How to Optimize SEO for AI Search in 2025

If you run a small business online, you might have noticed a dip in your organic traffic over the past year. You’re not alone. AI search is quietly rewriting the rules of online search.

Your customers may be finding answers on ChatGPT or Google before they click on your site. For small businesses, that means fewer visits, confusing analytics, and a lot of questions about what changed (and how you can fix it).

Don’t panic.

While it may seem like AI is yet another thing you’re supposed to adopt or pay for, the verdict is still out about how much search behavior is changing and what we can do as digital marketers.

To succeed in SEO for AI search in 2025, small businesses should focus on strategic updates to their site structure, content quality, and trust factors. This approach is supported by research on the evolving nature of search engines and AI tools.

This article gives you a clear, actionable approach to incorporating AI search into your SEO plan. We’ll start with a glossary of new terms and their definitions in plain English. Then we’ll look at how search has changed and why. Finally, I’ll offer the content optimization strategy I’m using to maximize search visibility that you can adapt to your own business. With this advice, you will feel informed, confident, and prepared for SEO marketing in the age of AI. You can still earn organic traffic from Google and AI search engines.

Glossary of AI SEO terms:

This article is going to cover a lot of information using some acronyms that didn’t exist a few years ago. For clarity and flow, let’s define these terms right off the bat.

• AI Search: Searches powered by artificial intelligence, such as Google’s AI Overviews and AI Mode, or standalone tools like ChatGPT and Perplexity.
• AEO (Answer Engine Optimization): A marketing strategy to improve your content so it gets picked up by tools like ChatGPT.
• AI Mode: A version of Google Search that uses artificial intelligence to answer questions in the search results.
• AIO (AI Overviews): Google’s summaries that appear at the top of some search results, using AI to give quick answers pulled from websites. Less commonly, AIO may stand for all-in-one or AI optimization.
• GEO (Generative Engine Optimization): A way of planning your content so it works well with AI tools that generate answers, not just with traditional search engines.
• LLM (Large Language Model): A type of AI trained on huge amounts of text to understand and generate human-like responses.
• SGE (Search Generative Experience): Google’s name for its AI-powered search experience that uses generative AI to provide quick summaries and answers directly on the results page.

How AI is changing search (and what it means for SEO)

The invention of AI search has introduced significant changes to traditional SEO metrics and strategies. Even if you’re not using sites like ChatGPT or Perplexity, you can’t avoid AI-powered search anymore. Google, Bing, and other search engines are leveraging AI.

The most obvious difference between AI search and traditional search results is the result presentation formats. Traditional search engines return a list of links to webpages related to the search query. In contrast, AI search provides a direct answer. This can look like a ChatGPT response or a Google AI Overview. AI-powered search engines summarize information from webpages to provide a quick answer directly in search results or within an AI chat conversation.

You can see this clearly with Google’s AIO: the answer engine result appears above the organic search engine results.

Beyond the presentation, here are the biggest differences between AI and traditional search:

• Search engines become answer engines
• Shift from keywords to conversations
• What AI search engines choose to cite
• The rise of zero-click searches
• Traffic from AI-powered tools may be more qualified

Search engines become answer engines

In addition to Google using AI alongside its existing search results, there are several AI-powered search engines that show answers, including Google’s DeepSearch, ChatGPT, and Perplexity. AI search engines don’t show search rankings. Instead, AI Mode uses a query fan-out technique to perform multiple searches simultaneously to address different parts of your initial query to generate a complete answer.

These emerging search trends show a shift from search engines to answer engines. Instead of using Google searches to find information, we’re using AI search tools to tell us information in a conversational way. Instead of finding someone else’s article on the “best AI tool for writing SEO rich blog content,” AI-driven searches offer you the best AI tool for writing SEO rich blog content for your specific needs. This level of personalization is changing where we search and how we search.

Shift from keywords to conversations

We can see that user behavior is shifting from the simple keyword matching of traditional search to longer, more context-based, more complex prompts. Conversational searches allow people to look for a broader range of information. As many as 70% of ChatGPT queries are totally unique, never Googled. People are asking questions like they would ask another person, with longer, more detailed, and more complex queries.

