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Abstract

This research investigates the transformative impact of artificial intelligence (AI) technologies on modern electrical engineering applications, with specific focus on smart grids, power systems, and industrial automation. The study explores how machine learning, deep learning, and other AI paradigms are revolutionizing grid management, enhancing power system stability, optimizing resource allocation, and improving automation processes. Through quantitative analysis of implementation data from multiple case studies and experimental setups,  this research demonstrates significant improvements in operational efficiency, fault prediction accuracy, and energy conservation. The findings highlight a 37% improvement in fault prediction accuracy, 22% reduction in energy consumption, and 45% decrease in system downtime across analyzed implementations. This research provides a comprehensive framework for electrical utilities, system operators, and industrial facilities to effectively integrate AI solutions within  existing infrastructure, addressing critical challenges of reliability, sustainability, and resilience in modern electrical systems.