An AI Management System (AIMS) is a set of interrelated or interacting elements within an organization to establish policies and objectives and processes to achieve those objectives regarding the responsible development, deployment, or use of artificial intelligence.

It is formally defined by the ISO/IEC 42001 standard, which is the world's first global standard for AI governance. Unlike a one-off risk assessment or a static policy document, an AIMS is a dynamic, continuous operational framework. It treats AI management not as a technical hurdle but as an organizational discipline, similar to how ISO 27001 manages information security or ISO 9001 manages quality.

An effective AIMS typically operates on the "Plan-Do-Check-Act" (PDCA) cycle:

• Plan: Establishing AI objectives, risk tolerance, and the processes necessary to deliver results in accordance with the organization's policies (e.g., defining "no-go" zones for AI use).
• Do: Implementing the processes and controls as planned (e.g., executing bias testing protocols or security reviews).
• Check: Monitoring and measuring AI processes and products against policies, objectives, and legal requirements, and reporting the results (e.g., continuous post-deployment monitoring).
• Act: Taking actions to continually improve performance and the AIMS itself (e.g., updating training data if drift is detected).

Strategic Impact: Implementing an AIMS is the primary pathway for organizations to achieve ISO 42001 certification. This certification serves as a powerful market differentiator, signaling to customers and regulators that the organization has rigorously operationalized its AI ethics and safety commitments, rather than just talking about them. It shifts AI governance from ad-hoc "firefighting" to a structured, auditable business process.