Emerging technology is becoming increasingly crucial to the efficiency and success of health systems.
Forty-nine healthcare leaders spoke with Becker’s about the emerging technology that has surprised them the most.
The leaders featured below are speaking at Becker’s 10th Annual Health IT + Digital Health + RCM Conference, Sept. 30-Oct. 3, 2025, at the Hyatt Regency Chicago.
If you would like to join the event as a speaker, please contact Scott King at sking@beckershealthcare.com.
As part of an ongoing series, Becker’s is connecting with healthcare leaders who will speak at the event to get their perspectives on key issues in the industry.
Editor’s note: Responses have been lightly edited for length and clarity.
Question: Which emerging technology has surprised you the most in the past year, and why?
Kathy Sanford. Senior Executive Vice President and Chief Nursing Officer, CommonSpirit Health (Chicago): I’m continually impressed by the innovative ways we’re leveraging technology to enhance patient care. One area that’s been particularly exciting is the application of robotic process automation (RPA). We’re seeing incredible results by using RPA to proactively identify individuals who are overdue for critical screenings before a patient visit and helping us ensure that no one falls through the cracks. The impact has been remarkable.
This isn’t just about efficiency; it’s about empowering our nurses and care teams to focus on what they do best: providing compassionate, personalized care, knowing that technology is working tirelessly behind the scenes to support their efforts and ultimately, save lives.
Martha Hyacinthe. Director of Patient Safety, HCA Healthcare (Nashville, Tenn.): Emerging technologies like generative AI and quantum computing have been particularly surprising in their rapid advancements over the past year. Generative AI tools, such as ChatGPT, have demonstrated unprecedented capabilities in creating realistic text, images and even code, transforming industries like content creation and software development.
For instance, generative AI is now used to draft marketing copy, design product prototypes and assist in medical research. Similarly, quantum computing has achieved significant milestones, with companies like IBM and Google enhancing qubit stability and error correction, paving the way for practical applications. These breakthroughs are reshaping industries, from logistics optimization to drug discovery, at a faster pace than expected.
Biju Samkutty. Chief Operating Officer, International and Enterprise Automation, Mayo Clinic (Rochester, Minn.): The most surprising emerging technology in healthcare over the past year has been the rise of multimodal generative AI assistants seamlessly integrated into clinical workflows. Unlike earlier AI solutions, these advanced systems synthesize data across clinical text, imaging, and laboratory results to deliver real-time decision support and streamline complex documentation tasks.
Their accelerated transition from pilot programs to enterprise-scale deployment—particularly within key specialties—has exceeded expectations and is poised to reshape care delivery models. This evolution marks a pivotal shift from AI as a back-office utility to a frontline clinical collaborator, enhancing our clinicians’ ability to provide truly differentiated, category-of-one care.
Dr. Anjali Bhagra. Medical Director of Automation, Mayo Clinic (Rochester, Minn.): The most compelling technological advancement in the past year has been the acceleration of agentic AI — intelligent automation systems designed not just to follow rules, but to think, adapt and act with purpose.
These AI agents are a step-change from traditional task-based automation. They exhibit goal-directed behavior, memory, real-time learning and tool integration, enabling them to plan, reason through ambiguity and execute complex workflows. What’s particularly striking is how quickly these capabilities are moving from theoretical frameworks to real-world prototypes and applications.
We’re now exploring how agentic AI can triage documents, support clinical teams and navigate the administrative maze with growing independence and precision. When done right, with deliberate human-in-the-loop design, it has the potential to amplify clinical excellence, unlock workforce capacity and scale impact without scaling effort.
Dr. Michael Maniaci. Chief Clinical Officer, Advanced Care at Home, Mayo Clinic (Rochester, Minn.): I think that the most surprising and impactful emerging technology in healthcare this past year has been the rapid evolution of multimodal generative AI agents. These systems can now see, hear, speak, and “reason”; interpreting clinical conversations, analyzing patient photos, and responding in real time with contextual intelligence.
In the Hospital-at-Home model, where care is decentralized and data is fragmented, this type of AI acts as a digital teammate, helping clinicians make faster, smarter decisions remotely. What’s most surprising is the pace of advancement; we went from simple chatbots to AI that can perform real-time documentation, symptom triage, and patient education in under 12 months.
