Author
Listed:
- Olga Degtiareva
- Tetiana Kuklinova
- Valeriia Slatvinska
- Volodymyr Hura
- Oleksandr Zadereiko
Abstract
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
Suggested Citation
Olga Degtiareva & Tetiana Kuklinova & Valeriia Slatvinska & Volodymyr Hura & Oleksandr Zadereiko, 2026.
"Risk-oriented product management of AI-based solutions in the energy sector,"
Innovation and Sustainability Articles, Innovation and Sustainability, vol. 6(2), pages 34-45, June.
Handle:
RePEc:cve:innsjn:v:6:y:2026:i:2:p:34-45
DOI: https://doi.org/10.31649/vis/2.2026.34
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cve:innsjn:v:6:y:2026:i:2:p:34-45. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Innovation and Sustainability (email available below). General contact details of provider: https://inns.vn.ua/ .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.