Artificial Intelligence Technologies in Official Statistics: Use Cases and Risks

This article explores the risks and opportunities of using generative artificial intelligence (GenAI) in the activities of statistical agencies. In the context of digitalization and the growing volume of data, GenAI is becoming a key tool for automating data collection and processing, optimizing analytics and increasing the accuracy of forecasts. However, implementing these technologies poses several significant risks, such as data leakage, cybersecurity threats, reduced trust in official statistics, and the lack of unified standards for data quality assessment. The purpose of the study is to identify potential risks of using GenAI and to propose recommendations for minimizing them by analyzing the use of artificial intelligence technologies in the work of statistical agencies. The results show that the most significant threats are related to data leakage, possibility of receiving inaccurate information, and cyberattacks on GenAI models. The article suggests risk management strategies, including developing AI usage policies, increasing algorithm transparency, and creating security monitoring systems. The novelty of this work lies in the comprehensive analysis of GenAI risks in the activities of statistical agencies, which has not been sufficiently covered in the scientific literature before. Unlike previous publications, the emphasis is placed on institutional and cybersecurity aspects, as well as on the need to develop international standards for data validation and risk management