Google AI Shopping. at the heart of AI Mode, isn't just a consumer-facing novelty. For B2B wholesalers, this evolution is a wake-up call. From AI-powered conversational search to real-time deal watching, Google is redefining product discovery with capabilities like query fan-out, agentic checkout, and virtual try-on. In a world where procurement teams expect quick, precise results, wholesalers need to rethink how they feed data into Google’s ecosystem, before AI decides which supplier gets the order.
AI Mode: More Than Just a Search Tab
Google’s AI Mode transforms search into a dynamic, conversational experience powered by Gemini. It mines context, breaks down complex queries, and delivers personalized outcomes through the Shopping Graph, a real-time, 50-billion-listing strong product index refreshed billions of times per hour. In early rollout, AI Mode surfaces agentic features like track-price alerts and automated checkout using Google Pay, but always with user control maintained. "AI Mode is where we’ll first bring Gemini’s frontier capabilities, and it’s also a glimpse of what’s to come. As we get feedback, we'll graduate many features and capabilities from AI Mode right into the core Search experience" says Google's VP, Head of Search, Elizibeth Reid.
B2B Angle: This embraces a new standard, buyers want flexible, voice-like interactions (e.g., “track price for bulk galvanized bolts under $500”) and expect supplier feeds to respond accurately.
Query Fan-Out: Shoppers Speak, Google Responds
At I/O 2025, Google revealed how AI Mode breaks user queries into subparts—performing multiple searches in real-time to deliver richer, more relevant results. Google’s concept of query fan-out refers to the way a single search query is distributed across its massive, distributed infrastructure to deliver results in under a second. When a user submits a query, Google doesn’t send it to one server; instead, it “fans out” the request to hundreds or even thousands of index servers (shards), each holding a portion of the web’s index. Each server processes the query independently, identifies its top matching results, and sends them back to be aggregated, deduplicated, and re-ranked by Google’s ranking algorithms. This fan-out and fan-in process allows Google to search billions of documents in parallel, ensuring speed, scalability, freshness of content, and resilience even if individual servers are slow or unavailable.
B2B Angle: For industrial clients searching complex specs, such as “high-temp rated, lead-free solder wire in bulk,” your product data must be granular and structured to get picked up and recommended correctly.
Agentic Checkout: Let AI Do the Heavy Lifting
Google’s AI can now track pricing, alert when affordable, and even check out for the buyer once conditions are met via Google Pay, no manual cart required. According to eMarketer, "Keeping customers within its own payment ecosystem helps Google maximize its profit per purchase. AI also increases the likelihood of a shopper’s dependence on the service, with long-term, repeated use...Google is trying to establish new shopping routines among digitally native shoppers like Gen Zers and Gen Alphas."
B2B Angle: Wholesalers must ensure accurate, real-time feeds with detailed variant info (GTINs, unit types, bulk pricing tiers), anything less and AI may skip over your products when matching or executing orders.
Virtual Try-On & Visual Inspiration: Not Just for Fashion
Google’s AI Mode isn’t limited to chat, it’s visual too. With a full-length photo upload, shoppers can virtually try on apparel listings using AI’s fashion rendering capabilities. While B2B doesn’t use this directly, the technology signals that visual-rich, immersive product discovery is capturing attention elsewhere. AI shopping agents rely on structured data, text descriptions, and visual signals when choosing, comparing, and recommending products. Instead of just parsing keywords, they now interpret product attributes, context, and intent. When your PDPs are rich with images, diagrams, videos, 3D renders, and annotated specs, the AI gets more reliable “training fuel” for answering buyer prompts like “Find me a stainless-steel valve with a 2-inch connection that looks easy to install.”
B2B Angle: Consider 3D or video previews, especially for industrial equipment with spatial fit concerns—investing here aligns with the direction Google is headed.
The Shopping Graph & Data Quality: The Core of AI Visibility
Google’s Shopping Graph is the AI-powered knowledge graph that underpins its new shopping capabilities, functioning as a constantly updated map of products, sellers, pricing, inventory, reviews, and attributes across the web. Much like the original Knowledge Graph for people and places, it helps Google’s AI understand what a product is, how it relates to alternatives and accessories, and where it can be purchased. This fuels capabilities such as product comparisons, personalized recommendations, and agentic buying (e.g., “buy this when it’s under $100 and in stock”). It also powers multimodal search, letting users identify products via images or screenshots. For B2B distributors, the implication is clear: the richer and more structured their product data—through feeds, schema markup, images, and detailed specs—the more likely their products are to be accurately represented in the Shopping Graph and surfaced by AI-driven shopping experiences.
B2B Angle: If your feeds lag or lack detail, AI gets blind spots. A tool like Feedonomics’ Flow or similar feed enrichment services can help you stay in the game across high-SKU, tech-heavy catalogs.
AI Shopping Trends & Broader Insights
- Comprehensive, AI-led product feed experiences are now central across the web, giving structured data primacy over traditional organic links.
- AI isn’t just functional, it’s beginning to broker customer loyalty, acting as an intermediary deciding whom to recommend.
- Experts question whether handing off shopping to AI fully is wise, concerns about transparency, loss of control, and trust persist.
- As increased conversational search happening in AI Mode, a potential bias in favor of advertisers begining to emerge.
B2B Angle: AI injects new power into procurement, but control and trust remain critical. Data quality, transparency, and predictive alignment are now competitive differentiators.
What B2B Wholesalers Must Do Now
Google AI Shopping isn’t just consumer-focused, it’s fundamentally reshaping e-commerce. For B2B, this means:
- Feed Excellence: Ensure granular, structured, real-time SKU-level data (e.g., GTINs, pricing tiers, variant attributes).
- AI-Ready Feeds & Enrichment: Use newer advanced, AI enabled, tools like Commergenix or similar to automate and enrich listing quality.
- Visual Innovation: Explore higher-quality visuals, 3D previews, and immersive product showings, even for non-fashion items.
- Trust & Control: Keep buyers in the driver’s seat, even with AI, through transparency, feedback mechanisms, and clear brand signals.
- Strategic Alignment: Align product teams, partners, data owners, and IT to create feedback loops optimizing for impressions, conversions, and AI-driven discovery.