Artificial Intelligence (AI) has become one of the most influential technologies in the field of computer networking. The increasing demand for high-speed communication, growing network complexity, and the rapid expansion of connected devices have created significant challenges for traditional network management systems. AI enables networks to operate more efficiently by providing intelligent decision-making capabilities, automation, predictive analysis, and enhanced security mechanisms. Through machine learning, deep learning, and data analytics, AI-powered networks can monitor traffic, detect anomalies, predict failures, and optimize resource allocation in real time. This paper presents a comprehensive review of AI applications in networking, highlighting its role in network management, cybersecurity, traffic optimization, and future communication systems. The study also discusses the benefits, challenges, and future directions of driven networking technologies.
Artificial Intelligence is transforming networking by introducing intelligent automation, predictive analytics, enhanced security, and efficient resource management. AI-powered networking solutions address many of the limitations associated with traditional network management approaches. Through machine learning and deep learning technologies, networks can operate more efficiently, respond to threats more effectively, and deliver improved performance. Although challenges related to privacy, data quality, and implementation remain, ongoing advancements in AI research continue to overcome these limitations. The future of networking will be increasingly driven by intelligent systems capable of autonomous operation, making AI a fundamental technology for next-generation communication infrastructures.
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How to Cite This Paper
DR. J. JOSELIN, SHAMRAJ. I, JUSWANTH. M (2026). An Evaluation of Intelligent Networking Systems Using Artificial Intelligence. International Journal of Computer Techniques, 13(3). ISSN: 2394-2231.