These tools are already being piloted to support nurses and physicians managing acute care in the home. For the first time, it feels like we’re developing a true ‘hospital intelligence layer’ where the building or technology becomes part of the care team. As both the physical hospitals and decentralized care modalities grow, this kind of technology will be essential to reduce workload, increase patient safety, and extend clinical reach. It doesn’t replace human care, it enhances it in ways we couldn’t imagine even a year ago.
Aditya Bhasin. Vice President of Software and Chief of Web Systems, Stanford Health Care and Stanford School of Medicine (Stanford, Calif.): The rapid advancement of multi-modal generative AI has been the most surprising and transformative development in healthcare this past year. Its ability to seamlessly integrate and analyze unstructured data (text, images, audio, video) is unlocking unprecedented innovation.
We’re already seeing remarkable improvements: personalized learning in medical education, accelerated research via automated literature reviews and clinical trial matching, and enhanced clinical practice through advanced diagnostics, patient communication, and staff wellness. What’s most striking is how swiftly these technologies have transitioned from experimental concepts to practical applications, improving patient outcomes and operational efficiency.
Lewis W. Marshall Jr. Chief Medical Officer, NYC Health + Hospitals/Lincoln Hospital (New York City): The past year has been an exciting time for healthcare as technology advances to meet challenges like staffing shortages, documentation burdens and increased patient volumes.
Two innovations surprised me the most:
- Ambient AI. AI scribes are reducing documentation time and improving accuracy, which is a game-changer for clinicians and patients alike.
- Agentic AI. The ability of agentic AI to plan and achieve goals with limited human interaction has huge potential, particularly in helping patients navigate the health system, schedule appointments and better understand their care.
Agentic AI could be especially impactful in managing chronic conditions like hypertension and diabetes by tracking treatment goals and alerting both patients and clinicians when intervention is needed.
That said, we must establish strong guardrails and human oversight to ensure these tools remain accurate, ethical and trustworthy.
Eric Smith. Senior Vice President and Chief Digital Officer, Memorial Hermann Health System (Houston): While many emerging capabilities are transforming different areas of healthcare, AI-based voice technology has stood out the most to me. One reason is the rapid expansion of solutions in this space, including established vendors integrating voice into their platforms. What has been even more surprising is the steady increase in patient adoption.
Interactive voice technology has existed for years, but it was often viewed as a source of frustration. Now, patients appear to be engaging with these tools, which is an encouraging shift given the potential they have to reduce administrative burdens and improve access to care.
Felix Segre. Director of Revenue Integrity, Memorial Hermann Health System (Houston): I would say, Real-time collaboration tools have pretty much saved all of us from the endless email threads and “final_v2_reallyFINAL_THISone.docx” nightmares. Tools like Google Docs, SharePoint Document, Slack, Miro, and Notion let you work on the same thing at the same time without stepping on each other’s toes—most of the time, anyway. You can watch your coworker type something, delete it, retype it, then delete it again, all in real time. It’s oddly satisfying.
No more guessing which version is the latest or digging through your inbox for that one file someone swears they sent. Need feedback? Just leave a comment, tag someone, and keep moving. Working across time zones feels less like a scheduling puzzle and more like… well, still a puzzle, but one you can solve. These tools make remote work feel almost like you’re in the same room, minus the awkward small talk in the kitchen. You still get stuff done, just in sweatpants. Honestly, they’ve turned chaos into something that at least looks like productivity.
Dr. David L. Reich. Chief Clinical Officer, Mount Sinai Health System; President, The Mount Sinai Hospital (New York City): The rapid development of agentic agents to facilitate patient engagement has been remarkable. At Mount Sinai Health System, we use an agentic avatar (“Sofiya”) to conduct pre-catheterization interviews to populate a nursing clinical database. For regulatory purposes, the process is overseen and reviewed by our nursing team for accuracy. The rapid acceptance and great reviews by patients are far beyond what we expected. We are now considering other options for scaling this technology.
