Artificial intelligence in the enterprise: It’s on

Companies as diverse as Pitney Bowes, General Electric, and Twitter are taking the plunge into machine learning. Here’s why

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After a long winter frozen in the technological permafrost, it's springtime again in the field of artificial intelligence.

A.I. is poised to take off in 2016 as enterprises begin figuring some element of it into their application portfolios. By 2018, artificial intelligence will be incorporated into about half of all apps developed, according to research firm IDC, and by 2020, savings fueled by A.I. -- in reduced people costs and increased workflow efficiencies, for example -- are expected to total an estimated $60 billion for U.S. enterprises.

Why A.I. now, when it was considered dead and buried a decade ago? The answer is cheap computer processing power and the allure of secrets buried amid a torrent of data that didn't exist in such voluminous quantities then.

"During the 'A.I. winter,' we didn't have enough data and computer processing power" to make the field technologically or economically practical, says IDC's director of cognitive systems and content analytics David Schubmehl.

Starting around 2013, things began to change. "Now we have plenty of computing power and more data than we know what to do with," he says. "We're still in the early days, but we have better machine-learning algorithms. The Siri of today is much smarter than five years ago. Siri five years from now will be tied into digital assistants and do even more stuff."

Within the typical enterprise, A.I. most often takes the form of machine learning -- that is, developing and deploying algorithms that can learn from and make predictions on large sets of data.

Machine learning should be at the top of every watch list kept by C-level executives, line-of-business heads and marketers, says Schubmehl. "CIOs may not have to do anything in 2016, but they sure should be thinking about it," he says.

Thinking, yes, and keeping close tabs on organizations that are taking a decisive leap into artificial intelligence. Read on for in-depth details on A.I. projects from heavy hitters such as Pitney Bowes, General Electric and Twitter.

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