The ever-growing data landscape drives initiatives to automate many aspects of the analytics lifecycle. From data access, enablement of semantics, and cataloging to BI and analytics, automation has become an integral part of our daily lives. Without learned automation being offered within the enterprise, it would be nearly impossible for us to grasp the vast data we have access to and more importantly, make sense of it. The logical architectures drive the modern implementations. Real-time data access leaves little room for error within the BI and analytics world. We are looking at enterprise solutions to offer us guidance and provide guard rails when we work with data. With that, we have to embrace and acknowledge the AI initiatives within our BI and analytics.