Applies quantitative and qualitative tools to analyze, assess, and monitor AI risk — translating insights from the MAP function into measurable benchmarks that evaluate system functionality, trustworthiness, and real-world impact before and during deployment.
Establishes the context for identifying and framing AI-related risks by recognizing that the AI lifecycle involves multiple interdependent actors — each with limited visibility into the full system — making it essential to surface and understand how those interdependencies can produce unexpected impacts.
Develops the organizational culture, structure, and processes needed to manage AI risk responsibly — aligning technical development with strategic priorities and embedding accountability across the full AI lifecycle, including third-party dependencies.
Allocates resources to address mapped and measured risks — executing response, recovery, and communication plans for AI incidents while leveraging insights from GOVERN, MAP, and MEASURE to reduce system failures, assess emerging risks, and drive continuous improvement through transparent, accountable documentation practices.