Enterprise AI For Dummies

Master the application of artificial intelligence in your enterprise with the book series trusted by millions

In Enterprise AI For Dummies, author Zachary Jarvinen simplifies and explains to readers the complicated world of artificial intelligence for business. Using practical examples, concrete applications, and straightforward prose, the author breaks down the fundamental and advanced topics that form the core of business AI.

Written for executives, managers, employees, consultants, and students with an interest in the business applications of artificial intelligence, Enterprise AI For Dummies demystifies the sometimes confusing topic of artificial intelligence. No longer will you lag behind your colleagues and friends when discussing the benefits of AI and business.

The book includes discussions of AI applications, including:

• Streamlining business operations

• Improving decision making

• Increasing automation

• Maximizing revenue

The For Dummies series makes topics understandable, and as such, this book is written in an easily understood style that's perfect for anyone who seeks an introduction to a usually unforgiving topic.

Auteur

Zachary Jarvinen, MBA/MSc is a product & marketing executive and sought-after author and speaker in the Enterprise AI space. Over the course of his career, he's headed up Technology Strategy for Artificial Intelligence and Analytics at OpenText, expanded markets for Epson, worked at the U.S. State Department, and was a member of the 2008 Obama Campaign Digital Team. Presently, Zachary is focused on helping organizations get tangible benefits from AI.

Texte du rabat

• Leverage the power of AI to maximize revenue
• Effectively implement AI-powered tools for breakthrough value

• Augment decision-making and streamline operations Demystify AI and make it work for your business Artificial intelligence can help you improve customer engagement, increase operational efficiency, automate decision-making, accelerate development, and control costs in your business. Yet to many business people, implementing AI remains a bit frightening and futuristic. Don't be intimidated! This book strips away the confusion about AI and helps you put it to work, making your business more effective and competitive. Get a grasp on the theory and technique of AI then dive into the steps of applying AI in your enterprise. Inside...

• Understand the basics of AI
• Explore common use cases for AI
• Connect AI techniques with practical applications
• Level the playing field with your competition
• Gather insight on how AI will affect the next decade

Contenu
Introduction 1

About This Book 2

Strong, Weak, General, and Narrow 2

Foolish Assumptions 3

Icons Used in This Book 4

Beyond the Book 4

Where to Go from Here 5

Part 1: Exploring Practical AI and How It Works 7

Chapter 1: Demystifying Artificial Intelligence 9

Understanding the Demand for AI 11

Converting big data into actionable information 11

Relieving global cost pressure 13

Accelerating product development and delivery 14

Facilitating mass customization 14

Identifying the Enabling Technology 14

Processing 15

Algorithms 15

Data 16

Storage18

Discovering How It Works 18

Semantic networks and symbolic reasoning 19

Text and data mining 20

Machine learning 22

Auto-classification 24

Predictive analysis 25

Deep learning 26

Sentiment analysis 27

Chapter 2: Looking at Uses for Practical AI 29

Recognizing AI When You See It 30

ELIZA 30

Grammar check 30

Virtual assistants 30

Chatbots 31

Recommendations 31

Medical diagnosis 32

Network intrusion detection and prevention 33

Fraud protection and prevention 34

Benefits of AI for Your Enterprise 34

Healthcare 35

Manufacturing 36

Energy 36

Banking and investments 37

Insurance 37

Retail 38

Legal 39

Human resources 39

Supply chain 40

Transportation and travel 40

Telecom 41

Public sector 41

Professional services 42

Marketing 43

Media and entertainment 43

Chapter 3: Preparing for Practical AI 45

Democratizing AI 46

Visualizing Results 46

Comparison 46

Composition 47

Distribution 48

Relationship 48

Digesting Data 50

Identifying data sources 52

Cleaning the data 52

Defining Use Cases 54

A B 55

Good use cases 55

Bad use cases 56

Reducing bias 58

Choosing a Model 59

Unsupervised learning 59

Supervised learning 60

Deep learning 60

Reinforcement learning 61

Chapter 4: Implementing Practical AI 63

The AI Competency Hierarchy 63

Data collection 63

Data flow 64

Explore and transform 64

Business intelligence and analytics 64

Machine learning and benchmarking 65

Artificial intelligence 65

Scoping, Setting Up, and Running an Enterprise AI Project 65

Define the task 67

Collect the data 68

Prepare the data 69

Build the model 70

Test and evaluate the model 72

Deploy and integrate the model 72

Maintain the model 72

Creating a High-Performing Data Science Team 73

The Critical Role of Internal and External Partnerships 74

Internal partnerships 74

External partnerships 75

The importance of executive buy-in 75

Weighing Your Options: Build versus Buy 75

When you should do it yourself 75

When you should partner with a provider 77

Hosting in the Cloud versus On Premises 77

What the cloud providers say 78

What the hardware vendors say 78

The truth in the middle 78

Part 2: Exploring Vertical Market Applications 81

Chapter 5: Healthcare/HMOs: Streamlining Operations 83

Surfing the Data Tsunami 84

Breaking the Iron Triangle with Data 84

Matching Algorithms to Benefits 86 <...