You don’t need another reminder that search is changing.

But what often gets missed in all the noise around AI and generative engines is this: the cost of doing nothing is quietly stacking up—and it could put your brand at a long-term disadvantage.

As ChatGPT, Perplexity, and Google’s AI Mode evolve, they’re not just changing how users find information. They’re changing what information gets seen, cited, and remembered. And if your brand isn’t showing up in these new results, someone else’s will.

Here’s what inaction could lead to:

  • Your content gets skipped when LLMs crawl on-demand for answers—favoring a competitor’s page instead.
  • Your brand gets left out of the next model update, which means months (or years) of missed visibility in AI-generated responses.
  • Your SEO channel stalls, because you’re optimizing for the wrong metrics—while others tie AI visibility directly to business outcomes.
  • Your narrative gets rewritten by third-party content, with no input from you on accuracy, pricing, or positioning.

This blog lays out a clear, practical framework for how to respond. Not with panic. But with precision. You’ll learn how to transition from traditional SEO to GEO (Generative Engine Optimization), what new signals and strategies matter, and how to lead this shift before it quietly passes you by.

Table of Contents:

Getting into the Right Mindset for Generative Engine Optimization

Above all, a testing mindset is necessary to find success in AI search. 

That mindset was already incredibly valuable for the past 20+ years of SEO, but it’s more important than ever given the pace of change, the gaps in data and visibility, and the variety of search engines demanding attention. 

“Set it and forget it” is no longer an option.

As an SEO, you’re likely being asked to explain AI search as it evolves—often in real time. Your role now blends SEO expertise, investigative thinking, and strategic foresight. Clear, transparent communication will build trust and unlock support.

You’ll also need new types of data—and new collaborators. Be ready to present use cases, surface challenges, and frame opportunities. Because without the right data, building a strong business case is nearly impossible.

Recommended Reading: AI Search & SEO: Impact and Opportunity by the Numbers

How to Navigate the Shift to Generative Engine Optimization

Navigating the shift from SEO to GEO starts with “chunking”—not only a method for structuring content for AI search, but also a strategic approach to breaking down this transition into manageable, actionable focus areas.

Recommended Reading: AI Search Trend Report: Data Across Hundreds of Brands

Chunking Your Strategy: Four Pillars for Transitioning from SEO to GEO

Divide your AI search roadmap into four actionable categories:

  1. Goals: Focus on the unchanging human and business goals behind search—while adapting to how AI alters behaviors, decision paths, and the organizational strategies needed to meet them.
  2. Content: Is every paragraph optimized for topic depth and intent? Collaborate across SEO, UX, brand, and PPC teams to meet user motivations with precision.
  3. Technical: Are your most valuable pages accessible to crawlers and LLMs? Use sitemaps, schema, markdown, and server logs to ensure comprehensive indexing.
  4. Reporting: What AI-specific metrics matter? Report transparently on business outcomes, human signals, and prioritize data-driven requests for budget and support.

Chunk 1: Aligning Goals for the GEO Era

We need to remember the goals toward which our work is in service. I don’t mean the quarterly goals our manager set for us; I mean the goals of the business and, more importantly, the goals of the people our business is trying to reach. 

Sure, AI search is different than organic search has been for the past 20+ years, but are the goals of the people using it really different? Probably not.

Human Goals of AI Search

As a human, I’m trying to accomplish something using search – making a purchase, learning something new, or planning an experience (etc.) – that’s not new or different. 

I’m going to use the tools I can trust to help me accomplish my goals in less time and with a higher quality outcome (which may be subjective). If it’s fun to use AI search to reach my goals, that’s a bonus.

Human Behavior in AI Search

What’s new and different about AI search is the way it can save us time in accomplishing our goals or increase the quality of the outcomes. 

That can change our behavior in ways that might manifest as fewer clicks from organic search, more direct or referral visits, more brand searches (and fewer non-brand searches), more pages viewed on our websites (or fewer, depending), and a shorter time to purchase in the customer journey. 

Business Goals of AI Search

Does AI search change our business goals? Probably not. The company we work for is still trying to earn revenue from people who are trying to fulfill a need.

Business Behavior in AI Search

Just like user behavior, organizational behavior may change in order to adapt to AI search.

This could mean:

  • Investing more in understanding customer needs in the AI context
  • Modifying or expanding content
  • Connecting long-siloed data sets
  • Partnering with platforms like seoClarity to track and respond to AI-driven changes

The degree of change required will vary by organization, but the need to evolve is universal.

Chunk 2: Rethinking Content for Generative Engine Visibility

When it comes to AI search, content is nearly everything. After all, if your content isn’t being surfaced, what is? Likely your competitors’.

Your Organization and AI Search

To thrive in a GEO world, your organization needs to understand how large language models (LLMs) evaluate and index content. 

