This research paper explores the integration of artificial neural networks (ANNs) and data mining to create hybrid intelligent systems that offer enhanced decision support. The paper emphasizes this approach's significance in overcoming traditional AI methods’ limitations. Through a comprehensive literature review, the study highlights the strengths of ANNs and data mining while identifying gaps in existing research on hybrid intelligent systems. The methodology section details the construction of the hybrid system, including the selection of ANN architectures, data mining algorithms, and integration strategies. Experimental validation using diverse datasets demonstrates the system's superiority over traditional AI methods in decision support applications. The paper also examines the real-world applications of the hybrid intelligent system in various industries, such as healthcare, finance, and manufacturing, while addressing ethical considerations for responsible deployment. In conclusion, the research highlights the immense potential of hybrid intelligent systems to significantly improve decision-making processes significantly, showcasing the value of combining ANNs and data mining for practical and impactful outcomes.