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Operationalizing in Modulos ​

Principle-based governance becomes credible when it produces an audit-ready trail: clear requirements, executed controls, linked evidence, and decisions that can be reviewed later.

Most organizations use:

  • One organization project to coordinate shared governance artifacts (policy, templates, decision gates, shared control library).
  • AI system projects for system-specific execution (evaluations, evidence, approvals, monitoring signals).

Most organizations only need one organization project to coordinate their organization-wide work. Multiple organization projects are mainly useful for multinational or multi-entity groups that need separate governance boundaries.

Where in Modulos ​

  • Project → Requirements for structured obligations
  • Project → Controls for execution and review
  • Project → Evidence for artifacts
  • Project → Testing for evaluation signals

Minimum viable “ethical AI pack” (per AI system) ​

Principle-based governance becomes actionable when each AI system has, at minimum:

  • scope statement (intended use, users, impact context)
  • data map (where data comes from, where it flows, where it is stored)
  • evaluation plan (what you test, thresholds, cadence, owners)
  • human oversight and escalation workflow (when humans intervene)
  • transparency and user guidance (what you disclose and how users should interpret outputs)
  • risk decisions (treat / accept) with an approval record

A sequence that works ​

1

Define scope and principles

Make it explicit which systems and decisions are in scope

2

Translate principles into controls

Choose controls that prevent and detect principle violations

3

Attach evidence continuously

Link artifacts to controls as they are produced

4

Review and approve

Use reviews to create a traceable governance narrative

5

Monitor signals

Use tests and monitoring outputs to keep governance current

Evidence linking (diagram) ​

Evidence should attach to the smallest meaningful claim and be reusable across controls and principles.

Measurement and remediation (diagram) ​

Turn “ethics” into continuous signals: evaluate, detect drift, remediate, and re-verify.

Exports (diagram) ​

Exports create point-in-time packages for stakeholders and internal audit.

Integrated Management System (IMS): ISO/IEC 42001 + ISO/IEC 27001 ​

Many organizations run principle-based AI governance through an Integrated Management System:

  • ISO/IEC 42001 provides the management-system backbone (roles, audits, continual improvement).
  • ISO/IEC 27001 provides the security governance baseline (access control, incident handling, supplier governance).

This supports reuse: one control execution and evidence set can support multiple frameworks.

See: ISO/IEC 42001 and ISO/IEC 27001.

Principles

Translate UAE AI Ethics principles into controls and evidence

Governance operating model

Requirements → controls → evidence → reviews

Testing

Evaluations as continuous governance signals

Disclaimer

This page is for general informational purposes and does not constitute legal advice.