2025

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Browsing 2025 by Author "Salikhov M. M."

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    Digitalization of the EU Manufacturing Sector: The Use of Artificial Intelligence
    (Національна академія статистики, обліку та аудиту, 2025) Salikhov M. M.
    This paper analyzes the statistical toolkit of Eurostat for collecting and processing data on the implementation of Artificial Intelligence (AI) in enterprises across European Union (EU) countries. The study defines the key aspects of evaluating the adoption of AI technologies, such as text mining, natural language generation (NLG), speech and image recognition, machine learning and deep learning, process automation, and autonomous system management. The application of this toolkit allows for the assessment of the digitalization status of the manufacturing sector in the EU and identifies trends in the integration of advanced technologies into business processes. According to data from 2024, it has been determined that the average level of AI penetration in EU-27 countries remains at an early stage, ranging from 1.46% for autonomous robots to 4.58% for text analysis. It has been analyzed that the most widespread technologies are text mining, NLG, and process automation (RPA/AI software), which can be attributed to their relative ease of implementation and lower investment barriers compared to AI systems embedded in devices, such as autonomous robots for warehouse automation or production assembly works, autonomous drones for production surveillance or parcel handling, etc. Geographic analysis reveals that the leaders in AI implementation are small to medium-sized economies with a high level of digitalization and developed innovation infrastructure: Luxembourg, Belgium, Denmark, Finland, Austria, the Netherlands, and Sweden. It has been established that text mining and NLG dominate in countries with advanced data analytics, while machine learning and image recognition are more characteristic of high-tech economies in Northern and Western Europe. It has been found that hardware-intensive technologies, such as autonomous robots, are less widespread due to high financial and technical barriers. In particular, a low level of AI adoption is observed in Eastern and Southern Europe, especially in Romania, Greece, Serbia, Cyprus, and Bulgaria. The study underscores the impact of the size and technological development of a country on the level of AI implementation: small, technologically advanced economies show leadership, whereas larger countries with traditional manufacturing sectors exhibit moderate use of these technologies. In Ukraine from 2026 the government plans to introduce national statistical monitoring of AI usage in enterprises. This will allow for the collection of detailed data on the digitalization of business and the public sector, facilitate the assessment of progress in implementing innovative technologies, monitor strategic priorities, and adjust development policies. Alignment with European standards of AI statistics will ensure comparability of data at the international level and contribute to Ukraine’s integration into global economic processes. The introduction of a national statistical toolkit is an important step for monitoring the digital transformation of the economy, assessing the impact of AI on the competitiveness of enterprises and industries, formulating informed strategic decisions, and developing national innovation policy.
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    Policy on the Development of Innovation Clusters in the EU. Conclusions and Tasks for Ukraine
    (Національна академія статистики, обліку та аудиту, 2025) Salikhov M. M.
    The article demonstrates that since the early 2000s, the EU’s cluster policy has transformed into one of the key instruments for achieving the strategic goals of the European Union. It has been established that the creation of clusters was embedded in the Lisbon Strategy and, since 2006, received formal regulatory recognition in the official documents of the European Commission. It has been identified that, thanks to the establishment of a High-Level Advisory Group, the foundations of a general cluster development policy within the EU were formed (which became the basis for the introduction of corresponding national policies), as well as specialized platforms and support mechanisms were launched. The study establishes that in EU documents clusters are considered a tool for enhancing the socioeconomic stability of regions (in particular through the implementation of smart specialization strategies), increasing industrial competitiveness, stimulating innovation in small and medium-sized enterprises, and forming transnational value chains. It is concluded that the EU's cluster policy has a complex, cross-sectoral character, combining not only the instruments of innovation, industrial, and regional policies, but also those of other policy areas. Based on the analysis of the EU experience, the following proposals are made: to establish a national-level expert group on cluster policy for developing the conceptual foundations of building a cluster ecosystem in Ukraine; to take measures to ensure coordinated actions among central executive authorities regarding the creation, functioning, and support of clusters within the framework of relevant policies; to designate the development of innovation clusters as a priority of state cluster policy (their development directions should correspond to the priority areas of innovation activity defined by Ukrainian legislation); to launch a budget program for providing state aid to such clusters; and to introduce tools to encourage the internationalisation of Ukrainian innovation clusters, in particular by creating cross-border partnerships with European clusters, research institutions, and businesses aimed at solving common problems under current challenges and threats.