IBM exec says data-related challenges are biggest reason AI projects fall through

Many ambitious artificial intelligence-backed projects never come to fruition due in large part to issues with data collection and cleaning, according to Arvind Krishna, PhD, IBM's senior vice president of cloud and cognitive software.

During an interview with The Wall Street Journal earlier this month, Dr. Krishna noted that a common reason projects using IBM Watson AI often unravel is that companies are unprepared for the amount of time and money they must spend just collecting and preparing data. Those unglamorous yet crucial tasks, he said, make up approximately 80 percent of an entire project.

"You run out of patience along the way, because you spend your first year just collecting and cleansing the data," he said. "And you say, 'Hey, wait a moment, where's the AI? I'm not getting the benefit.' And you kind of bail on it."

Still, Dr. Krishna maintained that the fairly common occurrence of halted AI projects is "the nature of any early technology." Even as so many fizzle out, IBM still has about 20,000 more ongoing AI projects, a number that he deemed indicative of overall success.

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