6 Reasons Why AI Projects Fail
CIO, August 6th, 2019
August 6, 2019,
Volume 257, Issue 1

Data issues are among the chief reasons why AI projects fall short of expectations. But if you can learn from the mistakes and commit to the long term, your AI efforts are more likely to pay off

"Eighteen months ago, Mr. Cooper launched an intelligent recommendation system for its customer service agents to suggest solutions to customer problems. The company, formerly known as Nationstar, is the largest non-bank mortgage provider in the U.S., with 3.8 million customers, so the project was viewed as a high-profile cost-saver for the company. It took nine months to figure out that the agents weren't using it, says CIO Sridhar Sharma. And it took another six months to figure out why..."

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