There are numerous classifications and definitions for Artificial Intelligence (AI) and these are evolving almost daily but, my simple view splits the technologies into 2 categories: Machine Learning , which includes automation and robotics (a.k.a. bots) . Analytics , which includes decision support (data manipulations to diagnose, optimize, or provide a result) and predictive support (forecasts and simulations to identify patterns, trends, and outcomes). Data literacy skills are essential to validate assumptions, confirm accuracy and ensure proper use of data in all areas of AI. Be sure your Data Scientist is more than just a statistician. The completeness, context and content of the data must be constantly appraised. So, once the number crunching is done, the results are available and the data-driven decisions are made, what's next? The next exciting challenge is to actually USE the results to improve your business. A few things to consider: ...