Rashed HaqEnterprise Artificial Intelligence Transformation
Sprecher: Daniels, Perry
RASHED HAQ is an AI and robotics technologist. He was recently appointed as the Vice President of Robotics at Cruise, one of the leading autonomous vehicle companies. He was previously the Global Head of AI & Data and Group Vice President at Publicis Sapient. He has spent over 20 years helping companies transform and create sustained competitive advantage through technology and data. Rashed holds advanced degrees in theoretical physics and mathematics. An accomplished author and sought-after speaker, Rashed frequently writes about the practical uses of AI in business.
Foreword: Artificial Intelligence and the New Generation of Technology Building Blocks xv
Prologue: A Guide to This Book xxi
Part I: A Brief Introduction to Artificial Intelligence 1
Chapter 1: A Revolution in the Making 3
The Impact of the Four Revolutions 4
AI Myths and Reality 6
The Data and Algorithms Virtuous Cycle 7
The Ongoing Revolution - Why Now? 8
AI: Your Competitive Advantage 13
Chapter 2: What Is AI and How Does It Work? 17
The Development of Narrow AI 18
The First Neural Network 20
Machine Learning 20
Types of Uses for Machine Learning 23
Types of Machine Learning Algorithms 24
Supervised, Unsupervised, and Semisupervised Learning 28
Making Data More Useful 32
Semantic Reasoning 34
Applications of AI 40
Part II: Artificial Intelligence In the Enterprise 43
Chapter 3: AI in E-Commerce and Retail 45
Digital Advertising 46
Marketing and Customer Acquisition 48
Cross-Selling, Up-Selling, and Loyalty 52
Business-to-Business Customer Intelligence 55
Dynamic Pricing and Supply Chain Optimization 57
Digital Assistants and Customer Engagement 59
Chapter 4: AI in Financial Services 67
Anti-Money Laundering 68
Loans and Credit Risk 71
Predictive Services and Advice 72
Algorithmic and Autonomous Trading 75
Investment Research and Market Insights 77
Automated Business Operations 81
Chapter 5: AI in Manufacturing and Energy 85
Optimized Plant Operations and Assets Maintenance 88
Automated Production Lifecycles 91
Supply Chain Optimization 91
Inventory Management and Distribution Logistics 93
Electric Power Forecasting and Demand Response 94
Oil Production 96
Energy Trading 99
Chapter 6: AI in Healthcare 103
Pharmaceutical Drug Discovery 104
Clinical Trials 105
Disease Diagnosis 106
Preparation for Palliative Care 109
Hospital Care 111
PART III: BUILDING YOUR ENTERPRISE AI CAPABILITY 117
Chapter 7: Developing an AI Strategy 119
Goals of Connected Intelligence Systems 120
The Challenges of Implementing AI 122
AI Strategy Components 126
Steps to Develop an AI Strategy 127
Some Assembly Required 129
Creating an AI Center of Excellence 130
Building an AI Platform 131
Defining a Data Strategy 132
Moving Ahead 134
Chapter 8: The AI Lifecycle 137
Defining Use Cases 138
Collecting, Assessing, and Remediating Data 143
Data Instrumentation 144
Data Cleansing 145
Data Labeling 146
Feature Engineering 148
Selecting and Training a Model 151
Managing Models 160
Testing, Deploying, and Activating Models 164
Testing 164
Governing Model Risk 165
Deploying the Model 166
Activating the Model 166
Production Monitoring 168
Conclusion 169
Chapter 9: Building the Perfect AI Engine 171
AI Platforms versus AI Applications 172
What AI Platform Architectures Should Do 172
Some Important Considerations 179
Should a System Be Cloud-Enabled, Onsite at an Organization, or a Hybrid of the Two? 179
Should a Business Store Its Data in a Data Warehouse, a Data Lake, or a Data Marketplace? 180
Should a Business Use Batch or Real-T
