Starting the AI journey as a knowledge manager
1 August 2021
Dr. Moria Levy
KMGN KM-AI course, session 21. We are approaching the last set of lectures in this course. Today Annie led the session and hosted Jay Zeidi, discussing and answering students' queries on the one-million-dollar question: How do we start? How can we put our foot in the door, and what shall we say so that we are invited to stay and join or even initiate an AI project?
So here we go:
Understand the business challenge. Do not speak in terms of AI or KM; instead, listen to what is on the customer's mind. Seek for the business need and understand it. Understand why the people you are speaking with are bothered. In some cases, the challenge and needs are enormous and should be narrowed down- scoped to some reasonable project. In other cases, they are tacit, and the process to uncover them will take some time. And, of course, there are circumstances where all is clear, and we can proceed.
Outline the possible solution and outcome. Take into consideration existing and potential data and the organizational context. Show how the challenge can be solved using AI.
Demonstrate similar projects, drawing confidence in the person you are speaking with.
In some cases, before you entered the door, all of the above has already been performed. So how do we, the knowledge managers, fit in?
I popped into such a situation a few weeks ago. An AI project was to begin, yet the business manager did not think to add in the knowledge manager. Too many people were already trying to jump on the AI wagon. I listened carefully, then started explaining the first steps of knowledge engineering to be taken, using terms of knowledge and data. The business manager understood at once that KM is crucial and that I have the knowledge and ability to walk him through this journey.
So, as we always say- start with listening. Add value. Be practical.
At the end of the day, we, as knowledge managers, have so much to offer here.
This post was initially published in LinkedIn