Google's AI Shopping Features in 2026: What Ecommerce Brands Need to Know

Google rolled out major AI-powered shopping features starting in mid-2025, and they're reshaping how shoppers discover and purchase products. If you're running a product-based ecommerce business—whether you're selling direct to consumers or to other businesses—this isn't another tech trend you can ignore. The fundamental mechanics of product discovery and online commerce are changing.

Here's what's happening and what it means for your business.

What Google Launched

Google's new AI Mode shopping experience combines three significant capabilities that are rolling out across the U.S.:

1. AI-Powered Visual Discovery with the Shopping Graph

Google's Shopping Graph now contains over 50 billion product listings, from major retailers to small local shops. More than 2 billion of those listings are refreshed every hour with updated prices, availability, reviews, and product details.

Here's what's different: When shoppers use AI Mode, they're not just getting search results—they're getting conversational guidance. Ask for "a cute travel bag for a May trip to Portland" and the AI doesn't just show bags. It runs simultaneous searches to understand what makes a bag suitable for rainy weather and long journeys, then filters results to show waterproof options with accessible pockets. The visual results panel updates dynamically as the conversation progresses, helping shoppers refine their choices through natural language.

2. Agentic Checkout

This is the feature that should get your attention. Shoppers can now tap "track price" on any product listing, set their preferred size, color, and maximum price, then wait for a notification when that price point hits. When they're ready to buy, they tap "buy for me," confirm the purchase details, and Google completes the checkout process on the merchant's site using Google Pay.

Google is literally executing transactions on behalf of shoppers. They're not just facilitating discovery—they're completing the purchase journey.

3. Virtual Try-On at Scale

The virtual try-on feature works across billions of product listings for shirts, pants, skirts, and dresses. Shoppers upload a full-length photo of themselves and see how clothing looks on their actual body type. This isn't simple photo overlay—it's powered by a custom image generation model that understands how different fabrics fold, stretch, and drape on various body types, preserving those details when applied to the shopper's photo.

The try-on feature is currently available in Search Labs (Google's experimental features program) in the U.S.

Google Isn't Alone: The Competitive Landscape

Before you dismiss this as another Google experiment that might not gain traction, understand that Google isn't the only player making these moves.

Amazon Is Already There—And Making Money

Amazon's Rufus AI assistant reached 250 million shoppers in 2025, and Amazon projects it will generate an additional $10 billion in annualized sales. The numbers that matter: customers who engage with Rufus are 60% more likely to make a purchase.

Amazon also launched features that mirror or exceed Google's capabilities:

• "Buy for Me" (piloted in April 2025): Allows purchases from third-party brand websites directly through the Amazon app

• Lens Live (September 2025): Real-time visual search

• "Help Me Decide" (late 2025): AI-powered guidance when shoppers feel overwhelmed by choices

If you sell on Amazon, these features are already affecting how your products get discovered and purchased. If you don't sell on Amazon but compete with brands that do, your customers are experiencing this level of AI assistance elsewhere and expecting similar experiences from you.

Microsoft/Bing Is Playing a Different Game

Microsoft's AI shopping features focus on research and comparison rather than transaction completion:

• Price comparison and price history tracking

• AI-generated buying guides and review summaries

• Price match monitoring that alerts shoppers after purchase if prices drop

• Automatic coupon application

Microsoft reports that Copilot + Bing shortened the consumer purchase journey by 30%. While their features don't include automated checkout like Google's, they're still conditioning shoppers to expect AI-guided product research and price optimization.

The Bottom Line on Competition

You're not preparing for one company's AI features. You're preparing for a fundamental shift in how product discovery and purchase decisions happen across multiple major platforms. Whether shoppers find you through Google, Amazon, or Bing, they're increasingly using AI to narrow choices, compare options, and make purchase decisions before they ever visit your site.

Why This Matters for Product-Based Ecommerce

The implications are straightforward: AI platforms now sit between you and your customer at multiple critical points in the purchase journey.

Discovery is conversational, not keyword-based. 

Shoppers aren't searching for "waterproof travel bag with pockets"—they're having conversations about their trip to Portland and letting AI translate that into product requirements. If your product data doesn't include the attributes AI needs to match those nuanced queries, you won't appear in results. Keywords in titles aren't enough anymore.

Purchase decisions happen before site visits. 

With virtual try-on, shoppers are evaluating fit and style before they ever click through to your site. Your product imagery and technical specifications need to be comprehensive enough for AI to make accurate recommendations. Poor photos or incomplete data mean you're eliminated before the customer even knows you exist.

Price monitoring is constant and automated. 

Google is refreshing billions of listings hourly. When shoppers set price alerts and Google or Amazon executes purchases at their target price, you're competing in a real-time pricing environment. Your static pricing strategy—where you set prices and leave them for days or weeks—puts you at a disadvantage against competitors using dynamic pricing.

B2B Product Sellers: This Applies to You Too

If you sell physical products to other businesses—industrial supplies, commercial equipment, bulk materials, anything with SKUs and shopping cart functionality—you're in the Shopping Graph alongside consumer brands. Google's article specifically mentions the graph includes "global retailers to local mom-and-pop shops," which means any business selling products online.

Your B2B buyers are experiencing this level of shopping sophistication when they purchase products in their personal lives. When they buy hiking boots or kitchen appliances, they're getting AI-guided recommendations, visual browsing, and frictionless checkout. Then they come to your B2B site and find a 1990s-era catalog interface with PDF spec sheets and "call for pricing."

The expectation gap is widening rapidly. B2B buyers increasingly expect:

• Comprehensive product data they can compare without contacting sales

• Visual browsing experiences, not just part numbers and text descriptions

• Real-time pricing and availability for standard products

• Simplified procurement processes

If your B2B competitors implement these capabilities while you're still requiring RFQs for catalog items with standard pricing, you're handing them business.

