How SEO Agencies Are Adapting to AI Search | RiseOpp

Full Transcript: Top 27 SEO Agencies in San Francisco

Search agency selection is changing as businesses look for partners that can handle both traditional SEO and AI-powered discovery.

This episode breaks down how SEO Agencies in San Francisco are evaluated across technical expertise, client satisfaction, Generative Engine Optimization, scalability, and strategic leadership.

Founders, marketers, SEO professionals, and growth leaders will learn how to compare agency partners based on long-term visibility, execution quality, and readiness for the future of search.

👉 Read the full guide:

https://riseopp.com/blog/top-seo-agencies-in-san-francisco

Transcript

SPEAKER_01 0:00

Welcome to today's deep dive. We are taking a look at a massive source today, the 2025 Growth Guide on San Francisco's top 27 SEO agencies.

SPEAKER_00 0:09

Yeah, it's uh there is a lot to unpack in this one.

SPEAKER_01 0:11

There really is. And you know, we all know traditional search is rapidly evolving, right? Like we are moving away from this idea of optimizing for a digital index, like a digital phone book. And instead, we're trying to hand our business card to um a conversational concierge, basically.

SPEAKER_00 0:26

A conversational concierge, yeah. I like that analogy.

SPEAKER_01 0:28

Right. So we're gonna figure out exactly how you get that AI concierge to actually recommend your brand to people.

SPEAKER_00 0:34

Because the urgency here is I mean, it's very real right now. Looking at the Siege Media study in our stack, AI search-driven traffic is now averaging uh 63.42% engagement.

SPEAKER_01 0:45

Oh wow, 63%.

SPEAKER_00 0:47

Yeah, it just officially edged out traditional organic search, which is sitting at, you know, 61.64%. The shift has already happened.

SPEAKER_01 0:54

So the machine brain is officially driving the majority of engagement now. So if we are no longer just like matching keywords on a page, how are these top agencies actually mechanically adapting to reach these LLMs?

SPEAKER_00 1:07

Aaron Powell Well, they are optimizing for generative engine optimization or GEO and answer engine optimization, AEO.

SPEAKER_01 1:13

Okay, GEO and AEO.

SPEAKER_00 1:15

Right. Instead of trying to just rank a page, the whole goal is to become a cited entity within an AI's generated response, like JAT GPT or Gemini.

SPEAKER_01 1:24

Got it.

SPEAKER_00 1:24

For example, the guide highlights intero digital and they use this patented predictive crawler that they call intero BOT.

SPEAKER_01 1:31

Intero BOT.

SPEAKER_00 1:32

Yeah. And instead of just scraping a site for keyword density, this bot actually simulates how an LLM crawls a page.

SPEAKER_01 1:38

Oh, that's smart.

SPEAKER_00 1:39

It maps the semantic relationships between concepts to predict what a model will actually value as a source.

SPEAKER_01 1:45

Okay. And the guide also mentions rank science using um an experimentation first framework. I assume that works similarly.

SPEAKER_00 1:51

I doubt, yeah.

SPEAKER_01 1:52

Like they are essentially A B testing different content structures against the AI models to see which, I don't know, specific phrasing or entities the AI prefers to synthesize.

SPEAKER_00 2:00

That is basically the core mechanism, yeah. They constantly probe the LLMs to reverse engineer how the model weights different data points before it generates an answer.

SPEAKER_01 2:10

But wait, I have a quick pushback here.

SPEAKER_00 2:12

Sure. Go for it.

SPEAKER_01 2:13

If everyone is just using bots to predict what other bots want to read and then structuring their content purely to appease that algorithm, aren't we just creating a massive feedback loop of like AI garbage? Where are the actual humans in this equation?

SPEAKER_00 2:28

I know, it sounds like a totally dystopian loop.

SPEAKER_01 2:30

It really does.

SPEAKER_00 2:31

But the architecture of modern LLMs actually prevents it. These models are specifically weighted to prioritize what is called information game.

SPEAKER_01 2:39

Information gain.

SPEAKER_00 2:40

Yeah, meaning they are programmed to look for net new data, original research, and you know, truly authoritative viewpoints.

SPEAKER_01 2:47

Oh, okay.

SPEAKER_00 2:48

You just can't fake that with AI generated fluff. So the agency is winning right now, they use a hybrid model.

SPEAKER_01 2:53

So humans are still involved.

SPEAKER_00 2:55

Very much so. They use AI for drafting efficiency and structure, but they apply strict human editorial oversight to inject real-world expertise. If your content lacks human-level value, the AI concierge simply won't cite you.

SPEAKER_01 3:10

So treating SEO as just like a technical IT test today is like building a massive library but forgetting to write any books.

SPEAKER_00 3:18

Aaron Powell That is exactly it.

SPEAKER_01 3:19

The AI doesn't care about your intricate shelving system, it only cares about the actual knowledge inside.

SPEAKER_00 3:24

Which completely shifts who handles SEO within a company. Because AI demands that kind of original data and thought leadership, you have to extract that knowledge directly from the CEO or the founders.

SPEAKER_01 3:36

Right. It's not just the tech team anymore.

SPEAKER_00 3:37

Exactly. You have to align it with sales and build a comprehensive brand strategy around it. That is why the most successful agencies are now operating at the executive level as fractional CMOs.

SPEAKER_01 3:47

Yeah, the guide points to Rise Op as a gold standard for this in San Francisco. Because they aren't just scaling keyword coverage across 100,000 terms, they are stepping in as a fractional chief marketing officer to drive overarching demand generation.

SPEAKER_00 4:02

Yeah. And Apollo is another prime example of the sources. They act as a virtual CMO specifically for IT and Sauce firms.

SPEAKER_01 4:09

Making that direct business connection.

SPEAKER_00 4:11

Right. They aren't just reporting on search volume. They were tying SEO initiatives directly to the revenue pipeline. They basically bridge the gap between technical AI optimization and actual boardroom strategy.

SPEAKER_01 4:23

It just shows that surviving this transition requires a completely different operational structure. You need the technical mastery to map semantic relationships for a bot, but you have to pair that with the high-level business strategy to actually produce the thought leadership that the bot craves.

SPEAKER_00 4:40

So for you listening, take a hard look at your own digital footprint. You have to ask: are you structuring your knowledge to be found by a standard search bar? Or are you structuring it to be understood and synthesized by a conversational AI assistant?

SPEAKER_01 4:54

That is the crucial question right now. And it leaves you with a pretty wild thought to ponder as we wrap up this deep dive.

SPEAKER_00 4:59

What was that?

SPEAKER_01 5:00

Well, if these generative engines eventually just give users the perfect synthesized answer right there on the screen without ever providing a clickable link to the source, what will website traffic even mean in the future?