Bree Andrews, MD. Chief Wellness and Vitality Officer, University of Chicago Medicine: Ambient technology for physician clinical documentation has impressed me in that it is a digital, patient and physician experience tool. It allows physicians to spend more time directly knee-to-knee with patients while creating a high-quality note. We are eager to use all functionality to minimize the need to recall or read or synthesize patient information such that each moment a patient is under our care can be used to create next steps for their treatment plan.
Patti Cuartas. Executive Director and Associate Chief Medical Informatics Officer, Mount Sinai Health System (New York City): I’m most surprised by the speed of AI implementation — particularly in voice, chatbots and automated clinical summaries. The thoughtful integration of these tools with our EMR has been impressive, resulting in clinically useful, accurate summaries for providers.
Tesha Montgomery. Senior Vice President of System Patient Access, Houston Methodist (Houston): One of the most exciting and transformative technologies to emerge recently is agentic AI — AI systems capable of acting autonomously, making decisions and executing complex workflows. Like many other organizations, we have seen success with ambient listening. At Houston Methodist, as these tools evolve, we’re harnessing their capabilities to fundamentally reimagine and enhance the health care experience for our patients and clinicians.
Some recent examples include replacing traditional interactive voice response systems (IVRs) with intelligent agents that allow patients to confirm, cancel or reschedule appointments, manage prescription refills and receive proactive outreach for specialty referrals, radiology and cardiac diagnostic orders. We’re also using large language models to evaluate call quality at a scale and depth far beyond what human teams alone could achieve. Agentic AI is paving the way for a future where health care is more intuitive, efficient and responsive — for both patients and providers.
Dr. Wendy Ross. Director of the Center for Autism and Neurodiversity, Jefferson Health (Philadelphia): The speed with which AI has been incorporated into medical care has been staggering. Its potential to assist patients with cognitive and executive functioning challenges, by helping them understand their diagnoses and care plans, is especially exciting.
Puneet Freibott. System Chief Nursing Officer, Beth Israel Lahey Health (Cambridge, Mass.): The two most surprising emerging technologies have been virtual cardiac rehabilitation and ambient listening.
Beth Israel Lahey Health adopted virtual cardiac rehabilitation as an amplifier to our traditional brick and motor cardiac rehab centers. We are finding that patients are excited about utilizing this model independently or as a hybrid model to complete their prescribed cardiac rehab.
Ambient listening was introduced in our ambulatory care setting a few months ago and is now being scaled to our inpatient case management, and wound care nurses. We are receiving unsolicited feedback about how this technology is single handedly improving the cognitive and time burden for our clinical staff.
Eric Snyder. Executive Director of Technology and Innovation, University of Rochester Medical Center – Wilmot Cancer Institute (Rochester, N.Y.): If I had to pick one emerging technology that surprised me most this year, it would be the rise of lightweight, multimodal AI models that are small enough to run on-premises without massive infrastructure.
These models are enabling faster, leaner prototyping and innovation within healthcare, challenging the belief that impactful technology must be slow, complex or expensive.
Melinda Cooling. Chief Nurse and Advanced Practice Provider Executive, OSF HealthCare (Peoria, Ill.): One of the most surprising emerging technologies in the past year has been the rapid advancement of AI in clinical documentation, particularly through ambient tools like DAX. These technologies passively listen during patient visits and generate real-time, structured notes that integrate directly into the EHR, which reduces documentation time and clinician burden.
Most surprising is how quickly these tools have moved from concept to real-world clinical use, with early results showing improvements in efficiency and provider satisfaction. This signals a major shift in how technology can meaningfully support clinicians and reshape top of license practice. It also illustrates the importance of leadership agility while preparing for new technology implementation into the clinical workflows.
Dr. Toyosi Olutade. Chief Medical Officer, UnityPoint Health-Quad Cities (Bettendorf, Iowa): Over the past year, I’ve been deeply focused on how artificial intelligence can be meaningfully integrated into clinical practice — specifically in ways that help physicians, advanced practice providers, and bedside clinicians improve their daily work.
