Google VP: SEO and AI Search Have “A Lot of Overlap”

The Ad Firm | November 2025

Google has confirmed what many in digital marketing have already recognized — the fundamentals of SEO marketing remain vital, even as search evolves under AI.

In a recent interview with Marina Mogilko (Silicon Valley Girl), Robby Stein, Google’s Vice President of Product for Search, explained that AI and traditional optimization now work hand in hand.

“AI thinks a lot like a person would,” Stein noted, describing how Google’s new AI Mode uses its own search engine “under the hood” to gather and evaluate credible sources.

According to Stein, businesses that want visibility in AI-driven results must still follow the same principles that guide strong SEO — helpful content, clarity, and trustworthiness — but now within a system that weighs context, reputation, and reasoning more heavily.

PR for AI: Reputation as a Ranking Asset

Stein compared this new dynamic to a form of “PR for AI.” He agreed with Mogilko’s observation that companies are now “investing in PR not for people to see it, but for AI.”

“If you’re a business and you’re mentioned in top business lists or from a public article that lots of people end up finding, those kinds of things become useful for the AI to find,” Stein said.

In practice, that means online reputation has become a measurable signal. Mentions in respected publications, credible directories, and widely read articles now feed into how Google’s AI understands and ranks brands. These external references help confirm that a brand is not only visible but validated by the broader web as part of search infrastructure.

In other words, the companies that manage reputation as a quantifiable asset will be the ones most visible in AI-driven search.

The Evolving Role of SEO in AI-Driven Search

Stein clarified that AI Mode doesn’t replace Google Search — it extends it. The AI performs internal searches, analyzes top-ranking pages, and blends reliable information into summarized answers.

“And so in the same way that you would optimize your website and think about how do I make helpful, clear information for people… think of an AI doing that search now,” Stein said.
“When it renders a response and provides all of these links for you to go deeper, that website’s more likely to show up. A lot of those standard best practices around building great content really do apply in the AI age.”

Asked whether AI optimization — often called GEO or AEO — is essentially the same as SEO, Stein replied:

“There’s a lot of overlap. Maybe one added nuance is that the kinds of questions people ask AI are increasingly complicated and tend to be in different spaces… a lot of how-to for complicated things or purchase decisions or advice about life things.”

He encouraged marketers to study these emerging use cases and the kinds of queries growing within them. He also highlighted Google Trends, Ads, and Search Console as underused tools for mapping how AI-influenced searches are becoming more conversational and detailed.

“Google Trends is a really useful thing,” he said. “I actually think people really underutilize that.”

Where SEO and AI Search Overlap

To better understand Stein’s comments, The Ad Firm analyzed key areas where traditional SEO and AI Search (GEO) share common ground.

1. Original, Expert, and Up-to-Date Content

Both Google Search and AI Search rely on the same foundation: expert, trustworthy, and current information.

In traditional SEO, Google’s algorithms reward content that shows experience, authority, and accuracy — especially when it’s regularly updated. High-quality, fresh information performs better in search results, particularly for topics that change over time.

AI Search works the same way. Models are more likely to use and reference content that demonstrates expertise and is recently updated. When information is current and verified through Google’s index or other live data, it becomes more visible in AI-generated summaries and recommendations.

2. Structured Data

Schema markup continues to help Google and Bing understand page meaning, authorship, and relationships. Even when AI models don’t read schema directly, the same structured signals improve how indexed data is organized—supporting both search listings and AI references.

3. Authority and Credibility

Reputation signals continue to matter. Backlinks, brand mentions, and citations from reputable publications build the same type of authority that both Google’s algorithms and AI systems rely on when selecting reliable sources.

4. Multimedia Optimization

Images and videos strengthen visibility in both search and AI results. Optimized filenames, captions, and metadata help search engines understand context and allow AI systems to reference those assets when generating responses.

5. E-E-A-T Principles

Experience, Expertise, Authoritativeness, and Trustworthiness continue to define quality.
Both traditional algorithms and AI models favor information that demonstrates genuine subject knowledge and transparent sourcing.

6. Relevance and Context

Search still begins with meaning, not just keywords. In the past, users might have typed “best coffee maker” and scrolled through ten blue links. Now, Google asks a series of follow-up questions behind the scenes — like “best coffee maker for small kitchens” or “top drip machines under $200” — but it still relies on the same well-written pages to build its answer.

If your content clearly explains those details, you’ll appear in both the search list and the AI overview.

AI Mode doesn’t replace SEO — it depends on it. Google’s systems still draw from the same foundation of well-structured, credible, and expertly written content. Brands that invest in these fundamentals will remain visible across both search results and AI-generated answers.

As a digital marketing agency, The Ad Firm will continue to explore how AI-driven search evolves — testing, measuring, and adapting strategies to ensure our clients stay ahead of every shift in how Google delivers information.