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How to Rank in AI Search Consistently

August 20, 2025

7 min read

Written by:

Power Digital Growth Marketing Partner

Power Digital is a full-service growth marketing agency helping brands accelerate their revenue with data, strategy, and execution. Known for our award-winning teams and nova technology, we bring clarity to complexity and build marketing that scales.

Reviewed by:

Tara Johnson Senior Content Strategist

Tara Johnson is a marketing strategist with 10+ years of experience in digital strategy, content creation, and advertising. At Power Digital, she leads content planning, creating high-impact resources that boost visibility and drive results. Tara believes in no magic wands—just smart content and a passion for sustainable, authentic growth.

Table of contents

1. Understand How AI Search Works
2. Optimize for Conversational and Intent-Based Queries
3. Structure Content for AI-Generated Summaries and Snippets
4. Focus on Topical Authority and Content Depth
5. Leverage Schema Markup and Structured Data
6. Prioritize High-Quality, Trustworthy Content
7. Improve Website Performance and User Experience
8. Stay Updated on AI Search Developments
9. Future-Proof Your SEO Strategy for AI Search

To Top

Since the birth of search engines, businesses have strived to make sure their content ranks as high as possible. After all, better rankings mean more eyes and more conversions.

But search engines have evolved significantly since their inception, and now, SEO strategists must juggle more variables to scale performance. Understanding and adapting to AI-driven search engines like Google SGE, ChatGPT-based search tools, and Bing AI has become a main focus. In fact, to stay competitive in the AI search landscape, SEO strategies need to align with AI-driven indexing, ranking factors, and content presentation.

From structured data and long-tail keyword targeting to authoritative content strategies, discover how to rank in AI search for greater reach and maximized returns.

Understand How AI Search Works

AI is not an enemy of SEO–far from it. Nevertheless, strategists must understand AI search deeply to develop high-ranking content and accurately analyze success.

In the early age of search engines, keyword matching reigned supreme. Search engines like Jump Station, WebCrawler, and Lycos used automatic web crawlers to index web page titles, headers, and text, allowing users to search for certain keywords and find matching results.

Later, engines like AltaVista implemented natural language search capabilities, which enabled users to input conversational queries (like “What is SEO?”) and receive decent results.

However, with the help of machine learning and natural language processing (NLP), AI-powered search engines can now determine a web page’s quality as well as its relevance. Google’s revolutionary PageRank algorithm primarily ranks results based on its internal and external links to lead users to more popular—and therefore more useful—pages.

The next major frontier for search engines? Generative AI.

Google’s Search Generative Experience allows users to ask highly specific, complex questions. The AI algorithm indexes and interprets pages to present the most relevant information as direct, conversational, and comprehensive answers.

In particular, AI search engines use algorithms to prioritize pages with authority. They determine this by looking for:

Backlinks from reputable sources.
Earned media coverage.
High-quality content with trustworthy sources.
Up-to-date information.
User satisfaction.

So, instead of striving to rank on SERPs, strategists must now work to appear in generative responses.

This begs the question: How can SEO specialists adjust their strategies to give AI search engines—and users—what they want?

Optimize for Conversational and Intent-Based Queries

As generative AI enables users to plan family vacations and find the best vehicles with single searches, SEO strategists must now cater to conversational, intent-based queries. This means content should be written in a natural, engaging tone that can be synthesized easily by AI-driven search engines.

What’s more, strategists can target these complex queries using a few key strategies:

Long-tail keywords – Short, exact-match keywords are phasing out in favor of long-tail keywords that capture user queries. These keywords often take the form of relevant, location-based, or intent-driven questions. For example, “Where can I find the best Italian restaurant with outdoor seating?”
Frequently asked questions (FAQ) sections – Strategists can incorporate FAQ sections on high-traffic webpages to naturally target long-tail keywords and intent-based queries. FAQs offer users direct, relevant answers to their most pressing questions—and appeal to generative AI search engines in the process.

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Structure Content for AI-Generated Summaries and Snippets

AI search often extracts answers directly from content for featured responses and “people also ask” SERP sections. Use these formatting conventions to increase the likelihood of AI search summary selection:

Clear headings – Place long-tail keywords and conversational queries in webpage headings so users and AI search engines alike can effectively scan for important information.
Concise answers – Remember the natural, conversational approach described earlier. And never underestimate the power of a FAQ section.
Bulleted and numbered lists – Lists help users quickly absorb the most essential information on a page. They also help AI searches more effectively index and rank a page’s content.
Structured data – Users can interpret different pieces of content intuitively, but search engines need a little more information. Strategists can help them out by including structured data that tells AI search algorithms exactly what’s on a page. More on this below.

