Google Cloud expands AI agent tools for healthcare
The tech giant unveiled a centralized hub where organizations can access pre-built agents as well as a protocol that allows multiple agents to communicate with one another, regardless of the technology stack used to build them.
The Google Cloud pavilion stand at the 2025 Hannover Messe industrial trade fair on March 31, 2025 in Hanover, Germany. (Sean Gallup / Staff via Getty Images)
Dive Brief:
- Google Cloud unveiled new tools for deploying artificial intelligence agents in healthcare, including a gallery of agents and a method to support multiple agents working together.
- The tech giant rolled out its Agent Garden, a centralized hub where organizations can access pre-built AI agents from Google, third-party companies, or healthcare organizations that create their own custom agents.
- Google also revealed the Agent2Agent Protocol, a framework that allows multiple agents to communicate with one another regardless of the technology stack used to build them.
Dive Insight:
AI continues to be an exciting technology for healthcare industry leaders, igniting hopes it could lessen providers’ heavy load of administrative tasks and extend the capabilities of the clinician workforce as the population ages and needs more care.
Agentic AI could be the next step when it comes to automating healthcare work, proponents say. Agents can handle more complex, multi-step tasks compared with earlier iterations of AI tools, like chatbots, said Aashima Gupta, global director for healthcare strategy and solutions at Google Cloud, during a press preview.
For example, one agent available in Google’s AI Garden, called the Deep Research Assistant, can comb through data and compile a report, showing the steps it took to reach its conclusions.
The next frontier for agentic AI is multi-agent systems, which allows agents to collaborate across multiple functions, Gupta said. The Agent2Agent Protocol announced would set a framework that allows those agents to communicate, even if they were built by different developers.
"Imagine entire systems powered by multiple AI agents working together autonomously to optimize things like revenue cycles, streamlining claims operations, even proactively addressing bottlenecks," Gupta said.
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