These include customer service and contact centers, software engineering and DevOps automation, IT operations, financial services process automation, healthcare administration, supply chain coordination, and security operations, where AI agents often operate simultaneously at scale, Dewan added.
Hyperscalers are taking different paths to production AI
AWS, however, is not alone in adapting its infrastructure for helping enterprises scale AI agents in production, and rival hyperscalers, such as Microsoft and Google, are approaching the challenge in different ways.
Microsoft’s approach with the Azure Foundry Agent Service, according to Chandak, differs from AWS: “Many of its agent runtime limits are fixed by design; they cannot be increased even on request.”
