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.”