Aleyda Solis identified several differences between traditional and AI search behaviors. For example, normal search queries average 4 words and usually fall into intent types like “navigational” (finding a certain website) or “informational” (finding specific facts or information). On the other hand, LLM prompts average 23 words, and may involve several minutes of follow-up questions to explore a concept or topic fully. The intentions are varied and often don’t fall into the usual search intent categories.

AI search can handle natural language queries with more nuance than traditional searches due to two important features: multi-step searches and NLP.

According to Google, you can ask “complex, multi-part questions” in AI Mode to access real-time data based on the fan-out query technique. In the background, Google will perform multiple searches related to your query to surface the most relevant answers.

LLMs like those used by Google’s Gemini and ChatGPT use natural language processing (NLP) to understand context. NLP is how computers understand and generate human-like responses. It’s what makes AI seem intuitive rather than robotic. It’s also what enabled them to find answers that are semantically related to queries instead of exact keyword matches.

What AI search engines choose to cite

This will depend on the platform, so let’s look at the two top AI platforms individually.

Google AI Overviews

• Summarize the most relevant search results
• 98% of the links rank in the top 100 for the search term
• Average 6.4 outbound links
• Shows sources in text, in-line, and on a side panel for brand visibility.
• Only about 52% of pages from AIO are in the top 10 organic results for the same keyword
• The links from AIO tend to have lower domain authority scores than organic results
• Most often cites user-generated content from forums like Reddit and Quora, Youtube, Wikipedia, or medical sites

The key here is relevance. Organically ranked content judges the page as a whole, including page experience and content depth, while AI search technology can look at just the relevant “chunks” of content that can be cited without full-page context.

ChatGPT

• Generates an answer using NLP
• Still uses Google or Bing to find information (for now)
• Most often cites Wikipedia and news sites
• Tends to surface smaller sites with lower domain authority scores
• 50% of links from ChatGPT 4o are to business or service websites
• Has in-line sources and footnotes that you have to manually expand

A word of caution: since AI tools–including LLMs–primarily function by predicting and generating answers based on their training data, the results can be misleading, inaccurate, or simply a hallucination. Since AI doesn’t have a true ability to think, reason, or verify, it’s important for you to critically evaluate every response.

The rise of zero-click searches

Let’s take a quick look back in time. When Google launched in the late 90s, it returned “10 blue links” per page for search queries. There were no ads, no rich results, and no AI-generated summaries.

Since then, Google has moved beyond the 10 blue links by introducing ads and SERP features like map packs and featured snippets. In 2024, Google started including generative AI Overviews along with the 10 blue links, ads, and other rich results on search engine results pages.

Google’s overviews respond to user queries with a direct answer drawn from related content. They appear on about 15% of Google searches, but informational searches may trigger AI overviews as much as 40% of the time. As a result, data shows that people have stopped clicking on organically ranked links as often.

Sparktoro found that less than half of Google searches in the USA in 2024 resulted in a click, while 58.5% were zero-click searches. Zero-click searches are when users find answers directly on the results page, and don’t click on a website. In a similar vein, Ahrefs found that AI Overviews lead to a 34.5% drop in click-through rates.

Traffic from AI-powered tools may be more qualified

However, other studies are showing that traffic may be more valuable. Semrush found that, on average, LLM referral traffic was 4.4% more valuable than other traffic, based on conversion rates.

Google’s representatives suggest that the websites linked from AIOs are earning more traffic that is more engaged:

• Google’s VP of Search, Elizabeth Reid, writes that “links included in AI Overviews get more clicks than if the page had appeared as a traditional web listing for that query.”
• Google’s John Mueller shares via Google Search Central Blog that “We’ve seen that when people click to a website from search results pages with AI Overviews, these clicks are higher quality, where users are more likely to spend more time on the site,” indicating results are more relevant than organic search results.

There is currently no way for site owners to differentiate traffic referred from Google by SERP feature or AIO, so we’ll have to wait and see if sites are losing traffic or gaining more qualified traffic. We have some advice further down about metrics to watch in the meantime.

