Most AI/machine learning projects report only on technical metrics that don’t tell leaders how much business value could be delivered. To prevent project failures, press for business metrics instead.
These developing issues should be on every leader’s radar screen, data executives say.
Business leaders must make the right calls on whether and how broadly to deploy AI models. Ask these tough questions.
Determining whether an AI solution is worth implementing requires looking past performance reports and finding the ground truth on which the AI has been trained and validated.
Connectors can bridge the organizational gaps that often thwart success with data science projects. Here’s how to manage this new kind of data professional.
