Health systems are not stepping into artificial intelligence from a place of calm or control. In the United States, spending now exceeds $4.5 trillion, with a significant share tied up in administrative work that adds complexity more than clarity. Clinicians are caring for more patients, navigating more data and making more decisions under pressure than ever before. The system is stretched. Artificial intelligence is entering at a moment when change is no longer a choice.

The discussion drew on the experience of three leaders who are not observing this shift. They are guiding it. Hal Wolf leads HIMSS, influencing digital health policy and implementation across more than 100 countries. Isaac Kohane, MD, PhD, Chair of Biomedical Informatics at Harvard Medical School, has spent four decades defining how data informs clinical care. Ran Balicer, MD, Chief Innovation Officer at Clalit Health Services, operates within one of the world’s most integrated health systems, where data and care are aligned across generations.

These are not just star panelists. They are system-wide architects.  What emerged from the hour-long conversation was not what artificial intelligence can do. It was a recognition that it is already doing more than most systems are prepared to guide and govern.

Dr. Kohane captured the tension immediately. “I think that we have to worry about the fact that we’re going both too slow and too fast.”

That statement reflects a reality many leaders feel but rarely express. Governance takes time because it must. Patient safety, validation and accountability require structure. Practice moves in real time. Clinicians do not have the luxury of waiting for perfect systems.

“They’re so desperate to do right by their patients to use other resources,” Dr. Kohane adds.

That instinct is not a weakness. It reflects a commitment to doing what is right for the patient. When clinicians turn to external AI tools, they are seeking clarity, speed, and confidence in their decisions. Artificial intelligence is already present at the point of care, shaping how physicians assess information, validate thinking, and move forward. The system is not adopting AI. The system is catching up.

This creates a condition that is difficult to measure and even harder to manage. Different clinicians use different ChatGPT platforms. Those tools produce different answers. Different assumptions shape those answers. Over time, consistency erodes. The system begins to operate with multiple definitions of truth (and the risk of varied outcomes).

Dr. Kohane’s warning is not about misuse. It is about misguided permanence. “The worst outcome will be if the worst parts of medicine get concrete poured over it, by AI.”

Artificial intelligence does not fix a system; without leadership, it accelerates the integration of incorrect assumptions. If workflows are inefficient, they become more efficiently inefficient. If bias exists in data, it becomes more precise. If fragmentation defines care, it scales.

This is not a failure of technology. It is a mirror held up to system-wide leadership.

Hal Wolf, among the health sector’s leading policy and operational voices, grounded this moment in proven experience. Health care has seen this pattern before. When internet connectivity entered hospitals, clinicians moved faster than governance. They created access where it was needed. Systems responded later. Risks were discovered after adoption.

Artificial intelligence now follows that same trajectory, though at far greater speed and with far greater consequences. Web connectivity gave quick access to information. Artificial intelligence influences how that information is interpreted and acted upon.

“We have to go faster,” Mr. Wolf said. “But there needs to be structure around it.”

That is the leadership challenge of this moment. Speed without structure creates exposure. Structure without speed creates irrelevance. The tension between the two is not something to resolve. It is something to manage continuously.

The industry has predictably responded to artificial intelligence. It has started where risk is lowest and return is clearest. Documentation, scheduling and revenue cycle optimization have become the entry points. These applications reduce burden and improve efficiency. They are necessary. However, they are not transformational.

The shift occurs when artificial intelligence moves into clinical decision-making. At that point, the question is no longer whether the system works. The question becomes whether it should be trusted.

Who owns a decision informed by an algorithm? How is accuracy validated? What happens when a clinician disagrees with a recommendation? These are not technical questions. They are questions of accountability. Artificial intelligence does not assume responsibility. It does not carry consequence. That remains with leadership.

Dr. Balicer reframed the conversation, shifting how the room thought about artificial intelligence. “There’s no such thing as AI neutrality. Algorithms are just opinions embedded in code.”

