AI-Driven Network Management and optimization

Authors

  • Laila Naji Aden University- Faculaty of Engineering
  • Mohsen S. Alsaadi Department of Electrical and Computer, Faculty of Engineering, King Abdulaziz University
  • Waheeb Ahmed Department of Computing, University of Science and Technology, Aden, Yemen https://orcid.org/0000-0003-4270-1422

DOI:

https://doi.org/10.64680/jisads.v3i2.58

Abstract

AI-Driven Network Management and Optimization refers to the use of Artificial Intelligence (AI) and Machine Learning (ML) techniques to monitor, control, and improve computer networks. This approach is transforming how network operations are performed in enterprises, telecom, cloud services, and IoT ecosystems. As a result, network optimization in the telecom industry was revolutionized, allowing for more dependable, scalable, and efficient networks. By anticipating possible failures and identifying network irregularities early on, AI also improves fault management before they affect service quality. Additionally, as the telecommunications landscape grows increasingly interconnected through 5G and IoT technologies, AI enhances network security by detecting and reacting to cyber threats in real-time. This study illustrates how AI-driven solutions can improve network performance in a number of industries.  The study also addresses the limitations of AI in network optimization and offers suggestions to industry participants on how to successfully incorporate AI technologies into current infrastructures for increased network resilience and efficiency. According to the paper's conclusion, AI-driven solutions offer significant improvements in network performance and quality of service, making them a promising path for the future of telecommunications. To reduce such hazards, it also highlights the necessity of strong AI models, ongoing observation, and ethical considerations. The results highlight AI's revolutionary potential in influencing the future wave of telecom infrastructure, guaranteeing consumers dependable and superior connectivity.

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Published

2026-01-11

Issue

Vol. 3 No. 2 (2025): Journal of Intelligent Systems and applied data science (JISADS)

Section

Research and Review articles

License

Copyright (c) 2026 Laila Naji

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