Generative AI for Retail Inventory Management is a practical, intermediate course that teaches retail professionals how to apply generative AI for retail demand forecasting, replenishment planning, and markdown optimization. Through hands-on demonstrations with ChatGPT and Claude, you will analyze retail data, generate SKU-level demand forecasts, automate reorder recommendations, optimize omnichannel inventory, and measure performance using GMROI and other core retail metrics. No coding is required, only a working understanding of retail operations.

Generative AI for Retail Inventory Management

Generative AI for Retail Inventory Management


Instructors: Starweaver
Access provided by Barbados NTI
Recommended experience
What you'll learn
Identify core GenAI capabilities for AI-driven inventory management in retail; build ROI-based cases linked to gross margin and inventory turn.
Apply GenAI demand forecasting with POS and external signals for store- and SKU-level predictions with explainable drivers.
Design automated replenishment, omnichannel allocation strategies, and AI store-copilot queries using ChatGPT and Claude.
Evaluate generative AI integration for POS, ERP, WMS, and e-commerce platforms, applying data governance for compliant AI adoption.
Skills you'll gain
- Time Series Analysis and Forecasting
- Performance Measurement
- Demand Planning
- Business Analysis
- Key Performance Indicators (KPIs)
- Enterprise Architecture
- Customer Demand Planning
- Inventory and Warehousing
- Merchandising
- Return On Investment
- Forecasting
- Inventory Management
- Data-Driven Decision-Making
- Operational Performance Management
- Inventory Control
- Order Management
Tools you'll learn
Details to know

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August 2026
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There are 2 modules in this course
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Felipe M.

Jennifer J.

Larry W.

Chaitanya A.
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University of California, Davis
¹ Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.