That insight is easy to acknowledge and difficult to operationalize. Every model reflects choices. What data is included? What outcomes are prioritized? What trade-offs are accepted? Those decisions are embedded in the system, shaping how it interprets information.

When a health system adopts an AI tool, it is not simply implementing technology. It is adopting a perspective.

At Clalit Health Services, alignment across payer and provider creates a system where priorities are consistent. Even there, external AI models introduce new assumptions. Those assumptions may not align with the system’s goals. If leadership does not define its own values, it inherits someone else’s.

This becomes real in proactive care. Artificial intelligence enables systems to identify patients at risk before they present. It allows for earlier intervention, often improving outcomes.

It also creates a new kind of pressure. “The toughest choice is what not to do,” Dr. Balicer said.

That statement deserves more attention than it receives. Health care has been built around responding to need. Artificial intelligence introduces the ability to anticipate it. When every patient can be flagged, every risk predicted and every intervention suggested, the system is no longer constrained by insight. It is constrained by capacity.

Artificial intelligence expands what can be done. It does not expand who can do it. Leadership becomes the act of choosing who does what based on validated data.

There is a moment that captures this shift. Imagine a primary care physician starting the day not with a schedule of patients who have called for appointments, but with a list generated by AI identifying individuals who are likely to experience clinical complications in the next six months. Some will develop chronic conditions. Some will require hospitalization. Some can be helped now – preventively.

The physician cannot see them all. Artificial intelligence expands what is possible. Leadership decides what is essential and permissible.

The industry often responds to complexity with activity. Organizations pilot, test and explore. They engage broadly without committing deeply. This creates motion. It rarely creates progress. Pilots are nothing more than experiments. At some point, leadership must decide what to scale, what to stop and what defines value.

Hal Wolf grounded the conversation in discipline. Without a defined, shared objective, effort becomes noise. Pilots create learning, though they often avoid decision-making. Leadership requires clarity. What problem are we solving? What outcome defines success? What are we willing to prioritize? Without those answers, artificial intelligence adds another layer of complexity to an already complex system.

Dr. Kohane brought the conversation back to the discipline of leadership. It cannot remain abstract. It must be informed by experience.

“Go and pay a few bucks and use three or four of the models… get a feel for what this does,” Dr. Kohane advised.

That is not a call for technical fluency. It is a call for leadership proximity. Leaders cannot guide what they do not understand. Artificial intelligence does not behave consistently across models. It produces different answers, shaped by different assumptions. Without direct engagement, those differences remain hidden, and leadership becomes removed from the very decisions it is responsible for guiding.

This is where many organizations hesitate. Artificial intelligence feels complex and complexity invites delegation. At this moment, delegation creates distance. Leadership is required to move closer, not further away.

Artificial intelligence is not reducing the role of leadership. It is redefining it.

This is not a gradual transition. It is already underway. Artificial intelligence is embedded in workflows, shaping decisions and influencing behavior in real time. The system is adapting whether leadership is ready or not.

The question is no longer whether artificial intelligence will shape the future of health. It will. The question is whether leadership will shape how it is applied.

Artificial intelligence will not fix health. It will scale whatever we allow it to touch. The question is whether it will scale what is best in health or what we have yet to fix.

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History, however, offers a useful caution. Breakthrough technologies in medicine rarely achieve their full potential simply because they exist. Their real impact depends on whether the institutions responsible for health-care delivery know how to adopt them wisely, integrate them responsibly and align them with their mission to improve patient health.

Artificial intelligence now stands at that same threshold. The industry has moved beyond fascination with what algorithms can do and entered a more demanding phase: determining how these tools should be evaluated, governed, and integrated into the environments where care is delivered. At the same time, some health professionals are turning to AI – not to augment their knowledge – but assuming the information is patient-care ready.

Across the health ecosystem, leaders are discovering that the most important questions about artificial intelligence are not technological. They are organizational, ethical and operational. Which AI systems genuinely improve clinical decision-making? Which tools strengthen the efficiency of hospitals and health systems? Which innovations introduce complexity without delivering measurable benefit?

