AI for Retail: A Practical Guide to Modernize Your Retail Business with AI and Automation

Length: 336 pages
Edition: 1
Language: English
Publisher: Wiley
Publication Date: 2023-04-11
ISBN-10: 1394184697
ISBN-13: 9781394184699
Sales Rank: #152610 (See Top 100 Books)

The coming of the AI revolution in brick-and-mortar retail

In AI for Retail: A Practical Guide to Modernize Your Retail Business with AI and Automation, Francois Chaubard, AI researcher and retail technology CEO, delivers a practical guide for integrating AI into your brick-and-mortar retail business. In the book, you’ll learn how to make your business more efficient by automating inventory management, supply chain, front-end, merchandising, pricing, loss prevention, e-commerce processes, and more.

The author takes you step by step from no AI Strategy at all to implementing a robust AI playbook that will permeate through your entire organization. In this book, you will learn:

How AI works, including key terminology and fundamental AI applications in retail
How AI can be applied to the major functions of retail with detailed P&L analysis of each application
How to implement an AI strategy across your entire business to double or even triple Free Cash Flow

AI for Retail is the comprehensive, hands-on blueprint for AI adoption that retail managers, executives, founders, entrepreneurs, board members, and other business leaders have been waiting for.

Cover
Title Page
Copyright
Dedication
Introduction: Why You Need This Book as a Retail Leader
    How to Use This Book
SECTION 1: Introduction to the AI Revolution
    CHAPTER 1: How AI Has Revolutionized Many Other Industries over the Last 20 Years
        Advertising Revolutionized by AI in 2000
        Baseball Revolutionized by AI in 2002
        Computer Vision Revolutionized by AI in 2012
        Speech‐to‐Text Services Revolutionized by AI in 2013
        Translation Services Revolutionized by AI in 2014
        Go Revolutionized by AI in 2016
        Air Travel Revolutionized by AI in 2019
        Cars Revolutionized in 2020
        Art and Game Development Revolutionized by AI in 2022
        Notes
    CHAPTER 2: The Three Myths of How AI Will Transform Retail
        Myth 1: Amazon Go (and the Me‐Too's) Will Eliminate Cashiers Globally
        Myth 2: AI Will Never Be Able to Do What I Do
        Myth 3: We Won't Need Grocery Stores Anymore; Online Shopping, Dark Stores, and Autonomous Delivery Will Hit 100% Market Share
        Notes
    CHAPTER 3: How AI Will Automate and Optimize Retail
        Real‐Time, Accurate Shelf Data
        The Algorithm
        Someone Has to Do It
        Note
    CHAPTER 4: Level‐Setting the AI Doomsday‐ism
        AI Is Going to Kill Us All
        AI Is Going to Take All of Our Jobs
SECTION 2: AI Theory
    CHAPTER 5: What Is AI?
        Intelligence
        Importance of Generalizability
    CHAPTER 6: From CPUs to GPUs
        CPUs Compared to GPUs
    CHAPTER 7: Optimization
        Linear Regression
        Convex Optimization
        Deep Learning
    CHAPTER 8: Measuring AI Performance
        Scoring AI
        Comparing Performance of AI Models
    CHAPTER 9: AI Learning Techniques
        Supervised Learning
        Unsupervised Learning
        Reinforcement Learning
    CHAPTER 10: Simulators and AI
    CHAPTER 11: OODA Loops
        Stages of the OODA Loop
        OODA Loops in Retail
    CHAPTER 12: Hierarchy of Data Maturity
        Hierarchy of Data Accuracy
    CHAPTER 13: A “General Theory for Retail AI”
        Non‐Convex Optimization Approach to Solving Retail
        Supervised Learning Approach to Solving Retail
        Reinforcement Learning Approach to Solving Retail
SECTION 3: Applications of AI in Retail
    CHAPTER 14: The Inefficiencies in Retail Today
        Core Inefficiencies in Retail
    CHAPTER 15: AI for Merchandising
        Current Roles, Processes, and Inefficiencies
        Think One Store at a Time
        How to Apply AI to Merchandising
        Making This Actionable
        Results
    CHAPTER 16: AI for Inventory, Ordering, and Supply Chain Management
        Current Roles, Processes, and Inefficiencies
        How to Apply AI to Inventory, Ordering, and Supply Chain Management
        AI Algorithms on Top of Sales Data
        AI‐based Ordering
        Making This Actionable
        Results
    CHAPTER 17: AI for Replenishment and Labor Management
        Current Roles, Processes, and Inefficiencies
        How to Apply AI to Replenishment
        Making This Actionable
        Results
    CHAPTER 18: AI for Labor Budgets and Scheduling
        Current Roles, Processes, and Inefficiencies
        How to Apply AI to Labor Budgets and Scheduling?
        Making This Actionable
        Results
    CHAPTER 19: AI for E‐Commerce and Customer Service
        Current Roles, Processes, and Inefficiencies
        How to Apply AI to E‐Commerce
        Making This Actionable
        Results
    CHAPTER 20: AI for Warehouse and Distribution Centers
        Current Roles, Processes, and Inefficiencies
        How to Apply AI to Warehouses and DCs
        Making This Actionable
        Results
    CHAPTER 21: AI for Checkout
        Current Roles, Processes, and Inefficiencies
        How to Apply AI to Checkout
        Making This Actionable
        Results
        Note
    CHAPTER 22: AI for Pricing and Promotion
        Current Roles, Processes, and Inefficiencies
        How to Apply AI to Pricing and Promotion
        Making This Actionable
        Results
    CHAPTER 23: Other AI Use Cases
        Loss Prevention
        HR
        Facilities and Maintenance
        Accounting and Financial Planning and Analysis (FP&A)
SECTION 4: Implementation
    CHAPTER 24: Create Your “AI Strategy and Road Map”
        Educate
        Explore
        Execute
    CHAPTER 25: Buying vs. Building AI
        Building AI Is Incredibly Difficult
        AI Specialists
        Framework for Building AI
    CHAPTER 26: How to Run a Proof of Concept Bake‐off Effectively
        How to Select AI Vendors
        How to Structure the POC Bake‐off
        Why Structure It as a Bake‐off
        Note
    CHAPTER 27: Transitioning to a Fact‐based, Data‐driven Culture
About the Author
Index
End User License Agreement