Google is rapidly expanding the use of generative artificial intelligence across its advertising business. Philipp Schindler, Google’s chief business officer, said Gemini models helped advertisers generate more than 1.5 billion campaign assets during the third quarter of 2026, marking growth of more than seven times compared with the same period a year earlier. The figure highlights the growing role of AI in producing advertising creative at scale.
The announcement came during Alphabet’s third-quarter earnings call on October 29, 2026. Google has been integrating Gemini into advertising products to help marketers create campaign materials, improve ad relevance and reach consumers through changing search behavior. The company is also expanding AI-powered advertising formats across Search, AI Overviews and AI Mode, positioning generative AI as both a creative tool and a way to improve advertising performance.
Key Takeaways
- 1.5 billion assets: Gemini models helped generate more than 1.5 billion advertising campaign assets in Q3 2026.
- More than 7x growth: The number of generated assets increased by more than seven times year over year, according to Philipp Schindler.
- AI-powered creation: Google’s advertising tools use AI to help produce and adapt creative materials for campaigns.
- Performance focus: Google is combining AI-generated creative with automated campaign optimization and improved targeting.
- Early customer results: Telstra reported a 52% increase in conversions and a 36% reduction in cost per order using AI Max to capture long-form and multilingual searches.
- Broader strategy: Google is expanding advertising across AI-powered Search experiences while attempting to preserve relevance for users and returns for advertisers.
What Did Google Announce About Gemini Ad Assets?
During Alphabet’s Q3 2026 earnings call, Schindler explained that Google is integrating Gemini models into its advertising infrastructure across three areas: ad quality, advertiser tools and AI-powered user experiences.
The reported 1.5 billion figure relates to campaign assets generated with Gemini models during the quarter. It demonstrates the scale at which advertisers are beginning to use Google’s generative AI capabilities.
These assets can include creative components such as headlines, descriptions, images and video, depending on the tool and campaign workflow. Google’s advertising products are designed to help marketers create variations from information such as a website URL, a marketing brief and campaign objectives.
The distinction between an asset and an advertisement is important. An asset is an individual creative component that can be used in an advertising campaign. A single campaign may use several assets, and generating an asset does not necessarily mean it was published, shown to consumers or responsible for a conversion.
Google’s announcement therefore measures the growing volume of AI-assisted creative production, rather than the number of advertisements served or the amount of revenue directly attributable to those assets.
How Gemini Is Changing Google’s Advertising Tools
Google is embedding generative AI into products that help advertisers create and manage campaigns.
One important area is Performance Max, Google’s automated campaign platform, and AI Max, its suite of AI-powered Search campaign features. These products help advertisers reach potential customers across Google’s advertising inventory and respond to a wider range of search queries.
Google has also introduced multimodal asset-generation capabilities through Asset Studio. Advertisers can describe their requirements and generate campaign materials in several formats, including text, images and video. The tools are intended to help businesses produce more creative variations without building every asset from scratch.
| Advertising task | How AI can help |
|---|---|
| Headline creation | Generate alternative headlines for different audiences and search intentions |
| Image production | Create campaign visuals from briefs and product information |
| Video creative | Produce video concepts, storyboards and advertising variations |
| Campaign adaptation | Adjust creative materials for different formats and placements |
| Search campaign management | Use AI-powered tools to reach relevant queries and optimize performance |
For small businesses, these capabilities could lower the practical barriers to producing a variety of advertising materials. Larger advertisers may use them to scale creative testing across products, markets and languages.
However, generated content still requires appropriate review. Advertisers need to check factual claims, brand consistency, product representation and compliance with advertising policies.
Why Google Wants More AI-Generated Advertising
Advertising performance depends on more than how many people see an advertisement. Creative relevance, audience targeting, campaign structure and the intent behind a search can all influence whether a user clicks or makes a purchase.
Generative AI gives Google more ways to create and adapt assets for different contexts. Instead of relying on a small set of manually produced advertisements, marketers can use AI to develop additional variations and test which combinations perform best.
Google says Gemini is also improving how its systems interpret user intent and determine which advertisements are relevant. During the earnings call, Schindler highlighted an update to product listing ads that added AI capabilities to help shoppers make more informed purchase decisions.
Google reported that satisfaction with the updated product listing experience increased by 19%, while dissatisfaction fell by more than half. These are company-reported results, and they should not be interpreted as evidence that every AI-generated campaign will achieve similar improvements.
The broader strategy is to connect creative production with campaign optimization. AI can help generate assets, while Google’s advertising systems use performance signals to decide where and when to show them.
Telstra Reports Higher Conversions With AI Max
Google also cited results from telecommunications company Telstra as an example of AI-powered advertising performance.