The more I learn about and experience ambient AI, the more convinced I become that we are on the cusp of a transformative breakthrough. AI scribes that return 60 to 90 minutes of time per day to clinicians are not just a productivity boost, they are a game-changer.
Empowering clinicians with more time to think, connect and heal is one of the most impactful investments we can make for the future of care.
Dr. Rahul Kashyap. Medical Director of Research, WellSpan Health (York, Pa.); Assistant Professor, Mayo Clinic (Rochester, Minn.): One of the most surprising and exciting emerging technologies in medicine this past year has been the explosive rise and integration of generative AI into clinical documentation and decision support — especially tools like AI scribes and multi-modal large language models (LLMs). This isn’t just an evolution, it’s a revolution in clinical intelligence.
What once felt like science fiction is now being embedded into daily workflows at lightning speed (AI listening to patient-doctor conversations and generating structured notes) is now already being piloted and integrated into EHR systems. From pilot projects to live clinical use, all in a blink (Speed of adoption). AI-generated notes rival — and in some cases, surpass — human scribes in quality, accuracy, and turnaround time, freeing up hours for physicians (Performance). Thanks to multi-modal LLMs, we now have tools that integrate voice, image, and data streams, capable of interpreting radiology, analyzing pathology, and even supporting robot-assisted surgery (Expansion beyond text). It’s not just about replacing tasks, it’s about reimagining how care is delivered.
Diane Constantine. Director of Clinical Informatics, University of Maryland Medical System (Baltimore): What has surprised me most this year is how quickly generative AI has moved from concept to real-world impact, especially in clinical documentation and decision support. Its integration into EHRs like Epic, and growing acceptance among nurses and clinicians, reflects a shift from skepticism to cautious optimism.
Reid Stephan. Vice President and Chief Information Officer, St. Luke’s Health System (Boise, Idaho): The speed at which generative AI is improving clinician documentation has surprised me. What started as experimental scribes are now context-aware, EHR-integrated tools that reduce burnout and improve patient interactions. The implications for scaling quality care are massive.
Dr. Pooja Vyas. System Vice President of Care Coordination and Physician Advisement, SSM Health (St. Louis): One of the most surprising and impactful emerging technologies in the past year has been the advancement of ambient clinical intelligence, particularly AI-driven tools that integrate real-time voice recognition and documentation automation within the EHR. As a physician and system leader focused on improving denials management and physician workflows, I’ve seen many documentation efficiency tools over the years, but ACI marks a true turning point.
These platforms go beyond simple transcription—they now understand clinical conversations, extract structured data, and generate near-final documentation embedded directly into the EHR. This technology not only reduces the documentation burden for physicians but also significantly enhances the specificity and completeness of notes, directly supporting accurate MCC/CC capture and medical necessity articulation. What’s even more surprising is the speed of adoption: major health systems have already gone live with ACI tools, and their integration into Epic workflows has proven to reduce denials and improve clinician satisfaction.
For health systems like ours, ACI presents a unique opportunity to align physician experience, documentation quality, and revenue integrity—essentially transforming clinical documentation into a frontline defense against denials without adding administrative burden to providers.
Dr. Matthew Breeden. Director of Medical Informatics, SSM Health (St. Louis): The most surprising development this past year has been the rapid rise of generative AI, especially its swift shift from experimental to operational use in clinical settings. This pace of advancement has outstripped the development of clear regulatory frameworks, particularly in the U.S., where oversight remains fragmented.
While agencies like the FDA and NIST are exploring guidance, there is no unified national policy, unlike the EU’s AI Act or the UK’s institutional oversight efforts. This regulatory gap allows for rapid innovation but raises serious concerns about unvalidated tools being integrated into clinical workflows. As clinical informaticists, we must stay engaged to help ensure these technologies are implemented safely and responsibly.
Jennifer Lavoie, RN, CPC, Director, Revenue Cycle Integrity, Rush University Medical Center (Chicago): Casechek has been an amazing surprise and game-changing SaaS vendor whose emerging technology brings much-needed automation around the high-dollar world of supplies, devices, and implants. The tool provides visibility for informed decision-making and the insights to drive positive financial outcomes.
