Artificial Intelligence for Business. Jason L. Anderson

      

      Table of Contents

      1  Cover

      2  Preface

      3  Acknowledgments

      4  CHAPTER 1: Introduction Case Study #1: FANUC Corporation Case Study #2: H&R Block Case Study #3: BlackRock, Inc. How to Get Started The Road Ahead Notes

      5  CHAPTER 2: Ideation An Artificial Intelligence Primer Becoming an Innovation-Focused Organization Idea Bank Business Process Mapping Flowcharts, SOPs, and You Information Flows Coming Up with Ideas Value Analysis Sorting and Filtering Ranking, Categorizing, and Classifying Reviewing the Idea Bank Brainstorming and Chance Encounters AI Limitations Pitfalls Action Checklist Notes

      6  CHAPTER 3: Defining the Project The What, Why, and How of a Project Plan The Components of a Project Plan Approaches to Break Down a Project Project Measurability Balanced Scorecard Building an AI Project Plan Pitfalls Action Checklist

      7  CHAPTER 4: Data Curation and Governance Data Collection Leveraging the Power of Existing Systems The Role of a Data Scientist Feedback Loops Making Data Accessible Data Governance Are You Data Ready? Pitfalls Action Checklist Notes

      8  CHAPTER 5: Prototyping Is There an Existing Solution? Employing vs. Contracting Talent Scrum Overview User Story Prioritization The Development Feedback Loop Designing the Prototype Technology Selection Cloud APIs and Microservices Internal APIs Pitfalls Action Checklist Notes

      9  CHAPTER 6: Production Reusing the Prototype vs. Starting from a Clean Slate Continuous Integration Automated Testing Ensuring a Robust AI System Human Intervention in AI Systems Ensure Prototype Technology Scales Cloud Deployment Paradigms Cloud API's SLA Continuing the Feedback Loop Pitfalls Action Checklist Notes

      10  CHAPTER 7: Thriving with an AI Lifecycle Incorporate User Feedback AI Systems Learn New Technology