The best books about artificial Intelligence (AI) and machine learning for managers and business leaders

Steve Finlay Author Of Artificial Intelligence and Machine Learning for Business: A No-Nonsense Guide to Data Driven Technologies
By Steve Finlay

Who am I?

I have worked in the field of machine learning and predictive analytics for many years. Having started out as a technical specialist, I have become increasingly interested in the legal, ethical, and social aspects of these subjects. This is because it is these “soft issues” that often determine how successful these technologies are in practice and if they are viewed as a force for good or evil in wider society. This has led me to write several books focusing on the practical and cultural aspects of these subjects and how best to apply them for the benefit of business, individuals, and wider society.


I wrote...

Artificial Intelligence and Machine Learning for Business: A No-Nonsense Guide to Data Driven Technologies

By Steve Finlay,

Book cover of Artificial Intelligence and Machine Learning for Business: A No-Nonsense Guide to Data Driven Technologies

What is my book about?

Artificial Intelligence (AI) and machine learning are proving to be the most transformative technologies of our age. This book cuts through the hype and technical jargon that is often associated with these subjects. It delivers a simple and concise introduction for managers and business people. The focus is on practical application and how to work with technical specialists (data scientists) to maximize the benefits of these technologies.

The books I picked & why

Shepherd is readers supported. When you buy through links on our website, we may earn an affiliate commission. This is how we fund this project for readers and authors (learn more).

Prediction Machines: The Simple Economics of Artificial Intelligence

By Ajay Agrawal, Joshua Gans, Avi Goldfarb

Book cover of Prediction Machines: The Simple Economics of Artificial Intelligence

Why this book?

In my experience, most of the books about AI and machine learning are written by people coming from a technical background. The thing I found refreshing about this book is that the authors are economists, not technologists. Therefore, they bring a somewhat different perspective to the subject. In particular, focusing on the fact that the foundation of almost all successful AI-based technologies is providing better ways to predict things of interest. This covers a huge range of applications from object recognition, to fraud prevention to strategic forecasting, and everything in between.


Human Compatible: Artificial Intelligence and the Problem of Control

By Stuart Russell,

Book cover of Human Compatible: Artificial Intelligence and the Problem of Control

Why this book?

As ever more powerful AI-based tools are created, Russell asks the question (and provides some answers) as to how we can ensure that we stay in the control of our creations. In particular, what safeguards are needed to protect us from something that will potentially be more intelligent than ourselves? Some might argue that this is all just science fiction and, even if it’s possible to build machines that are more intelligent than we are, it’s a problem for the distant future. However, there are many areas where AI is already making the key decisions about how we are treated. For example, whether or not to offer you a job or if you should get that loan you applied for. Consequently, I found this book to present a compelling case that controlling AI is something that we need to address as a matter of urgency, sooner rather than later.


Human + Machine: Reimagining Work in the Age of AI

By Paul R. Daugherty, H. James Wilson,

Book cover of Human + Machine: Reimagining Work in the Age of AI

Why this book?

Many writers have discussed the dangers that artificial intelligence and machine learning represent to our livelihoods, and how clever computers and autonomous robots will supplant us all in the workplace. What I like about this book is that it provides an alternative, and very optimistic, view of how these new technologies are being deployed. The authors present a future based on a partnership, in which artificial intelligence-based tools work in tandem with human workers, enhancing what individuals can do in the workplace rather than replacing them.


Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy

By Cathy O’Neil,

Book cover of Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy

Why this book?

Computers can be very clever and make near-perfect decisions in the right circumstances, but they are just machines. They are designed to perform certain tasks and make certain decisions, but they have no moral compass and no conscience. This means that if not designed properly, and without proper human oversight, they can drive unfair and biased decision-making that negatively impacts the lives of those subject to their decisions. This book was one of the first to highlight the “Dark side” of machine-based decision-making and bring it to the public’s attention. Through the use of many examples, it catalogues cases where the reliance on automated decision-making systems has led to poor outcomes, bias, and unfair judgments against certain sections of society.  


5 book lists we think you will like!

Interested in artificial intelligence, machine learning, and statistics?

5,309 authors have recommended their favorite books and what they love about them. Browse their picks for the best books about artificial intelligence, machine learning, and statistics.

Artificial Intelligence Explore 100 books about artificial intelligence
Machine Learning Explore 31 books about machine learning
Statistics Explore 16 books about statistics

And, 3 books we think you will enjoy!

We think you will like The Deep Learning Revolution, Discriminating Data: Correlation, Neighborhoods, and the New Politics of Recognition, and The Alignment Problem: Machine Learning and Human Values if you like this list.