Digital Technologies as Catalysts for Sustainable Economic Growth and Innovation: Algorithmic Models and Applications
Digital Technologies as Catalysts for Sustainable Economic Growth and Innovation: Algorithmic Models and Applications

Summary/Abstract: In the modern era, digital transformation has become an integral part of the development of economies and society as a whole. Digital technologies, such as automation, artificial intelligence, the Internet of Things (IoT), and analytical platforms, have great potential for optimizing economic processes, increasing productivity, and developing innovations. However, the implementation of digital technologies brings with it a number of challenges, including the need to adapt to the specific needs of different industries and effectively manage these processes. The purpose of this article is to develop an integrated algorithmic model for optimizing digital transformation aimed at maximizing economic growth and innovation in different industries. Special attention is paid to the development of mathematical models, in particular genetic algorithms and multi-criteria optimization methods, to predict the impact of digitalization on productivity, costs, and the innovative potential of enterprises. The article offers a comprehensive approach to assessing the economic effect of implementing digital solutions, in particular, through simulation modeling, which allows taking into account numerous factors affecting digital transformation, such as the development of digital infrastructure, the level of innovation and the adaptation of technologies to the specifics of each industry. Thus, the article not only offers a new methodology for optimizing digital transformation, but also contributes to the formation of tools for assessing and strategically managing digital solutions at the enterprise and state levels. The developed model can be an important step in improving digitalization strategies to increase efficiency and competitiveness in the face of globalization and technological change.

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