Scalable and Secure AI Infrastructure for High-Impact Industries

Abstract

As industries increasingly adopt AI-driven solutions, scalable and secure infrastructures become essential to manage data-intensive operations. This paper presents a modular design for scalable AI infrastructure that integrates advanced security protocols with cloud-native technologies. The proposed architecture ensures data integrity, protects sensitive information, and adapts to evolving workload demands. Applications in healthcare and finance are analyzed to demonstrate the model's versatility, highlighting improvements in scalability, reliability, and compliance. This framework serves as a blueprint for deploying secure AI systems in high-stakes industries.