Addressing Operational Disciplines on the AI Ladder

This chapter explores scenarios that organizations may encounter on their journey toward leveraging artificial intelligence (AI) for predicting, automation, and optimization. The scenarios are viewed across the contexts of various xOps approaches as a means toward continual operational improvement. xOps is a shorthand way to indicate various types of operational disciplines that are helpful for managing robust analytical platforms for AI and other forms in an agile and sustainable manner. The use of iterative design and receiving feedback is an essential part of developing a data topology and building an information architecture. First and foremost, the information architecture must adequately serve all of the applications and AI models that need data in a timely and consistent manner. Protecting the data so that the information can be viewed only by authorized users and addressing the increasing number of privacy rules and regulations can only be accomplished through forethought.