Wind energy is an important part of renewable energy. It requires complex wind energy conversion technologies and creative ways based on advanced analytics. This study provides a comprehensive analysis of artificial neural networks (ANNs) in wind energy systems, focusing on the most often used techniques in various applications. The research demonstrates that ANNs are effective substitutes for traditional methods, particularly in recent times. The methods are divided into four main application areas: optimal control, finding faults, examinations, optimized design, and modelling and predictions. A detailed analysis of every application area highlights the benefits and drawbacks of various ANN topologies, while a statistical research assesses the current state and potential trends in this sector. The study does a quantitative analysis of significant references, offering fresh statistical perspectives on the state of the field now and its potential futures. Furthermore, based on the conclusions of the literature analysis, the article concisely describes the primary challenges and technical shortcomings that occur while using ANNs in the context of wind turbines. A thorough table provides a concise summary of important references categorized by application categories and case studies, giving a consolidated viewpoint.