The Future of Google’s Revenue Depends on AI and So Does Your Brand Visibility

The Future of Google’s Revenue Depends on AI and So Does Your Brand Visibility - Maryanna Franco of BrilliantSEO

SEO Tips to rank with AI - Clicks are shifting and ROIs are more incertain than ever. How will Google leverage their income and what does it mean for companies. Here are SEO Tips to rank with AI by SEO expert Maryanna Franco, the founder of SEO agency BrilliantSEO:

1 - AI Search Is Changing Google’s Business Model. Here’s What It Means for Yours

AI Overviews are creeping into more and more queries, summarizing the answer before you even scroll. And if fewer users are clicking, what happens to the system that’s built on those clicks?

We’re already seeing ripple effects. GrowbyData reported that Amazon, usually a dominant force in Google Shopping ads, has quietly stepped back, leaving entire product categories wide open. Competitors such as Target, SHEIN, and Wayfair are all filling the space. More than just a temporary pause, this can be a sign Amazon is betting on a new kind of visibility?

Here’s the real question:

If Google’s revenue depends on clicks, and AI Overviews are killing CTRs, how does this business model survive?

And more importantly, how do we adapt before it fully flips?

2 - AI Overviews Don’t Work Like Ads (Yet)

AI Overviews, are still primarily focused on generating answers, not showing ads. While Google has begun experimenting with ad placements inside these Overviews in select regions, the core visibility of your brand still depends on how well Google understands you and not on how much you’re spending.

You can’t just bid your way into that box. Instead, AI Overviews pull from:

• Structured data (yes, your schema still matters)

• Entity recognition (make your brand a known and understood entity)

• Topical authority (claim your place by showing you are an expert

• Clear, structured content (LLMs don’t guess, they scan and summarize)

It’s still SEO, but also brand and semantics rolled into one.

3 - Ads Are Starting to Sneak In, But You Don’t Control Them

Google has begun testing ads inside AI Overviews; however, these are pulled automatically, mostly from Performance Max and Shopping campaigns you already run.

Unfortunately, as of yet, you don’t get to say: “Place this ad inside an AI Overview.” In summary, when it comes to ads inside AI Overviews:

• You can’t target those placements.

• You can’t optimize for them.

• You can’t track performance directly.

• You can’t even request inclusion.

Google decides what’s relevant, what fits the generated summary, and drops it in.

Think of it like this: AI Overviews are borrowing your existing campaigns and repackaging them. You’re in the conversation, but you’re not leading it. Again, at least not yet.

4 - The CTR Collapse Is Real (and It's Just Getting Started)

We’ve all felt it: your impressions look fine, maybe even better than usual, but your clicks are dropping hard.

According to SEMrush, AI Overviews appeared in 6.5% of queries in January. By March, that doubled to 13.1%. And as we all know, those aren’t background features but they’re at the front and center, above the ad and above the organic results.

Marketers on Reddit are reporting CTR drops of 30–40%, sometimes even higher, in categories where AI Overviews show up. One PPC manager called it “like watching your budget dissolve in real-time.”

And it makes sense. Why would someone scroll or click, when the AI already answered their question at the top of the page?

We are losing traffic and the entire real estate where that traffic used to live.

5 - But What Does Google Say?

To be fair, Google isn’t ignoring the concerns. Their official position is that AI Overviews actually drive better traffic. They argue that while quick-answer queries might lead to fewer clicks overall, the users who do click through are often more serious, curious, or intent-driven.

In their view, the AI Overview acts like a filter, handling the surface-level questions and sending the more engaged users deeper into your site. Google calls this “higher-quality traffic,” not lost opportunity.

It’s a valid point, especially for brands that rely on long-tail or high-consideration journeys. But here’s the challenge: you still have to show up, and in the right way, for that deeper click to even happen.

So while this doesn’t erase the CTR problem, it reframes it. The clicks may be fewer but possibly worth more.

6 - Google’s New Ad Game: Preparing for the AI Auction

Of course, Google isn’t just going to walk away from its cash cow. Ads will remain central, but instead of bidding for blue links or carousel slots, we’re likely heading toward a new kind of auction powered by AI context.

What we’re seeing in AI Overviews today is just the test phase. But imagine what happens when:

• The auction includes semantic relevance, not just keyword bids.

• Placement is decided by how well your brand fits the narrative the AI generates.

• Your Performance Max campaigns evolve into training material, not just ads, but data inputs into how Google understands and positions you.

It’s like someone else is repackaging your ad for a new format, and you’re not even invited to the strategy meeting.

7 - Google’s Experiments Go Deeper Than We Think

Behind the scenes, Google isn’t simply adjusting the layout of its results. It’s fundamentally reengineering how ads are matched to intent, moving beyond keywords toward a deeper, more contextual understanding of meaning:

• Their recent patents explore using user embeddings and contextual vectors to align ads with user intent, not just keywords.

• It’s part of a bigger move from literal keyword matching to semantic and intent-based ad targeting, mirroring how LLMs process language.

• Performance Max may eventually act as a training pipeline for future AI Ad placements: feed it enough signals, and Google figures out where your brand fits in generative responses.

