Search and shopping are starting to collapse into the same place, as AI-driven interfaces encourage users to move from questions to purchases without leaving the conversation. Google is now applying that AI-driven shopping approach directly to its search and advertising systems. Instead of moving from a query to a product page to a checkout screen, users are being encouraged to stay inside a single conversational flow.
According to reporting by the Financial Times, Google is expanding its AI-powered shopping experience by embedding personalised ads directly into its AI chat interface. The effort is built around what the company calls a “Universal Commerce Protocol,” designed to let retailers support product discovery, comparisons, and purchases without sending users to external websites.
For marketers, the change signals more than a new ad format. It points to a future where search, commerce, and promotion happen in one place, shaped by AI responses rather than ranked links.
From search to AI-driven shopping at Google
The Universal Commerce Protocol is meant to sit underneath Google’s AI Mode, which presents users with conversational answers instead of a page of blue links. In that flow, shoppers can ask follow-up questions, compare options, and receive tailored product suggestions. Ads and offers appear as part of that exchange, rather than as separate units clearly set apart from organic results.
Retailers participating in the programme include large chains like Walmart and Target, as well as merchants that sell through Shopify. For these sellers, the promise is straightforward: fewer steps between interest and purchase, and more chances to influence decisions while the shopper is still asking questions.
The experience feels closer to chatting with a salesperson than browsing a store. The AI can narrow choices, explain differences, and surface promotions that match what it knows about the shopper’s preferences and past behaviour.
A new kind of ad environment
The setup blurs long-standing lines in digital advertising. Traditional search ads rely on keywords and clear intent signals. Display and shopping ads rely on placement and visuals. In an AI chat, intent unfolds over time, shaped by a back-and-forth conversation. Ads are inserted into that flow, often framed as helpful suggestions rather than interruptions.
That raises questions about how marketers plan and evaluate campaigns. If an offer appears after several prompts and follow-up questions, what triggered it? Which part of the conversation deserves credit for the sale? Existing attribution models were not built for this kind of environment.
Brand teams also face a tone challenge. Messages that sound like standard ad copy may feel out of place inside a conversational answer. Offers need to align with the context of the discussion, or they risk being ignored or mistrusted. This pushes advertisers to think less about slogans and more about relevance at each step of the buying process.
Control of the customer journey
The deeper issue is who owns the relationship with the customer. When discovery, comparison, and checkout happen inside an AI interface, retailers have less direct contact with shoppers. Email sign-ups, browsing data, and on-site behaviour are harder to capture if users never leave the chat.
At the same time, platforms gain more influence over what products are shown and which offers appear first. Even small changes in how the AI frames options can shift demand. For large retailers, this may be a manageable trade-off for reach and convenience. For smaller brands, it could increase dependence on platform rules they do not control.
The dynamic is not unique to Google. Other tech firms are also testing ways to fold commerce into AI-driven experiences. The difference here is scale. Search has long been one of the most important entry points to online shopping. Changing how it works changes the balance of power in the retail and advertising ecosystem.
Measurement remains an open question
One of the hardest problems is measurement. In a chat-based flow, impressions, clicks, and conversions do not always map cleanly to user actions. A shopper might read several AI-generated responses, consider a product, and complete a purchase later, all without a clear moment that looks like a click.
Marketers will need new ways to understand performance that go beyond last-touch models. They will also need clarity on how data is shared, what signals are available, and how privacy rules are applied inside conversational systems.
Without that transparency, some brands may hesitate to shift large budgets into AI chat commerce, even if the reach is attractive.
What AI-powered shopping means for marketing teams
For now, Google’s move offers a preview of where digital commerce is heading. The path from question to purchase is becoming shorter and more guided, with AI acting as both advisor and gatekeeper.
Marketing teams should see this as a signal to rethink how they show up during discovery, not just at checkout. Product data, pricing, availability, and tone all matter more when decisions are made inside a conversation rather than on a product page.
Advertising is about being useful at the right moment, inside systems that are designed to keep users from ever leaving.
(Photo by Solen Feyissa)
See also: Zeta brings generative AI deeper into marketing operations with OpenAI
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