Implementing AI Systems: Transform Your Business in 6 Steps

  • 3h 30m
  • Tom Taulli
  • Apress
  • 2021

AI is one of the fastest growing corners of the tech world. But there remains one big problem: many AI projects fail. The fact is that AI is unique among IT projects. The technology requires a different mindset, in terms of understanding probabilities, data structures and complex algorithms. There is also a need to deal with complex issues like ethics and privacy.

This is where Implementing AI Systems comes in. You'll learn the step-by-step process for successful implementations of AI, backed up with numerous case studies from top companies. This book puts everything you need to know into one place – that is, it’s the handbook you need for AI. You’ll focus primarily on understanding the core concepts for AI like NLP, Machine Learning, Deep Learning and so on.

This book will help you find the right areas to apply AI.

What You’ll Learn

  • Put together an effective data strategy
  • Create models and how to successfully test them
  • Evaluate AI tools
  • Assemble the right team
  • Scale AI across an organization

Who This Book Is For

Primarily for managers, IT professionals and executives of mid-size and large companies wanting to implement AI in their organization.

About the Author

Tom Taulli has been developing software since the 1980s. In college, he started his first company, which focused on the development of e-learning systems. He created other companies as well, including that was sold to InfoSpace in 1996. Along the way, Tom has written columns for online publications such as,, and He also writes posts on Artificial Intelligence for and is the adviser to various companies in the space. You can reach Tom on Twitter (@ttaulli) or through his website ( where he has an online course on AI.

In this Book

  • The AI Landscape—Pros and Cons of the Technology
  • AI Foundations—What can the Technology Really Do?
  • Identify the Problem to be Solved—Where do You Start with Your AI Project?
  • The Team—The Main Roles for Your AI Project
  • Data Preparation—The Fuel for AI
  • Creating the Model—Where the AI Magic Happens
  • Deployment and Monitoring—It's Showtime!
  • Responsible AI—Ethics and Transparency
  • Future of AI—Expect the Growth to Continue for the Long-Term.