Google isn’t just matching words anymore—it’s comparing meaning. In a vector-based model, your content, brand, and user intent are turned into mathematical representations (embeddings). The closer those vectors are in meaning, the more likely your content is surfaced. Authority, then, isn’t just links or keywords, it’s semantic relevance across multiple dimensions. Google is comparing meaning.

8 - Which brings us back to Amazon

They recently pulled back hard from Shopping ads: up to 93% less presence in some categories. In my opinion, that’s not a coincidence but a strategic pause instead. They’re watching, waiting, maybe even helping shift the auction dynamics by stepping out. And when the new AI ad formats are more stable and more measurable, they’ll step back in with a bigger budget and cheaper and smarter ads.

9 - Google is quietly retraining its auction system for an AI-first world

The rules are changing: who gets visibility, what’s considered a conversion, where the click comes from.

And if you're still optimizing for old-school SERPs, you’ll be bidding on yesterday while your competitors are showing up in tomorrow’s answers.

10 - You Can’t Buy Your Way Into AI, But You Can Train It

If you want to show up in AI Overviews, whether through ads or organic mentions, it’s not just about bidding higher. It’s about being understood.

Right now, smart marketers are already shifting their strategy by:

• Running structured Performance Max campaigns to align with Google’s new ad surfaces

• Cleaning up product feeds and reinforcing brand authority

• Making sure their content and schema clearly define who they are and what they offer

• Merging SEO and PPC efforts instead of running them in silos

But here’s the deeper shift: AI Overviews and LLMs don’t just summarize search, they synthesize brand knowledge.

ChatGPT, Gemini, Perplexity and other LLMs don’t pull random links. They pull from what they’ve learned about you over time: they build an understanding of your brand through patterns, signals, and consistency across the web. That means visibility tomorrow depends on how well you're training the machines today.

A few key factors influence how you’re interpreted:

• Schema types like Organization, Product, FAQ, and Author give structured signals about what you offer and who’s behind it. The clearer and more complete, the easier you are to “understand.”

• Named entity disambiguation matters. If your brand is called “Swift,” Google needs to know you’re not a Taylor Swift fan blog or a software framework. Clear, unique context in your content and metadata helps.

• Consistent mentions across platforms like LinkedIn, Crunchbase, industry directories, podcasts, and the press. Create strong, verifiable signals that reinforce your brand as a known entity.

The better the model understands you, the more likely you are to appear in AI-generated answers, not because you paid for it, but because you made it easy to be included.

11 - What Does It Cost to Train the AI?

Here’s the part we don’t talk about enough: training AI systems to understand your brand isn’t free. It takes time, strategy, and consistent execution.

Structured data, content clarity, third-party validation, internal consistency: these all require effort. And not just from your SEO team. This is cross-functional: brand, content, dev, and PR all have to align.

Compare that to the old model: throw budget at keywords and outbid your competitors. Less complex, but often less sustainable.

The real shift here is in how marketing budgets are spent:

• Less on pure media (PPC)

• More on long-term content assets, technical SEO, and brand architecture

That doesn’t mean one replaces the other, but it does mean your spend now builds equity in how machines perceive you. And that equity is what gets you shown, quoted, or ranked inside AI-driven results.

So yes, it costs more up front (just like traditional SEO did). But you’re not just buying clicks anymore. You’re building visibility that scales with how LLMs think.

12 - The Revenue Model Is Shifting And So Should You

Google’s business model has always been built on clicks and getting paid whether through SERP ads or AdSense.

As AI Overviews take over the top of the page and start answering questions before users scroll, we’re watching the traditional search landscape dissolve in real time. And while Google experiments with ways to inject ads into these new formats, one thing is clear: we need to rethink how we earn visibility.

You can’t rely on PPC alone. You can’t expect a higher bid to fix invisibility. And you definitely can’t afford to wait until AI Overviews are the default because by then, the brands that matter will already be trained into the system.

Now is the time to adapt:

• To new ad formats

• A strategy based on brand visibility

• The idea that “meaning” will be everything

The next evolution of Google Search will reward structure, clarity, consistency, and entity recognition, with and without pay-per-click.

13 - And While Google Experiments, Others Are Moving Faster

It’s not just Google racing to reinvent search. Perplexity, ChatGPT (via plugins and browsing mode), and other platforms are already letting brands integrate more directly.

You can feed them structured sources, submit verified content, and in some cases, create your own plugin that acts as a branded knowledge layer.

That means if you're only focusing on Google, you might be missing opportunities to shape how you're understood across other AI-driven discovery platforms. Visibility in the AI era is about integration.

14 - Conclusion: The Architecture of Modern Visibility

Visibility in the AI era is built through alignment between paid media, structured content, technical precision, and brand strategy. PPC still plays a role, but it works best when it reinforces a brand identity that machines can recognize and trust. The brands that lead in this new reality will be those that invest in clarity, not just clicks, and approach visibility as a system to train, not just a space to buy.

Author:  Maryanna Franco - Founder of  SEO agency BrilliantSEO