The objective of any model is to test a hypothesis and determine if it can describe reality. The traditional research approach has been one of developing a hypothesis and designing of an experiment to prove or disprove the idea given a known set of parameters. The artificial intelligence (Ai) approach, on the other hand, is one of rapid iteration that augments analytical capabilities. Given that this computational approach lends itself to the use of vast amounts of unbiased data, its adoption is transforming the research landscape and offering insights that were often overlooked in the past. This presentation will provide an overview of Ai techniques, their purpose, uses and data collection with the goal of offering clarity on present and future possibilities. With the development of Ai, machine learning and deep learning technologies, we are coming ever closer to describing and simulating reality. The direction and limitations of Ai as they apply to the future of animal agriculture will be discussed.