A ski trip planning session turned into a case study in how fast AI-driven discovery has taken hold, our chief content officer Vladimir Hanzlik told the audience at EMARKETER’s Future of Digital summit. Sitting around the table with friends and family, phones out on Gemini, his group booked resorts, hotels, and ski schools in a matter of hours.

"What really struck me is that if you didn't turn up in those LLM recommendations, if you didn't show up in Claude or Gemini, there'll be literally zero chance that we will pick you," Hanzlik said, opening a conversation with VML's chief discoverability officer Heather Physioc on whether brands understand just how close that future already is.

Brands are "painfully aware"

Brands are painfully aware, Physioc said, but urgency splits by category.

"Travel is a natural fit for AI search given the complexity of trip planning," she noted. The sharper shift is in B2B tech, automotive, and other categories with long sales cycles. "Decisions that used to take weeks or months are compressing into hours, and brands are only beginning to grasp what that means for their business."

From discovery to agentic commerce

AI-driven shopping splits into two phases, and only one of them has arrived. Discovery has been building for years, Physioc said, and Google itself signaled as far back as 2009 that it was building an AI, not just a search engine. Agentic commerce, where the AI doesn't just recommend but actually transacts, is a different story.

"I don't think that people are really ready to fully trust it and hand over the keys and let it make purchase decisions for you," Physioc said, though she added it's "a highly plausible future." What's already happening, she said, is a dramatic shortening of the runway between recognizing a need and reaching a short list of options, even if the final purchase still requires a human decision.

Beyond the 80/20 rule

The biggest misconception clients bring her is that a clean, prescriptive playbook exists for ranking in AI search, the way marketers once chased the number-one spot on Google. That kind of clarity doesn't exist yet, Physioc said, and what works today may not work tomorrow.

The bigger structural shift is the end of the 80/20 rule that shaped SEO for years: the idea that most marketing efforts should go toward the content serving the bulk of search volume. AI search tools are now surfacing far more personalized, niche queries, and brands need an "ecosystem of evidence" to keep up.

"It can't just be about what we're saying about ourselves. Somebody on the outside of our brand also has to validate the things that we're saying," Physioc said, pointing to the rising importance of earned media, user-generated content (UGC), and lived customer experience in filling gaps that brand-owned content doesn't cover.

The measurement problem

Pressure builds from the C-suite to show results on AI visibility, but the proof isn't there. Physioc described widespread "tool fatigue" among clients facing aggressive sales pitches from platforms claiming to track AI search performance, with many unsure which tool, if any, is worth the investment.

Forget downstream sales attribution for now, Physioc said, and focus on simply being present in the AI-generated consideration set. "You kind of can't afford not to care about what's happening in these AI search answers," she said, adding that measurement frameworks are still being rebuilt to account for how individual channels contribute to a single, synthesized AI answer.

Where to start tomorrow morning

Physioc's advice for marketers: use AI search tools like a customer, not an executive. Think through the actual problems, motivations, and follow-up questions real buyers bring to these platforms, since reliable data on search volume and prompt behavior still doesn't exist. In its place, she urged brands to run search intelligence across platforms to see how people are discovering and deciding, not just on Google but on social and retail too.

Watch the full session.

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