Abstract

The rapid expansion of data sources, volumes, and formats—commonly referred to as the data revolution—has fundamentally transformed the environment in which official statistics are produced. National statistical offices are increasingly expected to deliver statistics that are timely, reliable, and of high quality, while simultaneously managing growing data complexity, heterogeneous sources, and rising expectations from policymakers and data users. In this evolving context, artificial intelligence (AI) has emerged as a potentially powerful enabler for modernizing statistical production and enhancing the role of official statistics in evidence-informed decision-making.
This paper examines the role of AI in modern official statistics from an institutional and governance-oriented perspective. Rather than focusing on specific algorithms or technical model performance, the paper explores how AI-based tools can be meaningfully integrated into official statistical workflows to support core statistical functions. It discusses the potential application of AI across key stages of the statistical production process, including data validation and editing, anomaly detection, record linkage and data integration, classification, and process automation. Particular attention is given to production environments characterized by large volumes of data, multiple data sources, and increasing reliance on non-traditional data inputs.
The paper highlights how AI can contribute to strengthening fundamental quality dimensions of official statistics, such as accuracy, coherence, consistency, and timeliness, by complementing established statistical methods and enabling more efficient handling of complex datasets. At the same time, it emphasizes that the adoption of AI in official statistics is not purely a technical matter. Effective implementation requires robust institutional frameworks, clear governance arrangements, and well-defined quality assurance mechanisms that ensure AI-supported processes remain transparent, accountable, and aligned with professional statistical standards.
Key governance and ethical considerations are discussed, including transparency, explainability, human oversight, and the responsible use of AI in statistical production. These elements are identified as critical for maintaining public trust and safeguarding the credibility of official statistics in an environment where automated and data-driven methods are increasingly used. The paper underscores the importance of positioning AI as a supportive tool that enhances, rather than replaces, human statistical expertise and established quality frameworks.
A central focus of the paper is the contribution of AI to evidence-informed decision-making. By improving the availability, reliability, and timeliness of statistical outputs, AI-enabled processes can strengthen the capacity of official statistics to support policy analysis, strategic planning, and public accountability, while preserving professional independence and statistical integrity.
By situating AI within the institutional practices of official statistics, this paper contributes to ongoing international discussions on how statistical organizations can navigate the data revolution while safeguarding trust, relevance, and quality. It provides a conceptual foundation for integrating AI into official statistical systems in a manner that reinforces governance, supports decision-making, and enhances the overall impact of modern official statistics.