Google Search Queries Hit a Five-Year High as Ad Revenue Growth Slows

Alphabet said in its third-quarter 2026 results, announced October 28, that search queries on Google are growing at their fastest rate in five years. In the same quarter, Google Search revenue growth slowed to 12 percent year over year, down from roughly 17 percent in the previous quarter, according to The Verge. The gap between those two numbers is the central tension in the quarter.

Alphabet reported consolidated revenues of $127.6 billion, up 25 percent. Google Services revenues rose 11 percent to $96.3 billion, and Google Search and other advertising revenues were $63.3 billion, according to the company's earnings release. Reuters reported that total revenue fell short of the $128.2 billion average analyst estimate compiled by LSEG. CNBC reported adjusted earnings per share of $2.67, against $3.02 expected.

Growth in Google paid clicks, meaning clicks on ads, slowed from 13 percent to 8 percent. Chief Business Officer Philipp Schindler attributed the slowdown in revenue growth mainly to currency effects, meaning exchange-rate shifts that change the dollar value of overseas sales, alongside changes in spending by advertisers in particular industries. Retail contributed the largest share of Search and other advertising growth in the quarter, per the earnings call. Before the report, analysts had expected Search revenue growth to slow to 14.7 percent from 16.8 percent, a figure Reuters cited ahead of results.

The monetization picture for AI Mode, Google's conversational search format, is the detail most relevant to the search business. Monetization refers to how well a usage pattern turns into revenue. Schindler said AI Mode queries are growing strongly but monetizing at a lower rate than traditional searches. He also said most AI Mode queries are incremental, meaning they are additional questions rather than replacements for existing searches. Google is expanding ads in AI Overviews, the AI-generated summaries that appear above results, and in AI Mode, including internationally and across multiple turns of US AI Mode conversations.

Advertisers appear to be spending through the change. Data from Tinuiti showed that its same-store advertisers, meaning accounts active in both periods, increased Google paid search spending 14 percent year over year in the third quarter while maintaining return-on-ad-spend (ROAS) targets.

On the infrastructure side, Alphabet plans to spend about $200 billion this year, largely to support AI. That spending, known as capital expenditure or capex, covers data centers, chips, and related equipment. The company held its 2026 capital expenditure outlook unchanged when it reported the quarter, and it expects a significant increase in capital expenditure in 2027. Alphabet shares have fallen about 14 percent since the earnings report, according to The Verge's November 4 report.

The broader context here is the arithmetic. Query volume is rising at a rate the company has not reported in five years, but each AI Mode query currently monetizes below a traditional search, and the company's ad load is expanding into new surfaces to compensate. If the incremental queries ultimately carry ads at comparable yield, the new inventory widens the revenue base that Alphabet's capital plan depends on. If they do not, the company will be funding a large infrastructure build with a core ad product whose growth rate has already slowed by roughly five points in a single quarter.

In my view, the figures to watch over the next few reports are the monetization gap between AI Mode and classic search, the paid click trend once currency effects fade, and whether the 2027 capex increase arrives alongside revenue growth that keeps pace with it. The quarter does not settle any of those questions. It does show a search product that is being used more often, in a format that is still being priced.

For people who track the ad market, the useful signal is that ad units are moving into generative answer surfaces, and that the company is reporting query growth and monetization as separate metrics. Those two numbers will determine whether the AI answer layer expands the market for search advertising or redistributes spend within it.