Without the Casechek software, making data connections between clinical care, supply chain, and finance is a manual process, where accuracy and visibility can be a challenge. By digitizing the coordination of vendor-supported clinical procedures, it closes long-standing gaps between the procedural areas such as OR, Cath Lab, Interventional Radiology, and the supply chain along with the revenue cycle (and all of the separate systems these areas use).
What makes Casecheck truly innovative is its real-time ability to detect discrepancies, prevent missed/incorrect charges, and ensure alignment with item purchasing contract terms. It’s the only solution I’ve seen that ties clinical, operational, and financial insights together in easy-to-use reporting and dashboards.
Ashok Kurian. Assistant Vice President of Data and AI, Texas Children’s Hospital (Houston): What’s truly remarkable in healthcare this past year is how multi-modal AI, supercharged by cloud computing, has become incredibly adept at synthesizing all forms of patient data. It’s no longer about analyzing just one data point.
These systems can now seamlessly integrate everything from medical images like MRIs and CT scans, to genetic sequencing results, electronic health records, and even real-time data from wearable devices. All of this is securely processed and stored in the cloud.
This capability provides healthcare professionals with an unprecedented, holistic view of a patient’s health, leading to much more precise diagnoses, highly personalized treatment plans, and significantly accelerated medical research by unlocking insights from previously siloed information. The sheer speed at which these sophisticated, data-intensive systems have moved from concept to practical application, thanks to the immense power and flexibility of cloud computing, is genuinely astonishing.
Dr. Nancy J. Beale. Vice President of Clinical Informatics and Chief Nursing Informatics Officer, Catholic Health (Buffalo, N.Y.): I believe the convergence of multiple emerging technologies — virtual care platforms, AI and remote monitoring — is serving as a catalyst for safer, smarter care models.
It’s not about one single technology but about how these systems integrate to create better patient and nurse experiences.
Dr. Ken Nepple. Associate Chief Health Information Officer, University of Iowa Health Care (Iowa City, Iowa): I have been amazed by the impact of AI-powered chart abstraction (from Evidently) within the EHR. The overall AI summaries (including ALL imaging and labs in one location rather than scattered) have made clinic so much more efficient. The recent ability to customize AI prompts has been like a superpower to personalize and identify important information including care gaps. Game changer.
Lynn Ansley. Vice President of Revenue Cycle Management, Moffitt Cancer Center (Tampa, Fla.): The most surprising emerging technology this past year has been the rapid evolution of AI copilots, especially in revenue cycle management. This shift not only boosts team engagement and productivity but also directly supports our financial performance. By reducing administrative overhead and accelerating workflows, we’ve seen improvements in our cost to collect and overall operational efficiency.
Dr. James Matera. Senior Vice President of Medical Affairs and Chief Medical Officer, CentraState Medical Center (Freehold, N.J.): I have been impressed with technology that can help two things, both helpful in improving the physician/patient relationship. Certainly ambient voice technologies have allowed physicians to spend more of their valuable time doing what they are trained to do, care for patients.
As this improves, I am sure physicians will see a decrease in the administrative burden placed on them. The second, of course, is Large Language Models (LLMs) which are becoming a reference for clinicians at times, much like Up To Date did starting back in the 90s. With these advances, we must continue to be stewards of the information and how, and if, it can apply of have clinical meaning and significance.
Dr. Salim Afshar. Faculty and AI Translation Lead, Health Systems Innovation Lab, Harvard T.H. Chan School of Public Health (Boston): The emerging technology that has surprised me the most in the past year is the development pace of frontier AI models. The velocity of development that has taken not only ChatGPT or Claude, but those that started much later such as xAI, which released Grok-3 in February 2025 and then in July Grok-4, enabling multimodal capabilities and real-time interactions is staggering.
These frontier models are immediately transforming the application and implementation capabilities of products and services in healthcare, transforming how we will work with AI. Remember, in March of 2025 Grok rolled out voice mode in English only and then by April it expanded to over 145 languages, combined with sub-second conversational speeds that outpace competitors like GPT-4o in benchmarks for fluid, context-aware dialogues.
