Riyadh Air is building its data and AI foundations alongside the airline itself, with governance, accountability and regulatory requirements embedded from the outset. Its approach moves beyond periodic compliance exercises towards a model in which governance and evidence form part of day-to-day operations.

In this case study, Data Sentinel explores how Riyadh Air is establishing a continuous Data and AI Trust foundation to support compliance with Saudi Arabia’s National Data Management Office (NDMO) framework and Personal Data Protection Law (PDPL), while preparing for AI adoption across the airline. It outlines the operating model, phased implementation and technology architecture being used to bring data governance, quality, AI governance and audit evidence together.

What you’ll learn

• Why Riyadh Air established governance authority and accountability before developing policies.
• How starting with one division can provide a model for scaling governance across an organisation.
• Why AI governance is being developed alongside, rather than after, the wider data governance programme.
• How Riyadh Air’s Trust Layer connects data discovery, classification and audit evidence with controls governing access to AI systems.
• How continuous governance can support regulatory compliance and AI adoption as the airline scales.