Intelligent automation has emerged as a transformative force in enterprise IT operations, combining artificial intelligence (AI), machine learning (ML), and robotic process automation (RPA) to streamline and optimize complex workflows. This study provides a comprehensive overview of intelligent automation and its impact on modern IT operations, including infrastructure management, incident response, service delivery, and system monitoring. By integrating AI-driven analytics with automation tools, organizations can achieve proactive issue detection, predictive maintenance, and faster resolution of operational challenges. The paper explores key technologies such as AIOps, natural language processing (NLP), and cognitive automation, highlighting their role in enhancing decision-making and reducing human intervention. It also examines practical applications across industries, including healthcare, finance, and cloud-based enterprises. Furthermore, the study addresses challenges such as integration complexity, data quality, skill gaps, and governance concerns, along with strategies to overcome them. The findings emphasize that intelligent automation is essential for improving efficiency, reducing operational costs, and enabling scalable, resilient IT operations in a rapidly evolving digital landscape.
Fajar Nugroho (Mon,) studied this question.