AI Search Isn’t Replacing Google, It’s Layering on Top, Similarweb Data

Rand Fishkin, the co founder and CEO of SparkToro, posted on LinkedIn on July 24, 2026, to say that Similarweb's newest report would "probably infuriate" two groups at once. The AI zealots who are certain every marketing dollar should already be chasing chatbot visibility.

And the AI skeptics who've suspected the hype was overblown but never had the receipts to prove it to a boss suffering from what Rand calls AI derangement syndrome. Most industry reports comfort one camp and annoy the other.

The Number That Should Worry The AI Zealots

Similarweb tracked audience overlap between ChatGPT and Google between March and May 2026, and 461 million of ChatGPT's 494 million users (95%) also use Google in the same window. Almost nobody has left Google for ChatGPT. They've added. The measurement question is whether this signal changes a decision, not whether it adds another number to a dashboard. Useful reporting connects visibility, engagement, and business outcomes without pretending every AI influenced journey will produce a clean click path. The same pattern also shows up in New Clovion Data, where the practical question is how the signal becomes visible.

The reporting question is whether this signal changes a decision. If it only creates another number in a dashboard, it adds noise. If it helps separate profile activity, website visits, calls, bookings, and direction requests, it can make local performance easier to understand.

The Number That Should Worry The AI Skeptics

Now for the half of the report that punctures the other side's confidence. Average monthly web visits across generative AI platforms hit 9.5 billion between June 2025 and May 2026, up 70% year over year. App downloads worldwide climbed to. The measurement question is whether this signal changes a decision, not whether it adds another number to a dashboard. Useful reporting connects visibility, engagement, and business outcomes without pretending every AI influenced journey will produce a clean click path.

Why The Disconnect Between Citations And Clicks Matters More Than Either Camp Realizes

The most useful chart in the whole deck, and the one I think gets underappreciated in the LinkedIn debate, comes from Aleyda Solis of Orainti. She points out that 65% of the URLs ChatGPT cites sit two or three folders deep, the pages. The measurement question is whether this signal changes a decision, not whether it adds another number to a dashboard. Useful reporting connects visibility, engagement, and business outcomes without pretending every AI influenced journey will produce a clean click path.

3 Things To Change In Your Strategy This Week

1. Split your reporting into two separate metrics. Track citation rate and citation folder depth as one key performance indicator that measures whether AI trusts your content enough to use it as evidence. Track referral landing pages and. The practical read is that brand signals need to be consistent enough for both people and AI systems to form a stable view of the company, its expertise, and its trust signals.

The Bottom Line

I don't think the AI zealots are wrong that something structural is shifting. Nine and a half billion monthly visits and a fivefold jump in citation rates in under a year are not a rounding error. But I also don't think the skeptics are. The practical read is that brand signals need to be consistent enough for both people and AI systems to form a stable view of the company, its expertise, and its trust signals.

The Number That Should Worry The AI Zealots in practice

Introduction Rand Fishkin, the co founder and CEO of SparkToro, posted on LinkedIn on July 24, 2026, to say that Similarweb's newest report would "probably infuriate" two groups at once. The AI zealots who are certain every marketing. The practical read is that brand signals need to be consistent enough for both people and AI systems to form a stable view of the company, its expertise, and its trust signals.

What the visibility signal actually changes

What the visibility signal actually changes: aI Search Isn’t Replacing Google, It’s Layering on Top, Similarweb Data: the Strategic Visibility Angle should be treated as a visibility signal, not a standalone headline. Introduction Rand Fishkin, the co founder and CEO of SparkToro, posted on LinkedIn on July 24, 2026, to say that Similarweb's newest report would "probably infuriate" two groups at once. The AI zealots who are certain every marketing dollar should already be. This connects with AI Search Optimization Isn’t the Hard Part when the same signal needs a clearer operating decision. A useful companion note is AI Overviews YouTube Gap, because it looks at a nearby part of the same system.

What the visibility signal actually changes: the practical question is whether the page, brand evidence, and surrounding content make the answer easier to trust. If that support is weak, search systems can still understand the topic but fail to connect it confidently to the brand.

What the visibility signal actually changes: that is why the response should begin with an audit of the evidence already on the site before creating a new asset. The fastest improvement is often a clearer page, a better internal link, or a stronger explanation of why the brand belongs in the answer.

Where the evidence needs to be tested

Where the evidence needs to be tested: a single study or ranking observation should not become a strategy by itself. It should become a diagnostic prompt: which source is being trusted, which query pattern is affected, and which part of the site would make that trust easier to earn?

Where the evidence needs to be tested: that keeps the response grounded. The goal is to improve the evidence chain around the topic rather than publish another summary that repeats what every other page already says.

Where the evidence needs to be tested: the important distinction is between a useful signal and a fashionable talking point. A useful signal changes the brief, the page structure, the linking plan, or the measurement view.

How to avoid overreacting to one data point

How to avoid overreacting to one data point: for content teams, the strongest move is to map the claim to existing assets before creating anything new. The right page may already exist, but it may need clearer headings, stronger internal links, fresher proof, or a better explanation of why the brand belongs in the answer.

How to avoid overreacting to one data point: this is also where title rewriting matters. A title should not copy the source headline; it should frame the practical implication so readers immediately know why the topic deserves attention.

How to avoid overreacting to one data point: the same standard should apply to every section. Each heading needs to earn its place by moving the reader through the evidence, not by repeating the outline in a more polished voice.

What this means for content and authority

What this means for content and authority: authority is becoming more contextual. It is not enough to be generally known in a category if the specific answer depends on a different source, a different index, or a different retrieval pattern.

What this means for content and authority: that means the content system should show consistent entities, related pages, credible references, and useful depth around the exact questions people and AI tools are asking.

What this means for content and authority: when the context is weak, AI systems can still mention the brand but describe it in the wrong frame. The fix is not more volume; it is cleaner evidence around the specific association.