Amazon Web Services (AWS) has today announced bold expansions in agentic AI during its Summit in New York, revealing both a new marketplace for AI agents and major infrastructure investments.
The announcements mark a milestone in AWS’s push to bring autonomous, agent-based workflows into mainstream enterprise use, a trend already gaining momentum in cloud computing.
One headline grabber was the launch of AWS’s AI agent marketplace, set to open immediately following the Summit. In collaboration with Anthropic, AWS will offer a storefront where developers and startups can list specialized AI agents. Enterprises will be able to browse, deploy, and manage these tools directly within AWS environments.
Amazon confirmed it will earn a share of the revenue from each agent sold through the marketplace, positioning the platform as a new commercial layer within the cloud ecosystem.
AWS chief executive Matt Garman emphasized that agentic AI is rapidly evolving from simple chatbot interfaces into systems capable of reasoning, planning, and executing on user goals across entire workflows. According to Garman, AWS has been enhancing its infrastructure to support this shift, including upgrades across compute resources, AI frameworks, and developer tooling.
The company also revealed that it is investing thirty billion dollars into artificial intelligence infrastructure across Pennsylvania and North Carolina. This move supports growing demand for cloud services in both private and public sectors.
A key part of AWS’s strategy includes enhancements to its Bedrock platform. New multi agent collaboration features were introduced, enabling developers to assign specific tasks to individual agents and manage them through a central coordinator. This is designed to help companies tackle more complex problems by combining agents with different skill sets and domain expertise.
Lastly, the Amazon Q Developer tool has been upgraded to handle tasks like software refactoring, continuous integration, and system simulation, allowing engineering teams to use agentic workflows for rapid development and testing.
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