
As artificial intelligence rapidly transitions from a novel technology into a cornerstone of modern business operations, a critical question emerges with growing urgency: Who pays when an AI makes a costly mistake? This “trust gap,” fueled by profound concerns over liability and unforeseen errors, represents a major barrier to the full-scale enterprise adoption of AI. This article analyzes the emerging