These types of capabilities will unlock super staffing services in healthcare, powering AI agents for tasks like multilingual patient follow-ups, diagnostic support, and administrative automation. The challenge is not technology, but health system transformation, in which health systems will need to build their capacity building processes for translating AI within their own context and constraints.
Dr. Chrisanne Timpe. Medical Director of Home-Based Medicine and In-Home Complex Care, HealthPartners Park Nicollet (Bloomington, Minn.): I am most impressed and excited by the use of Point of Care ultrasound in hospitals, skilled nursing facilities, and home based care as a reliable, efficient and cost effective diagnostic tool, when traditional radiology settings are unavailable or limited in capacity. My hope is to see this mode of technology become commonplace in home-based programs across the nation.
Anneliese Fischer. Revenue Cycle Manager, The Medical Center at Ocean Reef (Key Largo, Fla.): One emerging technology that’s really surprised me over the past year is the rapid advancement of generative AI in clinical decision support. The speed at which these tools have evolved and the potential they hold to assist clinicians with diagnosis, documentation, and patient engagement is both exciting and a little humbling.
From streamlining prior authorizations to automating denial management and predictive analytics for collections, the speed and scale at which these tools are being implemented is remarkable. For example, we’ve seen success using AI to flag claims likely to be denied allowing providers to use the correct Evaluation and Management (E/M) code and proactively correct issues before submission saving time, reducing cost, and improving cash flow.
We’re only scratching the surface of what’s possible, and it’s clear that thoughtful integration will be key to unlocking real impact.
Dr. Judd Hollander. Senior Vice President of Healthcare Delivery Innovation, Thomas Jefferson University Health (Philadelphia): Ambient listening surprises me the most. It is one of the few things where the benefits of a “soft ROI” have outweighed the costs. Clinician engagement and desire has paved the way for widespread incorporation, despite a lack of proven return on the balance sheet. It seems well on its way to becoming a standard tool that is required for operations.
Robb Wetmore. Director of Digital Healthcare, Variety Care (Oklahoma City): One of the most surprising—and game-changing—developments in the past year has been the evolution of ambient AI for clinical documentation. What began as glorified voice-to-text has transformed into something genuinely useful: tools like DAX Copilot now listen, understand, and generate notes in real time, freeing providers from screens and giving them back the one thing they never have enough of, time with patients. Our providers have made it clear—sometimes with friendly threats—that taking it away is not an option. They say it’s let them return to why they got into medicine in the first place.
Another area that’s quickly gaining ground—and one we’re keeping a very close eye on—is AI-assisted diagnosis, especially in imaging. Tools like AYE-DS and similar platforms are bringing diabetic retinopathy screening directly into primary care, allowing frontline teams to detect serious issues early without relying on specialist availability. But the real dream? Real-time radiology reads, particularly in areas like breast screening. For FQHCs and rural systems, the idea that an AI could flag something urgent the same day—not weeks later—has massive implications for equity and early intervention.
Both of these technologies reflect the same truth: AI is finally showing up not to replace clinicians, but to support them—quietly, effectively, and in ways that restore rather than erode the human side of care.
Dr. Rajiv Pramanik. Chief Information Officer and Chief Health Informatics Officer, Contra Costa Health (Martinez, Calif.): The rapid uptake of business platforms and expansion of ITSM tools to fit this realm.
Susan Ibanez. Chief Information Officer, Southeast Georgia Health System (Brunswick, Ga.): While I’m not really surprised by this emerging tech, I very happy to see it. I love the AI powered wearables. Smartwatches have been around for what seems like an eternity in tech years. The new AI functionality in the wearable segment I think will step up the population health game.
We all struggle in health systems to engage the patients in their care plan. This tech that we are all wearing some form of can help patients manage chronic conditions, remind or schedule appointments for patients, and predict health issues or changes in health in some cases. I think that it may be just the nudge that many of us need to be proactive in our health care management.
Dr. Nabil Chehade. Senior Executive Vice President and Chief Clinical Transformation, Innovation and Strategy Officer, MetroHealth System (Cleveland): My vote is for Agentic AI as it is anticipated to play a significant role in the evolution of health care delivery, potentially surpassing the impact of generative AI. It is expected to optimize complex administrative and clinical workflows by making autonomous suggestions and taking actions with minimal input from human prompts.
