AI risks, such as model errors and omissions, robotic miscues, and compliance issues, have led to substantial financial consequences. As a result, organizations are cautious. A recent Gartner report predicts by the end of 2025, 30% of generative AI projects will be abandoned after proof of concept due to factors like inadequate risk controls, escalating costs, poor data quality, or unclear business value. Although the report’s chart below provides valuable comparisons, imagine if it also included a quantified risk analysis, with additional rows for coverage limit, premium, and maximum risk tolerance, like an internal insurance policy.