What do AI tools in search mean for my business?

You may have seen conflicting advice on Reddit or LinkedIn about what to do now that “SEO is dead.” Bad actors are fear-mongering, often to promote their AI solution. It can feel overwhelming!

Luckily, the data shows that although people are using LLMs more often, Google is still the most popular search tool by a huge margin. So while it’s true that AI is reshaping how people find information, this doesn’t mean you need to go all in on learning some new marketing strategies or investing in expensive tools your business can’t afford. Search engine optimization is still a valid marketing strategy.

Here’s what we know so far:

• Google still monopolizes the search market, clocking 16 billion searches a day and capturing 89.6% of worldwide search engine market share
• ChatGPT had more than 5 billion visitors in August 2025, whereas Google has more than 100 billion visitors every month
• AI search tools are pulling information from the same established sources as search engines
• Virtually all people who use ChatGPT and Perplexity still use Google, too, indicating they’re not replacing search engines with LLMs

In short, AI-search is a new opportunity for visibility instead of a threat to the current search engine optimization system.

Should I switch to a generative engine optimization strategy?

No, you don’t need to abandon SEO for GEO. Adapt your SEO strategies to take the evolving AI search landscape into account without forgetting the fundamentals. AI is augmenting search, not replacing it.

The question becomes: where are AI tools getting the information for their automated content generation responses, and can you use SEO strategies to increase the odds your content appears?

Content optimization for AI overviews and AI-generated answers is still SEO

It’s still SEO, even if that stands for “Search Everywhere Optimization.”

Google’s main objective remains “to help people find outstanding, original content that adds unique value.” In other words, write content that offers insight and perspective that AI can’t.

To make your website more visible to search engines, LLMs, and social platforms, the best ways to compete are the same SEO strategies that have stood the test of time. Reaffirm your commitment to quality content that is highly relevant to your ideal customer, and add technical SEO to package your content accurately.

For example, a local therapist might include FAQ schema and review markup, while a SaaS business could add original data studies and customer onboarding walkthroughs to build trust and semantic relevance.

Now that we’ve established what has changed and why, let’s get into the actionable strategy part of the article.

How to maximize your chances of getting included in Google’s AIO

For the most part, keep doing SEO. LLMs and AI systems are still looking for content that is crawlable, helpful, and cited. However, some AI SEO strategies are more important now. There are four areas of SEO to focus on to stay relevant in AI search: content structure, trust signals, clear value and usefulness, and local and conversational optimization.

How you can win in AI Search:

1. Start with fresh, insightful content that AI can’t replicate
2. Improve your site’s structure and semantic clarity
3. Strengthen your website’s authority and trust signals
4. Optimize for local and conversational search queries

Here’s how to begin.

1. Start with fresh, insightful content that AI can’t replicate

Yes, content is still king in the age of AI. Google is still earning roughly 90% of search traffic, and every other search engine and LLM is sharing the remaining 10%. However, content marketers and SEOs need to be strategic. A competitive content strategy today blends first-hand human insights with strong technical SEO. When you combine value with structure, you serve all three audiences: readers, search engines, and the AI models now surfacing your content across new platforms.

AI models prioritize content that is helpful and fresh. The more useful and user-centered your content is, the more likely it is to be surfaced in AI Overviews or chat-style search tools.

• Demonstrate strong E-E-A-T signals by showing off your author credentials, backing up claims with solid data, and citing good sources
• Use human-first writing to explain, clarify, and simplify complex topics related to your business or industry
• Share real, valuable insights or original perspectives based on your real experience
• Use internal summaries, “what to expect” sections, and bulleted takeaways to increase comprehension
• Regularly update your service pages and blog posts with industry insights and include a “last updated” date to show content freshness

Take action: Answer customer questions directly and concisely on your services page using FAQPage schema markup. You can use a tool like Schema Markup Generator or a plugin for your content management system.

2. Improve your site’s structure and semantic clarity

AI tools can’t understand your content if it’s unstructured or vague. Clear organization and descriptive formatting help search engines, people, and AI platforms understand what your content is about.

