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Key Takeaways:
As adoption of AI search tools rises, the open web is feeling a little less, well, open.
ChatGPT reached 1 billion global monthly active app users in May, just three years after its launch. Perplexity counts 45 million. Google’s AI Mode crossed 1 billion monthly active users just a year after it was introduced, and its AI Overviews are now surfaced on 40% of all US Google searches.
As consumers increasingly use these tools to search and research, they’re spending less time on the open web. Already, searchers are staying in AI Mode between one and nine minutes longer than on a traditional Google search. And a 2025 Growth Memo study found that in about 75% of sessions, users never ventured out of AI Mode at all. The effect on open web traffic has been significant: One study of 218 websites across 12 industries found that organic search has lost close to a quarter of its traffic volume since the start of 2023.
This shift in consumer behavior has significant implications for advertisers, who have spent years building strategies around how consumers move from site to site, and channel to channel. As more of the customer journey takes place within AI environments, the cookie trail advertisers once relied on to track them is thinning out, and audiences are scattering across a growing set of walled gardens. The result is a more fragmented, complex environment that will force marketing teams to rethink how they reach and influence target audiences.
AI search will intensify fragmentation and complexity both in terms of tracking the customer journey and in managing campaigns across channels and platforms.
Consider a consumer who has a conversation in AI Mode that surfaces a particular brand. That interaction is essentially invisible to the advertiser—there’s no click or site visit to signal that it happened at all. The first sign of the consumer may be the purchase itself, leaving the brand with no way to trace what shaped their decision. This is a major shift for marketing teams accustomed to using cookies to follow consumers across the open web. And while Google may come out with features that allow advertisers to track consumers within AI Mode and AI Overviews, as of right now, those capabilities don’t exist.
Evolving consumer behavior is also likely to result in additional fragmentation, spread across an array of walled gardens—from other AI search tools like ChatGPT and Gemini, to social platforms like TikTok, Instagram, YouTube, and Reddit, all of which are rolling out similar AI features (Meta, for instance, recently launched their new AI assistant). This means marketing teams must confront a familiar problem—the media fragmentation that’s been making advertising work increasingly difficult, with over a third of full-service and media agencies already using 10 or more tools across their workflows—at an even greater scale.
Advertisers who want to stay competitive will need to adapt their strategies accordingly, trading the tactics built for a trackable open web for ones designed to reach and measure audiences across a scattered digital landscape.
In order to succeed as AI search changes the customer journey, brands will need to prioritize three things:
Let’s take a quick look at each of them:
Today, media diversification helps advertisers reach audiences across the growing number of channels and platforms where they spend time. This diversification will only grow more important as AI search changes the customer journey. As people shift away from the open web and into AI environments and other walled gardens, the path to purchase will become more fragmented and less observable. A diversified media mix will help teams capture more audience signals and stay present wherever consumers choose to discover, research, and make decisions.
Programmatic channels like video and CTV are well-suited for that diversification, particularly when advertisers layer on premium content and private marketplaces (PMPs) to keep honing in on target audiences.
Of course, spreading spend across more platforms compounds an operational problem that already plagues marketing teams: tech stack sprawl and disconnected systems. One study found that 40% of agencies cite siloed systems as a top challenge, second only to the inefficient processes those disconnected tools create. Finding ways to unify advertising workflows across channels will be key to meeting this moment, bringing scattered channels into a single view so teams can diversify without losing the holistic perspective they need to plan, buy, and measure effectively.
AI is likely going to exacerbate a model where consumers are only in market for a very small amount of time. The hours they once spent researching on the open web will compress as AI tools compile that research for them, which means that the touchpoints where advertisers can reach consumers mid-research will grow scarcer.
AI gives consumers the CliffsNotes, so brands will want to amp up the awareness and salience they’re driving outside of AI environments to stay top of mind for the moment a consumer does enter the market. Inside those environments, generative engine optimization (GEO) (also known as answer engine optimization or AEO) will be just as important, helping brands show up the way they intend when AI tools compile their summaries. Together, these efforts can help build the kind of familiarity that tips a brand into the consideration set when it comes time to decide.
At the same time, advertisers will need to expand their measurement approaches to get a more holistic view of performance. As more of the customer journey moves inside AI environments, the breadcrumbs (i.e., third-party cookies) advertisers once relied on to track them won’t exist in the same way. That could change if Google rolls out tracking within AI Overviews and AI Mode, or if OpenAI does the same for ChatGPT, but given the tools at hand, advertisers will need to lean more into sophisticated measurement tools to prove out success.
Layering on consideration metrics, incrementality studies, and modern modeling approaches like MMM and scenario planning will help advertisers capture a more complete picture of how the growing number of platforms and channels that influence their audience work together to drive impact.
Resetting expectations will also be key, as attribution won’t be as immediate as brands are used to. Teams accustomed to putting a dollar in and getting three dollars out almost instantly on platforms like Facebook and Instagram will find that pace is no longer the norm as advertising influence plays out over longer, less visible timelines. Proving the value of that spend will depend less on instant, click-based returns and more on measurement built to capture impact across the entire journey.
As AI changes how people discover, research, and make purchase decisions, it will change how advertisers approach their work just as fundamentally. Teams will need to adapt to more fragmentation and complexity, while simultaneously dealing with less visibility into their audience’s buyer journey.
In this new era, brands who diversify their media spend, lean into brand building, and evolve how they measure success will be better positioned to reach and influence audiences wherever they spend their time. And the sooner teams begin to adapt, the more they’ll be able to keep pace as AI continues to influence the customer journey.
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Looking to learn more about how AI is changing advertising work? We interviewed marketers across leading agencies and brands to find out how they’re using the technology, how it’s changing jobs and teams, how they see it transforming the industry in the coming years, and more. Download AI and the Future of Marketing for all our top takeaways.