Zero Trust Security - the concept of "never trust, always verify" - was a term coined by Forrester back in 2010. However, with the prevalence of data breaches today, this concept has taken on a larger role and interest among companies when it comes to security. Furthermore, most data breaches are found to be caused by internal threats and human error. This means companies must not only be monitoring for threats outside of their organization, but also internally. A couple of Gartner's Top Security Projects for 2019 include detection & response, and cloud access security broker (CASB). This should come as no surprise as companies continue to adopt SaaS applications and need AI/machine learning to keep up with the monitoring of all their users and data. A recent Capgemini report also found that 61 percent of enterprises can't detect breach attempts without AI. Machine learning helps companies protect against hackers and account takeovers by knowing locations, devices, IP addresses and times of a typical employee logging into a company's SaaS application, which provides valuable insight regarding unusual account behavior and can be a sign that a user account has been compromised. Machine learning can also help companies understand who exactly is accessing company documents, who the documents are being shared with, where the documents were downloaded from, who is modifying the documents and more. I invited ManagedMethods CEO Charlie Sander onto my daily tech podcast to discuss this topic further. ManagedMethods, is a leading provider of cloud application security solutions for mid-market companies, K-12 school districts and local governments. ManagedMethods provides an award-winning solution that empowers organizations with full and continuous control of cloud application data, including Google G Suite and Microsoft Office 365. ManagedMethods' API-based cloud security solution helps organizations gain data security against internal and external breaches by leveraging AI and machine learning-powered threat detection.