Regenstrief Institute and Suki partner to evaluate ambient AI in healthcare. Organizations share a commitment to understanding how ambient AI technologies impact clinicians, patients and healthcare delivery Regenstrief Institute and Suki, a leader in AI-powered ambient clinical documentation technology, are collaborating to explore how independent research and evidence generation can help healthcare organizations better understand the impact of ambient artificial intelligence technologies on clinicians, patients and healthcare systems. As ambient AI tools become increasingly integrated into healthcare workflows, health systems face important questions about their effects on clinician documentation burden, patient-provider communication, care quality, operational efficiency and trust. Regenstrief and Suki share an interest in advancing evidence-based approaches that help healthcare organizations make informed decisions about the adoption and implementation of these technologies. Suki develops AI-powered ambient clinical intelligence solutions that assist clinicians with documentation and administrative tasks. Regenstrief Institute is internationally recognized for its expertise in health informatics, electronic health records, implementation science and real-world evidence generation. Together, the organizations are exploring opportunities to contribute to a growing body of knowledge around ambient AI and its role in healthcare. "Healthcare organizations need rigorous, independent evidence to understand not only whether AI technologies work, but how they affect clinicians, patients and care delivery in real-world settings," said Rachel Patzer, PhD, MPH, president and CEO of Regenstrief Institute. "As ambient AI continues to evolve, research and evaluation will play a critical role in ensuring these technologies are implemented responsibly and effectively." Ambient AI technologies have gained attention for their potential to reduce administrative burden, support clinical documentation and allow clinicians to focus more fully on patient interactions. However, healthcare leaders, policymakers and providers continue to seek evidence regarding implementation, outcomes, user experience and long-term impact. Ambient AI platforms are designed to capture patient-clinician conversations and assist with documentation workflows, potentially reducing time spent on administrative tasks while supporting more focused patient care. As healthcare organizations continue evaluating emerging AI technologies, both organizations emphasize the importance of transparency, accountability and evidence-based decision-making. Regenstrief's longstanding expertise in healthcare data, clinical informatics and rigorous evaluations of innovative technologies positions it to help answer critical questions about how AI technologies perform in real-world clinical environments.

Suki launches Science at Suki to set a new standard for Healthcare AI. Press Releases September 10, 2026 New scientific initiative launches with the Suki Research Collaborative, uniting leading health systems and researchers to build the evidence base for Ambient Clinical Intelligence REDWOOD CITY, Calif., September 10 - Suki, the leading Ambient Clinical Intelligence (ACI) platform, today announced Science at Suki, an industry-wide scientific research initiative that builds on more than eight years of work at the intersection of AI and clinical care. The initiative will generate rigorous research and real-world clinical evidence to help establish methodologies and standards that advance healthcare AI. Healthcare AI is being adopted at unprecedented speed, but the evidence, standards and trust needed to support that adoption have not kept pace. A new study from the Consortium for Health AI (CHAI) and the University of Chicago's National Opinion Research Center underscores that widening gap: while 75% of respondents reported using AI, only 13% said they were very comfortable with it. More than half said AI made them trust healthcare less, and 93% reported at least one concern about AI in healthcare. As AI becomes increasingly embedded in clinical care, Suki believes that greater scientific rigor, transparency, and consistent standards for how these technologies are evaluated will close this gap between adoption and trust. That is the thesis behind Science at Suki and why it is a groundbreaking initiative that will help advance the potential of healthcare AI. At the center of the initiative is the new Suki Research Collaborative (SRC), a research network with leading health systems and academic institutions, including Regenstrief Institute, the National Center for Human Factors in Healthcare at MedStar Health, University of Miami Miller School of Medicine's Office of AI in Medical Education, and Rush University System for Health. Through this collaborative, Suki will study AI implementation, human factors and clinician adoption, workflow optimization, specialty care, rural healthcare, human factors and medical education, as well as help develop the much-needed standardized frameworks for measuring AI's clinical, operational, and economic impact. As AI adoption accelerates across healthcare, health systems are moving beyond asking whether AI works to understanding how well it works, how it should be measured, how it can be safely implemented at scale and what outcomes it actually delivers. Science at Suki was created to help answer those questions by bringing greater consistency and standardization to how healthcare AI is evaluated. Among the SRC's first initiatives, Suki and Regenstrief Institute are working together today to establish a gold-standard framework for measuring the performance and impact of Ambient Clinical Intelligence. Together, the two organizations will develop standardized metrics and evidence-based methodologies to help health systems evaluate the clinical, operational and financial impact of ambient AI, moving the industry beyond anecdotal success stories toward consistent, evidence-based evaluation. "The future of Ambient Clinical Intelligence won't be defined solely by technological breakthroughs. It will be defined by the quality of the evidence behind them," said Sudha Jayaraman, MD, MSc, FACS, Medical Director of Clinical Strategy and Research at Suki and Chair of the Suki Research Collaborative. "By bringing together leading clinicians, researchers, engineers, and health systems to generate objective evidence, we're helping healthcare organizations adopt Ambient Clinical Intelligence with the confidence needed to improve patient care, support clinicians, and advance the practice of medicine." Jayaraman joined Suki from the University of Utah, where she was a full professor and endowed chair focused on health innovation. She has authored more than 110 scientific publications and book chapters, received NIH funding for more than a decade, and serves as an expert scientific reviewer for the NIH. Science at Suki builds on a growing body of Suki research already published in peer-reviewed medical and scientific journals. These studies examine the performance, quality, safety, implementation and real-world impact of AI in clinical care, providing an evidence base that will continue to expand through Science at Suki and the Suki Research Collaborative. Published research includes: * Selecting, Scaling, and Measuring the Value of Ambient AI in a Nonacademic Health System: Multiphase Pilot Study, JMIR Med Informatics, June 2026 - Found 35% reduction in 'pajama' time and a projected revenue gain of US $2629 per provider per month. * A Conceptual Model for Ambient AI Adoption: Perspectives from Academia and Industry, JMIR Med Informatics, June 2026 - gives guidance for health systems on understanding and making informed decisions about ambient AI technologies * The Promise of Ambient AI Technology in Medical Education: Opportunities and Guardrails, JMIR Med Informatics, Aug 2026 - offers a framework for guardrails to support clinical learning and clinical skills acquisition in medical education Additional studies are underway across performance measures, safety in agentic AI, adoption and impact on clinical reasoning, with findings expected to be published in peer-reviewed open access journals to demonstrate transparency and accountability and enable trust. Science at Suki will continue to publish original research, develop evaluation methodologies and collaborate across healthcare to build the evidence and standards needed for the next generation of healthcare AI. About Suki Suki is a leader in Ambient Clinical Intelligence (ACI), transforming clinical conversations into intelligence that powers documentation, coding, revenue cycle, clinical reasoning, and other workflows across the care journey. EHR-agnostic and built for a wide range of specialties and care settings, Suki reduces administrative burden while assisting healthcare organizations improve clinical and financial performance. KLAS-validated results show Suki delivers more than $2,600 in average monthly financial impact per provider, alongside significant reductions in documentation time and after-hours work. Suki for Clinicians brings ACI directly into the clinical workflow, while Suki for Partners provides SDKs and APIs that embed Suki's intelligence into healthcare technology products. Suki is backed by Venrock, First Round, Flare Capital Partners, March Capital, and Hedosophia. Learn more at suki.ai, and follow Suki on LinkedIn.