In the realm of cybersecurity, humans are reaching the limit of what they are capable of handling. While it would be ideal for humans to be the ones that solve every problem, the scale and quantity of attacks in recent years has proven that we need to bring AI and machine learning into the toolkit. These methods would allow for significantly faster responses to threats (potentially being able to stop them altogether) and ultimately remove some of the strain on the system. While machines can't guard against all potential threats, they are especially well suited for certain attacks such as those that take place over a network, and can even go so far as to classify certain attacks in order to allow for easier identification. While an inherent flaw of machines is that they can be spoofed and tricked, this paper proposes that the quirks of the systems can be troubleshooted and worked out given proper monitoring and testing.