Answering those questions requires a perspective that bridges policy leadership, real-world care delivery, and the scientific foundations of biomedical informatics. That convergence of experience sits at the center of a “Views From the Top” mainstage discussion at the HIMSS Global Health Conference & Exhibition, where some 35,000 leaders whose work spans the global health ecosystem will examine how organizations can recognize the true value proposition of artificial intelligence applications before embedding them into health-care systems.

The perspectives shaping this discussion reflect three essential dimensions of responsible artificial intelligence in health: governance frameworks that guide innovation, operational insights from large-scale health care delivery, and scientific rigor grounded in biomedical informatics. Together, these vantage points illuminate the path from technological promise to practical value.

Governing Innovation in a Rapidly Changing Health Ecosystem

Digital transformation in health rarely succeeds simply because technology exists. It succeeds when organizations develop leadership frameworks capable of evaluating innovation, managing risk and aligning new tools with patient-centered goals.

Few leaders have observed the evolution of digital health across as many national systems and institutional environments as Hal Wolf, president and chief executive officer of HIMSS, Ran Balicer, MD, PhD, chief innovation officer of Clalit Health Services and Isaac Kohane, MD, PhD, chair of biomedical informatics at Harvard Medical School. The three will step onto the mainstage at HIMSS to share their “View from the Top” in a session titled: “Recognizing the ‘Value Proposition’ Criteria While Selecting AI Applications.”

Through his work with global government health ministries, hospital networks, and technology innovators worldwide, Wolf has consistently emphasized that technological progress must be anchored in governance and trust.

“Digital health transformation is not about technology alone. It is about leadership, governance, and the trust that allows innovation to improve care,” Wolf has said in discussions about global digital health transformation.

Artificial intelligence intensifies this leadership challenge because its influence extends far beyond traditional clinical tools. AI systems increasingly operate across multiple layers of healthcare delivery. Some applications assist clinicians by analyzing medical data or suggesting treatment options. Others function within hospitals’ and health systems’ operational infrastructure, helping manage patient flow, prioritize diagnostic reviews, and allocate scarce resources.

These operational algorithms rarely capture headlines; however,  they shape the environment in which health care is delivered. Decisions about which cases are reviewed first, how clinicians allocate their attention, and how health systems manage capacity can profoundly influence patient outcomes.

For leaders responsible for health systems, artificial intelligence cannot be treated as simply another technological upgrade. It must be evaluated through governance structures capable of understanding how algorithms function, what assumptions shape their recommendations, and how their use aligns with institutional priorities.

Without that oversight, innovation risks amplifying complexity rather than improving care. Instead of informing, it can spread misinformation.

Aligning Artificial Intelligence With the Values of Medicine

Governance provides the policy foundation for responsible adoption of artificial intelligence, but real-world implementation reveals a second challenge: ensuring that AI systems operate effectively within healthcare delivery itself.

Large population health systems increasingly use advanced analytics to anticipate risk, manage chronic disease, and allocate clinical resources across diverse communities. Within these environments, artificial intelligence is no longer a theoretical innovation. It is already influencing how health organizations prioritize patients, coordinate care and deploy limited resources.

That operational perspective is central to Ran Balicer, MD, PhD, of Clalit Health Services, one of the world’s most advanced data-driven health systems. The Clalit integrated infrastructure connects hospitals, clinics, and community health programs through longitudinal datasets that support predictive analytics at the national scale.

Experience within such systems reinforces an important insight: artificial intelligence models do not function independently of human judgment. They reflect priorities embedded in their design and the assumptions guiding their deployment.

“Algorithms are opinions embedded in code,” Balicer has observed in discussions about the role of artificial intelligence in population health.

In practice, this means that AI systems interpret clinical data through frameworks shaped by human choices. The way a model defines risk, prioritizes cases, or recommends interventions reflects decisions about what matters most within a healthcare environment.

