“Arijit Sengupta once wrote an entire book titled Why A.I. is A Waste of Money. That’s a counterintuitive title for a guy who makes his money selling A.I. software to big companies.
That’s borne out in a slew of recent surveys, where business leaders have put the failure rate of A.I. projects at between 83% and 92%.
Aible makes an unusual pledge in the A.I. industry: it promises customers will see positive business impact in 30 days, or they don’t have to pay. Their website is chock full of case studies.
The key, Sengupta says, is figuring out what data the company has available and what it can do easily with that data. ‘If you just say what do you want, people ask for the flying car from Back to the Future,” he says. “We explore the data and tell them what is realistic and what options they have.’
One reason most A.I. projects fail, as Sengupta sees it, is that data scientists and machine learning engineers are taught to look at ‘model performance’ (how well does a given algorithm do with a given data set at making a prediction) instead of business performance (how much money, in either additional revenue or cost-savings, can applying A.I. to a given dataset generate).”