Supply Chain AI Use Cases with Enterprise AI Agents

Описание: See how an AI supply chain agent optimizes inventory, pricing, and forecasting in real time using Sema4.ai Studio.

Learn more about Sema4.ai for supply chains: https://sema4.ai/usecase/supply-chain/

Watch this real-time demo of an AI supply chain management agent built with Sema4.ai Studio. See how grocery retailers can transform inventory operations with AI by managing perishables, analyzing stock levels, and forecasting demand.
Learn how the AI supply chain agent automates pricing, generates POs, and ensures availability—turning reactive workflows into proactive, autonomous operations.

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TRANSCRIPT HIGHLIGHTS :

Hi everyone, my name is James with Semaphore AI. Today, I’ll demonstrate our AI supply chain management agent built with Sema4.ai Studio. While supply chain agents apply across many industries, today’s demo focuses on food and beverage. This agent transforms how grocery retailers manage inventory by connecting three key areas: perishable management, inventory analysis, and demand forecasting. Let’s see it in action.

First, we’ll review perishable inventory. The agent immediately surfaces a prioritized list of items requiring action. Items with one to two days until expiration are flagged as critical, with recommendations for deeper price markdowns and placement in quick-sale areas. Items with more remaining shelf life, like ground beef, receive more moderate discounts. Let’s apply these changes. The agent updates pricing and generates shelf labels showing original and markdown prices for in-store staff.

Next, we’ll review stock levels. The agent highlights items below minimum thresholds and flags three products at risk of stockout. We’ll reorder those items. The agent automatically calculates optimal reorder quantities, increases inventory for critical products, and generates purchase orders with vendors.

Finally, let’s forecast next week’s demand. The agent analyzes weather forecasts, upcoming promotions, and historical sales data, then generates a visualization showing projected demand. Based on these insights, it recommends increasing orders for specific categories to meet expected demand.

This AI supply chain agent shifts inventory management from reactive to proactive. By combining real-time monitoring with intelligent forecasting, it helps reduce waste, prevent stockouts, and improve profitability—while freeing staff to focus on customer service.
Today’s demo showed this as a conversational agent, but it can also be deployed as a worker agent that autonomously monitors inventory, adjusts pricing, generates purchase orders, and escalates only critical alerts. This enables a fully autonomous, end-to-end supply chain workflow.