Proposal Description

The accelerating integration of Artificial Intelligence is fundamentally transforming the role of official statistics. AI systems increasingly rely on structured, machine‑readable data rather than traditional human‑oriented dissemination channels. In this context, the concept of AI‑Readiness has emerged as a critical capability for National Statistical Offices (NSOs): the ability to make data discoverable, interoperable, and reusable by AI systems.
This session explores the paradigm shift from a data‑first to a metadata‑first approach. Beyond technical aspects, AI‑Readiness reflects a deeper institutional transformation. The growing importance of data reuse, including through data linking and the once‑only principle, challenges traditional survey‑centric production models. Collecting data for single purposes is increasingly seen as inefficient and costly. Instead, modern data ecosystems require interoperability, shared standards, and coordinated governance across institutional and sectoral boundaries.
NSOs are therefore evolving toward a new role as data stewards. Rather than centralizing all data, they establish common frameworks, as data models, metadata standards, interoperability protocols, and governance mechanisms, that enable secure and trusted data exchange. This shift raises important questions: How can NSOs ensure data protection, confidentiality, and public trust in increasingly interconnected systems? The urgency is underscored by rapid technological developments and the increasing influence of AI on political decision‑making. If official statistics are not easily accessible to AI systems, there is a growing risk of misinterpretation, misinformation, and erosion of trust in public institutions. At the same time, inefficient data silos and fragmented infrastructures impose rising costs on governments.
This session will present concrete national experiences, covering strategies, and practical implementations of AI‑Readiness. The session will foster discussion on how NSOs can maintain their core values while adapting to a rapidly evolving data landscape. Ultimately, the session aims to position NSOs as essential actors in shaping trustworthy AI‑enabled societies, ensuring that official statistics remain a cornerstone of evidence‑based policymaking and democratic legitimacy in the digital age.

This session is expected to contribute to the strategic modernization of official statistics by providing participants with practical experiences and policy perspectives on AI-Readiness and data stewardship. Beyond raising awareness, the session aims to support NSOs in identifying concrete pathways for adapting their institutional mandates, governance frameworks and partnerships within national data ecosystems. By bringing together countries and organisations, the discussion will foster international learning and help shape a common vision for ensuring that official statistics remain discoverable, trusted, and relevant in an AI-driven world. Ultimately, the session seeks to strengthen the capacity of NSOs to act as trusted coordinators of data ecosystems and to safeguard evidence-based policymaking in the digital age. Beyond raising awareness, the discussion could contribute to the ongoing work of the Kigali City Group on AI Readiness for Official Statistics by identifying common challenges, good practices and priority areas for future methodological development.