How to Rank in AI Search Results
- Maciej Konarzewski
- 1 day ago
- 5 min read
AI SEO Ranking Fundamentals
It’s 2025, and online search has undergone significant changes. We’re not just typing keywords into Google anymore. We’re asking questions out loud to Alexa, Siri, and ChatGPT, and in return, we’re getting instant answers in natural language, often without ever clicking a link.
Welcome to the world of AI, where optimising for machines means understanding how humans talk. If you're running a website, creating content, or managing digital marketing in any form, you need to adapt. AI-powered search isn’t coming. It's already here.
This guide breaks down what AI SEO really means and how to optimise for it and rank in AI search results.
1. Traditional SEO.
Traditional SEO, or Search Engine Optimisation, refers to the foundational practices used to improve a website’s visibility in search engine results, particularly before the rise of AI-driven search tools. It focuses on techniques such as keyword research, on-page optimisation (including title tags, meta descriptions, and headers), creating high-quality, relevant content, ensuring strong technical performance (such as site speed and mobile-friendliness), building backlinks from reputable websites, and providing a seamless user experience.
It lays the groundwork for AI-enhanced search experiences by providing the structure, clarity, and authority that search engine algorithms rely on.
2. AI SEO Fundamentals.
AI SEO is the practice of optimising content and websites to rank in search results powered by artificial intelligence, such as Perplexity, ChatGPT, Google’s Search Generative Experience (SGE), and voice assistants. Unlike traditional SEO, which focuses heavily on keywords and backlinks, AI search engines prioritise natural language, topical authority, evergreen content, conversational search intent, and user-focused content. It’s about creating clear, helpful, and trustworthy information that AI tools can easily understand, summarise, and present as direct answers to user queries.
How to Rank in AI Search Results - AI SEO Main Principles.
Conversational Language
AI search engines rely on natural language to understand queries. This means that if you want your content to rank in AI search results, it needs to answer questions like a human. Let's use the topic of this blog as an example. Instead of optimising for exact phrase AI SEO, we interpreted the intent behind it.
We thought about what the user really wants to know when it comes to AI SEO, and addressed the question in plain English. Instead of stuffing pages with rigid keywords like “AI search results ranking,” we provide meaningful, helpful answers to the question: “How to rank in AI search results?”
Topical Authority
Forget obsessing over keyword density. AI values expertise and relevance across a broader topic. If you’re writing about your services, don’t just focus on one article. Build a content cluster around the subject to show authority. Whatever your services are, creating a series of interconnected, in-depth pieces helps AI understand your domain expertise and positions you as a trusted source in your field.
Structured Data
While AI understands content more flexibly, structured data (like schema markup) helps it understand the context more clearly. It’s especially useful for things like product listings, FAQs, and reviews.
Smart E-E-A-T
Experience, Expertise, Authoritativeness, and Trustworthiness (known as E-E-A-T) - a cornerstone of Google’s ranking algorithm still remains essential in the world of AI SEO.
Experience refers to the hands-on knowledge and lived experiences that you need to bring to a topic, giving the content genuine value.
Expertise highlights the level of skill or training you possess in a particular field, ensuring the content is informed and insightful.
Authoritativeness is about the recognition within the industry.
Trustworthiness, as demonstrated by credentials, secure website protocols, and genuine user reviews or citations, remains essential for credibility.
With the boom in smart speakers and mobile assistants, more users are searching using their voices. Optimise your content in a clear, direct, and natural tone. Use long-tail keywords that reflect how people speak.
Clear, Concise Answers
AI models pull from content that delivers direct, digestible information. Well-structured content with clear takeaways, bullet points, and summary boxes often performs better in featured snippets and answer summaries.
Strategic FAQ Sections
FAQs aren’t just for user convenience. They’re gold for AI indexing. Add an FAQ block at the bottom of your article or product page, covering real-world queries. Structure it with simple language and use schema markup to help AI recognise it.
Semantic Keywords
AI understands semantic relationships, so variety actually helps, not hurts. Instead of repeating the same keyword, use variations that mimic how people talk. For example, if your focus is “garden tools”, use phrases like: best tools for gardening, what tools do I need for planting?
Keep Updating Old Content
AI tools favour fresh, relevant content. Don’t let your old blog posts sit stale. Regularly update articles with new stats, insights, or emerging trends, links. Add new FAQs or summaries to align with current AI behaviours.
3. Core Technical Elements to Keep in Check When Optimising for AI SEO
Behind the scenes, your technical setup still plays a crucial role. Here’s how to tweak your site for the AI search results era.
3.1. Site Speed and Mobile Performance.
AI search results often prioritise content that loads quickly and works seamlessly on mobile. Make sure your site is fast, responsive, and cleanly coded.
3.2. Use Structured Data Where It Matters.
Implement schema.org markup for:
FAQs
How-to articles
Reviews
Products
Events
This helps AI tools like ChatGPT or Perplexity better understand and use your content in responses.
3.3. Clean URLs and Logical Site Architecture.
AI needs to crawl and interpret your site efficiently. Use clean, descriptive URLs and a sensible internal linking structure.
3.4. Optimise for Featured Snippets.
Use question-based subheadings, direct answers, and tables or lists to increase your chances of being featured in AI snippets or summaries.
4. How to Rank in AI Search Results. Conclusion.
AI SEO isn’t about tricking an algorithm, it’s about being the best answer to a human question. The winners will be those who combine technical know-how with real empathy and expertise.
If you want to appear in AI search results, focus on clarity, relevance, and helpfulness. AI is just the middleman. Your job is to connect.
Are You Ready to Optimise for AI Search?
Start by reviewing your top-performing pages and ask: Would this make sense if someone asked it out loud?
If the answer’s no, it’s time for a rewrite.
Frequently Asked Questions (FAQs)
Q1. How can I tell if my content is being used in AI search results?
While AI models often don’t directly cite sources, you can monitor tools like Google Search Console, analytics spikes from AI platforms, or brand mentions in AI answers to infer visibility.
Q2. Do AI search engines penalise overly optimised or keyword-stuffed content?
AI prioritises content that sounds natural and user-focused. Over-optimised pages with keyword stuffing or unnatural phrasing are often ignored in favour of more conversational, useful responses.
Q3. Should I write differently for AI tools?
The principles are essentially the same. Focus on clarity, usefulness, and relevance. However, ChatGPT-style models may favour more structured and explanatory content, while SGE prioritises verified, quick-to-digest information with strong source credibility.
Q4. What role does brand presence play in AI SEO?
A strong brand can increase your chances of being cited or surfaced in AI answers. AI tools often lean toward trusted, familiar sources, so building authority and consistent branding pays off.
Q5. Is AI SEO only for blogs, or does it apply to product and service pages too?
AI SEO applies across your entire site. Product and service pages should also use natural language, clear answers, and structured data to be picked up by AI systems, especially for featured snippets and voice search.
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