Multi-Cloud FinOps: AI-Driven Cost Allocation and Optimization Strategies
DOI:
https://doi.org/10.56472/ICCSAIML25-116Keywords:
Cloud Resource Optimisation, Multi Cloud Environment, Financial Accountability, Finops Strategies, Data IntegrationAbstract
While organizations are still chugging along the fast lane of technology evolution, they are also choosing a multi-cloud strategy to address their evolving and complex business needs. Multi-cloud is the use of services from various cloud providers (e.g., Amazon Web Services (AWS), Microsoft Azure, and Google Cloud), which offers flexibility, resilience, and performance optimization. However, managing and optimizing costs across multiple cloud environments is one of the biggest challenges organizations are facing. As cloud adoption increases, organizations are looking for ways to manage cloud costs efficiently while using resources optimally. Financial Operations (FinOps) is emerging as a key practice that is increasingly helping organizations manage cloud costs effectively. Cloud FinOps is a financial discipline and a cultural practice that seeks to bring together finance, engineering, and operations. It is focused on cross-functional collaboration in cloud spending to help optimize cloud resources, understand cloud costs, and drive financial accountability for the cloud. Cost allocation and Optimization-driven approach leveraging AI for FinOps in multi-cloud. Machine Learning, Predictive Analytics and Anomaly Detection-based AI technologies can be used for Cloud financial management. It discusses the tools/platforms available for multi-cloud FinOps and how AI can be integrated with them to automate activities like cost allocation, usage forecasting, optimization etc. It also discusses why the paper emphasizes the difficulties organizations encounter in implementing AI-based FinOps strategies, including data integration issues, model complexity, and organizational inertia. Justifying the need for such AI-based FinOps for enterprises operating in a multi-cloud, this article presents relevant literature, case studies and real-world examples. It also covers what lies ahead in cloud financial operations and how the convergence of technology evolutions, like AI and the cloud, will drive the future state of cloud cost management for the enterprise
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