This article highlights interesting applications of machine learning in the oil and gas industry in drilling, formation evaluation, and reservoir engineering. Each project uses a data-driven model to solve a previously complex problem using machine learning to augment an existing solution. Considering most of the rigs deal with human-machine interface systems, the role of human factors is at the heart of any successful operation. Eye-tracking technology can be useful in real-time operation centers where ocular movement data can improve the professionals’ performance. As the petroleum engineering discipline embarks on its second century of existence, what changes will academia make to keep up with the times?