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Google’s AI Search Expert: How to Get Ahead Before AI Changes Everything

What makes AI recommend one business - and ignore another? In this interview, Robby Stein, VP of Product for Google Search, breaks down how AI now decides what gets discovered, ranked, and recommended — and what founders, creators, and…

Marina MogilkohostRobby Steinguest
Oct 29, 202528mWatch on YouTube ↗

Summaries, chapters, transcripts, and FAQs on this page are made by uListen, not YouTube.

At a glance

WHAT IT’S REALLY ABOUT

Inside Google AI Search: ranking, agents, ads, and visibility strategies

  1. Google Search is evolving from keyword queries to natural-language, multimodal, AI-assisted experiences that “fan out” into many sub-queries and synthesize results using Google’s web index plus internal knowledge systems (local, shopping, finance).
  2. New AI Mode capabilities include richer local recommendations, research-and-book flows (e.g., restaurant reservations), and agentic actions like calling offline businesses to gather availability and prices—without recording calls.
  3. For businesses, visibility in AI recommendations still tracks classic SEO fundamentals, but PR/third-party mentions and well-maintained Google Business Profiles increasingly matter because AI systems look for reliable signals across the web.
  4. Ads aren’t expected to disappear; Google is experimenting with ad formats inside AI experiences, but the stated priority is building high-quality consumer utility first—especially for complex purchase and decision journeys.

IDEAS WORTH REMEMBERING

5 ideas

AI Mode ranks by decomposing your question into many searches.

Stein describes a “query fan-out” where a reasoning model issues dozens of related queries, pulls web results plus Google knowledge systems, then composes recommendations based on intent cues (e.g., “date night,” allergies, group size).

Local AI recommendations don’t use your ad spend as an input.

He states AI Mode doesn’t use ads information to decide recommendations; instead it uses web content and Google’s information systems, including claimed/updated business listings, menus, and reviews.

Agentic features shift Google from answers to actions.

Demos show Google researching across services (e.g., OpenTable/Resy) to present bookable times, and making real phone calls to local groomers to return prices/availability—useful for “offline” businesses without easy web flows.

PR becomes a core AI-discovery lever, not just a human one.

Because the model “Googles under the hood,” third-party articles, “top lists,” and widely discovered mentions can act as credibility signals the AI can retrieve and use when recommending “reliable businesses.”

Traditional SEO best practices still apply—now for an AI reader.

Stein emphasizes helpful, clear, reliable content remains foundational; the twist is optimizing for longer, more specific natural-language queries and multimodal prompts that AI users increasingly ask.

WORDS WORTH SAVING

5 quotes

AI Mode works is that it does something called the query fan-out technique.

— Robby Stein

So it doesn't use ads information. This is done entirely with… what's on the web and what's within Google's… information system.

— Robby Stein

Those are… not recorded.

— Robby Stein

Now you're investing in PR not for people to see it, but for AI entities to see it.

— Marina Mogilko

In the next era, lots of people will be able to build it, and so you really have to build something useful to people.

— Robby Stein

Read the available transcript
AI Mode “query fan-out” and reasoningPersonalization (opt-in) and future Gmail/Drive integrationLocal recommendations and booking workflowsAgentic phone calls to offline businessesAds in AI experiences and new ad formatsShopping Graph scale and multimodal product searchBusiness visibility: SEO + PR + reviews signalsProduct-building in 2025: finding gaps, user interviews, stickiness

High quality AI-generated summary created from speaker-labeled transcript.

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