The Impact of Artificial Intelligence on Managing Energy Infrastructure Development in the Age of Global Digital Transformation

Abstract

The article is devoted to the study of the development of scientific discourse on the application of artificial intelligence (AI) technologies in managing the development of energy infrastructure in the context of global digital transformation and the transition to low-carbon energy systems. The aim of the work is to identify the dynamics of publication activity, key thematic priorities and international scientific clusters based on the results of bibliometric analysis of publications indexed in the Scopus database for the period 2000–2025. The results obtained showed a rapid growth in scientific interest after 2020, which correlates with the development of Smart Grid, IoT, machine learning, predictive analytics technologies, as well as with the growing need to increase the resilience and cybersecurity of critical energy infrastructure. It was determined that the greatest intensity of research is observed in India, China, the USA, as well as in a number of European countries, which indicates the global nature of the topic. Semantic analysis of keywords allowed us to identify the dominant areas of scientific research: optimization of energy consumption and integration of renewable energy sources, development of intelligent energy grids and “smart” cities, implementation of digital twins of energy systems, use of forecasting algorithms and decision support. Based on the results, the conclusion was formulated that AI is becoming a strategic tool for the energy transition, ensuring increased energy efficiency, accuracy of network balancing, acceleration of response to emergencies, strengthening cybersecurity and achieving the Sustainable Development Goals. Practical recommendations include the development of standards for the use of AI in critical infrastructure, the creation of national energy data platforms and digital twins, strengthening institutional interaction between governments, businesses and scientific institutions, as well as the development of ethical and regulatory frameworks for the use of AI.