AI implementation requires a new type of manager

Over the past few decades (beginning with Peter Drucker) the study of management has steadily grown. Organizations began to realize that managers and leaders are not simply born, they need to be crafted, tested, and provided a culture that enables their success. Seth Godin, the entrepreneur/author, said it best, “Management involves very little in the way of shouting, hustling, or coercion. It's a chance to serve, instead.”

At its core, management is about articulating a set of values the organization is to follow, and adequately communicating these values so they become apparent in everything the organization does. Management provides a context of values, and individuals respond. This dynamic seems to operate best when there is a common understanding of those values in addition to the broad business goals of the organization. This has held true for the past many years when business goals and operations were well understood by both management and operational employees. With the emergence of artificial intelligence as a scalable tool, this dynamic seems to have changed.

Without an in-depth understanding of the complex tools that AI enables, management is unable to communicate effectively with their highly technical operational employees. Management becomes siloed from the key operations of the business. Highly technical employees build products and processes they believe to be valuable, but are in fact not aligned with the values of management. Management misunderstands the capabilities of AI and create strategies that the technology cannot support. The result is wasted time and resources, disappointed customers, low employee engagement, and the risk of being left behind as competitors successfully increase their technological capabilities.

To solve this problem, organizations now need an AI translator - a manager who oversees the entire team. The ideal manager knows quite a bit about analytics and AI and understand the technical capabilities of the organizations software engineers and data scientists. These managers also have the business skills to interact with upper management and can translate business strategy into a data science solution.

Over the next 12 months I will be working to become this translator. The training involves the mathematical and programming aspects of AI. My classmates and I will learn how to operate in the Agile framework and how to apply it to the strategic priorities of businesses in several sectors. Ultimately, the course provides the guidance necessary to become a catalyst in re-imagining the operations of an enterprise with the successful application of AI.

This blog is my way of sharing some of my learnings. My hope is that it helps shape some of your thinking around the practice of management and how you can remain an effective manager in the fast-changing world of AI.

Thanks for joining me at the beginning of this journey!