AI in retail

You can use Google Distributed Cloud (GDC) to connect to your store locations. This "Edge AI" infrastructure allows you to process real-time inventory and customer interactions locally, ensuring zero latency even if the store's internet connection is unstable. This local data is then "federated" into a central BigQuery warehouse that powers the e-commerce engine.

A way to implement this would be to ingest raw video streams from existing store CCTV directly into Vision Warehouse. Unlike older systems that required manual tagging, this uses natural language search over video. A manager can simply prompt the system to alert them when any shelf in the beverage aisle is more than 20% empty. The AI then continuously audits the visual shelf state against your digital inventory records. When it finds a discrepancy, the AI can automatically alert a floor associate's handheld device with a photo of the gap and directions to the replacement stock.

One way to do this is to uplevel your traditional keyword search with semantic search, which you can create using Vertex AI Search. Make discovery experiences on your sites or applications more relevant and ROI-driven with personalized search results, recommendations, and insights rooted in your product catalog. Leverage natural language processing, Google's unique web signals, Knowledge Graphs, and our commerce-tuned LLMs help your search bar understand intent-based queries like "What should I wear to a rainy outdoor wedding in October?."

Also, by enabling conversational filtering or search, the AI can dynamically ask the user questions based on their initial query to narrow down items. For example, the AI might ask if you're looking for casual or formal wear, or a specific size. This can drastically reduce the time it takes to find a specific or niche product.

Using Gemini Enterprise you could build a Store Associate Agent accessible on mobile devices. This agent is grounded in your company’s internal Standard Operating Procedures (SOPs) and real-time operational data. Associates can use voice-to-text to ask complex questions like, "How do I process a return for a damaged item without a receipt?" or "Summarize the morning manager's notes for the footwear department."

Manage the entire journey from discovery to checkout and beyond with a Shopping agent. Leveraging the Gemini family of models, the agent acts as a digital concierge, grounded in your full product catalog and customer loyalty data. More than just a chatbot, it acts like an expert who understands shoppers' personalized needs using complex reasoning and multimodal inputs to take consented actions to streamline the purchase.

For a high-volume catalog, you could set up an automated pipeline using Gemini 3 Flash. You feed the model raw inputs: technical specs, high-resolution images, and your brand's voice guidelines. To ensure quality at scale, implement a multi-agent review workflow. One Gemini agent drafts the description, a second reviews it for SEO, and a third agent checks for accuracy against the spec sheet. This allows a retailer to generate thousands of descriptions in hours rather than months.

To do so, you could integrate the Cloud Vision API into your mobile app or website's search bar. When a customer uploads a reference photo, the AI performs Object Localization to identify individual items. The system then maps these items to your catalog using vector embeddings. The AI should not only be able to find the item but also suggest the correct size based on the customer’s purchase history or a 3D scan.

Implementation involves funneling all unstructured customer feedback into BigQuery. You then use Gemini Enterprise’s Deep Research capability to perform theme clustering across millions of interactions. The AI identifies emerging trends before they show up in sales data. For example, it might notice a 15% uptick in customers asking about biodegradable packaging in support chats.

To manage a multi-vendor catalog, you can use Vertex AI to perform fuzzy matching and entity resolution. The AI uses multimodal understanding to "see" that the images and specs are identical despite the different text.

The practical approach is to create a "golden record" for every SKU, where the AI analyzes all incoming data streams, identifies duplicates, and selects the highest-quality image and most accurate description to represent the product. This ensures that your storefront remains clean and that inventory levels are accurately aggregated across all suppliers.

For retailers selling outdoor or home-improvement products (like solar panels, roofing, or sheds), you could integrate Google Earth Engine's high-resolution aerial imagery. When a customer enters their address, the AI uses computer vision to measure the roof's area, pitch, and shading from nearby trees.

A Vertex AI agent could then take these measurements and cross-references them with your current labor rates and material costs. Within seconds, it generates a precise, 3D-visualized sales quote. This removes the need for an initial site visit, allowing sales teams to focus only on high-intent leads that have already received and approved a preliminary "AI Quote."