Received 19.11.2026, Revised 30.04.2026, Accepted 25.06.2026 Published 10.07.2026

Risk-oriented product management of AI-based solutions in the energy sector

Olga Degtiareva, Tetiana Kuklinova*, Valeriia Slatvinska, Volodymyr Hura, Oleksandr Zadereiko

tanya2013001@gmail.com



AI-related innovation initiatives in the energy sector have traditionally been viewed as sources of organisational complexity and potential vulnerability. The study aimed to analyse the interplay between energy security and the resilience of energy systems, to explore emerging risks associated with digitalisation and the implementation of intelligent systems, and to evaluate the managerial and policy measures necessary for the effective integration of AI into energy infrastructure. To achieve the stated objectives, open-access sources were utilised and an integrated approach was applied, combining general scientific and specialised research methods, with particular emphasis on advanced analytical, monitoring and automated technologies. The findings underscored the importance of investing in technological, human, and regulatory capacities to fully leverage the potential of AI. At the same time, the role of AI-driven tools in modern energy systems is increasing due to their contributions to digital resilience, operational stability, predictive maintenance, cybersecurity, and strategic decision-making. However, these developments are accompanied by corresponding risks. That is why the modern management system must evolve from an administrative and control-oriented function to an intelligent, analytical mechanism that integrates human expertise with algorithmic decision-making. In this way, digital resilience extends the concept of system resilience by integrating information technologies and AI-driven analytics to anticipate, absorb, and recover from disruptions, whether caused by physical, technological, or cyber incidents. This integration reduces subjectivity, enhances the accuracy of operational decisions, and ensures a transparent, adaptive, and scientifically grounded approach to strategic coordination. By combining advanced analytics, AI-driven automation, and proactive risk management, energy systems can achieve enhanced stability, operational reliability, and cybersecurity resilience in increasingly complex and digitally interconnected environments. Furthermore, leveraging global best practices and fostering cross-border collaboration in AI innovation and cybersecurity can accelerate the transformation of energy enterprises toward sustainable, intelligent, and resilient infrastructures

digital environment; cyber risks; investments; product management; strategic planning; project management; operational risk
34-45
Degtiareva, O., Kuklinova, T., Slatvinska, V., Hura, V., & Zadereiko, O. (2026). Risk-oriented product management of AI-based solutions in the energy sector. Innovation and Sustainability, 6(2), 34-45. https://doi.org/10.31649/vis/2.2026.34

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