Underwriting Superintelligence: Backing Agents you can Sue — Rune Kvist, AIUC

Risk, rather than technical capability, remains the primary bottleneck for widespread AI adoption in critical sectors like banking and healthcare. AIUC addresses this by building "confidence infrastructure" through a standardized, quarterly-updated certification framework for AI agents. This process combines rigorous technical stress testing—simulating jailbreaks and hallucinations—with policy requirements to provide a clear risk profile for enterprises. By partnering with established insurers like Lloyd's of London, AIUC creates a mechanism where audit results directly inform insurance pricing, effectively acting as a neutral third-party ratings agency. This model bridges the trust gap between AI labs and government regulators, ensuring that safety standards evolve alongside rapid technological progress. Future expansion plans include applying these evaluation frameworks to frontier models and robotics to maintain consistent safety oversight across the entire AI stack.