Google’s AI Search Bet Still Has a Monetization Gap

By Tom Whitfield

Alphabet plans to spend about $200 billion on infrastructure in 2026, largely to support AI, even as Google’s Search revenue growth slowed to 12% year over year in the third quarter. The rate had reached roughly 17% in the previous quarter.

Paid-click growth slowed to 8% from 13%, even as Search queries grew at their fastest rate in five years. Alphabet shares have dropped about 14% since last week’s earnings report as investors weighed AI infrastructure costs against uncertain returns.

What changed in Search monetization?

Chief Business Officer Philipp Schindler identified currency effects as the biggest driver of the revenue slowdown, alongside changes in advertiser spending in certain industries. Google’s AI makeover also contributed: AI Mode queries were growing strongly, but they monetized at a lower rate than traditional searches.

Schindler expressed confidence in Google’s trajectory and said early advertising experiments showed promising results. That leaves two explanations the reported figures cannot separate: Google may be managing a deliberate ad rollout, or AI search may expose a broader weakness in converting answers into clicks.

Nate Elliott, an eMarketer principal analyst for AI and advertising, put the stakes plainly: “This is the first major disruption that Google is facing to its core business in decades.” Elliott’s concern centers on whether AI changes how people find information and whether they click the ads that fund Google.

Currency effects and advertiser caution explain part of the slowdown. Lower AI monetization, however, means faster queries have not yet produced stronger ad economics.

How can conversational search create more demand?

AI Overviews add generated summaries to ordinary results, while AI Mode turns a search into a conversation. Andy Taylor, Tinuiti’s vice president of research, noted that a Nike search still returns familiar shopping listings and text ads because the shopper wants shoes, not an AI explanation.

Schindler said most AI Mode queries are incremental, adding to a search rather than replacing it. Many sit high in the purchase funnel, when people research products before they know what they want; Google expects those visits to create advertising opportunities over time.

Google is expanding ads in AI Overviews and AI Mode, including internationally and across multiple turns of U.S. AI Mode conversations. It has also floated ads for the standalone Gemini app, with AI Mode formats potentially carrying over, but has announced no launch date.

Google and OpenAI still have to make conversational advertising satisfy advertisers without alienating users. More context can help match a request to an ad, but platforms must first identify which parts of a conversation carry commercial intent.

More queries may expand the market if their lower yield does not outweigh revenue from conventional searches. Until Google reports the balance, AI Mode remains a volume story without a proven monetization advantage.

What do advertisers see?

Tinuiti’s same-store advertisers increased their Google paid-search spending 14% year over year in the third quarter while maintaining return-on-ad-spend targets. Taylor said, “We’re still seeing a good return, and we’re not seeing performance take a hit.” He also described lower click-through as a problem Google still needs to solve.

Google does not let advertisers separately target AI ad inventory or view its performance. Steady aggregate results could mean AI traffic remains too small to move the numbers, or that it performs like existing inventory; Taylor believes the former is more likely.

Advertisers have evidence that Google still delivers returns. They cannot yet measure what AI ads contribute to those results.

Will AI add revenue or displace profitable searches?

Each incremental query can create revenue even when it earns less than a traditional search. The greater risk is substitution: AI Mode may pull users away from searches that Google monetizes more effectively, and a high share of incremental queries does not reveal how much revenue the replaced searches produced.

Conversational advertising promises more information about a customer’s needs, but that advantage is not automatic. Nate Elliott said it is not certain that conversational formats will prove more effective, because platforms still must identify the commercially useful parts of a conversation and pair them with the right ads.

An October working paper found that U.S. visits from ChatGPT ads generated $0.89 in retailer revenue per session, 64% less than the $2.45 generated by visits from Google Search ads. The study measured retailer sales rather than platform revenue, and its ChatGPT findings do not establish how Google’s own AI ads perform.

Taylor warned that intent can explain much of the gap. A Google search for Nike shoes may signal immediate purchase intent, while an AI query about running shoes may still represent research; the higher return from Google could therefore reflect the search context rather than superior ad delivery.

The evidence supports continued testing rather than a conclusion that AI ads add more value per visit. Conventional search still sets the commercial benchmark.

How long can Google take to settle the format?

Google has room for a measured rollout because its existing Search business still grows at a double-digit rate. Taylor pointed to the earlier mobile transition: phone traffic initially offered less value because shopping was cumbersome, yet that limitation eventually disappeared as formats improved.

Elliott said effective ad formats can take years. Search engines moved from banner ads to paid listings, and social media went through its own experimentation; today’s formats may not be the ones that ultimately prevail. His conclusion was blunt: neither Google nor any competitor has solved the model.

Alphabet’s mounting AI infrastructure bill raises the stakes. Search revenue still grows at a double-digit rate, but Google has not shown that conversational search can match traditional search economics. The next test is whether incremental AI queries generate enough advertising revenue to offset lower monetization and preserve advertiser returns as Alphabet’s roughly $200 billion infrastructure program continues.