AI got it wrong with high confidence. Now what?

This interview with a data analytics and AI leader argues that the widening gap between what modern AI models do and what operators can explain is already a liability for decisions affecting people or money; it outlines responsible responses to confidently wrong model outputs, the accountability of procurement and vendors, concerns the EU AI Act may induce superficial compliance, and warns that without stronger explainability practices many future systems will be unauditable.