If you have Googled anything in the last few years, you’ve likely come across an AI overview that summarizes some of the ranking pages to answer your query. Or maybe you wondered about the history of the Ottoman Empire or needed instructions to refill your car’s oil and turned to ChatGPT. AI is taking online search by a storm.
For search engine users, the rise of AI has made getting synthesized summaries of all the top internet easy. For companies and SEO experts, it involves figuring out how to adjust your content strategy to keep your content visible and to reach your customers. That’s why we’ve put together this guide on the future of AI search SEO to help you figure out where and how to tweak your content strategy to be ready for the growth of AI SEO.
Unlike traditional search engines that rely on keyword matching and indexed pages, AI-powered systems use large language models (LLMs) to interpret natural language in an attempt to deliver nuanced, conversational results.
Some of the leading AI search tools you may have used or heard of include:
Search is undergoing a fundamental shift that’s only getting started. In May 2023, Google began rolling out Search Generative Experience (SGE), now rebranded as AI Overviews, which places AI-generated responses above standard results. Microsoft integrated AI mode into Bing in early 2023 using ChatGPT-4, while platforms like You.com and Perplexity launched AI-first search tools that prioritize summarization and citations. Search engines now are prioritizing their own AI summaries at the top of the SERP in what used to be prime real estate for SEOs.
These AI tools are changing the way people interact with SERPs. In fact, a study from the Pew Research Center in May 2025 notes that people are significantly less likely to click on web pages listed in Google search results if there’s an AI summary present. They also only rarely click on the sources listed by the AI summary.
With the shift in how users interact with search engines, SEO is going to shift too.
Traditional SEO is built around optimizing for search engine crawlers and ranking within standard SERPs. This includes tactics you’re likely very familiar with, such as:
GEO—Generative Engine Optimization—targets AI searches. Large Language Models don’t crawl; they try to interpret the context and evaluate:
Because LLMs respond to context and credibility, not just ranking signals, you want to optimize content for semantic relevance, not just visibility. Adding GEO to your content strategy is another way to make your content visible in those AI-generated summaries—though traditional SEO still matters as well.
So if AI is going to change the way people search (and already is starting to do so), you need a content strategy designed to fit in that landscape. These are our four top tips for creating content that your readers will love and that works with AI.
Content these days has to walk a very fine line: being written for humans and for AI accessibility all at the same time. You don’t want to write a brilliant piece of long-form content only for it to be lost in the ether of Google, but you definitely don’t want to end up with AI slop. Some ways you want to cater your content for your readers and for AI include:
The goal here is to write content for your human audience but to make sure it’s fully AI accessible afterward. At the end of the day, good content is still king, so prioritize having well-written content and avoid losing that human touch while optimizing for AI search SEO.
AI works like any other search engine: it will rank your pages higher if they’re correctly set up with appropriate metadata. While AI tools don’t crawl the web like traditional bots, they still rely on structured, well-maintained websites. Technical SEO helps ensure your content is indexed by both search engines and used by AI models that reference top-ranking pages. Prioritize:
Just like with Google Search, AI systems reward content that’s well-structured and technically sound.
Optimizing for search engine results page (SERP) features can improve your visibility in both traditional and AI-generated summaries. Focus on:
Appearing in these SERP features improves your chances of being referenced by AI models—and therefore coming across your readers’ screens.
If you’re looking to build your pages in a way that makes it easy for AI tools to scan your content, focus on these five strategies:
By following these principles, your content becomes easier for AI models to recognize—which then helps you stay visible in the next era of online searches.
Even though it might feel like the search landscape is rapidly evolving, the core principles of technical SEO remain as important as ever. In fact, SEO hasn’t really changed—it’s only expanded to include AI searches. Staying on top of and implementing foundational technical best practices still pays dividends, both in traditional rankings and in AI-generated search results.
Structured data helps both traditional search engines and AI systems better understand the context of your content. Using it can help your content get featured in snippets and AI overview citations. To get the most out of your structured data:
Well-implemented schema makes it easier for AI systems to identify key facts and understand the relationships between ideas—boosting your content’s chances of being referenced in AI search results.
AI-powered search is no longer limited to just text, and your content strategy can capitalize on that. Many search engines and AI assistants now support multimodal inputs and outputs to blend text, images, and video to meet user needs. Make sure your site:
By incorporating diverse formats, you increase your visibility across a variety of SERP features. Your site could end up as the cited image in an AI overview or in an image carousel. That visibility will make your content more accessible and expand your reach.
All the general tips we’ve talked about so far are best practices for any type of AI search tool. While many core principles remain consistent, each model has its unique behaviors and ranking preferences. Some of the most prominent and widely used AI search engines—and the ones offering the most trackable performance insights today—include:
AI systems reward conversational content that mimics how people talk, so here are a few tips to optimize for conversational queries and natural language prompts:
By tailoring your content for the nuances of each platform—and optimizing for how people naturally ask questions—you’ll increase your visibility in both AI-driven and traditional search environments.
