Despite recent market turmoil, the AI revolution continues apace as new breakthroughs in models and architectures get applied across a growing number of industries.While AI’s impact on advertising is widely debated, one area is moving so quickly—with implications so potentially far-reaching beyond its narrow format—that advertisers should start planning around it now: AI search. A potential searchpocalpypseAnecdotally, many of us rely on AI search and seek it out—even if we don’t know we’re doing it. While official numbers are spotty, independent studies suggest that over 11% of Google searches now feature AI-generated summaries. Newer AI answer engines like Perplexity—which tops 20 million queries daily for its paid enterprise product—as well as Microsoft Copilot and ChatGPT search are also gaining ground, thanks in part to timely investments in brand advertising.The consequences of this are not escaping notice. In carefully worded statements during Google’s most recent earnings call, its chief business officer touted its own AI Overviews product, noting that “AI Overviews continue to drive higher satisfaction and search usage” while delivering revenue at “approximately the same rate” as conventional search results. While Google has a massive incentive to get this right, it is likely to struggle with some near-term misses. AI and large language models are popular precisely because they get people answers and information faster than clicking around—and that probably means fewer (though potentially higher-intent) searches long term. In all, Gartner predicts that traditional search engine volume will decline 25% by 2026. There’s also an open question around the optimal ad formats and pricing models for AI search. AI-generated answers take up a lot of real estate normally occupied by ads on Google, making an update on where and how ads appear—and associated growing pains—all but inevitable.It’s worth noting that Perplexity’s ad format, a sponsored follow-up question, is more akin to native advertising, with the company charging a CPM rather than a cost per click. Microsoft is also continuing to experiment with different ad formats for Copilot with varying success. An era of inflation and less advertising surface areaIf ever there were a year to spend big at the upfronts, this is it. As users get answers faster via AI and potential cracks emerge in traditional search volume and performance, new formats, and other ad mediums may need to pick up the slack. For many direct response advertisers, display is the closest substitute to search. Unfortunately, display is also likely to get hit as fewer searches translate to less organic traffic for publishers. While some anecdotal evidence suggests that this may not be happening evenly yet as Google and others better embed source links into AI answers, ultimately a trend of fewer or materially different searches spells trouble for search-dependent aggregators and publishers that drive a lot of display volume.All of this puts renewed pressure and a premium on video, TV, and social advertising. Although video on demand CPMs are forecasted to decline slightly in 2025—partially counteracting a spike in social—this may be short-lived or change quickly. The collapse of traditional SEO is also likely to contribute to CPM inflation. Brands that rely on organic search—such as Chegg and Hubspot—are seeing their traffic decline significantly, putting a hole in go-to-market strategies that only paid media can likely fill in the short term. Over time, content marketers will need to retool to market to agents and get into LLM training data.AI-native consumer expectationsAs users grow accustomed to immediate AI answers, brand marketers face a parallel challenge of meeting these heightened expectations across every other touch point. What this looks like will vary by industry, but the opportunities are there for the taking. After spending years investing in first-party data and related infrastructure, brands can now leverage this foundation to fine tune LLMs for a variety of applications and force the integration points that matter across their stack.Ultimately, where AI lives will determine how the ecosystem evolves. Brands can control more of this future or cede it to walled gardens. A decade ago, advertising was one of the earliest industries to deploy AI at scale, as systems relying on traditional machine learning models informed everything from programmatic bidding strategy, budget forecasting, targeting, click-through rate optimization, and more. By making the right moves in an evolving space, brand marketers can once again lead the way forward in AI.