As artificial intelligence tools continue to advance, the transformative potential in healthcare is becoming increasingly clear.

Historically, much of the focus has been on validating algorithms in controlled research settings. However, the real impact of AI is only realized when these technologies are integrated into everyday clinical practice and shown to improve health outcomes. Today, a growing number of health systems are not just exploring but actively investing in and implementing AI solutions, demonstrating their commitment to advancing healthcare through responsible and effective technology adoption.

Becker’s Healthcare, in partnership with the Joan and Irwin Jacobs Center for Health Innovation at UC San Diego, has compiled a list of leading U.S. health systems that are pioneers in demonstrated, outcomes-based AI solutions. These organizations are not only conducting transformative research but are also demonstrating tangible patient benefits from AI applications. Their success is characterized by a deliberate focus on ethical implementation, ensuring that AI technologies are used responsibly and effectively.

Given the challenge of tracking and evaluating these advancements, we highlight these leading health systems in AI for their robust leadership, outcomes-based studies and strategic investments.

Dive into the list below — alphabetically by state — to discover our top picks.

1. California — Kaiser Permanente

Kaiser Permanente, headquartered in Oakland, Ca., is the country’s largest private nonprofit healthcare organization, comprising 40 hospitals and 616 medical facilities. Kaiser has one of the nation’s most extensive patient care datasets, enabling the health system to develop and test its AI tools thoroughly for safety, effectiveness, accuracy, and equity before deploying them to patients, care providers, and communities.

Leadership

Daniel Yang, MD, Vice President of AI and Emerging Technologies. Dr. Yang oversees the safe, reliable, accurate, and equitable application of AI within the organization. He sets quality standards for AI across clinical operations, research, education, and administrative functions. Dr. Yang has established infrastructure to support the development and evaluation of diagnostic AI algorithms, including public datasets and third-party performance assessments. He also advances research methods for assessing AI’s clinical impact in real-world settings and represents Kaiser Permanente in the US AI Safety Consortium and the Coalition for Health AI.

Vincent Liu, MD, is a senior research scientist at the Kaiser Permanente Northern California Division of Research and Chief Data Officer for The Permanente Medical Group (TPMG). Dr. Liu oversees the Augmented Clinical Intelligence and Responsible AI Programs and the Systems Research Initiative, a multidisciplinary team supported by TPMG. His research explores sepsis, acute severe illness, informatics, and healthcare delivery, aiming to advance a learning hospital system. He is a noted expert in applied informatics.

Case studies

AI-related financial gifts
Kaiser has funded five healthcare organizations to pursue research projects deploying AI and machine learning (ML) algorithms to enhance diagnostic decision-making in healthcare. Awardees receive grants of up to $750,000, supported through funds from the Gordon and Betty Moore Foundation, to demonstrate the value of these technologies in diverse, real-world settings.

2. California — Stanford Health

Stanford Health Care is a nonprofit public benefit corporation and a leading academic health system comprising Stanford Hospital and more than 60 clinics throughout the Bay Area and beyond. Stanford Health has access to several innovation centers at the university, which bring together experts and leaders from academia, industry, government, and clinical practice to address critical and emerging issues concerning AI’s impact on healthcare.

Leadership

Michael Pfeffer, MD, Chief Information and Digital Officer, and Associate Dean for Stanford Health Care and Stanford University School of Medicine. Dr. Pfeffer has lectured worldwide on health information technology, and was featured in Becker’s Hospital Review as 10 physician CIOs to know and 12 standout healthcare CIOs. Earlier in his career, he helped lead the implementation of the largest electronic health record big bang” go-live at the time at UCLA Health, which involved over 26,000 users.

Nigam Shah, MBBS PhD, Professor of Medicine at Stanford University, and Chief Data Scientist for Stanford Health Care. His research group analyzes diverse health data (EHR, claims, wearables, weblogs, and patient blogs) to answer clinical questions, generate insights, and develop predictive models. At Stanford Health, he leads AI and data science efforts to advance disease understanding, enhance clinical practice, and improve healthcare delivery.

Case study

AI-related financial gifts/​investments
$15 million commitment from the Sandler Foundation to fuel healthcare innovation.

3. California — UC San Diego Health

UC San Diego Health, the region’s only public academic health system, provides patient care through its three hospitals — Hillcrest Medical Center, Jacobs Medical Center, and East Campus Medical Center — as well as specialized centers and numerous clinics across Southern California. Leveraging the resources of the Joan and Irwin Jacobs Center for Health Innovation (JCHI), UC San Diego Health is dedicated to ensuring that AI technologies are developed, evaluated, and deployed in a safe, respectful, and trustworthy manner.

