Google AI Mode Ads: How to Optimize Product Feeds for Gemini

Google has introduced two new Gemini-powered ad formats, Conversational Discovery and Highlighted Answers, designed to embed sponsored product placements directly into AI-generated search responses [1]. As Google’s AI Mode reaches more than 1 billion monthly users, these formats shift the primary lever for ad performance from traditional keyword bidding to the quality and specificity of a brand’s product data [2].

Data-Driven Creative

In the AI-driven search environment, advertisers no longer write ad copy; instead, Google’s Gemini model generates ad content on the fly by pulling information from a brand’s Merchant Center feed [2]. Because AI-powered searches are roughly three times longer than traditional keyword queries, generic descriptions are increasingly ineffective [2]. To remain competitive, brands must move beyond simple titles like "Blue Shirt" to detailed, attribute-rich descriptions that specify material, fit, use cases, and limitations [2].

Google has introduced optional conversational attributes in the Merchant Center to help the model interpret product relevance [2]. The most critical addition is the question-and-answer attribute, which allows brands to submit structured FAQ pairs—such as specific product capabilities—that map directly to the exploratory prompts users type into AI Mode [2]. Because these placements are not managed through traditional campaign targeting, eligibility depends on enrollment in AI-powered programs like Performance Max or Shopping campaigns, where the system autonomously determines when a product matches a user's intent [2].

Market Implications

These formats represent a significant shift in how ecommerce brands must approach visibility. While paid ads will carry a "Sponsored" label, they appear within the same recommendation flows as organic results, meaning that high-quality, structured data is now a prerequisite for both paid and organic discovery [1, 2]. The complexity of measuring performance is also rising; because conversational searches are less structured than traditional queries, advertisers face new challenges in attributing specific interactions or themes to long-term sales performance [1].

What to watch

• Rollout Timeline: While Google has confirmed these formats are part of its broader AI strategy, there is no set date for when they will surface for all advertisers [1].
• AI-Powered Shopping Ads: Monitor the broader release of AI-powered Shopping ads, a separate format for considered purchases like appliances or electronics, which Google expects to roll out later this year [2].
• Measurement Evolution: Watch for new reporting tools from Google as the company attempts to address advertiser concerns regarding how to track performance in non-linear, conversational search paths [1].

The transition to AI-generated ad creative effectively moves the creative burden upstream to operations and merchandising teams. Success in this new landscape will likely be determined by how well a brand’s internal product data can answer the increasingly nuanced questions posed by users in AI Mode [2].