Authors: R.V. Belyaevsky, R.F. Dzhuraev

Title of the article: Current aspects of forming a regulatory ecosystem for the introduction of artificial intelligence in the Russian electric power industry

Year: 2026, Issue: 4, Pages: 41-51

Branch of knowledge: 2.4.2. Electrotechnical complexes and systems (engineering)

Index UDK: 621.316

DOI: 10.26730/1816-4528-2026-4-41-51

Abstract: The relevance of the study is driven by the global digital transformation of the electric power industry, the need to integrate renewable energy sources and enhance system resilience, which necessitates revising the regulatory framework to adapt artificial intelligence (AI) technologies. The article presents a comprehensive analysis of strategic documents and institutional barriers hindering the implementation of AI in the Russian electric power sector. A comparative analysis of domestic AI development strategies and digitalization strategies for the fuel and energy complex (FEC) is conducted, alongside a review of global experience, including materials from the 2024 UNECE meetings. The methods employed include content analysis, systematic review, and expert synthesis. Systemic challenges are identified: fragmented and poor-quality data, the lack of certification standards for AI algorithms in critical infrastructure, regulatory inertia, and an interdisciplinary skills gap. Based on a synthesis of domestic and international practices, priority areas for improving the regulatory ecosystem are proposed: creating an industry-wide data space for the FEC, transitioning to risk-based regulation using “regulatory sandboxes”, implementing explainable AI (XAI) requirements, and introducing tax and tariff incentives for data cooperation. Special attention is given to quantitative estimates: international experience shows that AI improves renewable energy forecasting accuracy by 15–30% and reduces power supply interruptions by up to 40% in grid restoration systems. The key findings involve formulating specific recommendations for harmonizing regulations, incentivizing the exchange of anonymized data, and developing human resources, including networked master’s degree and continuing education programs. The practical significance is confirmed by an analysis of deployed projects («Prognostika» at the «Akademicheskaya» CHP plant, the automated intelligent fault detection system for power transmission line insulators at Rosseti Siberia, and 2Sigma.IVK» for smart metering), demonstrating AI’s effectiveness in routine processes and hard-to-reach facilities. The implementation of the proposed measures will create a sustainable ecosystem for the safe deployment of AI and ensure the technological sovereignty of the Russian electric power industry.

Key words: artificial intelligence electric power industry digital transformation regulatory framework smart grid digital twin cybersecurity data management

Receiving date: 26.05.2026

Approval date: 01.09.2026

Publication date: 27.08.2026

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