Artificial intelligence (AI) has come in and out of vogue more times than Madonna in the past 20 years: it has been hyped and then, having failed to live up to the hype, been discredited until being revived again. In the late 1990s, an observer at a World Wide Web technology conference reported that most of the proposals there had been floated, several years earlier, under the AI moniker and were now being recycled—good technology solutions looking for real business problems to solve.

AI’s biggest enemy may be the promises made by its proponents—ambitious entrepreneurs looking for venture capital or academics who underestimate the challenge of meeting the needs of business users. Artificial intelligence sounds like a good way to automate everything from entrapping hackers to following money trails, but we are still a long way from Stanley Kubrick’s HAL or Steven Spielberg’s AI.

Nonetheless, the AI-development community has generated techniques that are beginning to show promise for real business applications. Like any information system, AI systems become interesting to business only when they can perform necessary tasks more efficiently or more accurately or exploit hitherto untapped opportunities. What makes AI much more likely to succeed now is...