Google's parent company Alphabet reports slowdown in Search business revenue growth

Google's parent company Alphabet has reported a slowdown in revenue growth for its Search business. According to the earnings report, Search revenue grew by 12 percent year over year in the third quarter, down from 17 percent in the previous quarter.

The slowdown is particularly notable given that search queries are growing at their fastest rate in five years. However, growth in paid clicks - which generate revenue for Google through ads - has also slowed, from 13 percent to 8 percent in the same period.

Alphabet's plans to invest heavily in artificial intelligence (AI) have been a key factor in the company's recent spending spree, with around $200 billion allocated for infrastructure this year. However, investors are beginning to question whether these costs will yield sufficient returns.

Chief Business Officer Philipp Schindler attributed the revenue-growth slowdown to a combination of currency effects and changes in advertiser spending patterns. He also noted that AI Mode queries - which use Google's AI technology - are growing strongly but monetizing at a lower rate than traditional searches, raising questions about whether this reflects a deliberate rollout of ads or a more fundamental problem with advertising in AI search.

Google's search revenue growth is outpacing paid clicks in the first three quarters of 2026. This trend raises questions about the effectiveness of Google's advertising model in an era where artificial intelligence (AI) is increasingly influencing how people find information and interact with ads.

The shift towards AI-driven search queries is significant, as it changes the way users engage with advertisements. Instead of traditional text-based ads, AI Mode queries use Google's AI technology to provide more interactive and conversational experiences. This new format has been growing strongly, but its monetization rate lags behind that of traditional searches.

The disparity between growth rates for search revenue and paid clicks suggests that Google may be facing challenges in adapting its advertising model to the changing landscape of AI-driven search. In some cases, users are opting for AI Overviews, which provide generated summaries of search results, while others prefer a more conversational approach by electing AI Mode.

The company's argument is that AI is expanding the business, rather than cannibalizing existing revenue streams. According to Google, most AI Mode queries are incremental, adding new questions rather than replacing traditional searches. Many of these queries are also upper-funnel, meaning users are researching potential purchases before they know what they want.

Google's expansion of ads in its AI features continues apace, with new placements emerging in AI Overviews and AI Mode. This push includes international markets and multiple turns of conversations within US AI Mode interactions. The company is also exploring the potential for ads in its standalone Gemini app, although it has yet to provide a timeline for this development.

One challenge Google faces is finding ad formats that balance the needs of advertisers with those of users interacting with its AI tools. Competitors like OpenAI are grappling with the same issue. While some experts argue that AI-driven advertising holds significant potential, others caution that it must be implemented carefully to avoid alienating consumers.

For now, advertisers appear to be reaping rewards from Google's AI ads. Tinuiti's clients saw a 14 percent increase in Google paid search spending during the third quarter, with their return-on-ad-spend targets remaining intact. However, the lack of transparency regarding these ad campaigns poses a problem for marketers seeking to optimize their strategies.

Advertisers are currently unable to isolate the performance of AI-specific inventory or break out its results from existing ad traffic. As a result, it is unclear whether AI ads are performing similarly to traditional formats or if they are still too small to have a noticeable impact on overall campaign metrics.

The ambiguity surrounding the profitability of AI advertising is a pressing concern for Google's business model. The company's efforts to integrate artificial intelligence into its search engine have raised questions about how much revenue these ads will generate and whether they can replace traditional formats.

While some queries in AI Mode are likely to be additional, potentially increasing revenue, there is also a risk that these interactions may divert users away from searches that are more lucrative for Google. The company's claim that most AI Mode queries are supplementary does not provide insight into the potential losses from searches displaced by AI.

The promise of conversational advertising lies in its ability to elicit more nuanced information about user needs, but platforms still face challenges in identifying relevant aspects of these conversations and matching them with targeted ads. It's not a guaranteed success that it will translate into more effective advertising, notes Elliott.

Preliminary research on ChatGPT ads has yielded mixed results, suggesting that richer conversations do not automatically lead to increased retail sales. A working paper focused on retailers' sales rather than platform revenue highlights the need for further investigation into how Google's AI ads compare to traditional formats.

Google's foray into AI-powered advertising is still in its early stages, and it remains to be seen whether these innovative formats will live up to their promise.

A key challenge lies in measuring the effectiveness of AI ads versus traditional formats, which can lead to misleading conclusions about their performance. A working paper focused on retailers' sales rather than platform revenue highlights this issue, emphasizing the need for more nuanced analysis. This complexity is due in part to the varying levels of purchase intent behind different search queries.

For instance, someone searching for a specific product like Nike shoes may already be ready to buy, whereas an AI tool seeking recommendations on running shoes is likely still in the research phase. This distinction can impact ad effectiveness and sales return, making it crucial to account for these differences when evaluating AI ads.

While Google's existing business has given it the luxury of time to experiment with AI advertising, its mounting investment in this area raises the stakes. As Elliott cautions, finding effective ad formats can take years, a lesson learned from the evolution of search engines and social media platforms.