Traditional SEO tools may not yet offer complete coverage of AI-driven search experiences—but a new wave of reporting solutions is emerging to bridge the gap.
There are a lot of SEO metrics, but which ones matter for AI search SEO? Key metrics to focus on include:
Since AI search focuses more on credibility and relevance than on traditional rankings, visibility can come in the form of mentions and summaries rather than blue links.
While AI searches are still relatively new, there are tools that are adapting to help you keep track of your most important metrics:
As AI search adoption increases, expect more tracking solutions to emerge. Just like SEO matured with its own analytics stack, AI SEO reporting will become a core part of modern marketing analytics within the very near future. Start experimenting with these tools now to stay ahead of the curve and get a head start above your competitors.
Working with AI to produce AI-optimized content is increasingly essential. Modern AI systems—like ChatGPT, Gemini, and MarketMuse—can help you with identifying content gaps and topic clusters that you can write about, speed up the drafting process, and create content outlines for you.
Don’t think of AI replacing your content creators. Instead, pair AI with human experts to speed up the content creation process without losing what makes human-written content great.
Another way to AI-prep your content strategy is to apply the hub and spoke model. The hub and spoke model is a content architecture that creates a central “hub” page targeting a broad, high-value topic, supported by multiple “spoke” pages that address related subtopics in depth. Each spoke links back to the hub and to one another.
For example, when Maveneer came to 97th Floor in 2023, they wanted content that would rank, so we gave them a hub and spoke strategy with comprehensive overview hubs targeting keywords like “warehouse automation” and “order picking.” After establishing those hubs, we could expand to spokes with drill-down articles like “order picking technology” and “automated sorting systems” linked to and from the hub. This structure improves internal linking, site navigation, and topic authority to search engines and AI systems alike. In fact, for Maveneer, their domain authority R skyrocketed from 3 to 34, and they saw an 886% increase in search impressions YoY.
Search is evolving—and fast. More people are relying on AI to answer their questions and give them potential solutions. With AI browsers popping up, there are only going to be more AI search developments. These platforms don’t just display a list of blue links. Instead, they generate dynamic responses by pulling insights from multiple sources, often without traditional attribution or visible rankings.
For enterprise brands, this shift has major implications.
In this new paradigm, visibility isn’t just about ranking #1—it’s about being referenced, cited, or summarized by AI models at the moment a customer asks a question. Failing to adapt means losing organic visibility at critical touchpoints—especially early in the customer journey when buyers are still gathering information.
Enterprise brands that invest in AI search SEO now can make sure they’re ahead of the curve and stay visible. AI isn’t replacing internet searches—it’s reshaping it. And enterprise brands that evolve their strategies now will be best positioned to lead out in the next era of SEO.
Let us become your strategic AI SEO Partner. If you're ready to win in search, let's talk.
AI search changes how content is discovered and ranked. Instead of serving links based on traditional signals like keywords and backlinks, AI engines generate answers by analyzing semantic context, brand credibility, and how consistently information is presented across the web. SEO strategies now need to account for language models, generative outputs, and prompt-based user behavior to maintain visibility.
AI Search SEO is the process of optimizing your website and content for visibility in AI-generated search experiences. This includes engines like ChatGPT, Perplexity, and Google’s AI Overviews. It combines traditional SEO principles with new tactics focused on LLM citation patterns, structured data implementation, and prompt-level query optimization.
Structured data helps AI systems interpret your content accurately. By implementing schema types like FAQ, Author, or Organization, you provide machine-readable context that supports brand visibility in generative results. It also improves how large language models identify trustworthy content when forming responses to user prompts.
AI-generated visibility is measured through citation tracking, brand surfacing in prompt outputs, and contextual audits across engines like Claude and Perplexity. At 97th Floor, we use GEO reporting to analyze how often your brand is cited, how it's framed, and whether it appears in the right generative moments.
Content that performs well in generative search is factually accurate, semantically structured, and consistent across owned and third-party sources. Language models favor content that demonstrates authority, clearly defines entities, and aligns with natural user prompts. Long-form, educational content tends to earn higher visibility.
AI Search SEO strengthens every part of your digital strategy. Insights from generative search patterns inform more effective messaging, targeting, and campaign timing across all channels.
It supports your SEO efforts by revealing new search behaviors and surfacing optimization opportunities beyond the traditional SERP.
It enhances content marketing by aligning assets with full-query prompts, increasing the chances of being cited by AI engines.
It improves digital advertising by identifying top-of-funnel questions that can be used in ad creative, landing pages, and audience segmentation.
It also builds on our AI SEO capabilities by offering deeper insights into how language models evaluate and present your brand across platforms.
Together, these efforts help create a unified strategy where every channel benefits from smarter data and a stronger presence across the evolving search landscape.
