The goal of this final work is the education of the readers on the subject of “artificial intelligence in a business sense”. The readers will learn about the important aspects of artificial intelligence and its use in the business world. They will learn about machine learning, its algorithms and its classification into supervised and unsupervised machine learning. Both of these classifications will be thoroughly described and simplified using examples. Machine learning will be defined and its algorithms and methods will be listed. This work will describe the regression and classification problems of supervised learning and will describe the aspects of unsupervised learning such as vocal recognition and neural networks. Voice recognition will be thoroughly worked through using an example of a program that uses it. The work is filled with graphs and tables that additionally explain the subject at matter. The readers will learn about lots of possible current and future uses of artificial intelligence in the business world and will be shown examples of the aforementioned uses. The comparison between supervised and unsupervised learning will be covered and so will the differences between classification and regression problems and algorithms. The readers will also gain knowledge of the differences between artificial and biological neural networks. The result of this work is a simplified source of information regarding artificial intelligence in the business world, machine learning, neural networks and so on... The work contributes to the scientific and educational communities by providing an additional way to access information and an aggregated data set on the subject at hand.