Saudi National AI Risk Management Framework: a simple guide

In July 2026 the Saudi Data and AI Authority (SDAIA) launched the National AI Risk Management Framework, a guiding reference for government and private entities that offers a unified national methodology.

Why AI risks are different

• They appear during operation: risks can surface unexpectedly after a system goes live, not only before.
• Performance changes over time: how a model performs today is no guarantee of how it performs months from now.
• Behaviour is hard to explain and reproduce, which makes identifying and assessing risk more complex.

Four connected stages

1. Define context and scope: what is the system, where is it used, and who does it affect?
2. Identify, assess and treat risks: using a matrix that combines likelihood and impact.
3. Monitor: track the system's performance and risks after go-live.
4. Review continuously: update the assessment whenever the system or its environment changes.

Seven principles

Fairness and integrity, privacy and security, humanity, reliability and safety, transparency and explainability, accountability and responsibility, and social and environmental benefit.

Three steps to start

1. List every AI use case in your organisation, including off-the-shelf tools.
2. Assess each one with the likelihood-impact matrix and set treatment priorities.
3. Name an owner to monitor each model after go-live, not just before.

How many AI tools are used in your organisation today without a risk assessment?

Need to assess the risks of AI use in your organisation? Contact us.

Source: Saudi Press Agency