Rapid development outpacing regulation

Mitigation strategy

1. Establish a **Dynamic, Risk-Based AI Governance Framework**. Implement internal policies, aligned with international standards (e.g., NIST AI RMF, OECD Principles), that mandate continuous AI inventory mapping, lifecycle-spanning risk assessments, and defined accountability structures to proactively manage novel risks. 2. Mandate **Meaningful Human-in-the-Loop Oversight**. For all high-risk or sensitive AI applications (e.g., hiring, creditworthiness), enforce a "human-in-the-loop" review process, establish clear escalation pathways for inconsistent or harmful model outputs, and require detailed logging and documentation of all critical automated decisions. 3. Promote **Globally Interoperable and Agile Regulation**. Engage in international and domestic policy advocacy to support the creation of nuanced, risk-proportional regulatory standards that are technology-neutral, harmonize across jurisdictions, and incorporate mechanisms (such as regulatory sandboxes) to rapidly adapt to emergent AI capabilities.