By Mark Cecchini
What is artificial intelligence? If you search for a definition on the Web, you will find a confusing array of meanings. You can even get a little worried if you take some recent science-fiction films too seriously.
But there’s no need to be confused, much less fearful. We’re here to help.
Executive Education at the Darla Moore School of Business, in partnership with the cloud software company Domo, has created a course that will help non-technical executives understand how AI can work for their organizations. It will demystify AI by exploring its history, present and future directions, then showing how participants can implement it to enhance and grow their own companies.
This two-day course will be offered both in-person and virtually from November 29-30, 2022. See the full schedule and learn more about the course here.
Like much of what happens at ExecEd, the idea for this course grew out of relationships developed through our existing programs.
The CFO of Domo, Bruce Felt, is a member of the Business Partnership Foundation here at the Moore School. As I learned more about his company, I started pitching to him an idea for a course we could create together. The scope of the course evolved as we talked about it. My original idea was to do something closer to the Business Analytics courses I teach. But we decided an AI course would offer something new, something that more and more businesses need to know about. Since my research is in machine learning (the engine of AI), it is also a natural fit with my interests and expertise.
According to Deloitte Insights, 28% of companies are getting strong outcomes in AI. The rest are trying to play catch up. While I don’t have state-specific statistics to support this, I think it’s safe to assume that that South Carolina is behind on those statistics. We are trying to help companies that would like to dip a foot into AI, or at least want to put it on their radar. This course is about making AI closer to reality for such companies.
This course takes off in April, but we’ve already tested it out with a pilot program. The participants were BPF board members, and organizations we’re close to through our existing programs – entities such as Coca-Cola, and the U.S. Army. We even had some folks from the Department of Defense’s Joint Artificial Intelligence Center. The pilot was very successful – in the sense that participants learned a lot, and we, the instructors, learned how to make the course more meaningful and successful.
We also learned how valuable it can be to have a partner such as Domo. At one point, a participant mentioned that it would be great if the software could do a certain thing. A Domo team member, who was participating remotely, asked us to hang on a minute, and made a change to the backend software on the spot to make it happen. This is an additional benefit of the software as a service platform of Domo. Changes can be pushed out to the web instantaneously.
I started out talking about definitions. Here’s one from an IBM teaching site:
“At its simplest form, artificial intelligence is a field, which combines computer science and robust datasets, to enable problem-solving. It also encompasses sub-fields of machine learning and deep learning, which are frequently mentioned in conjunction with artificial intelligence.”
The focus of our course probably fits best into that “sub-field” of machine learning. Participants are likely to be interested in using their existing data sets for regular business outcomes such as: loan default probability, how to better manage customer churn, to detect the likelihood of fraud, or how better forecast demand or future sales. These are age-old business problems, but AI is a sharper knife to cut through the noise. Our goal with this program is to start with the practical things, we will leave “Terminator 2” to the movie theaters.
Reach out to us if you want to know more. We look forward to having you participate.
Mark Cecchini is associate dean of Executive Education, and School of Accounting professor and department chair at the Darla Moore School of Business. His teaching and research interests include financial and managerial accounting, information systems, business analytics, control systems and the application of machine learning to business problems.
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