Search

It’s no secret that AI has completely rewritten the rules of search.

As a result of this shift, many brands are already experiencing a decline in organic traffic. Consequently, the rise of AI SEO is often cast as a defensive play against these falling metrics. This line of thinking, however, only serves to address the surface-level concerns, while misunderstanding the current transformation underway: a fundamental shift in how consumers seek information.

Search is no longer a one-way, input-driven process; it’s now a dynamic, interactive interface. In turn, traditional keyword-based strategies are no longer relevant or effective. So how do marketers get their brands back in front of searchers? By moving from a defensive posture, into an offensive one that confronts AI head on.

What is AI SEO? Or GEO? (Or AEO?)

No matter what your organization calls it, optimizing your content for large language models (LLMs) is pretty similar to traditional SEO practices. Both involve optimizing a brand’s content so that it appears when someone is searching for information online.

The main difference is that while traditional SEO optimizes content for search engines’ algorithms, this new type of SEO is optimized for large language models like ChatGPT or Gemini. This means, rather than appearing in Google’s list of blue links, the focus is on encouraging generative engines to cite your content when they provide an answer.

But Wait– Is My Organic Search Traffic Coming Back?

Probably not.

Search has undeniably shifted: At least 6% of searches are taking place on LLM platforms, and approximately 60% of searches are now zero-click. Out with clicks and ranks, in with influence and sentiment.

Today, conversational AI pervades the digital experience, making this shift more than just one of search engines adjusting their UI. While most search engine marketers have already contended with featured snippets or knowledge graphs, AI is poised to become even more disruptive. Customers are increasingly choosing LLMs for their mix of conversational qualities and instant answers, making them more appealing for answering complex or specific questions.

How Will LLMs Change Consumer Behavior?

Let’s start by dissecting how consumers use the internet to find what they need. 

For decades, people primarily turned to search engines like Google. When a consumer wanted something they had to type in simple, keyword-based questions, like “dishwasher not working.” Then, they’d scroll through a page of search engine optimized pages that may or may not actually answer their question.

While this method of search meant a lot of people viewed your website, it very rarely resulted in people thoroughly reading your content, then deciding to purchase your product or service. It could help you build brand equity at scale, especially if your content was helpful, but consumers were often too high in the funnel to actually open their wallet.

This resulted in a push around conversion rate optimization. The idea was that by bringing offer engagement from 1% to 2%, your SEO revenue could theoretically double. But that still left 98% of the pie. The next step would be paid retargeting, trying to capture customers that later realized they didn’t have the time or patience to fix their dishwasher.

But unfortunately, offers and ads won’t solve the problem of unengaged and uninformed consumers.

Now, with tools like ChatGPT, consumers are shifting to “generative intent.” This means instead of plugging in key words and manually searching for what they want, they can use an LLM to help solve their exact problem. For example, telling an LLM that “sometimes my dishwasher leaks and the dishes won’t get clean,” will prompt it to generate a series of troubleshooting steps. If the user realizes that troubleshooting is too much work, they can ask for a referral to a local appliance repair company. Once they’re linked to your website, all they need to do is call.

This plugs a lot of leaks in the marketing funnel… for the marketers who are able to seize the moment, anyway.

What LLMs Mean for the Future of Search

This new era of digital engagement is based on the seamless delivery of information from brand to consumer via agentic proxy, meaning users get a complete, ready-to-use answer immediately, without having to browse different websites.

The future of search now extends beyond traditional search engines themselves, and into a new landscape where these proxies run searches on behalf of consumers. So, while organic traffic numbers may decrease, the quality of consumer engagement will increase. The consumer base will be smaller, but become more engaged and informed, and ready to take decisive action. 

This adjustment in consumer behavior calls for a reassessment of the marketing funnel. Consumers will expend less effort on their search journeys. LLMs remove many of those research steps by condensing what it thinks will be the most important information in its response to an initial prompt. From there, these platforms are able to guide consumers through additional questions and additional pieces of the sales funnel in a single conversation instead of multiple searches. In this way, LLMs have become sales departments of their own: pulling information and context from all corners of the internet. 