Focus on Topical Authority and Content Depth

Everyone loves a genuine and trustworthy industry thought leader—a go-to source for relevant information. That includes AI search engines. AI search favors comprehensive, well-structured, reputable websites that demonstrate expertise on related subjects—also known as topical authority.

The first step of any topical authority SEO strategy is crafting high-quality content. Beyond that, strategists can appeal to AI search engines by structuring content in a clear and indexable way. For example:

Identifying key topics to showcase expertise.
Building pillar pages for content.
Creating interlinked topic clusters.

These conventions provide AI models with accessible, authoritative information and clear topic relationships that enhance their generative responses.

Leverage Schema Markup and Structured Data

When a user views a webpage, they can quickly assess and interpret its contents. For example, they understand what’s contact information, what’s a photo of the business storefront, and what’s a list of services. Search engines, though powered by AI, can’t make those same judgments—without a little help, that is.

That is where schema markup and structured data come in.

AI-powered search engines rely on structured data to understand content relationships and display rich snippets on SERPs. To be featured, consider implementing:

FAQ schema.
How-To schema.
Entity-based markup.

With Google, strategists can check structured data and preview rich results using their Rich Results Test.

Prioritize High-Quality, Trustworthy Content

AI models eat up quality content—using the EEAT model:

Experience – Is the content written by an industry leader or a scrappy, knowledgeable field agent? Content can display experience using case studies, credentials, anecdotes, and other relevant data.
Expertise – Search engines push results that provide users with comprehensive and insightful information. Highlight expertise by outlining and explaining content in a clear, accessible way.
Authoritativeness – Authority signals to users and search engines that content is reputable and valuable. Write content with a strong and distinct voice worthy of an industry thought leader.
Trustworthiness – Above all, content must be true, fact-checked, and backed by quality sources. Google notes that while all EEAT factors matter, trust is the most important. Most content will only demonstrate some of the other factors, but high-quality pages must display trustworthiness.

It’s important to note that Google search doesn’t use EEAT as a specific ranking factor. That said, search quality raters rely on it to determine the value of the algorithm’s results pages.

Improve Website Performance and User Experience

AI search also considers engagement metrics and user satisfaction when ranking content—because happy users usually beget more happy users.

Reduce bounce rates and improve SERP ranking by optimizing these key user experience (UX) factors:

Page speed – Users don’t just want quality content—they also expect it to load immediately. Faster page speeds have shown a direct impact on the number of conversions a company’s site makes. One study found that a 0-4 second load time produces ideal conversions.
Mobile responsiveness – As of 2024, mobile users make up more than 60% of website traffic—and that percentage will only continue to grow. Ensure high-quality mobile experiences by refining the user interface and boosting mobile page speed.
Navigation – Users and AI search engines all value intuitive website navigation for quick and efficient information access. Explore different ways to structure content, prioritizing logical page progressions and clustered topics.

Great SEO strategists know that high-performing content relies on high-quality user experiences, and users are more inclined to trust a page that’s easy to find, loads quickly, and looks professional.

Stay Updated on AI Search Developments

As AI search continues to improve and evolve, strategists must adapt accordingly. Anticipate shifts in SEO strategy by monitoring the latest innovations in AI search capabilities: Google SGE updates, OpenAI advancements, industry trends, and more.

For example, Google recently announced an experimental version of their Gemini AI assistant that factors a user’s search history into generative responses, adding further personalization and conversationalism to search results. Advancements like these will constantly push strategists to up their SEO game.

In addition to this research, strategists can take the offensive by constantly tracking and analyzing their search performance to fine-tune SEO. Eliminate guesswork and optimize rankings by measuring key performance indicators (KPIs) such as:

Organic conversions.
Search visibility.
Organic traffic.
Click-through rate.
Keyword rankings.
Backlink metrics.

In an ever-shifting search engine landscape, businesses can keep steady footing with robust SEO strategies built to shift with it.

Future-Proof Your SEO Strategy for AI Search

AI search is leading users to relevant, valuable, and personalized information. Ensure your content makes the cut by adapting your SEO strategies for the new age of searching.

You can maintain ranking and visibility by developing a deep understanding of AI’s inner workings, adopting conversational language to target high-intent queries, leveraging structured data for rich results, optimizing user experience, and more. Focus on user intent, structured content, and high-quality information to stay ahead of the competition—and firmly in users’ search results.

Want to know how else you can increase revenue and accelerate growth? Connect with the experts at Power Digital. Some of the world’s most ambitious brands have worked with us to achieve 2.6 times faster growth than the industry average. Learn what we can do for you by reaching out today.