Data Science can be described as extracting meaningful patterns from data using machine learning (ML), artificial intelligence (AI) and visualization methods. The Office for National Statistics (ONS) of the United Kingdom describes data science more broadly as applying the tools, methods and practices of the digital and data age to create new understanding and improve decision-making. ONS created a Data Science Campus in 2017 to investigate the use of new data sources and help build data science capability for the benefit of the UK. A new generation of tools and technologies is being used to exploit the growth and availability of these new data sources and innovative methods to provide rich informed measurement and analyses on the economy, the global environment and wider society.

The UN Statistical Commission established the UN Committee of Experts on Big Data and Data Science for Official Statistics (UNCEBD) 10 years ago to explore the benefits and challenges of using Big Data and corresponding new methods, tools and applications. UNCEBD developed – among others – guidance on the use of remote sensing for estimating agriculture statistics, scanner data for prices statistics, AIS shipping data for maritime transport and mobile phone data for the estimation of tourism, population and transport indicators. In 2022, UNCEBD created the Data Science Leaders Network (DSLN) to develop guidelines for integrating AI and data science in the work of statistical offices. AI and data science can be used to automate business processes, to gain efficiencies in the work of statistical offices or to develop fast indicators for emerging issues. Ultimately, AI and data science will play an important part in the modernization and transformation of the production processes of statistical offices.

DSLN is chaired by Osama Rahman, the Director of the Data Science Campus of ONS, and embarked on the preparation of a Playbook on how to integrate Data Science in the work of National Statistical Offices (NSOs). After several virtual events in 2023, it held a first in-person Sprint in Dubai in January 2024 on the topic of integrating data science into the production of official statistics to inform and enhance policy decisions, with a special focus on the transport sector.

Recently, DSLN and the United Nations Network of Economic Statisticians , which is chaired by Mr. Andre Loranger (Chief Statistician of Canada) and Ms. Aishath Shahuda (Deputy Chief Statistician of the Maldives Bureau of Statistics), agreed to organize a Sprint aimed at enhancing the capabilities of NSOs in the use of innovative AI and data science applications for the production and dissemination of economic statistics. This Sprint will consist of two preparatory webinars in November and December 2024 and will conclude with an international symposium in Dubai in January 2025 hosted by the Federal Competitiveness and Statistics Center (FCSC) of the United Arab Emirates.

This AI and Data Science Sprint for Economic Statistics is poised to be a pivotal event in the ongoing efforts of the statistical community to integrate advanced data science techniques within the framework of national and international statistical systems. By highlighting successful use cases and discussing the strategic integration of new technologies, the sprint will help in shaping the future of economic statistics production. This Sprint will also be an important step in the further development of the Data Science Leadership Network playbook and seeks to empower NSOs with cutting-edge tools and methodologies for statistical production.

All efforts are made to provide a broad horizon scan of ongoing projects undertaken at the national and international levels by the statistical community and its partners. Appropriate deliberate reference will be made to implementing the System of National Accounts 2025.