Use of Big Data and Artificial Intelligence by NSOs in Latin America and the Caribbean: Evidence from a Regional Consultation (2022-2025)
Conference
Format: CPS Abstract - IAOS 2026
Keywords: alternative data sources, artificial intelligence,, big data, official statistics
Session: Data sources for AI
Tuesday 12 May 11 a.m. - 12:30 p.m. (Europe/Vilnius)
Abstract
Over the past decade, National Statistical Offices (NSOs) have increasingly explored Big Data and Artificial Intelligence (AI) as complementary sources and tools for the production of official and experimental statistics. In Latin America and the Caribbean (LAC), this transformation has been supported by the United Nations Regional Hub for Big Data and Data Science in Brazil, through technical cooperation, capacity development, and systematic monitoring of regional practices.
This paper presents a comparative overview of the use of Big Data and AI by NSOs in the LAC region based on the results of an annual international consultation conducted between 2022 and 2025. The consultation collects harmonized information on the adoption of non-traditional data sources—such as web scraping, satellite imagery, mobile phone data, scanner data, and financial transactions—their application across statistical domains, and the integration of AI tools along the statistical production process.
The analysis highlights a clear evolution over the period. While early responses (2022–2023) were predominantly characterized by exploratory studies and pilot projects, more recent results (2024–2025) show a gradual transition toward institutionalization, with increased use of Big Data in official statistics and more structured plans for future implementation. The paper also documents the growing use of AI solutions, including machine learning models and large language models, particularly in data processing, analysis, and dissemination stages.
In addition, the results shed light on the technological infrastructures in place, major constraints faced by NSOs—such as legal, organizational, and capacity-related challenges—and priority areas for regional cooperation and investment. By providing a longitudinal perspective, this study contributes empirical evidence on the maturity trajectory of Big Data and AI use in official statistics in the LAC region and offers insights to inform strategic planning, capacity-building initiatives, and international cooperation.