Cloud-Native AI refers to artificial intelligence systems designed to run and scale within cloud environments from the outset. Rather than treating AI as a standalone workload, these systems use cloud-native technologies such as containers, microservices, APIs, orchestration, and automated deployment to manage model training, inference, data pipelines, and supporting services.
This approach is useful when AI applications need to handle changing workloads or serve models across distributed applications. For example, an AI platform can independently scale inference services as demand rises, deploy updated models through automated pipelines, and connect them with cloud data stores and application services without scaling the entire system together.
