How Quickly Does AI Really Move? And Is It Really Too Fast for Effective GEO Strategy?

Every few weeks, a new AI model or feature lands, making you wonder whether it’s worth building a generative engine optimization (GEO) strategy at all. If the ground keeps shifting, why pour effort into a plan that might be obsolete by Friday?

It’s a fair question, and plenty of marketers are asking it. We surveyed 142 professionals for our white paper on how marketers are handling GEO, and some said their biggest concern about generative search is how quickly it keeps changing.

Those worries, however, don’t represent the majority view. Among the 105 respondents who see GEO and SEO as having both similarities and differences, the largest group (35%) named the knowledge and skills gap as their top concern, while rapid change ranked last at 16%. So, for most marketers surveyed, the biggest obstacle is not knowing where to start. Which is good news, because you can close a knowledge gap. 

What are marketers actually saying about rapid change, and does the evidence back them up? Partly. Here’s a breakdown.

What Marketers Are Saying About the Pace of Change

When we asked about the biggest concerns with generative search, knowledge and skills gaps came first, measurement and attribution second, and rapid change appeared in the mix, with some rather blunt answers.

One respondent put it this way: “It’s changing too quickly to have any actual impact. The strategy I have today is not going to be relevant a week from now.”

Another pointed at the demands of keeping things current: “Rapid evolution of LLM changes means constantly revising measurement frameworks and content strategies.”

And a third tied pace to the problem of interpreting data, noting concerns with the fast-changing landscape and approaches: “It’s difficult to separate internal factors from external factors when there are data peaks and valleys.”

These are fair complaints. Nobody enjoys building a plan on ground that feels like it’s tilting. But even though you can’t slow the changes, you can build a plan that doesn’t depend on them.

How Fast Is AI Changing?

AI is changing fast in some places, and slow in others. The trick is knowing which is which.

What moves quickly:

• New model versions and features from major AI companies arrive regularly, and the names change before most of us have memorized the last ones.
• Third-party AI visibility tools add features, tweak their methods and sometimes disagree with each other. 
• Platforms themselves shift. ChatGPT Search launched on Halloween 2024, and Google has been rolling out AI Overviews and AI Mode ever since.
• Answers vary from run to run. Ask a large language model (LLM) the same question 5 times, and you may get 5 different answers, because these models pick from a range of likely words rather than one fixed result.

What barely moves:

• Search systems, whether classic engines or AI providers’ own, that still have to find, crawl and understand your content.
• Models that still lean on sources that look credible and well documented.
• Readers who still reward pages that answer their question.
• Brands with a long, well-covered history online, which still get recognized more reliably.

Our CTO, Stewart Snow, has spent a lot of time busting AI myths and digging into how large LLMs work. His take: “A huge portion of GEO is really SEO ranking.” AI tools have to search somewhere, so they borrow from proven search playbooks instead of reinventing them. 

So does the evidence back the worry? Partly. The surface is constantly shifting: New models, features, platforms and tools keep arriving. But underneath, the foundation is surprisingly steady: Search, credible sources and useful content all still matter. 

Brands with a strong body of content still have something to build on.

The Knowledge Cutoff Problem Is Real — and Workable

This is the one place the “too fast” argument has real teeth. Every model is trained on a large body of data, including information off the internet. That training data has a cutoff point. After that, its built-in knowledge doesn’t include newer information. 

For marketers, that’s a genuine weakness. Launch a new product after a model’s cutoff date, and the model’s built-in memory has never heard of it.

Three things keep this from being a dead end:

• 1. Models get replaced: Each new release comes with a new cutoff date, and your recent work may become part of what it learned.
• 2. Many models can search the web: Depending on the query, a live search can pull your new page into the answer even if the model’s built-in knowledge doesn’t include it.
• 3. Your response is the same either way: Whether you’re waiting on a model update or hoping to surface through search, the move is to build the signals those systems pick up on.

