This IDC Survey Spotlight provides analysis of the deployment location/computing model used for AI/ML/DL workloads. Specifically, this Survey Spotlight highlights the broad use of public cloud and expected increase of private cloud and edge location for specific phases and use cases.
"Today, public cloud leads the deployment location for run of AI/ML/DL workloads due to the scale of compute and storage resources available, as well as easy access to AI services, but with the need for organizations to hold on to their IP and insights adoption, private cloud adoption is expected to increase for the training phase of most of the AI deployments," said Ritu Jyoti, research director, for IDC's Enterprise Storage, Server, and Infrastructure software team at IDC. "This will lead a broad reconfiguration of the on-premises infrastructure supporting AI workloads."
Analytic applications, Cognitive/artificial intelligence, Customer relationship management applications, Integration and process automation middleware, Intrusion detection and prevention, Supply chain management applications