Tatyana Sushkina. Director of Revenue Cycle, Prosser Memorial Hospital (Prosser, Wash.): From a revenue cycle perspective, the most surprising emerging technology this past year has been the rise of AI-powered automation, especially in claims follow-up, denial prevention, and coding support. These bots are now handling tasks that used to keep entire teams buried in spreadsheets and sticky notes.
Honestly, I’m starting to think some of them deserve their own office keys. The speed at which they’ve integrated with EHR and billing systems is impressive and a little terrifying, in a good way. It’s like having a supercharged intern who never sleeps and doesn’t ask for coffee breaks.
Michael Laukaitis. Director of Revenue Cycle Analytics, UT Southwestern Medical Center (Dallas): The technology that caught me off guard is this new breed of self-directed AI agents. Ours tracks payer policy changes: it harvests updates from disparate websites, auto-summarizes the relevant ones, flags those taking effect within 30 days, and stores the documents for audit. The ease with which it took over a task that once drained hours from analysts shows how suddenly the line between human and software responsibilities is shifting.
Dr. Deepti Pandita. Chief Medical Informatics Officer and Vice President of Clinical Informatics, University of California Irvine Health (Orange, Calif.): The technology that has surprised me most over the past year is generative AI, particularly its rapid evolution from experimental to practical clinical applications. What’s striking is not just the capability to generate text, images, and insights, but its potential to transform workflows—reducing administrative burden, enhancing patient engagement, and even supporting clinical decision-making.
The speed of adoption and innovation, paired with the ongoing need for governance, equity, and trust, underscores both its promise and responsibility. For healthcare, this is no longer a futuristic concept; it’s happening now.
Robert V. Boos. Vice President of Revenue Cycle, Centra (Lynchburg, Va.): The emergence of generative AI in healthcare has surprised me the most this past year. While we’ve long anticipated the role of AI in diagnostics and analytics, the speed at which generative tools have begun transforming documentation, coding, and patient engagement has been remarkable. What excites me is the potential to reduce administrative burden while actually improving accuracy and patient communication, a rare combination in healthcare innovation. The challenge now is ensuring thoughtful integration into clinical and revenue cycle workflows.
Sandeep Rustagi. Chief Data Analytics Officer, University of Mississippi Medical Center (Jackson, Miss.): While Generative AI and LLMs have certainly seen spectacular growth, I find the foundational rise of AI chips equally fascinating. Who would have thought these chips would become one of the most strategic levers in geopolitical dynamics in such a short span of time? Clichéd but likely true – with AI, we are witnessing a once-in-a-lifetime technological revolution.
Dr. Giovanni Piedimonte. Vice President of Research and Research Integrity Officer, Tulane University (New Orleans): Without a doubt, quantum computers are the most surprising and impactful technology to emerge in recent years, and their momentum has quickly accelerated with the recent launch of new, faster, and more powerful machines. Quantum computers can solve highly complex statistical problems that are way beyond the capabilities of today’s computers, across various industries, including medicine and pharmaceuticals.
A notable example is the discovery of the tertiary structure of caffeine, which provided detailed information about its conformation, electronic properties, and interactions, all of which would have been impossible with a traditional computer system. This could enable unprecedented business capabilities, which will likely draw significant investments from both private and government sources worldwide.
Unfortunately, the United States is rapidly falling behind other countries, especially China, in deploying this highly strategic technology due to relatively limited research and development investment in the field. Reversing this trend soon will be absolutely critical to maintaining U.S. leadership in the future.
Dr. Yasir Tarabichi. Chief Medical Informatics Officer, Ovatient; Chief Health AI Officer, MetroHealth System (Cleveland): The most surprising development this year has been the speed with which LLM-based tools for information retrieval and documentation have penetrated clinical workflows.
While their ability to deliver rapid, seemingly authoritative answers has met a real need for timely, evidence-informed decision support, this widespread adoption also raises important questions: do we truly understand the risks of epistemic drift, automation bias, or misplaced trust in AI-generated knowledge? These tools are filling a vacuum, but often faster than we’ve established the infrastructure to govern or validate them responsibly.