Those decisions carry ethical implications. When artificial intelligence helps determine which patients receive immediate attention or which cases are escalated for further review, transparency about how algorithms function becomes essential to maintaining trust among clinicians and patients alike. The scientific frontier of health-care AI reinforces that concern.

Isaac Kohane, MD, PhD, who has also served as a co-author of the Institute of Medicine Report on Precision Medicine, which has served as the template for national efforts, has spent decades exploring how machine learning can advance medicine while preserving the judgment that defines clinical practice. His research emphasizes that artificial intelligence in healthcare must align with the ethical traditions and professional responsibilities of medicine.

“AI systems in medicine must ultimately reflect the values of the profession they serve,” Kohane has written in discussions about AI alignment in biomedical informatics.

This perspective highlights a crucial distinction between technological capability and clinical responsibility. Many AI models entering healthcare environments were originally designed for broader computational tasks rather than the nuanced realities of patient care. Medicine operates within a landscape shaped by uncertainty, empathy, and accountability, and technologies introduced into that environment must reflect those values.

Ensuring that artificial intelligence aligns with the principles guiding health-care delivery, therefore, represents one of the most important scientific and ethical challenges facing the future of health.

The Discipline Required to Make Innovation Matter

The health sector has experienced waves of technological enthusiasm before. Electronic health records promised seamless information exchange, but then introduced administrative burdens on health professionals when implemented without thoughtful workflow design. Data analytics promised unprecedented insight, but sometimes led to fragmentation when systems failed to communicate across institutions.

Artificial intelligence now stands at a similar moment in the evolution of health technology.

Its capabilities in supporting decision-making flow are extraordinary, yet realizing them will require disciplined leadership to evaluate, integrate and govern AI tools within health-care delivery systems. Health leaders must learn to ask deeper questions before embracing the next algorithmic breakthrough. What problem does this system truly solve? How does it strengthen clinical practice? What assumptions guide its recommendations? How does its use advance the mission of improving patient health?

These questions move the conversation beyond technological novelty toward operational practicality. It’s among the many reasons these three global leaders step to the HIMSS stage together.

Artificial intelligence will undoubtedly reshape the health ecosystem in the years ahead. Its long-term impact, however, will not be determined solely by the sophistication of algorithms or the speed of technological progress. Along with how to leverage AI, ChatGPT and LLMs, users require heightened cognitive awareness.

It will be determined by whether the health community develops the discipline and ability required to translate innovation into systems that strengthen care, support clinicians and improve the health of the populations they serve.

The real story of artificial intelligence in health is no longer about what machines can do. It is about how wisely the health sector chooses to use them.

The post From AI Excitement to Execution: Why Health Leaders Must Now Master the “How” appeared first on Medika Life.

It was the fall of 2022 when large language models and Generative AI burst out of research labs and onto Main Street. Since then, every day seems to bring another AI breakthrough that challenges how work gets done.

In my role advising organizations on AI strategy and deployments, I see a consistent pattern among healthcare leaders: excitement about what AI could unlock, paired with exhaustion from the volume of noise, pressure, and competing claims.

Welcome to 2026.

As predictions flood inboxes and social feeds, focused on what AI might do next, I want to ground the conversation in something more useful. Rather than forecasting outcomes, let’s focus on three forces already at work—forces that will determine whether AI delivers real value in healthcare or quietly stalls.

Will 2026 be a year of boom, bust, or backlash?

The honest answer is yes.

Boom: Early Wins—and an AI Arms Race

Let’s start with what’s working.

Healthcare is seeing real, if narrow, gains from AI:

• Ambient documentation reduces administrative burden
• Imaging and pathology tools iare mproving speed and consistency
• Operational and revenue cycle applications driving incremental efficiency

These are not moonshots. They are targeted solutions addressing specific pain points. And they matter.

At the same time, healthcare is now firmly in an AI arms race.