That last point is where the work is. If a cutoff date is holding you back, prepare for the next update:

• Invest in digital PR.
• Earn mentions and backlinks from credible sites.
• Keep your off-site profiles accurate. 
• Publish content that experts want to cite. 

Waiting doesn’t help. Newer brands get guessed at, sometimes incorrectly, because there isn’t enough reference material about them. You fix that by creating the reference material.

SEO Has Been Here Before

Marketers have lived through rapid change before: Panda arrived in 2011, Penguin followed in 2012 and Hummingbird entered the scene in 2013. Later came mobile-first indexing, the Helpful Content Update and a steady run of core updates that sent rankings swinging. Updates like these triggered a familiar reaction — fear of penalties and SERP changes, and a rush to rewrite everything.

Some of those fears were earned. Shortcuts got punished.

What didn’t get punished was the work underneath. Pages built by people who knew their subject, written for the reader and backed by a trustworthy site kept holding up. Google’s quality guidelines have spelled out that idea for years, and today it’s been dubbed E-E-A-T (experience, expertise, authoritativeness and trustworthiness).

Side by side, they look like this:

Pay attention to the bottom row: What survives is the same for both SEO and GEO.

One reason GEO feels scarier is that the measurement is more difficult. In SEO, you can usually see what happened. With AI search, only about a third of our respondents (33%) say whether AI search has changed their organic traffic. When you can’t see the results, every change looks like a threat. 

What Marketers Are Doing Right Now

Nobody can tell you which tactic is the single best one. But we can show where the marketers we surveyed are focusing their efforts:

• 47.18%: Structured data and schema updates.
• 46.48%: Authoritative long-form content.
• 44.37%: Optimizing for conversational queries.
• About two-thirds: Adjusting content priorities in response to AI search, mostly by focusing on expertise within their own organization.

What’s on that list is familiar:

• Schema helps search engines access and understand your pages. 
• Long-form, expert-led content gives AI systems something worth citing. 
• Conversational optimization matches how people phrase questions. 

Another telling number — all 13 respondents who said they were “very familiar” with GEO made some changes to their SEO strategy. But there’s a clear gap between those already acting and those still waiting:

• 28.17%: Plan to change their strategy but haven’t done so yet.
• 7.75%: Haven’t changed their strategy at all.
• 7.75%: Have attended in-house GEO training.
• 55.6%: Don’t have a dedicated GEO budget.

Build a Plan That Can Survive Any Update

If next week’s announcement could wreck your strategy, it’s too narrow. Build one that can stand up to the changes.

• Build on E-E-A-T principles: Show real experience and expertise. Put named experts on your pages and interview them for fresh insights.
• Make helpful content the standard: Answer the question your audience is asking, then answer the follow-up.
• Fix the technical basics: Keep your content crawlable, put key information in plain text rather than JavaScript and use clean schema for search engines’ AI tools to draw on.
• Invest in off-site presence: Digital PR, directory listings, reviews and social signals all give AI systems reasons to trust you.
• Measure what ties to business results: Track AI-assisted conversions through your own analytics and CRM, not just third-party visibility scores. 
• Treat tool data as a pulse check: Third-party AI visibility numbers are estimates, so use them for direction — don’t build your budget on them.

You don’t need to rebuild your strategy every time a model or platform changes. Keep the fundamentals in place and adjust your tactics as the technology evolves.

AI Moves Fast. Build on What Doesn’t

Is AI changing quickly? Yes. But is it changing too quickly for you to do anything about it? No.

It’s understandable to worry that your strategy won’t matter in a week. But the work that earns visibility — helpful content, demonstrated expertise and a strong on-site and off-site presence — has held up through every major search shift so far. It’s also the best bet for showing up in AI answers.

The biggest risk is getting left behind because of a “wait and see” attitude while competitors build authority first. So, stop waiting for the pace to slow and things to settle. Start with the fundamentals and adjust the rest.