This text is an automatic translation from Русский. It was generated by AI and may contain inaccuracies.
Read original →The Digitalization Paradox in Russia's Economy
A machine learning study of Rosstat data has revealed a paradox: industries leading in digitalization experience 60-80% more problems. An analysis of two development models for Russia's digital economy.
Digital transformation has long been viewed as a universal recipe for boosting economic efficiency. It would seem that the more actively an organization adopts digital technologies, the greater its resilience and competitiveness. However, analysis of Rosstat data has revealed an unexpected pattern. The industries leading Russia's digital transformation are simultaneously facing the greatest number of barriers hindering further digitalization.
The study has effectively identified a paradox of the digital economy. The more actively an industry implements artificial intelligence, Big Data, and modern software solutions, the stronger its dependence becomes on IT infrastructure, data quality, and the shortage of qualified personnel.
What was analyzed
The research was based on open Rosstat data about the digitalization of organizations across various economic sectors for 2024. The Rosstat data reflected spending on digital technologies, software usage, implementation of artificial intelligence, the Internet of Things and big data technologies, as well as obstacles hindering digital transformation of enterprises across all types of economic activity. The analysis covered virtually all key sectors of the Russian economy represented in Rosstat statistics for 2024.
The challenge in analyzing the data was that such data arrays are virtually impossible to analyze using traditional statistical methods, since the data was distributed across multiple tables, had different structures, and varying levels of detail.
How the analysis was conducted
A proprietary intelligent data processing methodology was developed to handle the information, which made it possible to combine disparate Rosstat data into a unified model for subsequent analysis using machine learning methods. After preliminary data processing, various cluster analysis algorithms were applied, which allowed industries to be grouped according to the degree of similarity in their characteristics in the context of digital transformation.
