Predictive Maintenance (PdM) has revolutionised power network maintenance, especially electrical system maintenance. Predictive Maintenance and artificial intelligence (AI) may revolutionise power network maintenance, according to this article. Past reactive maintenance practices in power networks have caused expensive downtime and unanticipated breakdowns. AI analyses massive volumes of data from sensors, IoT devices, and past maintenance records to provide Predictive Maintenance. Predictive Maintenance uses powerful machine learning algorithms to find data patterns, trends, and anomalies to help utilities and operators forecast equipment problems. AI-powered Predictive Maintenance has several benefits. Monitoring equipment health and performance helps utilities optimise maintenance plans, decrease downtime, and prolong asset lifetime. Early identification of possible faults permits preventative maintenance, reducing catastrophic failures and guaranteeing power network stability. This article examines AI-powered Predictive Maintenance in power networks and electrical systems. Case studies and real-world examples show how AI-driven initiatives improve asset dependability and operational efficiency. The report also examines data quality, system integration, and regulatory compliance issues related to AI technology adoption in maintenance. AI-powered Predictive Maintenance trends and future directions are also examined in the report. AI can integrate with edge computing, 5G connectivity, and sophisticated analytics methods like predictive modelling and digital twins. Utility power networks may improve resilience and performance by adopting these advances. To conclude, this article provides a complete review of Predictive Maintenance in power networks and shows how AI-powered solutions have transformed electrical system maintenance. AI helps utilities optimise asset management, cut costs, and assure power infrastructure dependability and efficiency in the face of changing challenges