In organizations where SEO and content are separate, content creators will need to adopt new skills and workflows—learning from what SEO teams are already doing to optimize content for AI search visibility.

Your Current and Potential Audience in AI Search

At SMX Advanced Boston, I thought Will Reynolds and Garrett French had great (and very different) ways of saying you need to understand your audience. 

Depending on your organization, you may need a closer partnership with people or teams who do UX, brand research and marketing, PPC and paid social. 

Recommended Reading: Integrated SEO: Unify PPC & Organic to Maximize SERP Presence

Yes, we can see some of the words people use to try to accomplish their goals, but motivations and emotions that usually go unspoken need to inform your AI search content strategy in what is likely becoming an incredibly personalized space.

Brand vs. Non-Brand Traffic in AI Search

AI search engines and LLMs are currently excellent at synthesizing answers to broad informational queries—which means users often get what they need without clicking on a website.

Recommended Reading: Understanding AI Search Engines: Facts All SEOs Should Know

As a result, many sites have seen steep declines in traffic from non-brand informational searches. But the journey doesn’t end there. Users still need to make decisions—and in those final steps, they’re evaluating which brands are most relevant, trustworthy, and valuable.

That’s where the opportunity lies: connecting the dots between top-of-funnel informational queries and your brand’s products or services, so you’re part of the consideration set even when clicks are scarce.

A “Technical” Approach to Content for AI Search

Even with guidance from SEO teams, in my experience, most content production and evaluation retains a high level of subjectivity. With LLMs and AI search, we need to be more rigorous about making sure the content we’re putting on our pages is worth having there. 

Since each chunk of content can be measured for relevance to a topic, the more chunks on a page that are relevant to a topic and its subtopics, the more potential value that page has for the searcher and the business.

How do we Measure Content Success in AI Search

Of course we will try to use visibility in AI search as a measure of success. But assuming that, for privacy reasons, there will be huge gaps in data, we will need to look more at business outcomes and human signals.

Business outcomes should be straightforward and already in place. These look like leads, conversions, sales, revenue, etc. Some human signals may be in place, such as social shares and traffic, ratings and reviews, and other quantified subjective actions. 

Other human signals, such as brand searches and citations, may need a layer of sentiment analysis to determine the degree of success.

Chunk 3: Optimizing Technical Foundations for AI Indexing

In some ways technical SEO for generative AI search is the simplest, since it’s relatively consistent with many years of practice. Your content needs to be crawled before it can be indexed, and indexed before it can earn traffic or produce revenue.

Crawling Is As Critical for AI Search as it is for SEO

If you want to meet your business goals, you still need crawlers to spend most of their time on indexable URLs that have the potential to provide value. 

That means you need access to your server logs so you can see what the crawlers are requesting and how much. That’s a start for AI crawl analysis, but joining the server logs with your traffic, conversion and visibility data will take you much farther.

Here are some starter questions to think about when it comes to crawling for AI search:

  • What is being crawled, and what are the response codes?
  • Are the most valuable pages being crawled?
  • What isn’t being crawled? Is core content missed?
Make It Easier for AI Search Engines and LLMs to Understand Your Content

Most enterprise websites are using XML sitemaps and some may even be using RSS feeds with clever logic to get pages crawled.

But there are also ways to increase the odds that your content is easily parsed and well understood so it can be as fully and correctly indexed as possible. 

Structured schema is likely more important than ever as an indexing aid. Also use markdown to make it easier for AI systems to parse your pages.

Chunk 4: Evolving Your Reporting Strategy for GEO

We need to know what’s happening in SEO and AI search, and we need to communicate that to other parts of the organization. In this AI era, that’s no different from the past couple decades of SEO. 

The Purpose of Reporting for AI Search

Whether it’s classic SEO or GEO, reporting is about trust.

Transparent reporting builds credibility and opens the door to the resources you need—whether that’s budget, headcount, or leadership or stakeholder buy-in. Your reports should not only inform, but also advocate for the strategic importance of your work.

Use Reporting To Gain Support for Your AI Search Strategy

In an ideal world, your organization wants you to be successful so it can be successful. 

Be clear about what’s needed to help the organization better understand what’s happening in AI search and what you need to make better decisions (for example: budget or engineering support).

Find Support (It’s Out There)

You’re not navigating this shift alone—the entire search industry is learning, testing, and adapting together.

At seoClarity, we know our clients are facing the same challenges—and uncovering the same opportunities. Whether you need help interpreting AI-driven visibility shifts, aligning your strategy to GEO, or identifying the right data to act on, we’re here to support you.

It’s why we built Clarity ArcAI, the only end-to-end solution for tracking, researching, optimizing, and reporting on AI search.

Reach out to us—or connect with peers, follow thought leaders, and keep the conversation going. The more we share, the faster we all move forward.

Schedule a Demo