How Should Forward-Thinking Brands Think About AI SEO?

Marketers should focus on earning visibility across both traditional search engines and AI platforms to meet the current moment. The emphasis should be on offensive strategies, on proactively shaping your brand’s reputation in the “eyes” of AI. Think of it as digital PR. Here’s what to consider: 

1. Use Query Fanout to Build FAQs

An easy first step is adding FAQs to ungated content, focused on addressing questions that people ask search engines and LLMs. FAQs help LLMs find your content by providing clear, structured answers that are a close match to a user’s query and search intent. A measurement platform like Profound is recommended for identifying these prompts, but keyword data can be used as an alternative.

FAQs work well because LLMs use “query fan out” to break down a user’s query into multiple related sub-queries, sub-topics and intents. It then executes several of those smaller queries simultaneously across multiple data sources. That information is then combined and synthesized into one complete answer. So, by creating these FAQs, you’ll be able to provide highly relevant answers for those machine-generated queries.

2. Use Structured Content

Influencing LLMs means speaking in a machine’s language. Content should be structured, unique and useful, optimized for topics over keywords. Structured content like schema markup assists helps the LLMs break down content into smaller “chunks” that are consistently categorized with relevant headlines, and grouped into topics.

3. Optimize for Topics, Not Just Keywords

Topical optimization focuses on creating small content clusters that address broader subjects and themes from multiple angles. This builds topical authority, which increases the likelihood of your content being picked up by AI.

4. Standardize Your Presence Offsite

AI tools get their brand information from across the entire web, not just a brand’s own website. Information is gathered from publicly available data sets, including Wikipedia, customer reviews, file shares, archives and more. 

This means marketers must proactively feed AI accurate, valuable information so it can educate consumers and shape their opinions on a brand’s behalf, extending a brand’s influence beyond its own site to social media, forums and authoritative sites like Reddit, their Google Business Profile, Wikipedia, LinkedIn and Apple Maps.

This enables AI to promote a brand’s unique value propositions, equipping it with comprehensive information to influence consumer opinions and, in some cases, mitigate negative consumer sentiment.

5. Rethink SEO Measurement

On the measurement side, tracking clicks and rankings becomes less important than tracking influence and sentiment. You can do this by employing social media monitoring tools that track brand mentions across social platforms, and by monitoring reviews on sites like Yelp and Google. 

In this new digital era, KPIs must reflect this ongoing transformation. These new KPIs might include:

• Visibility: Number of relevant prompts where your brand appears. You should be able to break this down by platform, since each LLM platform uses a slightly different algorithm.
• LLM Referral Traffic: How many people access your site from an LLM. You can track this easily in Google Analytics using source/medium filters.
• LLM Sentiment Score: Measures how often LLMs surface positive, negative, or neutral feedback about your brand, along with some of the common themes within that feedback.
• Citation Rates: How often your brand is cited by LLMs for user queries. Keep an eye on which pages are cited most frequently, and how often people actually visit those cited pages. If a page is cited often and gets a fair amount of human traffic, that’s a highly valuable page.

Other brands might want to track more specific metrics, like how often your user generated content results in a citation, or how often your site is being cited compared to third-party publishers.

With that said, don’t forget to keep an eye on some of your legacy metrics – like keyword rankings, most popular pages, backlink quality, crawl errors, and the technical quality of your website. These are still important for search, and may influence your performance on LLMs.

Conclusion

The rise of AI in search represents a fundamental pivot. The era of chasing clicks and rankings is coming to a close, to be replaced by a reality where influence and sentiment are king.

Brands that cling to defensive, keyword-based strategies will find themselves increasingly invisible as consumers turn to conversational AI for answers. The path forward lies in an offensive approach: proactively shaping your brand’s narrative across the entire web, creating structured, authoritative content that AI can trust, and redefining success through metrics that measure true influence.

By embracing this change, you’re preparing your brand to be the definitive, recommended answer for the next generation of highly-informed and ready-to-act consumers.