AI-Enabled Multi-Cloud Strategies: Balancing Costs and Performance

Abstract

In today's digital landscape, organizations increasingly leverage artificial intelligence (AI) to optimize their multi-cloud strategies, balancing costs and performance effectively. This paper explores the integration of AI technologies in managing and orchestrating resources across diverse cloud environments. We analyze how AI-driven algorithms can facilitate real-time decision-making, enabling organizations to allocate workloads dynamically based on performance metrics and cost considerations. Through case studies and empirical data, we demonstrate the impact of AI on improving resource utilization, minimizing latency, and reducing overall cloud expenditure. Furthermore, we discuss the challenges of implementing AI-enabled solutions, including data security, compliance, and vendor lock-in, while proposing frameworks to address these issues. Ultimately, this study aims to provide actionable insights for enterprises seeking to harness the full potential of AI in their multi-cloud strategies, ensuring a competitive edge in an ever-evolving market.