The transition to electric mobility requires the coordinated evolution of vehicles, charging infrastructure, power systems, and intelligent digital platforms. This study examines the role of Industry 4.0 technologies in enabling large-scale electric vehicle (EV) adoption and effective EV grid integration and synthesizes the existing evidence into a coherent analytical framework to support planning and policy decision-making. A systematic review of 27 peer-reviewed studies published between 2018 and 2025 was conducted in accordance with PRISMA 2020 guidelines, capturing the acceleration of electromobility following the consolidation of Industry 4.0 technologies and the emergence of large-scale policy commitments worldwide. The analysis covers six technology families, including the Internet of Things, big data and analytics, artificial intelligence and machine learning, blockchain, digital twins, and extended reality, and examines their applications in smart charging, grid vehicle coordination, fleet optimization, and vehicle-to-grid services. The findings show that analytics and artificial intelligence consistently enhance operational reliability and efficiency, while digital twins are increasingly applied to infrastructure siting, grid impact assessment, and scenario analysis. Building on these results, the study proposes a three-layer analytical framework composed of physical, digital, and decision layers, together with a functional EV grid generation integration model that links technology readiness to system-level deployment. In addition, a transition timeline for the 2025–2040 period and a concise set of key performance indicators are introduced to support evaluation and comparison. Policy implications for Ecuador and Latin America emphasize interoperability, data governance, realistic cost assessment, and a phased approach to vehicle-to-grid deployment.
Pozo-Burgos et al. (Sat,) studied this question.