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IBM insists its revised AI strategy – a scaled down, less world-changing goal – is working. The job of stimulating growth was entrusted to Arvind Krishna, a computer scientist who became CEO last year after leading the recent overhaul of IBM’s cloud and artificial intelligence businesses.

But the great visions of the past are gone. Today, rather than shorthand for technological prowess, Watson stands out as a sobering example of the technological hype and arrogance traps around artificial intelligence.

Artificial intelligence’s march in the mainstream economy will be more of a step-by-step evolution than a disaster revolution.

A New Wave to Ride

In its 110-year history, IBM has repeatedly pioneered new technologies and sold it to companies. The company has so dominated the mainframe market that it has been the target of a federal antitrust lawsuit. PC sales really increased after IBM entered the market in 1981, confirming small machines as essential tools in corporate offices. In the 1990s, IBM helped traditional enterprise customers adapt to the Internet.

IBM executives began to see AI as the next wave to take off.

Mr. Ferrucci first presented the idea for Watson to his bosses at IBM’s research labs in 2006. He thought that building a computer to tackle a question-and-answer game could advance science in the field of artificial intelligence, known as natural language processing, where scientists program computers. recognize and analyze words. Another research goal was to develop automated question answering techniques.

After overcoming initial skepticism, Mr. Ferrucci assembled a team of scientists—eventually more than two dozen—working at the company’s lab in Yorktown Heights, NY, about 32 miles north of IBM’s headquarters in Armonk.

The Watson they built was a room-sized supercomputer with thousands of processors running millions of lines of code. Storage disks were filled with digitized reference works, Wikipedia entries, and electronic books. Computing intelligence is brute-force work, and the massive machine required 85,000 watts of power. In contrast, the human brain works with the equivalent of 20 watts.