As enterprises accelerate AI adoption, their cloud strategy determines whether they can efficiently train models, scale workloads, and ensure compliance. Given the computational intensity and data sensitivity of AI, businesses must choose between hybrid cloud and multi-cloud architectures. While both hybrid cloud and multi-cloud approaches offer distinct advantages, understanding their nuances is crucial for organizations aiming to build robust AI infrastructure. 

This article explores the key differences between these strategies and provides practical guidance for enterprises preparing for AI adoption.