Another hot buzzword topic, often purposely conflated with true Artificial Intelligence, is Machine Learning. Machine Learning is also used by vendors as a term for what is really Robotic Process Automation. While the three coexist and can bleed over into each other, you should know the differences between them and why they might or might not be of value to you.
According to Chris Bishop, director of the Microsoft Lab at Cambridge and professor at the Universities of Cambridge and Edinburgh, Machine Learning should be seen as a subset of artificial intelligence. Machine learning algorithms build a mathematical model of sample data, known as “training data”, in order to make predictions or decisions without being explicitly programmed to perform the task. Machine learning algorithms are used in the applications of email filtering, detection of network intruders, and computer vision, where it is infeasible to develop an algorithm of specific instructions for performing the task. Machine learning is closely related to computational statistics, which focuses on making predictions using computers. The study of mathematical optimization delivers methods, theory and application domains to the field of machine learning.
Machine learning uses large data sets to recognize patterns and make decisions about active data streams.
Again, like Artificial Intelligence, Machine Learning applications are currently of limited value at the management level to small business owners. You want your database and DMS protected by Machine Learning algorithms, but that would be contracted out by your database solution provider, not by you or your IT guy.