This is an excerpt from the original article published on InformationWeek.
You have been tasked with using artificial intelligence to predict when you might lose a customer. You work with historical data and business stakeholders. You build a model that shows it could have predicted lost customers a few weeks before they churned. You show the algorithm off, prove it can work and demonstrate how much it will save the company in lost revenue. Leadership likes it. It’s time to implement it. Now what? This is where eight out of 10 AI projects fail, not because the tech doesn’t work but because moving from a one-and-done experiment to a fully operationalized enterprise solution requires different skills.