What You Need to Do Now

This isn't about making small optimizations to your existing strategy. The underlying mechanics of product discovery have changed.

1. Audit Your Product Data Quality

Go beyond basic product descriptions. Every SKU needs:

• High-quality images from multiple angles (lifestyle shots showing products in use, detail shots showing texture/materials, scale/dimension references)

• Complete technical specifications in structured formats

• Accurate, real-time pricing

• Current inventory status

• Customer reviews and ratings

• Proper categorization and attributes

Google's AI uses this data to understand your products and match them to shopper queries. Missing data means you're invisible to AI-powered recommendations, regardless of how good your products are.

2. Implement Structured Data Markup

Schema markup isn't a "nice to have" anymore—it's how AI systems understand your products. At minimum, implement:

• Product schema (name, description, SKU, brand)

• Offer schema (price, availability, condition)

• Review schema (aggregate ratings, review counts)

• Organization schema (business details, contact information)

This structured data tells Google's AI exactly what you're selling, at what price, and whether it's available. Without it, AI can't confidently recommend your products.

3. Rethink Your Pricing Strategy

If Google is monitoring prices hourly and executing purchases when shoppers' price thresholds are met, static pricing puts you at a disadvantage.

You need:

• Competitive price monitoring capabilities

• Dynamic pricing rules based on inventory, competition, and demand

• Clear value propositions beyond price (quality, service, warranties, unique features)

Race-to-the-bottom pricing isn't sustainable, but being consistently overpriced when automated systems are comparing your products to dozens of competitors in real-time will kill your visibility.

4. Optimize for Visual Search and AI Understanding

Product photography needs to be technically excellent:

• Consistent lighting and backgrounds

• Multiple angles (front, back, sides, top)

• Lifestyle images showing products in context

• Detail shots of key features

• Images that accurately represent color, texture, and scale

But beyond quality, your images need descriptive file names and alt text that help AI understand what's being shown. "product-image-1.jpg" tells AI nothing. "waterproof-nylon-travel-backpack-front-view.jpg" gives AI context to work with.

5. Get Google Merchant Center Right

If you're not using Google Merchant Center, start now. If you are using it, audit for:

• Feed accuracy and completeness

• Update frequency (daily minimum, hourly if you have volatile pricing or inventory)

• Error rates (fix disapproved products immediately)

• Product data quality (use all available attributes)

Google Merchant Center is how your products get into the Shopping Graph. Poor data quality here means poor visibility in AI Mode shopping experiences.

Ecommerce Platform Readiness: What You Need to Know

All major ecommerce platforms already integrate with Google Merchant Center:

• Shopify: The official Google & YouTube app provides automatic sync. Updates sync every 24-48 hours.

• WooCommerce: The "Google for WooCommerce" plugin handles feed management and automatic syncing with Merchant Center.

• BigCommerce: Native Google Shopping integration is built directly into the platform.

• Magento/Adobe Commerce: Multiple extensions available (both free and paid options from vendors like Magmodules and Wyomind).

These platforms were built primarily for traditional Google Shopping feeds, and they handle the fundamentals that feed into AI Mode—product data, pricing, inventory, and images. However, to maximize your visibility in AI-powered shopping experiences, you'll likely need to enhance beyond your platform's default settings.

What this means for you:

Your platform gets your products into the system, but you'll need to:

• Increase feed update frequency (move from daily to hourly if your pricing or inventory is volatile)

• Enhance your product data beyond platform defaults (add custom attributes, more detailed descriptions, multiple high-quality images)

• Implement proper schema markup on your product pages (your platform's default settings may not be comprehensive enough)

• Consider supplemental feeds or third-party feed management tools if your platform's native capabilities are limited

The platform handles the technical integration. You're responsible for the data quality that determines whether AI recommends your products.

6. Monitor Your Competition in AI Search

Start testing how your products appear in AI-powered search experiences. Search for the problems your products solve using natural language queries. See which competitors appear, what product data they're showing, and how your offerings compare.

This isn't traditional SEO competitor analysis. You're evaluating how AI interprets and recommends products in conversational contexts.

The Reality Check

Here's what I'm not saying:

I'm not claiming this will replace traditional ecommerce overnight. Google has announced ambitious features before that took years to gain meaningful traction.

What I am saying:

The trajectory is clear. Google is moving from showing search results to actively participating in transactions. Amazon is already generating billions in additional sales through AI shopping features. Microsoft is shortening purchase journeys by 30% through AI-guided research.

When multiple major platforms are monitoring prices, recommending products through AI, facilitating virtual try-ons, and in some cases completing purchases on behalf of shoppers, they're fundamentally changing the role of search and discovery in commerce.

The brands that prepare for this now will have competitive advantages. The brands that wait to see if it "really takes off" will be playing catch-up while their competitors are already capturing this traffic.

Your customers are experiencing these features today. Whether they're using them for every purchase or just experimenting, their expectations are being set by AI-guided shopping experiences that are more sophisticated than what most ecommerce sites offer.

The question isn't whether this matters. The question is how quickly you'll adapt to the new reality of AI-powered commerce—and whether you'll lead that adaptation or react to it after your competitors have already captured market share.

The features are rolling out now. Your product data, pricing strategy, and technical infrastructure need to be ready.

WSI helps mid-market ecommerce brands increase revenue through performance marketing and AI search optimization. We focus on measurable outcomes—traffic that converts, visibility that drives sales, and strategies built for the way people actually shop in 2026. If you're ready to stop losing ground to competitors who've already adapted to AI-powered commerce, let's talk.