Abstract

The modern data ecosystem is rapidly transforming, and statistics is increasingly relying on Artificial Intelligence (AI) and Machine Learning (ML) methods. Official statistics face new challenges, including the rapid growth of data volumes, the integration of non-traditional data sources, and the need for timely and high-quality analytics to support decision-making. This session focuses on new tools and methodologies that enhance the effectiveness of statistics, from data collection to forecasting and evidence-based policymaking.
This presentation presents the case of Georgia and demonstrates how AI and ML can support the modernization of official statistics. In Georgia, the volume of data is steadily increasing through administrative data, digital services, business data, and open data platforms. In this context, the adoption of modern analytical approaches is essential to ensure faster data processing, improved data quality, and more efficient use of resources.
Particular attention is given to several key areas:
• the use of administrative and big data sources to strengthen official statistics;
• the application of machine learning models for forecasting, now casting, and risk assessment;
• large-scale data classification and coding, as well as automated identification of anomalies and outliers
• automated data quality control, anomaly detection, and process optimization;
• strengthening evidence-based policymaking and analytical capacity in the public sector.
In addition, AI-driven solutions are being introduced to improve user experience and accessibility of official statistics, including chatbots for website navigation, automated responses to frequently asked questions, simplified statistical data search, and the development of an AI assistant for the NACE classification system.
Georgia’s experience demonstrates that integrating AI and ML into statistical practice can significantly enhance the overall effectiveness of the national statistical system. By adopting these modern tools, statistical institutions in Georgia can process and analyze growing volumes of data more efficiently, improve the accuracy and reliability of information, and support timely, evidence-based decision-making. This combination of improved data quality, institutional cooperation, and capacity building strengthens the ability of Georgia’s statistical system to meet emerging challenges and contributes to better-informed policies across social, economic, and public sectors.