Artificial Intelligence for Business A Roadmap for Getting Started with AI.

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Anderson, Jason L.
Otros Autores: Coveyduc, Jeffrey L.
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Newark : John Wiley & Sons, Incorporated, 2020.
Temas:
Artificial intelligence > Economic aspects.
Intelligence artificielle > Aspect économique.
Artificial intelligence > Economic aspects
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Intro
  • Table of Contents
  • Preface
  • Acknowledgments
  • CHAPTER 1: Introduction
  • Case Study #1: FANUC Corporation
  • Case Study #2: HR Block
  • Case Study #3: BlackRock, Inc.
  • How to Get Started
  • The Road Ahead
  • Notes
  • 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
  • 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
  • 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
  • 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
  • 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
  • CHAPTER 7: Thriving with an AI Lifecycle
  • Incorporate User Feedback
  • AI Systems Learn
  • New Technology
  • Quantifying Model Performance
  • Updating and Reviewing the Idea Bank
  • Knowledge Base
  • Building a Model Library
  • Contributing to Open Source
  • Data Improvements
  • With Great Power Comes Responsibility
  • Pitfalls
  • Action Checklist
  • Notes
  • CHAPTER 8: Conclusion
  • The Intelligent Business Model
  • The Recap
  • So What Are You Waiting For?
  • APPENDIX A: AI Experts
  • AI Experts
  • Chris Ackerson
  • Jeff Bradford
  • Nathan S. Robinson
  • Evelyn Duesterwald
  • Jill Nephew
  • Rahul Akolkar
  • Steven Flores
  • APPENDIX B: Roadmap Action Checklists
  • Step 1: Ideation
  • Step 2: Defining the Project
  • Step 3: Data Curation and Governance
  • Step 4: Prototyping
  • Step 5: Production
  • Thriving with an AI Lifecycle
  • APPENDIX C: Pitfalls to Avoid
  • Step 1: Ideation
  • Step 2: Defining the Project
  • Step 3: Data Curation and Governance
  • Step 4: Prototyping
  • Step 5: Production
  • Thriving with an AI Lifecycle
  • Index

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