Statistical organisations face rising demands for timely, granular, trustworthy data amid tightening resources and rapid technological changes. These pressures require statistical organisations to modernise processes, strengthen governance, innovate continuously, and take advantage of emerging technologies such as Artificial Intelligence (AI) to remain relevant and resilient.

Endorsed internationally and supported by a mature ecosystem of standards, tools, guidelines, and expert communities, the standard for Statistical Data and Metadata (SDMx) provides a practical and scalable framework to address these challenges. SDMX allows statistical organizations to begin with a small project and gradually scale to enterprise-level operations, unlocking benefits such as efficient automation through flexible, mature tools and platforms, standardized approaches to data modelling, processing, and dissemination, as well as strong community support.

SDMx also plays a critical role in the AI era. By providing structured data, rich metadata, and standardised access mechanisms, it enables AI systems to discover, interpret, and retrieve official statistics more accurately and transparently. At the same time, AI can accelerate SDMx implementation through automated metadata creation, data modelling, and quality management.

Together, SDMx and its global ecosystem provide a sustainable foundation for modern, interoperable, AI-ready statistical systems that improve efficiency, strengthen trust in official statistics, and support better-informed decision-making.

Read the business case for SDMx (English) for more details on how SDMx delivers value and addresses challenges faced by statistical agencies worldwide through modernising the data lifecycle, improving efficiency and reducing cost, complexity, and implementation risk.