Verily in ‘25 and beyond: powering AI for precision health

When I stepped into the role of CEO of Verily two years ago, I shared our plan to double down on precision health and focus our product portfolio on providing the data and technology to unlock the promise of AI and data science to improve healthcare.

We have made significant strides since then. We strengthened Verily’s leadership team, welcoming executive leaders who helmed teams at Apple, Microsoft, and McKesson. We launched Workbench, our scalable research environment used by customers including All of Us, the Michael J. Fox Foundation, and Helix to manage and expand access to large multimodal data sets. We announced Lightpath, our next generation chronic care management solution, which pairs AI-based technology with clinical experts to provide personalized care for individuals living with conditions such as diabetes and obesity. We scaled our Viewpoint research solutions, including our protocol digitization capabilities, and added new customers such as Geisinger, One Oncology, and Children’s Hospital of Orange County to our growing network of site partners. We grew our public health business, with the CDC selecting Verily Sightline to run their national wastewater monitoring program, covering up to 400 sites, and testing for a growing list of infectious diseases that includes covid, Mpox, and flu. And in December of last year, we completed separation of our technical and operational infrastructure from Google, so we can continue to grow as an independent company within Alphabet.

Our solutions address unique challenges in care delivery, clinical research, and public health, and provide advanced devices for digital measurement. They are all built using a common data model and technology: our Verily platform, developed to address the need to more systematically and securely organize complex healthcare data and drive real-time uses of AI to enable more personalized care and research.

In our work across healthcare, our customers face a consistent challenge: how to make sense of and harness massive amounts of health data. Common barriers include data silos, quality issues, and governance challenges, including lack of common consent frameworks. For example, hospitals create an estimated 50 petabytes of data in a year, and yet, 97% of that data remains unused. As generative AI continues to quickly advance, many healthcare AI applications still rely on public data sources, because proprietary healthcare data isn’t optimized and consented for use.

As an Alphabet company that has worked across many parts of healthcare, we have the technology, talent, and resources to address this critical challenge. The Verily platform works with existing cloud solutions and is built in a secure way, prioritizing privacy, security, and data governance needs while enabling users to harmonize, model, and activate data to unlock precision healthcare. Today this platform powers Verily’s own solutions, while connecting Verily and partner-generated data from across the healthcare ecosystem, as we build the foundation to advance future customized solutions for our customers.

What sets our platform apart is its ability to unify data with our opinionated data model, using standards including USDM, OMOP, and FHIR, which means we can integrate nearly any new data source and data model used by our customers. Through the platform, we ensure data is accurate, traceable, and interoperable, with auditability and high reliability standards built in. This deep attention to the data layer and a strong governance approach enables us to transform raw data into something clinically-meaningful that can power workflows.

Today, we are using large-scale datasets on the platform to advance AI applications and new methods to make AI fit for purpose for healthcare. This enables us to tackle transformative data and AI projects for our life science, payer, and provider customers while adopting industry-leading safety and privacy practices. The platform’s agile infrastructure paired with our regulatory expertise enables us to quickly adjust to evolving government and industry standards as needed.

Across our solutions today, we are implementing AI agents to reduce the time and mental energy spent on manual processes and to help us scale care and data science teams. We take a thoughtful approach to understanding AI’s strengths and limitations, and where it can best play a role in augmenting human workflows. Where it is technically and clinically appropriate, we see potential for AI agents to help recommendations that are both broadly evidence-based and enterprise-tailored, adapting to an organization’s unique needs.

On the care side, Verily’s data platform makes it possible for us to offer a robust AI-enabled experience in our Lightpath solution, available in January 2026. Lightpath Metabolic will provide comprehensive and flexible metabolic care, offering support for multiple tiers of acuity, to improve outcomes for those living with diabetes or obesity or who are on a weight management program. Verily's platform will use agents to triage and escalate a member to our clinical team and to encourage members day to day with personalized suggestions on healthy eating, activity, and overcoming obstacles. The use of predictive modeling to identify risk and individual needs can help lead to better, faster, and lower-cost care—providing efficiencies for payers and providers and more personalized care for members.

In clinical research, large language models (LLMs) and agents are proving to be effective approaches to improve trial operations and recruitment. Today 90% of clinical trials fail due to problems with recruitment, design, and data, leading to delayed treatment for millions of patients and driving up healthcare costs. We believe AI can make a significant difference here. Through our Viewpoint solutions, we have already seen that we can speed the digitization of clinical trial protocols by 70%, which can accelerate overall study startup times. We are now extending these efforts to support clinical trial matching and drive efficiencies across other parts of clinical trial workflows, as we continue to advance the use of ML-based digital measures to improve clinical research.

In public health, through our Sightline solution, data enables us to more efficiently monitor and mitigate disease on a public health level. We are proud of our wastewater work with the CDC and our expansion into the UK through our partnership with Bangor University. With potential threats such as bird flu on the horizon, we see significant opportunities to better use data to tackle infectious disease interventions. For a sponsor running a vaccine trial, we can now detect surges in disease activity in advance of clinical testing to better target recruitment efforts and inform site selection, helping to drive more efficient enrollment and decrease study start-up times. On the commercial side, this data can help inform where to deploy disease awareness campaigns for market-approved infectious disease vaccines, treatments, and diagnostics and help inform supply chain decisions, enabling us to better control outbreaks when they happen. And we’re continuing to advance new frontiers for novel public and private sector applications, including adding new data points and capabilities to support environmental testing and biosurveillance.

We believe in the transformative potential of AI to make care and research more efficient for organizations while delivering more personalized care pathways for patients. Through our platform approach, we can help customers activate their data directly in care environments and research workflows, provide access to a unique data ecosystem to enrich and enhance customer data, and can offer the deep clinical, regulatory and scientific expertise needed to do this well. We believe, as AI-powered solutions continue to accelerate in the next few years.

2025 and beyond will be an exciting year for Verily as we bring new products to market that realize our precision health vision. We hope to work with you in this journey ahead.