Artificial Intelligence Software Is Booming. But Why Now?

Marc Benioff, left, chief executive of Salesforce, talked with Matthew Panzarino, editor in chief of TechCrunch, at its Disrupt conference in San Francisco last week. Credit Beck Diefenbach/Reuters

SAN FRANCISCO — This is the year artificial intelligence came into its own for mainstream businesses, at least as a marketing feature.

On Sunday, Salesforce.com, which sells online software for sales and marketing, announced it would be adding A.I. to its products. Its system, called Einstein, promises to provide insights into what sales leads to follow and what products to make next.

Salesforce chose this date to pre-empt Oracle, the world’s largest business software company, which on Sunday evening began its annual customer event in San Francisco. High on Oracle’s list of new features: real-time analysis of enormous amounts of data. Oracle calls its product Oracle A.I.

Elsewhere, General Electric is pushing its A.I. business, called Predix. IBM has ads featuring its Watson technology talking with Bob Dylan. These moves, along with similar projects at most major tech companies and consulting firms, represent years of work and billions in investment.

There are big pushes in A.I. in agriculture, manufacturing, aviation and pretty much every other sector of the economy.

It’s all very exciting, the way great possibilities are, and clearly full of great buzzwords and slogans. But will other companies see any value in all this or understand if A.I. has value for them?

“No one really knows where the value is,” said Marc Benioff, co-founder and chief executive of Salesforce. “I think I know — it’s in helping people do the things that people are good at, and turning more things over to machines.”

Mr. Benioff wasn’t selling Einstein’s capabilities short. He was talking about the long-term value of artificial intelligence, which is passing through a familiar phase — a technology that is strange and new, that sometimes overpromises what it can do and is headed for uses not easily seen at the start.

Cloaked inside terms like deep learning and machine intelligence, A.I. is essentially a series of advanced statistics-based exercises that review the past to indicate the likely future, or look at current customer choices to figure out where to put more or less energy.

Perhaps a better question than “What is the value?” of this explosion of advanced statistics is “Why now?” That shows both the opportunity and why many companies are scared about missing out.

Much of today’s A.I. boom goes back to 2006, when Amazon started selling cheap computing over the internet. Those measures built the public clouds of Amazon, Google, IBM and Microsoft, among others. That same year, Google and Yahoo released statistical methods for dealing with the unruly data of human behavior. In 2007, Apple released the first iPhone, a device that began a boom in unruly-data collection everywhere.

Suddenly, old A.I. experiments were relevant, and money and cheap data resources were available for building new algorithms. Ten years later, computing is cheaper than ever, companies live online and in their phone apps, and sensors are bringing even more unruly data from more places.

Amazon, Google and the rest have exceptional A.I. resources for sale, but many older companies are wary of turning their data over to these upstarts. That, along with fear of a competitor getting on top of A.I. first, is a big motivation for some to try things out.

Salesforce is selling Einstein as a system that can work predictive magic without having to look at your data, in what Mr. Benioff calls a “democratizing” move that will create millions of A.I. users who are not engineers.

He said this on his way to attend a series of customer focus groups around the country, however — strong evidence that customers don’t get it yet, even if they’re willing to try it.

“There’s fear of Google and Microsoft controlling everything, and there’s a desire to apply A.I. to anything that’s digital,” said Michael Biltz, managing director of Accenture’s technology vision practice. “People are going to have to experiment, most likely first on pain points like security and product marketing.”

How will we know when the A.I. revolution has taken hold? A technology truly matures when it disappears. We don’t marvel at houses with electricity now, or the idea of driving to work at 60 miles an hour. We can say “phone” and mean a hand-held computer with NASA-level processing power and a professional-quality camera for taking selfies with our drones.

A.I. is probably heading for the same places, invisibly sorting through lots of data everywhere to continuously update and automate most of our lives. Goodness knows what the weird new tech thing will be about at that point.

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