Current Journal of Applied Science and Technology

As smart energy systems become central to national sustainability strategies, the issue of data sovereignty—the right of nations to govern data generated within their borders—has gained critical importance in the broader context of global digital governance and energy security. However, most existing AI systems lack built-in mechanisms for jurisdictional compliance and local control. This paper investigates how Artificial Intelligence (AI) can support data sovereignty in smart grid environments. Using a comparative multiple-case study approach—including Gaia-X, Microsoft EU Data Boundary, a decentralized energy pilot in India, and Saudi Arabia’s NEOM, which represents a sovereignty-by-design model aligned with Vision 2030—the study examines AI-enabled compliance mechanisms, federated learning, and sovereign cloud infrastructures. Expert interviews with stakeholders in policy, energy, and AI provide further context. Findings show that AI offers strong potential for enforcing sovereignty when supported by aligned legal frameworks and sovereignty-by-design architecture. For example, in India’s pilot project, federated AI reduced cross-border data transfers by more than 70% while maintaining forecasting accuracy. Beyond the energy sector, the proposed conceptual framework has applications in finance, healthcare, and smart cities. In particular, the NEOM case highlights Saudi Arabia’s leadership in embedding ethical and cultural governance into AI-enabled sovereignty. Practical recommendations are made to guide sustainable and ethical AI deployment in digital energy infrastructure. These results support global digital sovereignty goals and align with SDGs related to clean energy, innovation, and governance.