Roadmap to learn about AI (for business leaders)

Artificial Intelligence (AI) has finally passed its hype summit and is now beginning to be integrated in daily operations. Now, it is being used to power chat bots and recommendation engines, and more applications are being announced all the time. In fact, most business leaders now take it for granted that AI will be a transformative technology. This means that knowing how, where, and when to incorporate these new capabilities into your business could well determine your company’s future.

But before you can make those decisions, you’ll need to learn how it works. AI isn’t like some earlier technologies, such as Enterprise Resource Planning (ERP), where you could afford to stand back and let your vendor take charge. The ways AI can impact your business are so varied and profound that you should be involved in designing and prioritizing the AI related programs.

Grasping even the basics of this technology takes time. To help you fast-track your AI learning I wanted to gather below the best programs, books and websites (according to my opinion). I believe that working your way through this list will enable you to develop a good understanding of the new technology in an accelerated time period.

I have divided this list into a three-part curriculum designed to get you up to speed on AI in just a few months:


1. Why does AI matter?

AI creates value in various ways (e.g. finds patterns, forecasts events, classifies images), principally through machine learning or deep learning. Unlike traditional programming, where every command must be written in advance, machine and deep learning iteratively develop their models with data and find the optimal outcome without being specifically programmed to complete that particular task.

I designed this section of the curriculum to lead you to more questions, such as why has AI become relevant so suddenly? How are companies applying it now? How will AI affect society and geopolitical relations? Take a look at:


The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies, Erik Brynjolfsson and Andrew McAfee

Superintelligence: Paths, Dangers, Strategies, Nick Bostrom

AI superpowers: China, Silicon Valley, and the New World Order, Kai-Fu Lee

Web sites and magazines:

AI Monday event / MIT tech review / Medium

Podcasts in Spotify and iTunes:

AI in industry / Exponential view / Anatomy of Next


2. What are the building blocks of AI?

After digesting the terminology, key concepts, and reasons for the AI boom, you will need to lift the bonnet to see how the actual engine works. In this section, you will look further into both machine learning and deep learning algorithms. You may need to refresh your high school mathematics a bit, particularly linear algebra, derivatives, and probability. Your goal will be to understand the kinds of problems these algorithms can solve, and which sort is best suited for which kind of challenge.

My recommendations include:


Architects of Intelligence: The truth about AI from the People Building It, Martin Ford (One of the Financial Times’ Best Books of the Year, 2018)

The Book of Why? The New Science of Cause and Effect, Judea Pearl and Dana Mackenzie

Prediction machines: The Simple Economics of Artificial Intelligence, Ajay Agrawal, Joshua Gans, and Avi Goldfarb

Podcasts in Spotify and iTunes:

Machine Learning guide

Web sites:

Medium (search for Machine learning or Deep learning) / Youtube, e.g. presentation by Siilasmaa


AI camp  (Over 170,000 people have signed up for the Elements of AI course. Produced by University of Helsinki and Reaktor)


3. How does it really work?

The final step in your journey is to develop a simple machine learning or deep learning program. I understand that investing more than two workweeks is a lot to ask, but it’s actually the best way to get a sense for what AI can and cannot do for you. I guarantee that the hands-on experience of developing your own AI program will give you a deep understanding of the power of an AI algorithm.

I suggest you check out:


Introduction to Machine Learning with Python, Andreas Müller and Sarah Guido

Make your own Neural network: An In-depth Visual Introduction with Python, Michael Taylor and Mark Koning


Coursera, Andrew Ng / Google training / Aalto Executive Education. (mostly free or low price).

A few skeptics say AI is just the flavor of the week, and in another year, will be replaced by another trendy technology. I disagree. With AI, we are already long past that point. Many industries are already using machine learning to improve their understanding of their customers and the productivity of their employees. Executives who don’t want to be left behind and would like to take advantage of their company’s current opportunities should start studying now. Once you educate yourself about AI and its potential applications, you will start seeing opportunities everywhere!