Leadership

Karandeep Singh, MD, Joan and Irwin Jacobs Endowed Chair in Digital Health Innovation, UC San Diego School of Medicine, and inaugural Chief Health Artificial Intelligence (AI) officer at UC San Diego Health. As part of his new role at the Jacobs Center for Health Innovation, he is also leading the development and implementation of AI-driven solutions that enhance clinical decision-making and patient outcomes. Dr. Singh is recognized nationally for his expertise in AI and digital health.

Christopher Longhurst, MD. As combined Chief Medical Officer and Chief Digital Officer, Dr. Longhurst leads UC San Diego Health’s technology strategy, driving initiatives that advance the infrastructure across UC San Diego and the UC Health system, while also overseeing the clinical activities of the academic medical center. Dr. Longhurst, who has a rich background in medicine and informatics, is also the Executive Director of the Jacobs Center for Health Innovation, where he spearheads groundbreaking initiatives that drive positive change in the digital healthcare landscape, ultimately helping to improve the patient experience.

Both leaders have published on the growing significance of the Chief Health AI Officer role, which is expected to become essential for maximizing AI’s benefits while managing its risks.

Case studies

AI-related financial gifts/​investments

$22 million for the Jacobs Center for Health Innovation to help build a first-of-its-kind mission control center to manage patient flow across the continuum, as well as boost the center’s AI innovation portfolio.

4. California — UC San Francisco Health

UC San Francisco Health is a public academic health system that includes three medical centers, two hospitals, two children’s hospitals and specialty clinics, as well as a psychiatric hospital and clinics in the region. The university’s versatile and robust internal AI platform allows UCSF clinicians, administrators, and scientists to utilize large language models while ensuring that both the prompts and the data remain securely within UCSF’s enterprise cloud.

Leadership

Sara Murray, MD, inaugural Chief Health AI Officer and Associate Chief Medical Information Officer. Dr. Murray is a visionary leader in health informatics, digital health, and data science. She spearheads the creation of robust infrastructure and governance processes to deploy impactful and ethical AI solutions. Dr. Murray shapes the strategic vision for scaling AI to revolutionize healthcare delivery at UCSF Health and beyond.

Bob Wachter, MD, Chair of the Department of Medicine and author of The Digital Doctor, which explorers the digitization of healthcare delivery. In 2024, he chaired groups examining the impact of AI on patient safety, and has been a fierce advocate of the transformative potential of generative AI in healthcare.

Case study

AI-related financial gifts/​investments

$5 million gift to develop AI monitoring platform.

5. Massachusetts — Mass General Brigham

Mass General Brigham is a private nonprofit health system that includes two academic hospitals, three specialty hospitals, seven community hospitals, home care services, and more. As a world-recognized leader in research, it is home to one of the largest hospital system-based research enterprises in the U.S., with an annual research budget of $2 billion. The health system taps into Mass General Brigham AIs expertise to translate research into clinical practice. With a team of clinicians, data scientists, and engineers, the center addresses complex healthcare challenges and offers comprehensive product development and advanced computing resources.

Leadership

Adam Landman, MD, Chief Information Officer for Mass General Brigham. Dr. Landman specializes in using IT to enhance healthcare delivery. He leads technology solution delivery and support across all Mass General Brigham hospitals and practices. He collaborates to design and implement a forward-looking digital strategy that addresses frontline needs while integrating emerging technologies and ensuring efficient and effective support.

Keith Dreyer, PhD, DO, Chief Data Science Officer. Named to the inaugural Time 100 AI List, Dr. Dreyer, also vice chair of radiology, manages numerous AI algorithms for medical imaging. He ensures their effectiveness and privacy, explores AI-based reimbursement, and studies the potential for autonomous AI in healthcare.

Rebecca Mishuris, MD, Chief Medical Information Officer and VP, Digital. Dr. Mishuris is helping to lead Mass General Brigham’s use of technology to help measure physician workload, prevent burnout, and make an impact on both physicians and patients. She explores how technology intersects with the quintuple aim of healthcare, with a current focus on digital solutions for enhancing physician well-being, quality, and equity.

Case studies

AI partnership with GE Healthcare
Clinical trial screening using generative AI

AI-related financial gifts/​investments

Mass General Bringham has invested $30 million in an Artificial Intelligence and Digital Innovation Fund to invest in venture stage companies whose offerings further the health system’s strategic initiatives.

6. Minnesota — Mayo Clinic

The Mayo Clinic is the largest integrated, not-for-profit, private medical group practice in the world, comprising 16 hospitals, 50 multispecialty clinics, and one mobile health clinic. The health system has over 200 AI projects at various stages. Data scientists and clinician-researchers are using AI and machine learning to derive insights from extensive patient data, quickly solving problems and creating new healthcare tools and treatments. The Mayo Clinic has also built a new Research Department for AI and Informatics, established a Center for Digital Health and a Department of Quantitative Health Sciences, and launched the Mayo Clinic Platform.

