The transformative impact of artificial intelligence on cloud infrastructure management

Vissarapu, Srikanth (2025) The transformative impact of artificial intelligence on cloud infrastructure management. World Journal of Advanced Engineering Technology and Sciences, 15 (3). pp. 614-626. ISSN 2582-8266

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Abstract

This article examines the profound transformation of cloud infrastructure management through the integration of artificial intelligence technologies. Traditional approaches to cloud management, characterized by manual intervention and rule-based automation, have proven increasingly inadequate as environments grow in scale and complexity. AI-driven approaches are revolutionizing core operational functions through predictive resource allocation, autonomous fault detection, intelligent security monitoring, and cost optimization frameworks. The article investigates how machine learning and deep learning techniques enable systems that not only react to events but anticipate them, fundamentally shifting operations from reactive to proactive models. Through a mixed-methods research approach combining qualitative interviews, quantitative surveys, and operational metrics analysis, the article identify both technical performance improvements and organizational impacts across diverse industry sectors. While benefits are substantial, the study also highlights persistent challenges including implementation complexity, data quality issues, skill gaps, and cultural resistance. The article suggests that successful AI adoption in cloud management requires not merely technological implementation but comprehensive organizational transformation spanning people, processes, and governance frameworks. As cloud environments continue to evolve, AI capabilities are transitioning from competitive advantage to operational necessity, redefining the relationship between infrastructure and business value.

Item Type: Article
Official URL: https://doi.org/10.30574/wjaets.2025.15.3.0913
Uncontrolled Keywords: Cloud Infrastructure Management; Artificial Intelligence; Predictive Auto-Scaling; Self-Healing Systems; Aiops
Depositing User: Editor Engineering Section
Date Deposited: 16 Aug 2025 12:59
Related URLs:
URI: https://eprint.scholarsrepository.com/id/eprint/4517