Gemini in Chrome and Gmail, and Google’s AI distribution conduit

In September, Google announced Gemini in Chrome, an initiative to insert Gemini touchpoints into the Chrome browser on Windows and Mac. Google described this integration as an “agentic browsing assistant” that could “clarify complex information” across browsing tabs. Last week, Google expanded this integration to iOS for signed-in users in the US.

Separately, today, Google announced CC, a new Gemini-powered email assistant that connects to a user’s Google Calendar, Gmail, and Google Drive accounts to deliver daily digests of upcoming tasks. CC belongs to Google’s experimental Labs portfolio of products; users can request to test it, but it isn’t currently available to the general public.

These product integrations are interesting in the context of the point-counterpoint dynamic that took place last week when ADWEEK published a story claiming that Google employees had revealed that ads would be introduced to Gemini in 2026. Google’s VP of advertising, Dan Taylor, quickly took to X to refute the claim, stating:

This story is based on uninformed, anonymous sources who are making inaccurate claims. There are no ads in the Gemini app and there are no current plans to change that.

The idea of ads being introduced to Gemini, on its face, seems uncontroversial and altogether predictable: Google operates the world’s largest advertising platform, so it isn’t averse to advertising as a business model and could probably fairly effortlessly expand that product coverage to new surface areas in Gemini. But considering the application of ads to Gemini raises a crucial, if seemingly frivolous or inane question: what is Gemini?

The question is important, because Gemini describes two different products:

• Gemini is a family of multimodal AI models;
• Gemini is a consumer-facing chatbot accessible via the web and a mobile app.

Ultimately, the question of whether ads will be introduced to Gemini presents a false distinction predicated on a category error.

“Ads in Gemini” can be taken to mean that ad placements are inserted into the consumer-facing apps. But ads in Gemini can also be taken to mean that the various products that Google has empowered with Gemini might include ads. By that latter definition, ads already exist in Gemini, as I’ve documented in my Google’s Gambit series (parts one, two, and three): ads were introduced to AI Overviews in October 2024 and to AI Mode in July 2025. Per Alphabet’s Q3 2025 earnings report, AI Overviews sees 2BN monthly users (AI Mode is significantly smaller than AI Overviews, at 75MM DAU per Alphabet’s Q3 earnings).

Moreover: Google revealed in its Q3 2025 earnings call that ads in AI Overviews monetize at “the same rate” as those in general Search. A credible claim can be made that AI Overviews is the largest AI-focused consumer product in existence from an MAU perspective (see my discussion of ChatGPT’s unit economics and probable MAU scale here). And AI Overviews and AI Mode already monetize through ads at parity with the company’s core revenue engine, Search.

In this sense, whether ads are ever inserted into Google’s Gemini app is largely irrelevant: Gemini already monetizes with ads through the vast surface areas of AI Overviews and AI Mode. And in fact, for that reason, the user base scale of the Gemini app is also mostly inconsequential: Google has consistently applied Gemini to its portfolio of consumer-facing products, like Search, Chrome, and Gmail, in ways that may not directly incorporate advertising but nonetheless support the advertising business model.

I made the point in a recent post on X that Meta’s initiatives to bolster advertising with AI comprise two strategies:

1. Improve ad relevance and optimization efficiency with AI-empowered infrastructure, like its Lattice, GEM, and Andromeda models, as well as the company’s Advantage+ advertiser suite, which automates many facets of campaign optimization. These efforts improve advertising pricing.
2. Improve content relevance with models that pair users with the content they’ll find most engaging. These efforts improve time spent, and therefore the number of ad impressions served per session, holding ad load constant.

Per Meta’s Q3 earnings call, the efforts related to content relevance are bearing material fruit: Meta’s CFO noted in the call that these initiatives resulted in “5% more time spent on Facebook and 10% on Threads,” and that “generally growth in family DAP was healthy at 8% year-over-year in Q3 and daily usage continues to grow across each of Facebook, Instagram, and WhatsApp.” This illustrates how the largest consumer tech products can utilize AI to grow advertising revenues not just by building new, AI-first products that incorporate ads, but through applying AI to existing products to increase engagement.

This distribution strategy is fairly obvious, but it’s worth highlighting, since it disproportionately benefits incumbents. A company like OpenAI must navigate what I’ve called the AI-search incentive problem as well as the broader growth trap when it (inevitably) introduces ads. And the longer one of these companies waits to unleash that monetization paradigm, the smaller the share of its total TAM that has experienced the product without it.

That’s a challenging tension to navigate. Meanwhile, a company like Google or Meta can apply AI to existing products to improve retention, engagement, or both in ways that bolster the existing monetization model to which its users have grown accustomed.

Google, in particular, is advantaged here: it has already transformed its most prominent consumer product, Search, into an AI-empowered experience and is monetizing it through ads. This was Google’s Gambit, and it is manifest. The entirety of Google’s consumer-facing product suite (including YouTube), as well as the Google Cloud Platform, is a distribution conduit for the company’s AI initiatives. This spans multiple billions of consumers, all of which are already monetized through ads. Every dollar Google invests in AI research and development can immediately improve an existing revenue line item.