Leadership

Bhavik Patel, MD, Chief AI Officer of Mayo Clinic in Arizona. He heads Mayo Clinic’s Advanced AI and Innovation Hub in Arizona, driving the expansion of AI solutions across the health system’s practice, research, education, and business operations. His research focuses on developing AI models that help healthcare providers efficiently utilize all available data.

John Halamka, MD, president of the Mayo Clinic Platform, an ecosystem for innovators. Dr. Halamka leads a portfolio of platform businesses dedicated to transforming healthcare through artificial intelligence, connected devices, and a network of trusted partners. With over 25 years of experience in emergency medicine and medical informatics, he is an expert in shaping and implementing healthcare information strategy and policy.

Matthew Callstrom, MD, is the head of the Generative Artificial Intelligence program at Mayo Clinic, leading its strategy across the enterprise. Dr. Callstrom is the chair of the Mayo Clinic Midwest Department of Radiology and Mayo Clinic’s medical director for Strategy, as well as serves as a member of the Mayo Clinic Board of Governors and Board of Trustees and holds the academic rank of professor of radiology, Mayo Clinic College of Medicine and Science.

Case studies

AI-related gifts/​investments
$20 million gift from Dwight and Dian Diercks to accelerate MayoClinic’s AI adoption.

7. New York — New York University Langone Health

New York University Langone Health is a private nonprofit system consisting of the NYU Grossman School of Medicine and NYU Grossman Long Island School of Medicine, along with more than 300 locations in the New York City area and Florida. These locations include six inpatient facilities, a children’s hospital, and four emergency rooms. The health system is at the forefront of digital health innovation, leveraging the expertise of the The Center for Healthcare Innovation and Delivery Science as well as the The Predictive Analytics Unit in the MCIT Department of Health Informatics, which uses data and modeling to predict health outcomes across NYU Langone. It is one of the first health systems to develop a large language model using clinical documentation and demonstrate its value in a series of downstream prediction tasks.

Leadership

Nader Mherabi, Executive Vice President and Vice Dean, and Chief Digital and Information Officer. Mherabi leads NYU Langone Health’s digital transformation, enhancing workflows, revolutionizing the digital patient experience, and leveraging big data to improve care and efficiency. He has extensive experience in integrating clinical systems and designing large-scale IT solutions.

Leora Horwitz, MD, MHS, Director, Division of Healthcare Delivery Science and Founding Director of the Center for Healthcare Innovation and Delivery Science. Her work focuses on improving the safety and quality of healthcare delivery.

Yindalon Aphinyanaphongs, MD, PhD, assistant professor in the Center for Health Innovation and Delivery Science, and Director of Operational Data Science and Machine Learning. His sought-after research focuses on machine learning, predictive analytics, translational clinical data science, translational predictive analytics. Dr. Aphinyanaphongs leads a team of engineers and data scientists dedicated to transforming healthcare through AI.

Paul Testa, MD, Chief Medical Information Officer. He leads many digital health and AI initiatives across NYU Langone, including the integration of informatics and IT.

Case studies

8. North Carolina — Duke Health

Duke Health is a private, not-for-profit medical system that includes three inpatient facilities — Duke University Hospital, Duke Regional Hospital and Duke Raleigh Hospital. The health system includes the Duke Institute for Health Innovation (DIHI) whose mission is to accelerate health innovations by partnering with Duke University School of Medicine and its clinical network. The health system’s AI efforts are also supported by Duke AI Health, while the Duke Margolis Institute for Health Policy supports AI policy research. Duke Health is one of the founding sites for the Coalition for Health AI and the Health AI Partnership.

Leadership

Michael Pencina, PhD, inaugural Chief Data Scientist and Vice Dean for Data Science, Duke University School of Medicine. Pencina is spearheading Duke’s efforts as a founding partner of the Coalition for Health AI, aiming to enhance AI trustworthiness through guidelines for credible, fair, and transparent health AI systems. An internationally recognized expert, he advises on AI tools and algorithms, shaping best practices for their use in clinical medicine.

Suresh Balu, MD, Associate Dean for Innovation and Partnership for the School of Medicine, and Program Director for the Duke Institute for Health Innovation (DIHI). Dr. Balu leads a team driving innovations in healthcare, education, and research. He also spearheads data science initiatives, integrating digital strategies, AI/ML, and algorithmic decision support to improve care safety, quality, and efficiency.

