Skip to content 
Google has announced a expansion of its AI-powered tools aimed at transforming how users shop for fashion and home decor. Through its newly enhanced AI Mode, users will be able to generate outfit suggestions and room design ideas based solely on text prompts. The experience integrates Google’s Shopping Graph and virtual try-on features to connect users with shoppable items that match their style preferences. These updates are set to roll out in the U.S. later this fall.
AI Mode Brings Visual Styling to Google Search
Google’s AI Mode now integrates generative AI with the company’s massive Shopping Graph to make styling advice part of everyday search. As explained by Lilian Rincon, Google’s VP of Product Management, AI Mode is designed to help users transition seamlessly from inspiration to purchase. The experience allows users to describe what they want from travel bags to outfit themes and instantly receive visuals and matching product listings.
This upgraded version of AI Mode uses Gemini AI to interpret and expand on vague prompts. For instance, a user can type “cute travel bag for rainy weather” and receive suggestions filtered by function, weather compatibility, and aesthetic appeal. The right-hand panel in Search dynamically updates with product visuals and relevant options from a pool of over 50 billion listings. Google emphasised that its Shopping Graph is refreshed more than two billion times per hour, ensuring users see only the most up-to-date product availability and pricing across global and local retailers.
Vision Match Now Offers Full Looks and Decor Styles
According to Google’s Director of Product, Consumer Shopping, Danielle Buckley, the upgraded Vision Match feature can now generate entire outfits and interior themes based on a user’s text description. Previously limited to identifying single items, the tool will now curate coordinated looks such as “coastal living room with boho accents” or “Y2K summer outfit with platform shoes.” It then finds real-time product matches that visually resemble the generated concepts.
The feature remains text-based and does not support image uploads. However, Buckley noted that Vision Match will be free to use and seamlessly integrated into Search. This sets it apart from niche competitors like VisualizeAI and RoomsGPT, which focus on interior design based on photos but lack real-world shopping tie-ins.Vision Match utilizes the vast product pool in the Shopping Graph to generate a visual lineup based on user style preferences. Buckley said this creates a more intuitive bridge between conceptual ideas and actual purchasable items.
Virtual Try-On Opens to All U.S. Users
Google has opened up its previously beta-tested tool called the tool that allows one to test drive it with any of the available devices whether it be the mobile devices or the desktop platform. The feature enables the customers to post a complete length photo of them and get a preview of how an outfit would appear on their personal body.Using a bespoke fashion specific image generation model, the try-on tool supports clothing texture, drape and fit on diverse body types. It maintains fabric behaviour such as stretch and folding and gives out results that depict the actual physics in the real world on real individuals.
Items supported by the tool include shirts, pants, skirts and dresses. With just a few seconds, the most visually appealing billions of listings of clothing can be tested and shown to the shoppers on the Google Shopping Graph. Users have a chance to save or share looks that have been created after viewing them before making a purchase.Haley Henschel, the senior shopping reporter, who had tried the app during its beta version, was mentioned saying that she found herself impressed and mortified at how realistic the outfits created by the AI demonstrated on her photo that she personally uploaded.
Agentic Checkout and Smarter Price Tracking
In order to make the process of purchasing more efficient, Google has decided to implement agentic checkout as well, a feature that is meant to purchase items on behalf of the user when the prices have reached their desired value. Users can track prices of any product afterward by clicking an option to receive updates on other products in the same category after choosing preferences such as size, color, and maximum budget.As soon as the right offer is on the table, Google informs the customer.
In case the user decides to continue, Google will pay the merchant directly using Google Pay and the item will automatically be added to the cart and purchase will be completed.This is an update to Google which has decided to improve its price alerts and customize it further. Users will no longer be subject to manual tracking checking back as they will be able to track by designated purchase criteria.
The AI Powered Search Becomes the hub of Shopping
Google is looking to consolidate the online purchasing process around its Search platform by incorporating AI insight into its repository of products. The possibility of getting style directions, seeing the looks, stepping outside, tracking the prices, and making a purchase – in a single location, is a significant rebranding in user interaction with online shopping.As contrasted to regular shopping platform tools, Google AI Mode acts as a visual assistant app that understands purpose and personalizes the offers according to situation. Highlighting on this, Rincon emphasized that users do not have to make a long scroll-down anymore with endless listings.
The customers have a chance to consider customized concepts and pursue them at the correct moment, on sale.The service will be launched as consumer hunger is on the rise to find new, disruptive shopping experiences. The inclusion of personal stylists, home designers, and checkout assistants, who are all run on AI, is one of the main indicators of the way the future of search-based commerce looks like to Google.The new options will be implemented completely in the U.S by the end of the year. At the moment, users in the U.S. are able to experiment with the functionality of the feature by mobile and desktop versions of Google Search.
