It seems like everyone in marketing is talking about AI search, and for good reason—AI search engines and AI overviews are reshaping the way that we browse the web, with more users turning to these as sources of information, and fewer than ever actually visiting websites.
With this shift now well underway, most digital marketers feel an urgent need to measure and maximize the value of AI traffic. But before you can effectively measure the impacts of AI search, you need to take a few key steps to lay out the groundwork for success. In this article, I’ll lay out 3 steps to help digital marketers and others adapt to these changes.
1. Clearly Define Your AI Search Goals
According to some estimates, as much as 50% of Google search queries now generate an AI overview, while just 1% of searchers actually click on the links that are cited in an AI summary, according to Pew.
When you consider the added impact of AI search engines, which make it hard to access the webpages that LLM platforms pages extrapolate from or summarize, you start to see how and why this is a fundamental shift for digital marketing, rather than a short-term flash in the pan.
These changes put pressure on marketers to take action to maximize and measure the impact of AI mentions and queries, but it’s important not to act hastily, out of a sense of FUD. Instead of making an impulse decision, think critically about the value of an AI click, with the understanding that its value is different (though not necessarily lesser) than the value of a visit to your website.
Once you understand what AI search means for your business, you’re ready to develop a strategy and accurately interpret the value of an AI citation. Without that context, you’ll be lost before you even get started.
2. Double Down on Gated Content and Original Research
AI search is leading to a massive decline in website sessions—that much is clear. But, at the same time, it’s important to note that some webpages are seeing an uptick in visitors, or at least are not experiencing the decline that other pages are seeing.
Landing pages for valuable gated content, for example, are generally not being hit by the drastic decline in website sessions that have hit other web pages on most corporate sites.
This means that marketers and others can still get users to visit their site when they offer compelling gated research that’s actually worth clicking on and downloading. In some niches, like B2B, data is often an effective tool for this, particularly original research. At AvePoint, for example, we focus on delivering content and original research (like our recent 2025 AI study) that features original, objective, brand-agnostic research.
In short: the days of the form-fill are far from over! You can still get users to click past the AI citation or overview by offering valuable information that an LLM search result can’t summarize, surface, or query.
3. Don’t Abandon Traditional SEO
While the shift to AI search is a profound change, the sudden rise of AI search has led some to conclude that traditional search is dead—and that just isn’t the case.
AI search is a fundamental shift, but many of the tactics that powered SEO success before AI—careful keyword research, strong technical SEO, thoughtful on-page optimization, and so on—are still relevant for AI search.
As a result, it’s important to keep in touch with the pillars of AI success. Retain your SEO experts and continue to rely on their expertise. Just remember that the context around search (and the business logic that ties into it) has changed.
Move Strategically, But Don’t Reinvent the Wheel
At the end of the day, AI search signals a radical but exciting shift for marketers, and really anyone who has a website. Instead of immediately scrambling to quantify the impact of your AI presence, it’s important to first define what an AI citation means to your business, and to create a strategy around that contextualized knowledge.
The way we browsed the web has changed, but that doesn’t mean you have to reinvent the wheel. With proper preparation and strategy, you can get close to AI success.