Kerri Webster. Vice President and Chief Analytics Officer, Children’s Hospital Colorado (Aurora, Colo.): AI-powered generative models have shown transformative potential, from diagnosing diseases via imaging to designing novel medications. What amazes me the most is how these technologies are collectively reshaping medicine rather than any single tool alone.
Tim Sibert. Director of Revenue Operations, Family Care Center (Colorado Springs, Colo.): I didn’t expect to be as impressed by robotic process automation 2.0 as I am. We now have bots performing nuanced tasks like denial pattern recognition and real-time eligibility checks, essentially functioning as a tireless digital workforce.
Dr. Nirmit Kothari. Associate Chief Medical Officer, Baptist Memorial Hospital – Memphis (Memphis, Tenn.): Generative AI has become one of the most promising technologies in healthcare, from documentation automation to patient engagement. Its ability to integrate with EHRs, radiology and surgical planning makes it a cornerstone of the future healthcare ecosystem.
Dr. Chris DeFlitch. Vice President and Chief Medical Information Officer, Penn State Health (Hershey, Pa.): AI, specifically the practical applications like conversational tools and generative documentation, has been a standout. When trained on reliable data and validated by experts, these tools can dramatically improve patient and staff experiences.
Tom Andriola. Chief Digital Officer and Vice Chancellor of IT and Data, UC Irvine (Irvine, Calif.): I’ll mention three, one not surprising and two that are emerging and interesting to watch in the next 12-24 months.
The most surprising and impactful technology in 2025 has been the acceleration of AI, particularly in its clinical integration and patient-facing applications. From the performance alongside radiologists to the forecasting of outcomes in chronic disease management to the somewhat surprising acceptance of AI-powered virtual assistants for patient engagement (recently reported 77% patients willing to use them). The speed of adoption and depth of integration, including the emergence of first-generation agentic AI solutions, are hurling toward mainstream.
The Internet of Medical Things (IoMT) – The network of connected medical devices and wearables that continuously monitor patient health, enabling real-time data collection and monitoring to reduce hospital readmissions and improve chronic care management. Wearables and smart implants are reaching professional-grade quality. Couple this with the above AI for patient engagement, and it starts to look like “AI everywhere, all the time.”
Mixed Reality (MR) in Surgery and Training – The combination of virtual reality and augmented reality to create immersive environments for surgical planning and medical education. Surgeons can now rehearse complex procedures in virtual environments, improving outcomes and reducing errors. Additional use cases for both training and live surgical assistance show measurable improvements in precision and confidence.
The advances in technology to improve the quality and access of healthcare continues. But the big question in front of us is one of AI Observability and ultimately trust. Advancement and adoption are two different things. The technology we have available today is far ahead of our ability to understand it, explain it, adopt it, and build trusted frameworks around it.
Garrett Olin. Chief Information Officer, Shasta Community Health Center (Redding, Calif.): I think one of the most surprising and rapidly advancing technologies is the use of digital twins of patients. The concept of creating real-time virtual models for diagnosis and treatment simulation is evolving from theory to practice at an astonishing pace.
Laura Wood. Program Administrator, Northwest Regional Campus, UAMS Health (Fayetteville, Ark.): The rapid advancement of generative AI in healthcare education has surprised me the most this past year. Tools like AI-powered tutoring systems and automated content creation are transforming how medical knowledge is delivered and absorbed. It’s impressive how quickly these technologies are being integrated into curricula, helping educators personalize learning and students gain deeper, more interactive experiences.
Salim Saiyed, MD, MBA, FAMIA, Chief Medical Information Officer, UT Health Austin; Assistant Professor, Hospital Medicine Division, Internal Medicine Department and Assistant Professor, Population Health: In the past year, AI adoption within healthcare has been the most surprising successful emerging technology. From Ambient AI generating documentation, to creating chart summaries, Radiology reads, to clinical decision support, the pace at which AI has been deployed and integrated has been unprecedented. I believe this is the just the start, Healthcare systems will continue to expand the use in more novel ways to improve patient and physician experience to improve healthcare.
