Generative AI for Retail Inventory Management

Generative AI for Retail Inventory Management

Instructors: Professionals in the Industry

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2 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

5 hours to complete

Flexible schedule

Learn at your own pace

2 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

5 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Identify core GenAI capabilities for retail inventory management; 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 GenAI integration for POS, ERP, WMS, and e-commerce platforms, applying data governance for compliant AI adoption.

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There are 2 modules in this course

GenAI for Retail Managers: Optimizing Inventory with AI is a practical, intermediate course that teaches retail professionals how to use Generative AI to improve inventory management, demand forecasting, replenishment planning, and markdown optimization. Through hands-on demonstrations with ChatGPT and Claude, you'll learn to analyze retail data, generate SKU-level demand forecasts, automate reorder recommendations, optimize omnichannel inventory, and measure inventory performance using GMROI and other key retail metrics. No coding is required—just a basic understanding of retail operations.

You will build repeatable AI-powered workflows for everyday retail inventory decisions using real-world datasets, guided prompts, and practical business scenarios. The course includes in-video questions, hands-on labs, role-play activities, quizzes, and a course-end project that culminates in a personalized 90-day GenAI implementation roadmap. Designed for retail managers, inventory planners, merchandise analysts, category managers, and retail operations leaders, this course helps you confidently integrate AI into retail operations to reduce stockouts, lower inventory costs, and drive better business outcomes.

This foundational module equips retail managers with a clear mental model of how generative AI works and where it creates the most value in the retail inventory lifecycle. Learners explore core GenAI capabilities from demand narrative generation to stockout prediction and automated reporting mapped directly to the stages of assortment planning, purchasing, replenishment, markdowns, and liquidation. Using a real Kaggle retail dataset, learners identify the highest-impact AI opportunities in a store context and build a data-backed ROI business case ready to present to leadership.

What's included

11 videos2 readings1 assignment1 peer review1 discussion prompt

11 videosTotal 50 minutes

Welcome to GenAI for Retail Managers 3 minutes
Module Introduction 2 minutes
What is Generative AI? (Retail Edition) 4 minutes
GenAI Capabilities That Matter in Retail Inventory 2 minutes
Current State of AI in Retail: Trends and Adoption Barriers 6 minutes
The Retail Inventory Lifecycle: End to End 4 minutes
Identifying High-Impact AI Opportunities Using Real Data 6 minutes
Building Your AI Opportunity Map 5 minutes
The Three-Part ROI Framework for Retail AI 6 minutes
Building the ROI Model Live with ChatGPT 7 minutes
Communicating the Business Case to Non-Technical Stakeholders 6 minutes

2 readingsTotal 10 minutes

Welcome to the Course: Course Overview5 minutes
LLM to ROI: How to Scale Gen AI in Retail Link 5 minutes

1 assignmentTotal 30 minutes

Foundations of GenAI for Retail Inventory Management30 minutes

1 peer reviewTotal 10 minutes

Hands-On-Learning: Map Your Store's AI Opportunities and Build the ROI Case 10 minutes

1 discussion promptTotal 5 minutes

The Highest-Impact Stage in Your Inventory Lifecycle5 minutes

This module is the practical engine of the course. Learners use ChatGPT and Claude to build real demand forecasting workflows combining POS history with external signals like weather, events, and promotional calendars. They generate store-level and SKU-level predictions with plain-language explanations, design automated replenishment workflows, model promotional lift, and optimize markdown timing. The module also covers performance measurement: defining and tracking the KPIs that matter most, building AI-generated weekly performance summaries, and creating a phased 90-day GenAI implementation roadmap. All exercises use real Kaggle retail datasets.

What's included

11 videos1 reading1 assignment2 peer reviews1 discussion prompt

11 videosTotal 60 minutes

Module Introduction 3 minutes
How AI Augments Traditional Demand Forecasting 4 minutes
Generating SKU-Level Forecasts and Replenishment Triggers with ChatGPT 8 minutes
Seasonal Pre-Positioning and Vendor Communication with AI 6 minutes
AI-Driven Markdown Timing and Clearance Optimization 4 minutes
Generating Markdown Recommendations and Anomaly Alerts with ChatGPT 6 minutes
Building an AI Store Copilot for Daily Inventory Queries 6 minutes
Key Inventory Metrics and AI-Generated Performance Summaries 5 minutes
Calculating KPIs and Generating Weekly Reports with ChatGPT and Claude 6 minutes
Building and Presenting Your 90-Day GenAI Inventory Roadmap 7 minutes
Course Wrap-Up and Final Thoughts 4 minutes

1 readingTotal 5 minutes

Unlocking Value in Generative AI for Retail Link 5 minutes

1 assignmentTotal 30 minutes

AI-Powered Demand Forecasting, Replenishment, and Performance Measurement30 minutes

2 peer reviewsTotal 70 minutes

Hands-On-Learning: Generate Your Store's AI Performance Report and 90-Day Roadmap 10 minutes
Project: GenAI Retail Inventory Mini-Challenge60 minutes

1 discussion promptTotal 5 minutes

Anticipating Resistance to AI on Your Team5 minutes

Instructors

Professionals in the Industry

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