Every EHR vendor, medical device company, life sciences firm, and digital health startup is racing to declare itself “AI-native.” Roadmaps are packed with copilots, assistants, agents, and automation claims. No vendor wants to be perceived as falling behind.

That pressure is accelerating innovation—but it’s also compressing timelines, encouraging over-promising, and pushing organizations to adopt faster than they can realistically absorb.

Boom energy is real.

But it is also uneven and fragile.

Prediction: Within two years, most AI used in provider organizations will arrive embedded inside core systems and devices already in use. Intelligence will not be something teams “add on”; it will be something they inherit.

Recommendation: Understand where AI is already embedded across your vendor ecosystem and what’s coming next. Engage early through advisory councils or pilots. Engage and prepare clinicians before introducing these capabilities into workflows. AI should never arrive as a surprise.

Bust: When Pilots Multiply, but Value Doesn’t

Generative AI has dominated innovation agendas, yet only a fraction of pilots ever reach sustained production. A survey cited by MIT reports that roughly 95% of business AI pilots fail to generate measurable returns.

This is not evidence that AI lacks value.

It is evident that many organizations lack discipline.

High failure rates are normal in early markets. Technology matures. Tools improve. But value only materializes when leaders focus on fundamentals: design, data readiness, workflow integration, and ownership.

Most AI initiatives fail not because the technology doesn’t work, but because success is never clearly defined. Projects are launched out of curiosity, vendor pressure, or fear of being left behind. Clinical impact, operational accountability, and economic value are clarified too late—if at all.

Equally damaging is the underestimation of the human systems AI enters. Healthcare work is relational, regulated, and trust-dependent. When AI is introduced without redesigning workflows, preparing staff, or clarifying responsibility, it creates friction—not relief. Adoption then stalls quietly.

Prediction: In 2026, organizations will run fewer AI pilots—but with much higher expectations. Boards and executives will require clearer evidence of clinical, workforce, or financial value before approving new initiatives.

Recommendation: Move from “fail fast” to “fail before you scale.” Define success upfront, assign ownership early, and redesign workflows in tandem with technology. AI initiatives without a credible path to value should be halted immediately.

Backlash: Fear, Workforce Anxiety, and the Trust Gap

The most underestimated force shaping AI’s trajectory in 2026 is neither technical nor financial.

It’s human.

History offers context. When automobiles first appeared, they were seen as dangerous and socially disruptive. Red Flag laws required people to walk ahead of vehicles waving flags and capped speeds at just a few miles per hour. These laws weren’t about innovation—they were about fear, control, and adjustment.

Healthcare AI is entering a similar phase.

Workforce research shows healthcare workers are among the most cautious about AI adoption, citing concerns about trust, transparency, and job impact. This caution is not irrational. Healthcare has a long history of technology being imposed rather than co-designed.

As a result, scrutiny is increasing—particularly from labor organizations and state legislators. Recent bills, including those limiting AI’s role in clinical decision-making and licensed practice, reflect not anti-innovation sentiment, but unresolved trust and knowledge gaps.

Innovation does not scale without trust.

In 2026, AI scrutiny will intensify, especially with labor organizations and at the state legislative level.

As I write this, the Chair of the New York State Senate Committee on Internet and Technology just introduced a bill (S7263) to “protect patients and front-line care workers from the adverse effects of AI tools in risky or untested settings.”  The bill prohibits chatbots from performing the duties of licensed nurses and puts strong guardrails around the use of AI in healthcare settings.”

I often write about the need for a balanced approach to defining both the “gas and guardrails” that guide AI’s use in health and medicine. Incentives and safeguards are equally important.

Prediction: Expect increased legislative activity and labor engagement around AI in healthcare throughout 2026. Such actions should not be dismissed simply as anti-innovation. They reflect something deeper: a trust and knowledge gap that needs to be closed.

Recommendation: Create durable AI value by investing in workforce and consumer education. Clinicians need clarity—not just on how AI works, but on how it supports professional judgment rather than replaces it.

