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By Caitlin Proctor Huston, On-Page SEO and Content Marketing Expert
Last Updated: July 9, 2025
If you run a small business online, you might have noticed a dip in your organic traffic. You’re not alone. AI search is quietly rewriting the rules of online search.
Your customers are getting answers from ChatGPT and 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 can 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.
Key takeaways:
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.
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 are 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:
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 “10 Best Law Firms in Los Angeles,” AI-driven searches offer you the best LA-based lawyer for you. This is changing where we search and how we search.
We can see that user behavior is shifting from the simple keyword matching of traditional search to longer, more context-based, complex queries. 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 can 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 a 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.
This will depend on the platform, so let’s look at the two top AI platforms individually.
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.
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.
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 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. To tie zero-click searches to AI search directly, Ahrefs found that AI Overviews lead to a 34.5% drop in click-through rates. However, there is some good news along with this ominous data.
However, other studies are showing that traffic is 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:
Currently, there is 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.
You have probably 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:
In short, AI-search is a new opportunity for visibility–not a threat to the current search engine optimization system.
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?
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.
Keep doing good 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 elements of SEO to focus on to stay relevant in AI search: clear value and usefulness, content structure, trust signals, and local and conversational optimization.
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. Competitive content 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.
How you can win in AI Search:
Here’s how to begin.
AI models prioritize content that is helpful and fresh, so your site needs to demonstrate your “E-E-A-T” factors. 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. 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 the information is. Strengthen these signals by using recent data, especially if it’s original, and displaying the date your page was most recently updated.
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.
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.
Take action: Update two blog posts to include a clear summary box with key takeaways.
Build your brand recognition and trust to get noticed by AI systems. You can do this with on-page SEO tactics and off-page SEO. Your goal is to be visible, memorable, and credible.
Take action: Make sure your website’s About page clearly explains who you are, where you operate, and why you are trustworthy.
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.
Take action: Write or update one page to answer a local or service-based query from your customer reviews.
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 while visibility metrics like impressions increase. Hone 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 could be from ready-to-buy visitors. When it comes to traffic, focus on quality over quantity 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.
Look for these metrics in Google Search Console and Google Analytics 4 as compared to your organic traffic:
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.
ZenUp’s article “7 Signs to Use a Landing Page for Google Ads” recently earned a prominent spot in the AI Overview for the keyword “signs to use landing page for google ads” within four months. Despite a low domain authority, low clicks, and moderate rankings, our highly-relevant structured content appears above the 10 blue links.
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 outline using semantic keyword data from Semrush and SurferSEO 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 article ranks on page one and appears in the overviews for its target keyword. While it receives 0 direct clicks, it earns 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.
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:
This shows that AIOs are pulling content that’s relevant, well-organized, trustworthy, and fresh. You don’t need to overhaul your site. Keep creating content with SEO best practices.
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 a 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.
Traditional SEO aims to get content to show up as one of Google’s 10 blue links, the organically ranked webpages on the first page of Google searches. AI SEO builds on traditional SEO to help content show up in new places and formats, such as Google’s AI Overviews, Perplexity, and ChatGPT. It’s part of a broader trend of zero-click search optimization, which involves optimizing for rich results to earn featured snippets, People also ask answers, or local map packs.
Optimizing for traditional SEO relies on keyword research. AI search optimization focuses on incorporating clear, structured data that directly answers users’ search queries without needing to click through to a website.
Content that is well-structured, trustworthy, and clearly written is more likely to be picked up by AI.
– Use schema generation and testing tools
– Continue using SEO platforms like Ahrefs or Semrush
– Track visibility through AI-related SERP features where possible
– Focus on content quality and structure more than new tools
AI tools surface content that’s easy to extract, so format matters as much as quality.
No. Most of the tools you’re already using for SEO work just fine for AI search, too. The best tools are the ones you’re likely already using.
– Use schema generation and testing tools
– Continue using SEO platforms like Ahrefs or Semrush
– Track visibility through AI-related SERP features where possible
– Focus on content quality and structure more than new tools
Don’t get distracted by shiny tools. Focus on good, clear content.
Yes. AI search levels the playing field by prioritizing clarity and trust over budget.
– You don’t need a massive content library
– Answer specific questions related to your niche clearly and helpfully
– Use structured data and local content- Focus on building authority in your industry
You don’t need to outspend the competition; you just need to provide the best answer.
Caitlin Proctor Huston is an on-page SEO and content marketing expert with a proven track record of driving millions of visitors to businesses. She specializes in SEO writing, content strategy, and conversion optimization, helping brands scale and grow their online presence effectively.
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