The Artificial Intelligence Underwriting Company (AIUC) is introducing a framework designed to address one of the biggest barriers to enterprise AI agent adoption: trust and security. Emil Lassen, from AIUC, discussed how the new AIUC-1 framework applies traditional enterprise standards, certification, audit, and insurance models to the emerging world of autonomous AI agents. The approach mirrors established practices from other high-stakes industries where certification and underwriting have enabled wider adoption of new technologies. The framework tackles a critical challenge for enterprises considering deploying autonomous AI agents in production environments. As AI agents take on increasingly complex and autonomous decision-making roles, enterprises need mechanisms to verify security, reliability, and trustworthiness before deployment. AIUC-1 provides a structured approach through standards and certification, creating what Lassen described as an "enterprise flywheel" where standards inform certification, which enables audit and insurance coverage. A key component of the AIUC-1 approach is red teaming based on established standards—a methodology designed to identify vulnerabilities and ensure systems can withstand adversarial attacks. This technique could prove crucial for accelerating enterprise adoption by providing structured, repeatable security validation. By bringing familiar governance and risk-management frameworks to AI agents, AIUC-1 aims to provide the verification infrastructure that enterprise risk officers and procurement teams require before integrating autonomous AI systems into business-critical operations.