AI System Register: Your First Governance Step

Why the register comes first

Every AI governance framework, whether the Veridio AI Governance Framework, ISO/IEC 42001, the NIST AI Risk Management Framework, or the EU AI Act itself, begins with the same requirement: know what AI you have. Risk assessment, transparency obligations, human oversight requirements, and regulatory compliance all depend on having a complete, accurate inventory of AI systems.

Without a register, governance is blind. An organisation cannot classify systems by risk tier if it does not know the systems exist. It cannot assign accountability for AI decisions if it has not identified which decisions are AI-assisted. It cannot report AI incidents to regulators if it cannot distinguish AI-driven outcomes from other operational processes.

The register is not merely an administrative exercise. It is the foundation document that makes every subsequent governance activity possible.

What a register should contain

A comprehensive AI system register records, for each AI system: the system name and a plain-language description of its purpose; the business function it supports; the named owner accountable for its governance; the data categories it processes (including personal data); its risk classification under both internal criteria and applicable regulation; its lifecycle stage (development, pilot, production, decommissioned); the vendor or provider if externally sourced; and the date of last review.

For systems classified as high-risk, the register should additionally record: the affected population (employees, customers, public); the automated decisions the system makes or informs; the human oversight mechanism in place; the model version currently deployed; and references to the associated risk assessment, impact assessment, and validation records.

The register should be a living document, updated whenever a new AI system is procured, an existing system is materially modified, or a system is decommissioned. Many mature organisations integrate register updates into their procurement workflow, so that every new SaaS contract triggers a classification check.

The shadow AI problem

Shadow AI is the governance equivalent of shadow IT: AI systems in use across the organisation that are not visible to the governance, compliance, or security functions. It is a widespread problem. Most organisations, when they conduct their first comprehensive inventory, discover significantly more AI systems than they expected.

Shadow AI arises because AI is increasingly embedded in everyday software. A marketing team using an AI-powered content tool, a finance team using AI features in their forecasting software, a customer service team using an AI chatbot platform, an engineering team using code-generation assistants: each of these represents an AI system that may process sensitive data, make or inform consequential decisions, and create regulatory obligations. Yet none may appear in the organisation's technology register because they were adopted as features of existing tools rather than as standalone AI deployments.

The register is the antidote to shadow AI. By systematically cataloguing AI use across every function, the organisation brings invisible AI into governance scope. This is not about restricting AI use; it is about ensuring that AI use is visible, accountable, and appropriately governed.

Getting started

The fastest path to a working AI system register is to start with a structured template rather than a blank spreadsheet. A template provides the right fields, the right structure, and the right level of detail from day one, so the organisation spends its time populating the register rather than designing it.

The Veridio AI System Register template covers all the fields described above, with built-in risk classification, lifecycle tracking, and governance fields. It maps to three principles of the Veridio AI Governance Framework and forms the first document in the Governance Starter Pack.