When you structure content logically with clear headings, sections, and topics, it helps search engine crawlers and LLMs understand what your page is about. Schema markup helps special structures like product descriptions and frequently asked questions stand out. Then, when people search for something similar to a frequently asked question you answer, it’s easier for the search engines to pull your data and satisfy the search query.

Structured data includes schema markup as well as relevant headings and scannable lists. These elements make your content easier for search crawlers to extract.

• Optimize your content for AI with semantic relevance, content gap analysis, topical authority, and logical content structures
• Use structured data (like HowTo or LocalBusiness) to provide context about your services and pages
• Format your pages simply with headings, subheadings, short paragraphs, and bullet point lists
• Include metadata
• Include microdata
• Include summaries and clear transitions in all your blog articles to help people and AI tools find the most relevant parts
• Don’t rely on keyword research; publish content that is actually valuable for your audience
• Create useful content that incorporates semantic optimization to fill keyword gaps with related concepts and natural language variations
• Be mobile-friendly

Take action: Update two blog posts to include a clear summary box with key takeaways.

3. Strengthen your website’s authority and trust signals for AI-driven search

AI tools are trained to prioritize credible, high-quality sources, so your site needs to clearly demonstrate your “E-E-A-T” factors on and off your site. Boost your trustworthiness by keeping your content fresh and relevant, too.

E-E-A-T stands for experience, expertise, authority, and trust. It’s something Google values, even though it isn’t a direct ranking factor. E-E-A-T signals measure content’s credibility based on an author’s perceived first-hand experience, use of verified sources, and earned mentions and backlinks from reputable, relevant websites.

Content freshness refers to how accurate and up-to-date your information is. Strengthen these signals by using recent data, especially if it’s original, and displaying the date your page was most recently updated.

• Build your brand recognition and trust
• Prove your experience and expertise across your service pages and blog content by stating your qualifications and credentials, linking to past work, and showcasing your first-hand knowledge
• Fact-check your claims and use trusted sources to make sure your site is reliably accurate
• Include backlinks to positive brand mentions, industry recognition, and news features to build credibility and increase external trust signals
• Establish a clear business identity and consistent brand messaging across all your owned channels
• Cultivate a positive reputation from reviews and media mentions
• Manage negative sentiment proactively with reputation management techniques
• Diversify your digital marketing strategy to include places where LLMs are more likely to find you, like Reddit, Wikipedia, and YouTube

Take action: Make sure your website’s About page clearly explains who you are, where you operate, and why you are trustworthy.

4. Optimize for local and conversational search queries

AI tools and Google both prioritize content that reflects how real people talk and where they’re searching from. Clear, natural, location-aware language gives your business a better shot at being included in AI-generated results.

• Use natural language phrasing to communicate like your customers talk, not like an AI
• Claim and optimize your Google Business Profile with categories, hours, photos, and service descriptions
• Feature local reviews
• Use consistent NAP information across your site, Google Business Profile, and social profiles
• Use the kind of phrasing your customers use, like “How much does a dental cleaning cost in San Francisco?” or “Do you offer weekend appointments?”

Take action: Write or update one page to clearly answer a local or service-based query from your customer reviews.

Measure your website’s performance in AI search results

The immediate impact on direct website traffic is the increase in zero-click searches, which results in your organic traffic decreasing. However, this doesn’t mean a complete loss of value. Adjust your expectations for how your organic traffic will look moving forward with more zero-click searches. Look beyond the click.

The goal shifts from getting a click to improving brand visibility and recognition within AI-generated answers. Let your stakeholders know about these shifts in traffic patterns and clicks, emphasizing that increased brand visibility and higher-quality, pre-qualified traffic can still lead to more overall conversions.

Expect to see overall traffic numbers decline. You may see visibility metrics like impressions increase. Home in on engagement tracking with signals like time on page and conversions. If you aren’t already, track your conversion attribution metrics. Unfortunately, there’s an inherent difficulty in reporting traffic, as LLM referrals often appear as direct traffic, and Google doesn’t differentiate traffic from AI Mode, AI Overviews, and traditional searches.

