Enterprise Operating Model

An effective enterprise operating model for AI security assigns explicit ownership across the full lifecycle so risk decisions, controls, and evidence do not fall between teams. AppSec and Security own threat interpretation, risk qualification, and security acceptance criteria; AI and Platform own shared model, retrieval, tool, and identity controls plus telemetry and policy hooks; Product owns user and workflow behavior and launch tradeoffs; Data and Privacy own data, tenant, retention, and provenance boundaries and approve sensitive-data use and external sinks; Engineering implements controls and replay/regression instrumentation; and Governance and Leadership own risk acceptance, investment, and escalation records. This model creates clear decision rights, faster coordination, and accountable security outcomes for enterprise AI systems.