TLDR: Google Cloud announced significant expansions of its healthcare AI partnerships at Google Cloud Next 2025, collaborating with major health systems like Highmark Health, Hackensack Meridian Health, and Seattle Children’s Hospital. These alliances aim to integrate generative AI into daily workflows to combat healthcare worker burnout, streamline operations, and enhance patient care through advanced AI agents and platforms.
At its Google Cloud Next 2025 event in Las Vegas, Google Cloud unveiled a substantial expansion of its healthcare partnerships, deepening collaborations with prominent U.S. health systems. These new alliances underscore Google Cloud’s commitment to equipping clinicians, nurses, and administrators with cutting-edge AI-powered tools designed to manage increasing workloads, reduce burnout, and streamline patient care. The initiative focuses on integrating generative AI into daily workflows to help healthcare providers access complex clinical information faster, enhance decision-making, and improve patient experiences.
Key partnerships announced include collaborations with Highmark Health, Hackensack Meridian Health (HMH), and Seattle Children’s Hospital. Each partnership is centered on leveraging AI to address systemic inefficiencies impacting both patients and healthcare professionals. For instance, Highmark Health, a national blended health organization, is already utilizing Google’s generative AI tools, with Richard Clarke, chief data and analytics officer at Highmark Health, noting that over 14,000 of their 40,000 employees are using the technology and have surpassed 1 million prompts. Clarke highlighted the ‘advancement in multimodality’ and how ‘advances with Imagen, Google’s text-to-image generating model, have specifically allowed the company to revisit solutions.’
Hackensack Meridian Health is developing AI-powered agents to reduce strain on healthcare workers, particularly in post-operative and nursing workflows. These agents are designed to follow up with patients after surgery, conduct automated assessments, and flag issues for clinical teams. ‘We’ve created systems where AI can call patients post-procedure, collect information, generate next steps, and alert aftercare teams accordingly,’ explained a representative. HMH also employs natural language processing (NLP) to rapidly scan structured and unstructured patient data, enabling researchers and clinicians to form clinical hypotheses more efficiently.
In collaboration with Seattle Children’s Hospital, Google Cloud developed the Pathway Assistant, a generative AI-powered agent aimed at improving clinicians’ access to complex information and best practices. This tool, created with input from over 50 healthcare providers, has shown strong indications in initial pilots of its potential to improve patient outcomes by reducing provider workloads, thereby allowing doctors more time and mental bandwidth for direct patient care. Aashima Gupta, Google Cloud’s global director of healthcare strategy and solutions, stated, ‘The sheer volume and complexity of healthcare guidelines present a significant challenge for physicians, often making crucial information difficult to access at the point of care.’
Beyond specific applications, Google Cloud also introduced new foundational tools for deploying AI agents in healthcare. These include the AI Agent Development Kit, an open-source toolkit for creating sophisticated, collaborative AI ecosystems; the Agent2Agent Protocol, an open standard for seamless communication between AI agents regardless of their underlying technology; and Agentspace and Agent Garden, centralized platforms offering access to a broad selection of AI agents from Google, third parties, or custom builds. The Deep Research Agent within Agent Garden is specifically designed to synthesize and analyze vast healthcare data, delivering insights in clear, actionable reports. Gupta envisions ‘entire systems powered by multiple AI agents working together autonomously to optimize things like revenue cycles, streamlining claims operations, even proactively addressing bottlenecks.’
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These advancements signify a shift from isolated, task-focused bots to intelligent, interconnected systems capable of managing complex workflows across departments. The overarching goal is to modernize healthcare systems, reduce human error, enhance communication, and improve care coordination, ultimately transforming the healthcare industry.
