CIOs achieving AI success in ‘small iterative steps’

Craig Stephenson, senior client partner and managing director of the North America CIO/CTO Practice at Korn Ferry, has a keen sense of what companies need from IT executives. In recent years, the veteran headhunter has placed CIOs and chief digital officers at Express Scripts, Fannie Mae, KPMG, DuPont, American Express Global Business Travel, TSYS and Goldman Sachs.

At the 2019 MIT Sloan CIO Symposium, “Leading the Smarter Enterprise,” Stephenson participated in a panel on the four paths companies typically take to transform their business models for success in the digital era.

Here, in this short video filmed at the event, Stephenson shares his thoughts on how CIOs are using AI to build the smart enterprise and singles out a common roadblock that stands in the way of AI success.

Editor’s note: The following has been edited for clarity and length.

What are the chief ways that CIOs are using AI to build the smart enterprise?

CIOs are dealing with a tremendous amount of challenge and pressure this day and age; the pace of change only continues to accelerate. And certainly data, AI and ML are all issues that they are addressing in a very rapid pace. As it relates to AI, they’re learning very quickly on the fly. And I think they’re taking small iterative steps to try to get things accomplished, to create greater insights, and certainly anything to do around the lines of analytics as it relates to business information, data, et cetera, will go a long, long way in helping the organization move forward.

For organizations that haven’t achieved AI success, what are the biggest roadblocks?

Some of the organizations that are experiencing challenges with AI — and you could throw in similar challenges with cyber or data, or digital — really has a lot to do with the fact that the … key stakeholders are not aligned. And so what that means is that it’s much harder to make accomplishments on things that are emerging or trending. And you have to get that buy-in established to have dollars to invest and go forward.

So, as a result, I would say there are probably pockets of [AI] success in some of those organizations. But to the extent it takes so much time to educate, bring people up to speed and to gain that buy-in and consensus, it can be really, really hard for organizations to make great progress there.

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