According to Schindler, Telstra used AI Max to capture longer and multilingual search queries and recorded a 52% increase in conversions alongside a 36% reduction in cost per order.
| Reported metric | Result |
|---|---|
| Increase in conversions | 52% |
| Reduction in cost per order | 36% |
| Campaign approach | AI Max targeting long-form and multilingual queries |
These figures are attributed to Google’s earnings-call remarks. The announcement did not provide enough detail to establish that the results can be reproduced by every advertiser or that Gemini-generated creative alone caused the improvement.
The example nevertheless illustrates Google’s wider proposition: AI can help advertisers identify additional search opportunities and deliver campaign experiences suited to how consumers actually express their needs.
For businesses operating across multiple languages or serving customers with varied search habits, the ability to respond to more specific queries could create additional opportunities to reach potential buyers.
Google Is Expanding Ads Across AI Search Experiences
Google’s AI strategy is also changing where advertisements appear.
The company is expanding advertising in AI Overviews and AI Mode, which allow users to explore questions through AI-generated responses and more conversational search experiences. These formats create new opportunities to connect users with products and services during research and discovery.
Schindler said Google was expanding AI Mode advertising into international markets and introducing multi-turn ads in AI Mode in the United States. Multi-turn interactions allow users to continue a conversation through follow-up questions rather than completing their research in a single search.
For advertisers, this could provide additional ways to reach consumers earlier in their decision-making process. Someone researching a complex purchase, for example, may ask several questions before choosing a product.
For Google, the challenge is to make advertising useful within these experiences without undermining trust. The company says its approach is to prioritize user experience and engagement before scaling formats that demonstrate returns for advertisers.
The long-term commercial impact remains uncertain because AI-powered search experiences are still evolving. Advertisers will need reliable measurement to determine how these placements contribute to conversions and whether they complement or replace traditional search advertising.
What the 1.5 Billion Figure Means for Advertisers
The sharp increase in generated assets suggests that AI-assisted creative production is moving beyond experimentation into large-scale advertising workflows.
For marketing teams, the potential benefits include faster production, more variations for testing and easier adaptation across formats. AI can also help smaller businesses produce creative materials that would otherwise require more time, staff or external agency support.
But asset volume alone is not a measure of advertising effectiveness. Producing more headlines, images or videos is valuable only if the additional material helps reach the right audience, improves campaign outcomes or reduces the cost of producing effective creative.
Advertisers should therefore measure AI tools against practical indicators, including conversion rates, cost per acquisition, return on advertising spend, creative approval rates and the amount of human editing required.
Businesses must also account for the possibility that increased creative volume can produce inconsistent quality. Human review remains important for ensuring that generated assets accurately represent products and meet legal, brand and platform requirements.
The Bigger Picture
Google’s Gemini advertising milestone illustrates how generative AI is becoming part of the infrastructure behind digital advertising. AI is no longer limited to helping marketers brainstorm ideas; it is increasingly embedded in the systems used to generate campaign materials, interpret user intent and optimize performance.
The development also strengthens Google’s ability to connect its AI models with its existing advertising ecosystem. If AI-generated assets help marketers work faster and deliver measurable results, they could become a standard part of campaign production. Yet the commercial value will ultimately depend on performance rather than output volume alone. Advertisers will need evidence that the technology delivers better results, while Google must ensure that the growing presence of AI-generated advertising remains relevant and trustworthy.
FAQs
1. How many ad assets did Gemini generate in Q3 2026?
Google’s chief business officer, Philipp Schindler, said Gemini models helped advertisers generate more than 1.5 billion campaign assets during the third quarter of 2026.
2. How much did Gemini-generated advertising assets grow year over year?
The number of campaign assets generated with Gemini models increased by more than seven times year over year, according to Google’s Q3 earnings-call remarks.
3. What types of advertising assets can Google’s AI tools generate?
Depending on the product, Google’s AI advertising tools can help produce headlines, descriptions, images, videos and other campaign creative. Advertisers can use these materials across supported Google advertising formats.
4. Does generating more AI ad assets guarantee better results?
No. A higher volume of creative assets does not automatically translate into more sales or lower advertising costs. Performance depends on factors including audience relevance, creative quality, targeting and campaign optimization.
5. How is Google using Gemini to improve advertising performance?
Google is integrating Gemini into its advertising infrastructure to help interpret user intent, improve ad relevance, generate campaign creative and support AI-powered campaign tools such as AI Max and Performance Max.
Looking Ahead
Google is likely to continue embedding Gemini into more advertising workflows as it seeks to make AI-powered creative production and campaign optimization easier for businesses. The next important indicators will be whether advertisers report sustained improvements in conversion rates, production efficiency and returns, rather than simply generating more assets.
For marketers, the practical opportunity is to use AI to accelerate creative testing while maintaining human oversight of brand identity, accuracy and compliance. The 1.5 billion figure signals that AI-assisted advertising has reached substantial scale within Google’s ecosystem, but its lasting significance will be determined by how effectively those assets connect businesses with customers.
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