Digital Lexicon Hub

An organization-wide set of policies, roles, processes, controls, and continual-improvement practices used to govern the responsible development, provision, and use of AI systems.

An AIMS turns fragmented AI principles into auditable operating practices. It helps organizations coordinate legal, security, data, product, procurement, and operational responsibilities while providing evidence to customers, regulators, and assurance providers.

A company establishes an AI inventory, assigns owners, classifies uses by risk, requires impact assessment for defined cases, monitors production models, audits controls, and tracks corrective actions through a single governance system.

A management system demonstrates structured governance, not that every AI output or system is safe or high quality. Certification does not replace system-specific testing, legal analysis, security engineering, or human oversight.

An AIMS applies a management-system approach to AI governance. It establishes scope, leadership accountability, policy, objectives, risk and impact processes, operational controls, competence, documentation, performance evaluation, internal audit, corrective action, and continual improvement. ISO/IEC 42001 specifies requirements for such a system and can be integrated with other management systems.