Digital transformation (DT) in the energy sector is pivotal in meeting energy transformation challenges. DT is reshaping energy production, distribution, and consumption by integrating advanced technologies such as artificial intelligence (AI), the Internet of Things (IoT), blockchain, and digital twins. While existing research has extensively documented individual technological applications, there remains a significant gap in understanding how these technologies interact synergistically in real-world implementations [11]. Comprehensive analyses comparing digital transformation outcomes across different socioeconomic contexts are limited, particularly regarding the scalability of swarm electrification models. These technologies collectively address the ‘three Ds’ – decentralisation, decarbonisation, and digitalisation – essential for the evolution of modern energy systems. By leveraging these innovations, the sector can significantly enhance efficiency, optimise renewable energy integration, and expand access to underserved regions.One of the most impactful applications of DT is in the realm of decentralised energy systems, exemplified by swarm electrification. This concept, pioneered by Groh et al [3], utilises interconnected solar home systems (SHSs) to form scalable microgrids that evolve from standalone setups to full integration with national grids. These systems empower communities by facilitating energy sharing, reducing operational costs, and creating new income streams. Case studies from Kenya, Madagascar, Yemen, Germany, and Bolivia demonstrate the real-world success of swarm electrification in bridging the energy access gap while advancing sustainability goals.AI plays a pivotal role in digital energy systems by enabling predictive maintenance, optimising energy flows, and improving system reliability. Algorithms analyse vast datasets in real time to forecast energy demand, detect anomalies, and automate grid management. IoT further complements AI by providing the physical infrastructure to gather and transmit data, enabling real-time monitoring and control of energy assets. Together, AI and IoT support the development of smart grids and energy communities, fostering greater flexibility and resilience in energy networks.Blockchain technology is emerging as a transformative tool for energy trading and distribution. By enabling peer-to-peer (P2P) energy markets, blockchain enhances transparency and reduces transaction costs. This decentralisation of energy trading allows consumers to become prosumers, actively participating in energy production and exchange. Projects such as Esmat et al. decentralised platforms exemplify how blockchain empowers individuals and communities to take ownership of their energy futures while ensuring security and scalability.Despite these advancements, the implementation of digital technologies in energy systems is facing significant challenges. High initial costs, the complexity of integration, and cybersecurity risks pose barriers to widespread deployment. Furthermore, the digital divide in underserved regions limits equitable access to these transformative solutions. Environmental concerns related to the energy consumption of digital infrastructures, such as data centres and blockchain networks, also require attention. Addressing these issues necessitates a multi-stakeholder approach involving policymakers, industry leaders, and researchers to create enabling environments for innovation.This review provides a comprehensive analysis of the role of DT in advancing energy systems, focusing on AI, IoT, blockchain, and swarm electrification. It synthesises insights from over 100 scholarly sources, including real-world case studies, and evaluates the social, economic and technological impact of digitalisation on energy systems. The study adopts a mixed-method approach, integrating literature analysis, quantitative modelling, and case study evaluations to provide actionable insights for policymakers and industry practitioners.The findings of this review highlight the transformative potential of DT in addressing energy challenges, particularly in achieving the United Nations Sustainable Development Goal 7 [2]: universal access to affordable, reliable, and modern energy. By adopting digital innovations, energy providers can enhance operational efficiency, integrate renewable energy sources, and support community-based energy initiatives. The concept of swarm electrification exemplifies how decentralised approaches can complement centralised grids, ensuring scalability and adaptability to local needs.Policy recommendations emphasise the need for financial incentives, capacity-building programmes, and regulatory frameworks to facilitate digital adoption. Investment in human capital is particularly critical, as skilled personnel are required to implement and manage complex digital systems. International cooperation and knowledge sharing are essential to ensure digital transformation efforts align with global sustainability goals.In conclusion, DT represents a paradigm shift in energy systems, offering solutions to some of the sector’s most pressing challenges. Realising its full potential requires overcoming technical, financial, and institutional barriers. This review underscores the importance of a collaborative, multidisciplinary approach to harnessing the power of digital technologies for sustainable energy transitions.

The study explores how military-inspired leadership principles and decision-making frameworks can be effectively integrated with business continuity and management practices to enhance organizational resilience. The aim is to investigate how combining military leadership models with BCM, Agile methodologies, and crisis communication strengthens an organization’s adaptive capacity and recovery capability. Research objectives are: (1) to integrate BCM approaches — including PDCA, BIA, and recovery objectives (RTO, RPO, MTPD, MBCO) — with military decision-making models such as Mission Command and the OODA loop; (2) to examine Agile principles and STARCC as complementary frameworks; and (3) to synthesize recent literature (2020–2025) and practitioner insights (Jatautaitė, Radvilė, & Terminas, 2025) to develop a holistic resilience model. Findings indicate that iterative planning, decentralized decision-making, rapid feedback loops, and structured communication significantly enhance organizational resilience. The study proposes an integrated framework combining military leadership, BCM tools, Agile methods, and crisis communication to sustain adaptability, performance, and competitive advantage.

Why do some organizations hold together under severe pressure while structurally comparable ones do not? This paper addresses that question by developing and testing an integrated five-dimension resilience framework, strategic, operational, technological, cultural, and regulatory, against cross-industry survey data and three organizational case studies. Survey data were collected from 365 managers and executives across finance, manufacturing, technology, and healthcare between 2023 and 2025, and analysed using SPSS and Structural Equation Modeling. The cases, Maersk (cyber resilience), Toyota (supply chain resilience), and Cisco (digital transformation resilience), were selected for their documented disruptions and verifiable recoveries. Survey results place strategic resilience first in organizational priority, with technology second and regulatory resilience last except in financial services. SEM confirms that technological resilience partially mediates the relationship between strategic planning and performance, while cultural resilience functions primarily as a moderator. In practice, the framework works best as a diagnostic tool: it identifies which dimension is currently the binding constraint on performance.