Prioritizing AI Security Risks With Quantification | Kovrr

As AI and GenAI become embedded in core operations, the report argues that organizations must shift from qualitative, static assessments to business-context-driven risk quantification to manage AI security effectively. It emphasizes enterprise-wide visibility into sanctioned, shadow, and embedded AI; explains why traditional prioritization fails in fast-evolving AI environments; and shows how expressing AI risk in financial and probabilistic terms enables consistent, defensible prioritization and control selection for boards, regulators, and GRC leaders.