Tom Davenport says AI is entering its second stage

Artificial intelligence is set this year to go mainstream as organizations implement AI into an increasing number of decision-support system and design ever-smarter machines.

For an idea on just how hot, artificial intelligence professionals are showing up on a number of the top technology job reports for most in-demand job roles. One study suggested AI professionals could soon overtake the data scientist for the number one slot.

One expert that sees the trend first hand is Tom Davenport, President’s Distinguished Professor of Information Technology and Management at Babson College, and cofounder of the International Institute for Analytics.

Davenport says early adopters of artificial intelligence are now ready for phase two – putting it to work for customers and getting real value from it.

In addition to his work at Babson, Davenport is also a Fellow at the MIT Initiative on the Digital Economy and a senior advisor to Deloitte Analytics. He teaches analytics and big data in executive programs at Babson, Harvard Business School and School of Public Health, and MIT Sloan School. His areas of expertise include robotics, autonomous vehicles, self-driving cars, artificial intelligence, and many other topics.

Davenport says he sees three primary trends in artificial intelligence in 2017:

“I think the artificial intelligence activities in many companies so far have been basically ‘science projects,’” Davenport acknowledges. “But I’ve talked to a number of companies over the past few weeks that are quite serious about putting AI into some sort of actual production environment, whether it’s for customer service, or in some cases embedding it into a product.” A perfect example is deep learning, a branch of artificial intelligence that enables a product to make recommendations to the customer based on prior experience, Davenport says.

“I think the time for experimentation on the part of the early adopters – the most sophisticated companies – is past. Now we’re moving toward actual production,” Davenport says.

This bodes well for data professionals who have an early lead on prized AI skills, Davenport says. So far, the majority of those professionals work for top vendors or consultancies. But AI skills are rapidly rising to the top of the demand ladder in a number of industries.

“I think there probably aren’t more than 100 people in the world that are really knowledgeable about deep learning, for example, and most of them work for the leading companies out on the West Coast,” Davenport says. “It’s going to be a challenge.”

So what separates the early adopters from the rest of the pack when it comes to AI work?

“Assembling a set of capabilities,” Davenport says. “Getting the people together that can do this work and that have a portfolio of different types of projects.