topics like how to rank on ChatGPT.

For AI, topical depth signals expertise and authority. So, to demonstrate authority, brands should pick a topical focus and create multiple pieces that explore specific or related aspects under that umbrella.

Offsite authority encompasses multiple aspects related to how your brand performs across the web, from brand mentions to community engagement, such as:

The more your brand is mentioned across the web, the more AI notices. These external signals indicate authority.

Regular publishing and content optimization are as essential to AI visibility and how to rank in AI search results as they are to SEO. AI tends to use content that reflects the most current understanding of a topic, so it typically pulls from newer indexed sources. How does this affect your website?

If your competition is updating their site copy and publishing blogs or other content more recently than you, they’re more likely to be referenced by AI.

What’s the point of learning how to rank in AI search if you can’t determine its effectiveness? That’s where tracking comes in, and there are a few methods you can implement. One is the manual method, which is time-consuming yet effective. There are also tracking tools available, like Semrush or Rankscale, that automatically monitor brand mentions and citations across search engines like Google AI Overviews, ChatGPT, and Perplexity. You can also check GA4 for traffic sources from AI systems, such as chat.openai.com, perplexity.ai, etc.

During the tracking process, here’s what to note:

Google AI Overviews are the AI-generated summary at the top of search results. To track your results here, start by selecting keyword sets that are high-intent, problem-based, and comparison queries. For example, we would use these: “best ecommerce agency Austin”, “how to improve ecommerce SEO”, and “Magento vs Shopify for B2B”.

Input each into Google to see if an AI overview appears. If so, check if your brand is:

Document each finding and repeat the process every other week or once a month.

With these generative and search AI systems, your tracking will focus on brand mentions, citations, and recommendations. The tracking process for how to rank in AI search for these systems is similar to Google AI overviews. Begin by creating your list of test prompts. Include 10-20 across these buckets: awareness, consideration, and decision stage. For example, we would include: “Best Magento development agencies”, “Top ecommerce SEO companies”, and “Who should I hire for B2B eCommerce?”.

Run each prompt in all three AI systems: ChatGPT, Perplexity, and Gemini. You will be looking for brand mentions and links to your site in sources. As demonstrated in our guide to how to rank on Perplexity, links to your site are a real win as they are a clickable source. Harder to track are indirect mentions where your content is summarized but not credited, but it’s possible if you see brand-specific phrasing or summaries that mimic your content.

Track your prompts and data accordingly and repeat twice a week or every month to track progress.

Tracking your competitors’ mentions and citations across AI systems helps you understand if they are showing up and, more importantly, why. Here’s how to track competitor rankings in AI search results effectively.
Begin by selecting 3-5 direct competitors, including any that are “high-authority” content creators. Run the process using your prompts and track the competition’s appearance across systems.

Here’s what you are looking for:

Figuring out how to rank in AI search results isn’t really that different from “traditional” SEO practices. In fact, we’ve seen that the higher a website ranks in SERPs, the more likely it is to show up in AI Overviews, ChatGPT, and Perplexity. So the top 10 websites ranking organically in traditional search results are likely dominating AI visibility in their vertical.

Like SEO, AEO and GEO are a long game, requiring strategy, time, and effort for success. The process requires some heavy lifting, which is why many brands decide to partner with a team that can manage the complexity, from strategy to execution to tracking. At Living Proof Creative, we focus on growth and results through transparent, thoughtful strategies aligned to each brand’s goals. If you’re ready to explore a creative digital strategy grounded in living proof, we’re ready to talk.