Healthcare’s AI transformation: Agents, search, and platforms

As AI continues to evolve from a buzzword into a business essential, new advancements like AI agents and AI-powered search are improving healthcare. Here’s what you need to know.

Generative AI’s meteoric rise over the past three years has sparked a fresh wave of innovation that stands to transform nearly every industry — perhaps none more than healthcare. The potential applications for gen AI are vast, ranging from summarizing patient-doctor encounters to scheduling appointments and extracting key patient data for prior authorization requests to assisting with diagnoses and treatment recommendations.

At Google, we believe that AI, harnessed boldly and responsibly, has the potential to transform health outcomes on a planetary scale — and we’re deeply committed to delivering the technologies, tools, and resources that help everyone, everywhere live healthier lives.

More importantly, better health doesn’t happen alone. Some of our biggest breakthroughs have been achieved through collaborations with world-class clinical, public health, and academic organizations — from detecting breast cancer with the accuracy of a radiologist to sequencing genomes faster than ever before to screening hundreds of thousands of patients for diabetic retinopathy.

Healthcare’s digital transformation is only just beginning, and we want to ensure that the advancement of AI technologies is a joint effort with the healthcare ecosystem — not just something that’s happening to it. With that in mind, let’s explore some of the biggest developments we see making an impact as organizations put AI to work.

1. AI agents are transforming healthcare workflows.

Across all industries, we’re moving into the era of AI agents, powered by gen AI. These intelligent systems can proactively search for information, plan multiple steps ahead, and take actions to achieve specific goals — marking a significant shift from AI as a tool to AI as a collaborative partner.

AI agents act as a bridge between the promise of AI to reimagine workflows and the realization of that value. This is particularly critical given that healthcare workers are accustomed to established practices and may be hesitant to adopt new solutions, especially when they are unclear about the benefits of a new technology or feel that it increases their workload.

Within healthcare, AI agents offer new ways to tackle persistent industry issues, such as easing administrative burdens that often take focus away from patient care. Our research shows that clinicians spend more than a third of their week on tasks like maintaining patient records, completing insurance forms and referrals, documenting procedures, and filing information for claims. AI agents can assist with many of these processes, automating back-office tasks like scheduling and paperwork or quickly summarizing a patient’s medical history.

Highmark Health, for example, one of America's most prominent healthcare organizations, built an application that offers agentic capabilities offering Allegheny Health Network clinicians the ability to analyze medical records for potential issues, and suggest relevant clinical guidelines to strengthen submissions — leading to reduced administrative burden and an improved patient experience. Bayer is also developing an AI Innovation Platform that leverages gen AI to assist healthcare developers with building AI-powered apps that help radiologists streamline image analysis and data analysis tasks to improve diagnostic efficiency.

AI agents are poised to shape a new healthcare paradigm, leading to more resilient healthcare organizations, a connected, collaborative ecosystem, and improved patient well-being.

2. AI-powered search is improving access to information.

Healthcare providers are overwhelmed by the vast amounts of information they have — including research papers, fragmented patient records, new guidelines, and more — and little time to process it and make sound decisions. This challenge is compounded by the difficulty of searching medical information using traditional keyword searches, which often struggle with complex medical terminology and abbreviations.

The emergence of semantic search, powered by clinical knowledge graphs, empowers healthcare workers to quickly and easily find the most relevant and accurate information from a wide range of clinical data, including electronic health records (EHRs), scanned documents, and other sources. For instance, AI-powered search can not only find results mentioning “diabetes” in patient records but also pull up other relevant information like the latest treatment research, prescribed medications and test results, or common comorbidities. While this example illustrates the potential of AI search, healthcare organizations will need the ability to ensure the accuracy and factuality of AI-generated response, such as grounding responses with high-fidelity or providing citations to verifiable sources.

In addition, many of our customers and partners are combining AI-powered search with gen AI models like Google’s multimodal Gemini models. This allows clinicians to ask questions about a patient record and get back answers quickly, making it easier to find the exact information they need. One of the leaders in this area is MEDITECH, a pioneer in the EHR space, which integrated advanced AI-powered search and summarization into its Expanse EHR system. The new capabilities give clinicians quick and intuitive access to comprehensive patient information, allowing them to instantly review past provider notes to confirm conditions like sepsis or surgical site infections within minutes, eliminating lengthy chart reviews.

3. AI platforms are essential for AI success.

Gen AI is a powerful tool for boosting productivity and improving access to health information. At the same time, many organizations are realizing that implementing AI requires not only investing in models but also platforms that make it easy to bring gen AI to life. AI platforms provide access to powerful models, along with capabilities to develop, deploy, manage, and secure AI solutions at scale, empowering healthcare providers to move quickly from concept to real-world impact.

In addition, teams need tools to build, evaluate, and monitor models while mitigating challenges like algorithmic bias, hallucinations and model drift. Vertex AI offers a unified environment for addressing these concerns, offering features for rigorous evaluation, bias detection, grounding and continuous monitoring. This ensures the reliability and accuracy of AI outputs and responses, paving the way for integrating AI into healthcare workflows and clinical routines.

Choosing the right platform can be a differentiator for driving value faster. Companies need models that have been rigorously tested and reviewed for bias, along with a spectrum of platform capabilities that help abstract away the complexities of adopting AI. Beyond the ability to assess, evaluate, optimize, and fine-tune models, they also need ways to ground gen AI in their data to reduce the risks of inaccurate responses and hallucinations. Platforms can also simplify some of the more complicated aspects of operationalizing AI by providing enterprise-grade governance, orchestration, and security built in.

And since AI is only as good as the data that fuels it, leaders will also need to consider how well the broader platform ecosystem supports building secure data foundations. The introduction of Gemini 2.0 marks a leap into the new agentic era, bringing new advances to process diverse data types — including, clinical records, operational data, unstructured notes, medical images, audio, and video. To make the most of these new capabilities, healthcare organizations need the ability to bring together disparate data and integrate it with advanced analytics and the latest AI solutions.

The Cloud Healthcare API, for instance, facilitates ingesting, storing, and managing key healthcare data types, including HL7v2, FHIR, DICOM, and unstructured text. Cloud Healthcare API also enables providers to connect clinical and medical data to the full power of the Google Cloud ecosystem, such as BigQuery and Vertex AI, to unlock more valuable insights with data analytics and AI.

Building the next era of healthcare

Whether you’re on the front lines of patient care or pushing the boundaries of cutting-edge medical research, it’s clear AI is rapidly transforming the healthcare landscape — from streamlining back-office operations to eliminating bottlenecks to accelerating drug development and new research discoveries. Organizations need to understand the latest advancements to ensure they can make smart technology decisions today that will enable them to meet the future of healthcare tomorrow.

Embracing AI responsibly and strategically — and most importantly together — will empower the healthcare industry to deliver better patient care, improve operational efficiency, and drive innovation for a healthier future.

To learn more about the state of AI in healthcare, read our in-depth 2025 healthcare trends report.