Governance

AI Auditability

Definition

The ability of an AI system's behaviour, decisions, and data flows to be independently examined and verified. Auditability requires comprehensive logging, version-controlled model artefacts, and documented decision trails—all prerequisites for EU AI Act conformity assessment.

Related Terms

AI Transparency

The principle that AI systems, their capabilities, limitations, and decision-making processes should be understandable to affected users, deployers, and regulators. The EU AI Act mandates transparency obligations at multiple risk tiers, from simple chatbot disclosure to full technical documentation for high-risk systems.

Model Registry

A centralised repository for versioning, cataloguing, and managing trained ML models throughout their lifecycle—from experimentation through staging to production. A model registry is the foundation of reproducible, auditable AI deployments.

Data Lineage

The ability to track data's origin, movement, transformations, and consumption throughout a system. Data lineage is essential for AI auditability, debugging model behaviour, and demonstrating GDPR and EU AI Act compliance to regulators.

Related Services

Eu Ai Act Compliance

Knowing the Terms Is Step One. Applying Them Is Step Two.

Book a 30-minute call to discuss how these AI concepts translate to your specific industry and business challenges.