Traffic from Google and traffic from LLMs are still worth tracking. Your analytics may show fewer clicks, but if you’re showing up in AI search results, those clicks may be from ready-to-buy visitors. Focus on quality over quality moving forward.

Use Google Analytics 4 to identify the sites that refer to your site. If you have enough traffic, you can start to look for signs that your LLM traffic is more qualified. This isn’t a perfect method, since many LLM referrals show up as direct traffic instead of a referral. Still, it can help you get a sense of where you’re visible and how that group behaves on your site.

Specific KPIs to watch for AI search engine visibility

Look for these metrics in Google Search Console and Google Analytics 4 as compared to your organic traffic:

• Number of pages that are crawled and indexed
• Number of visits from referrals
• Number of branded searches
• Conversion rate
• Engagement rate
• Time on page
• Reviews that mention how they found you

You can monitor your visibility in AI Overviews via Semrush or another paid tool, and track your brand mentions with Google searches, Google Alerts, or third-party tools.

Case study: What SEO for AI search strategies got my content featured in Google’s AI Overview

In my role as the head of content marketing for an SEO startup called ZenUp, I incorporated technical SEO strategies to earn a backlink from a Google AIO. ZenUp’s article “7 Signs to Use a Landing Page for Google Ads” (now removed) earned a prominent spot in the AI Overview for the keyword “signs to use landing page for google ads” within four months of its publish date. Despite a low domain authority, low clicks, and moderate rankings, the highly relevant structured content appears above the 10 blue links.

The strategy: Structured, user-first content creation

I selected a long-tail keyword based on clear brand alignment, low competition, and moderate search volume. I searched the top-ranking results to ensure I had an accurate user intent. I wrote the SEO outline using semantic keyword data from Semrush and Surfer SEO to ensure complete topical coverage.

The author is an experienced business writer, and he included a case study featuring a subject-matter expert, which helped strengthen E-E-A-T signals. The article includes valuable content, including data-driven insights and real-life examples of ads and landing pages.

The data: Higher impressions, zero clicks, mid-range position

The article ranked on page one of Google and appeared in the AI overview for its target keyword. While it received 0 direct clicks, it earned relevant brand impressions that indicate visibility even without traffic.

Other SEO professionals have shared similar reports with an “alligator” shape as impressions rise and clicks fall.

Features that likely helped it get captured in Google’s AIO

This article wasn’t the most comprehensive or the top-ranking result. But it was well-structured, clearly written, and optimized to be useful for people and AI search. The combination of clear answers, structured formatting, and trust signals makes your content more likely to be picked up. Here are the on-page optimization and content strategy elements I think helped the most:

• Last updated date was published at the top of the page
• Clear, semantically structured outline to fully cover the topic
• Key takeaways were listed near the top of the article
• FAQ section was marked up with FAQPage schema
• Logical heading hierarchy and content chunking
• Scannable formatting with bulleted lists and short paragraphs
• Real-world examples and case study quotes from a qualified expert
• Original data was included
• Industry-leading authorities cited
• Internal linking to related service and blog pages
• Strong technical SEO, such as fast page speed and mobile responsiveness
• Author byline and bio showed experience and expertise
• Long-tail keyword targeting with strategic search intent alignment

This shows that AIOs are pulling content that’s relevant, well-organized, trustworthy, and fresh. My best recommendation? You don’t need to overhaul your site. Keep creating content with SEO best practices, and watch what works for you. 

Plan a sustainable SEO strategy that works for AI search

People are searching for information in new ways, but they still want the same thing: a real business with helpful solutions and clear answers. Use bylines, first-hand experience, and your genuine expertise to stay human-centered. You can refocus your SEO strategies without reinventing them.

Prioritize helpfulness, clarity, and structure over trends or volume. Write with your audience in mind, not a bot. Emphasize your real expertise as a real business. Use simple formatting and schema markup to help both people and AI tools understand what you’re writing about.

Don’t overhaul your site because someone said you needed to. This is new and emerging technology, and we are all still learning what will make a difference and what won’t.

Instead, focus on what makes your business useful and trustworthy. That will earn you positive attention in every kind of search.

FAQs about search engine optimization for AI search