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Assessing AI Readiness: Planning for Today — and Tomorrow

Part 4 in a series on the journey to AI success.


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No question about it: Artificial intelligence is becoming an increasingly essential component for virtually every type of business — and its importance is likely to escalate in the near future. As Beena Ammanath, executive director of the Deloitte AI Institute, puts it: “Today, AI is no longer an afterthought. Tomorrow, it will be everywhere.”

As established earlier in this series, AI is impacting industries from health care to manufacturing to financial services to retail and beyond. Nearly two-thirds of the 2,700-plus executives who participated in Deloitte’s most recent annual “State of AI” survey report that AI is already giving them a competitive edge. Nearly 75% expect to incorporate AI into every enterprise application with the next three years. And more than three-quarters agree that AI will transform their organizations.

“In the next 10 years, we can expect that access to infrastructures and speed of computing will allow organizations to scale AI like never before,” Ammanath says. The result: a more connected world that might include self-managing supply chains, call centers that know what customers need before they call, extreme levels of individual product personalization, and even satellites that can predict climate-related crises to improve warning and response times. “This all sounds futuristic now, but with the pace of change we’re seeing in the market, it could soon be reality,” Ammanath says.

Meanwhile, one massive AI challenge facing every organization is how to manage today’s initiatives while also planning for what’s down the road.

The AI team at Cleveland Clinic knows all about weighing the big-picture, extended view against the need to quickly solve smaller, more immediate problems. “We have an opportunity right now to revolutionize the entire health care spectrum, from how we research disease and generate discovery to the entire care delivery process,” says Chris Donovan, executive director of enterprise analytics for the 6,500-bed health system, which employs more than 70,000 people in several U.S. and overseas locations. While continuously working toward that ambitious long-term goal, his team continues to tackle a variety of current projects.

One recent example is a model that allows care coordinators to determine which patients within a specific population are most at risk for future health problems or conditions causing increased health care expenditures. “The question is, can we change from acute care — that is, making you better — to preventative care — that is, keeping you from getting sick?” Donovan says. The team built a model with algorithms that use predictive risk scores to identify such patients, including those who aren’t showing symptoms of a particular condition but appear to be moving in that direction. “By using that score and the results, we can provide that information to our care coordinators. They can use that to inform their work and decide which patients to focus on and reach out to first,” he says. “That’s been really successful.”

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