AI-Driven Workload Balancing and Security Integration for Sustainable Cloud Computing

Abstract

The rapid expansion of cloud computing has significantly increased energy consumption, carbon emissions, and electronic waste while introducing critical security vulnerabilities such as data breaches, unauthorized access, and multi-tenancy risks. This paper proposes an integrated AI framework that combines intelligent workload balancing with advanced security mechanisms to promote sustainable and secure cloud operations. Leveraging predictive analytics, reinforcement learning, and zero-trust principles, the framework optimizes resource allocation and mitigates threats across IaaS, PaaS, and SaaS models in public, private, and hybrid deployments. Conceptual evaluation indicates potential energy savings of 20–35% alongside enhanced threat detection accuracy.