The Rise of Augmented FinOps and AIOps: How AI is revolutionizing multi-cloud management

Palanisamy, Ganeshkumar (2025) The Rise of Augmented FinOps and AIOps: How AI is revolutionizing multi-cloud management. World Journal of Advanced Engineering Technology and Sciences, 15 (3). pp. 359-370. ISSN 2582-8266

The rise of Augmented FinOps and AIOps represents a transformative shift in multi-cloud management. As organizations increasingly adopt multi-cloud strategies to leverage the unique capabilities of different providers, they face unprecedented complexity in managing costs and operations across disparate environments. Augmented FinOps extends traditional financial operations by incorporating artificial intelligence, evolving cost management from reactive to predictive and prescriptive. This enables accurate resource attribution, anomaly detection, optimization recommendations, and natural language interfaces. Meanwhile, AIOps addresses operational challenges through unified observability, predictive issue detection, automated root cause analysis, and intelligent automation. These disciplines are built upon technological foundations, including deep learning for pattern recognition, natural language processing for interface simplification, time-series analysis for predictive capabilities, and reinforcement learning for optimization. Despite implementation challenges related to data privacy, algorithm transparency, and integration complexity, organizations adopting structured implementation strategies gain significant competitive advantages through enhanced operational efficiency, optimized cloud costs, and improved service reliability.