AI-Powered Inventory Manager: Using AI to Improve Forecasting, Reduce Waste, and Optimize Supply Chain Performance - Softcover

Hasting, Godfrey

Softcover

ISBN 13: 9798184243313

Publisher: Independently published, 2026

Synopsis

Most inventory problems do not start in the warehouse.

They start in decisions.

A delayed purchase order.
A weak forecast.
A missed demand signal.
A supplier delay nobody saw coming.

These small failures can quietly grow into stockouts, excess inventory, wasted capital, operational bottlenecks, and lost revenue.

In today’s fast-moving business environment, traditional inventory management is no longer enough.

Spreadsheets, static reorder points, manual forecasting, and reactive planning cannot keep up with volatile demand, global supply chain disruptions, rising customer expectations, and increasingly complex operations.

This is where artificial intelligence changes everything.

AI-Powered Inventory Manager is a practical, business-focused guide that shows inventory professionals how to use artificial intelligence to make smarter inventory decisions, reduce waste, improve forecasting accuracy, and build resilient supply chains.

This book goes beyond theory.

It translates AI into real operational value.

Whether you manage inventory in retail, e-commerce, manufacturing, pharmaceuticals, FMCG, logistics, or wholesale distribution, this book shows you how modern AI systems can transform daily inventory operations and long-term supply chain strategy.

Inside this book, you will learn how to:

• Use AI-driven demand forecasting to predict sales more accurately and reduce costly planning errors.
• Optimize stock levels using intelligent models that balance service levels, safety stock, and working capital efficiency.
• Detect slow-moving inventory before it becomes dead stock and expensive waste.
• Prevent stockouts by identifying supply risks, demand spikes, and replenishment failures early.
• Improve warehouse operations through AI-powered visibility, automation, and operational intelligence.
• Evaluate supplier performance using predictive analytics and smarter procurement decision-making.
• Integrate AI tools with enterprise systems such as ERP, business intelligence platforms, and inventory management software.
• Measure ROI and prove the business value of AI-driven inventory transformation.

This book is designed for professionals who want practical results, not buzzwords.

This book is for:

Inventory Managers who want stronger control over stock levels, replenishment, and service performance.

Warehouse Leaders seeking improved operational efficiency, inventory visibility, and smarter storage strategies.

Procurement and Supply Chain Professionals looking to make better sourcing and supplier decisions using data-driven intelligence.

Operations Managers and Business Leaders responsible for reducing cost, improving service quality, and increasing operational resilience.

Even if you have no technical background in artificial intelligence or machine learning, this book explains complex concepts in clear business language with practical examples you can apply immediately.

You do not need to be a data scientist.

That is exactly what this book teaches.

Artificial intelligence is rapidly changing how businesses plan, buy, store, move, and replenish inventory. Companies that adapt early will gain a major competitive advantage through lower costs, faster decisions, better service levels, and stronger resilience during disruption.

AI-Powered Inventory Manager gives you the knowledge, frameworks, and practical strategies to lead that transformation.

If you want to reduce waste, improve profitability, strengthen supply chain performance, and become a smarter inventory decision-maker, this book will become an essential resource in your professional library.

The future of inventory management is intelligent.

Start building that advantage today.

Edition details

• Publisher: Independently published
• Publication date: 2026
• Language: English
• ISBN 13: 9798184243313
• Binding: Paperback
• Number of pages: 448