Practical Applications of Network Management Tools in Emerging Technologies

Abstract

The rapid evolution of emerging technologies—such as the Internet of Things (IoT), edge computing, 5G network slicing, and artificial intelligence (AI)—has significantly reshaped network management practices. As networks become increasingly complex, large-scale, and diverse, traditional approaches relying on manual oversight and static, rule-based systems are no longer sufficient. To address these growing demands, modern network management is shifting toward intelligent, automated solutions capable of real-time analysis, dynamic resource allocation, and improved security. This article examines the practical applications of advanced network management tools, with a particular emphasis on AI-driven monitoring, anomaly detection, automation, and the move toward standardizing network intelligence. Based on recent technological developments from 2019 to 2025, it evaluates how these tools contribute to building more resilient, adaptive, and secure networks. The discussion highlights key advantages, including predictive maintenance, faster fault detection, optimized traffic handling, and proactive threat response. However, it also addresses limitations such as privacy risks, potential algorithmic bias, and integration challenges with legacy systems. Emerging trends such as self-healing networks, federated learning, and intent-based networking are explored as future directions for scalable and intelligent infrastructure. By addressing both the benefits and challenges, this article emphasizes the essential role of AI enhanced network management in enabling next-generation connectivity.