The distribution of malware is ever-changing. Not only are new samples released, but new types of viruses as well. For example, cryptojackers are a relatively recent breed of malware unknown until the advent of cryptocurrency. Interestingly, from a machine learning perspective, it's not only the types and distribution of malware that are evolving, but also their definitions, something known as concept drift. To be more specific, a 15 year-old virus is likely no longer executable in the systems currently in use. Consequently, it cannot harm a user, and is therefore no longer an instance of malware.
By tracking the drift of malware, and even predicting it, an organization is better able to channel its resources to the correct type of defense, inoculating itself from future threats.
