Implementing AI Systems

Guest Forward (Say from a CEO/founder of an AI company)

Introduction (Quick overview of what the book will cover, chapter-by-chapter)

Chapter 1: AI Landscape
ΓÇóLook at the growth opportunities and the need for digital transformation. But also highlight the challenges with AI implementations.
Chapter 2: Identify The Problem To Be SolvedΓÇóThe problem can be internal (such as with improving operations) or external (helping to provide better customer experiences). This chapter will look at cases where companies have been successful with this.
Chapter 3: Data Preparation
ΓÇóThis often does not get enough attention. But data preparation is absolutely essential and full of mine fields. There will be a look at how to identify/clean the data, such a with various tools and techniques. This chapter will also describe strategies for data ethics, governance, provenance and compliance.
Chapter 4: Building the AI Team
ΓÇóThis shows what skillsets are required and how to recruit the right people. There will also be a look at setting up the right incentives, roles and duties.
Chapter 5: Creating the Model
ΓÇóThis chapter will focus on what algorithms to use, how to select the parameters and how to test/train the models. There will also be coverage on the various types of tools to select and when to create in-house ones.
Chapter 6: Deploy The Model
ΓÇóHere there is a look at strategies for having limited releases and rollouts. There will also be a look at different approaches for the design of the UI so as to get better adoption.
Chapter 7: Monitoring
ΓÇóThis chapter will show how to keep track of the model and know when to make changes/upgrades.
Chapter 8: Scaling AI
ΓÇóThis has proven to be extremely difficult for organizations. So in this chapter, there will be a look at strategies to show how AI can move the needle.
Chapter 9: The Future
ΓÇóAgain, there needs to be a different mindset. Thus, for a successful AI implementation, it''s important to look at change management strategies.
Chapter 10: The Future
ΓÇóThis will be a recap of the main takeaways of the book and also a look at major trends with AI.
Appendix A: Resources like blogs, videos and websites
Appendix B: AI Tools (TensorFlow, DataRobot, Microsoft AI Builder, etc)
Appendix C: AI Glossary