The Myth of Agile AI/Machine Learning in the Enterprise

Today, "Agile" AI/Machine Learning (AI/ML) in the enterprise is largely a myth -- and it has little to do with building a model. Rather, enterprise AI/ML agility is constrained by bureaucratic data acquisition processes, complex security needs, immature cloud security practices, and cumbersome AI/ML governance processes. Unfortunately, in many enterprises these issues have resulted in failed projects, deflated expectations, and perhaps most importantly, missed opportunities to deliver real value. I have spent several years helping large banks accelerate the adoption of AI/Machine learning and related technologies. In this article I will discuss the core issues and obstacles to agile AI/ML in the enterprise that I have experienced and then offer a few lessons learned and some practical steps that provide a starting point for turning the Agile AI/ML myth into reality.