Google says AI Mode makes less money per search. Its answer is more ads

Happy Tuesday.

If you run paid search, here's a sentence worth taping to your monitor.

"It's worth noting that the strong growth in AI Mode queries had an impact because of the lower monetization we were seeing in AI Mode," Google's chief business officer, Philipp Schindler, said on Alphabet's earnings call on October 28, per Search Engine Roundtable.

Translation: people are using AI Mode a lot, and Google makes less money per query there than on a normal results page.

Search still brought in $63.4 billion in the quarter. But search ad revenue grew 12%, against 15% a year earlier, and missed analyst estimates for the second quarter running, Marketing Dive reports. Alphabet's shares plunged.

Schindler's answer, in the same reply, was more ads: Google is "now scaling ads within both AI Overviews and AI Mode to more users and more queries." The same day it announced ads in AI Mode for ten more countries, among them Australia, Canada, India and Singapore, with Brazil, Mexico and the UK planned for the fourth quarter.

In the U.S. it's launching multiturn ads, which "show up on responses to follow-up user queries as users engage in back and forth conversations with AI Mode," a spokesperson told SER.

So the ad follows the conversation now. Google says AI Mode queries run three times longer than traditional searches on average, and that click-through rates are already similar for sponsored and organic product listings there. That's Google grading its own homework, and the claim covers product listings. Text ads weren't part of it.

Sundar Pichai put it this way: "Just like our shift to mobile over a decade ago, we are focused on building the best search user experience, followed by monetization." That's the honest order. The experience comes first, then the money, and the money comes from you.

Before your 2027 search budget is locked, ask your agency to report AI Mode and AI Overviews separately from classic search, every month. And hold back a slice of budget as a test, so you have your own numbers before the ad load in AI Mode catches up with the usage.

When Google gets the monetization right, who do you think it'll be getting it from?

Today’s sponsor:

Cyrus Shepard, founder of Zyppy, summing up the day after Google reported:

Add a fourth line: Google makes less per AI Mode query than per classic search, by its own account. The only party it's clearly working for is the person asking the question.

56.3%. B2B marketers prioritizing their brand's visibility inside large language models, in Marketing Week's State of Brand in B2B survey of 300, per Marketing Week. And 54% are investing in GEO.

Only a third (33.1%) are building campaigns that earn media to drive AI citations. Everyone wants to be in the answer. Fewer are doing the slow work that gets you quoted in it.

See how much of your search spend sits on research questions, the kind that turn into long AI Mode conversations.

Paste in: your Google Ads search terms report for the last 90 days, with spend and conversions. You get back: four intent groups with spend and conversions each, plus a shortlist of expensive research terms. The full Search Intent Classifier adds content recommendations and flags mixed intent.

When a platform changes the rules mid-quarter, the instinct is to fire off instructions. Move budget. Test the new format. Send me numbers daily.

Fast instructions produce fast confusion. Your search lead hears "cut," your agency hears "test" and finance hears "savings."

Slow down instead. Write one page: what we believe about AI Mode, what we don't know yet, which number will tell us, and who decides when we see it. Share it with the search team and the agency in the same meeting, so they hear the same thing at the same time.

Then step back. A team that understands the reasoning can make the next ten calls without you. A team that only got the instruction will be back in your inbox by Thursday.

If more of the search happens inside Google's answer, make the clicks that do land count:

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The AI Marketing Experimentation Framework is our five-stage method for testing AI changes and scaling only what works: audit the workflow, design a light test, measure it against revenue, govern it, then scale. Use it when a platform hands you a new AI format and a confident chart.

First step this week: write the test down. The framework's version runs 30 to 60 days on a small cohort, with one success metric and a decision threshold, measured against pipeline velocity, acquisition cost or lifetime value.

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