# ISO/IEC 42001:2023 A.6.2.3 — AI system design and system architecture

- Source: https://support.icompaas.com/compliance/iso-42001-2023/a-6-2-3-ai-system-design-and-system-architecture
- Section: [Compliance](https://support.icompaas.com/compliance) › [ISO/IEC 42001:2023 (AI Management System) Annex A Controls](https://support.icompaas.com/compliance/iso-42001-2023) › Technological controls
- Last updated: 2026-06-05
- Publisher: iCompaas, Inc. (https://www.icompaas.com)

**ISO/IEC 42001:2023**·Annex A `A.6.2.3`·high·Component: **Technological controls**

## What this control requires

> AI system design and architecture shall be documented and reviewed to support robustness, explainability, security, and governance.
> 
> — ISO/IEC 42001:2023, Annex A A.6.2.3

### In plain English

AI system design and architecture shall be documented and reviewed to support robustness, explainability, security, and governance. In practice, this means you can prove you review governance-level controls on a defined cadence.

## Why it matters

ISO 42001 is the first audited evidence regulators, customers and investors can ask for that you are managing AI risk. Each Annex A control is a check-box in that audit; it is also the management system enterprises are starting to require from AI vendors before an MSA can be signed.

This control is rated **high**. Auditors expect a named owner, a remediation SLA, and a tooling artefact that evidences continuous operation.

## What an auditor looks for

An ISO 42001 auditor verifies you have an AI policy, a risk-based system of impact assessments for each AI system, lifecycle controls from data acquisition through retirement, and third-party-AI controls that pierce the vendor's wrapper to underlying model behaviour.

Within **Technological controls**, the assessor will trace your implementation back to the catalogue reference (Annex A A.6.2.3) and look for objective evidence on the latest two assessment cycles.

## How to implement

#### Secure Development

**Pipeline.** Require code review, SAST (Semgrep / Snyk Code), SCA (Dependabot / Renovate), secret-scanning and IaC scanning in the merge pipeline.

**Branch protection.** Protected branches enforce reviews, signed commits and passing CI before merge; document the protection rules as the control evidence.

#### Configuration Management

**Policy-as-code.** Codify the control as Service Control Policies (AWS), Azure Policy initiatives, or Organisation Policy (GCP) so the platform enforces what the document promises.

**IaC.** Gate Terraform / Pulumi / CloudFormation changes with Checkov / tfsec / OPA so misconfigurations never reach production.

**Drift.** Run a CSPM (Wiz / Prisma / Defender for Cloud / Security Command Center) over every account and route findings to a single risk register.

### Operational checklist

-   **Review.** Document the trigger, the owner and the cadence.
-   **Document.** Document the trigger, the owner and the cadence.
-   **Govern.** Document the trigger, the owner and the cadence.
-   **Scope:** governance.

## Evidence to collect

-   **Code Repo Scan.** Source-control evidence — branch protection, required reviewers, CI status, SCA / SAST reports.
-   **Infra Scan.** Continuous infrastructure-posture telemetry — AWS Config, Azure Policy compliance, GCP Organisation Policy, Wiz / Prisma findings.

Repository and architecture evidence should demonstrate that AI system design and architecture are documented, reviewed, and governed to support security, robustness, explainability, and oversight. Focus: AI system design and system architecture.

## Common pitfalls

-   CI security checks set to warn-only; the merge button is faster than the security feedback.
-   Manual cloud-console changes that never make it back to Terraform — drift accumulates until the next outage forces a reconciliation.

## How it maps to other frameworks

Computed from shared tags, control component and key-operation subjects — handy when you are reconciling controls across an audit.

-   [**ISO/IEC 27001:2022 A.8.28** — Secure coding](https://support.icompaas.com/compliance/iso-27001-2022/a-8-28-secure-coding)

## Related controls in ISO/IEC 42001:2023

-   [**Annex A A.6.1.2** — Objectives for responsible development of AI systems](https://support.icompaas.com/compliance/iso-42001-2023/a-6-1-2-objectives-for-responsible-development-of-ai-systems)
-   [**Annex A A.6.2.8** — Development of AI system](https://support.icompaas.com/compliance/iso-42001-2023/a-6-2-8-development-of-ai-system)
-   [**Annex A A.6.1.3** — AI system design and development process](https://support.icompaas.com/compliance/iso-42001-2023/a-6-1-3-ai-system-design-and-development-process)
-   [**Annex A A.6.2.2** — AI system requirements and specification](https://support.icompaas.com/compliance/iso-42001-2023/a-6-2-2-ai-system-requirements-and-specification)

## References

-   [ISO/IEC JTC 1/SC 42 — ISO/IEC 42001:2023](https://www.iso.org/standard/81230.html)
-   Catalogue identifier: `Annex A A.6.2.3`

Topics: secure developmentarchitecture governanceapplication securityarchitecture managementconfiguration management