Mark Sendak, MD, Population Health & Data Science Lead at the Duke Institute for Health Innovation. Dr. Sendak leads interdisciplinary teams of data scientists, clinicians, and machine learning experts to develop technologies addressing real clinical challenges. Additionally, he directs the DIHI Clinical Research & Innovation scholarship, training medical students in business and data science for healthcare innovation, and co-leads the Health AI Partnership to advance the safe and equitable use of AI in healthcare. He is the co-inventor of software that scales machine learning and real-world evidence across health systems.

Case studies

AI-related gifts/​investments
$30 million award from The Duke Endowment to elevate research in computing, artificial intelligence, and machine learning.
$10 million donation by the Margolis Family Foundation to Advance Health Policy.

9. Ohio — MetroHealth (Case Western affiliated)

MetroHealth is a public healthcare system that operates five hospitals, four emergency departments and more than 20 health centers and 40 additional sites. It is considered a safety-net health system that cares for everyone, regardless of their ability to pay. The health system uses a multidisciplinary approach to optimize value-based care through initiatives like the Population Health Innovation Institute, which is transforming patient care by advancing clinically integrated delivery methods.

Leadership

David Kaelber, MD, PhD, Chief Medical Informatics Officer, Vice-President of Health Informatics and Patient Engagement Technologies, and Founding Director, Center for Clinical Informatics Research and Education. His informatics research expertise spans electronic health records, personal health records, health information exchange, telehealth, big data, and clinical informatics education

Nabil Chehade, MD, Executive Vice President and Chief Clinical Transformation Officer. He is responsible for all aspects of clinical transformation, digital and population health. Dr. Chehade specializes in clinical transformation, focusing on social barriers and health equity. He has led numerous projects in EHR implementation, physician engagement, health system strategy, and governance.

Yasir Tarabichi, MD, Medical Director of the Virtual Care Enterprise, and Director of Clinical Informatics for Research Support. Dr. Tarabichi focuses on EHR-based strategies for precision population health, educates providers on health data literacy, and supports research, clinical applications, and quality improvement initiatives.

Case studies

Use of an AI sepsis model to speed up administration of antibiotics
A randomized quality improvement study to reduce disparities using an AI no-show model

10. Tennessee — Vanderbilt Health

Vanderbilt Health is a nonprofit, private health system that includes seven hospitals and more than 200 clinics. In 2024, Vanderbilt’s Department of Biomedical Informatics launched ADVANCE, a pioneering center for health AI. Utilizing advanced data analytics, machine learning, predictive modeling, and generative AI, ADVANCE aims to enhance decision-making, accelerate discoveries, and improve clinical outcomes.

Leadership

Peter Embi, MD, Professor and Chair, Department of Biomedical Informatics, and Senior Vice President for Research and Innovation. An internationally recognized leader in biomedical informatics, his expertise includes clinical, research, and public health informatics, as well as data-driven learning health systems.

Bradley Malin, PhD, Vice Chair for Research Affairs Department of Biomedical Informatics, and Co-Director of the AI Discovery and Vigilance to Accelerate Innovation and Clinical Excellence (ADVANCE) Center. His research focuses on advancing AI/ML technologies within organizational, political, and health information systems. Key contributions include distributed data processing for medical record linkage, intelligent auditing for protecting electronic records, and algorithms for anonymizing patient data for research.

Adam Wright, PhD, Professor of Biomedical Informatics and Medicine at Vanderbilt University Medical Center, and Director of the Vanderbilt Clinical Informatics Center (VCLIC). He has led funded projects on clinical problem lists, malfunctions in clinical decision support systems, approaches for sharing clinical decision support nationally, and adverse event detection using machine learning.

Case studies

11. Wisconsin — University of Wisconsin Health

University of Wisconsin Health is a public-private partnership that includes both public and private entities, comprising six main hospitals in Wisconsin and Illinois. The health system is one of three nationwide trials (along with UC San Diego Health and Stanford Health Care) of an AI program developed by Epic and Microsoft. UW Health is home to the Health Innovation Program (HIP), which is a campus-wide program focused on transforming healthcare delivery and population health across the state and nation.

Leadership

Chero Goswami, System Vice President and Chief Information and Digital Officer. Goswami spearheads initiatives that drive healthcare innovation and transformation, aiming to optimize patient outcomes, boost physician effectiveness, and enhance community care.

Brian Patterson, MD, Physician Administrative Director for Clinical AI. Dr. Patterson collaborates with hospital leadership to enhance healthcare quality, efficiency, education, and research through information technology. He has developed predictive analytics and machine learning models, improving patient care by predicting sepsis and assessing fall risks.

Case studies

*Article originally published by Becker’s Healthcare.