From Awe to Analytical

The year ahead will test the resolve of leadership. Transformation in healthcare is rarely linear—and never clean.

Vendors will continue to showcase breakthroughs. The hype will continue. But 2026 is not the year for cheerleading.

It is the year for realism.

The most effective leaders are moving from awe to analysis—recognizing that AI value does not come from the technology itself, but from the opportunity it creates to rethink how work gets done.

In that sense, AI value is—and always will be—a uniquely human process.

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A Conversation Without Borders

Among the diverse voices at the Forum were three standout attendees—one from Ghana, another from Brazil, and still another from India—all deeply committed to advancing scientific discovery and digital transformation in health, all sitting at one table coincidentally. Their presence reinforced the idea that innovation emerges not from a single system or nation but from a mosaic of lived experiences, cultural insight, and shared human purpose.

At a time when geopolitical divisions grow and xenophobic rhetoric clouds practical need, this convening of minds from across continents stands as a counterpoint: progress in medicine and public health demands openness, not isolation.

Today, two out of five HIMSS members live outside the United States, representing the tremendous growth in its international reach.

Global Minds and Shared Missions

Consider the stories behind some of the most transformative scientific breakthroughs. Dr. Tu Youyou, who drew upon traditional Chinese medicine to isolate artemisinin, reshaped malaria treatment and saved millions. Tu received the 2011 Lasker Award in clinical medicine and the 2015 Nobel Prize in Physiology or Medicine jointly with William C. Campbell and Satoshi Ōmura for her work.

Dr. Salvador Moncada, born in Honduras and later based in the UK, changed the future of cardiovascular medicine through his work on nitric oxide. And Dr. Pardis Sabeti, born in Iran and raised in the United States, played a critical role in genomic tracking during the West African Ebola outbreak. These are not anomalies—they are the natural result of cross-border learning and purpose-driven science. In recognition of his tapping into the power of collaboration to accelerate biomedical discoveries, Dr. Salvador was nominated by the President of Honduras to serve as the country’s first Ambassador to China. 

Such examples underscore a larger point: global health challenges—from infectious disease to chronic illness—cannot be solved in silos. They require knowledge sharing, inclusive research, and the integration of clinical science, population health data, and epidemiological insights gathered across geographies. HIMSS is paving the way for people and countries to come together.

Today, health information flows freely across continents. Clinical trials are increasingly multinational. Genomic datasets used to train AI models include samples from diverse populations. Epidemiological patterns—from outbreaks to noncommunicable disease trends—are informed by data from regions that span income levels and infrastructure capacity. This global interconnectedness of knowledge is not only valuable—it is vital.

Health innovation now depends as much on access to ideas and information as on access to raw data or funding. Each individual—whether a clinician, data scientist, policymaker, patient or communicator—contributes to this ecosystem through their choices within their workplace, organization, advocacy group and community. These local actions ripple outward to impact global outcomes.

When people are empowered to think boldly and act collaboratively—regardless of where they are from—their influence transcends borders. This is especially true in a world where diseases migrate, health inequities persist, and environmental factors increasingly shape population health. No one country has a monopoly on the future of medicine, and no one person is immune to illness.

Science and Technology as a Bridge

Science is not merely technical; it is relational. It is built on trust, transparency, and the willingness to share. When data is exchanged openly—on disease trends, therapeutic outcomes, or environmental health risks—it becomes a force for public good. When it is withheld or politicized, it delays solutions and costs lives.

As HIMSS convened global thinkers in a borough symbolic of reinvention, the message was clear: advancing AI in health is not just about algorithms—it’s about equity, empathy, and inclusion. Those values begin not with policy mandates but with people. Beneath sessions on technology and policies, the conversation continually returned to the reality—it’s about people working collaboratively.

Every organization has the power to foster a culture where global voices are welcomed, collaboration is incentivized, and ideas are judged not by origin but by merit. The future of health will be shaped by how willing we are to embrace human potential, wherever it begins, and work with people who can help advance human health wherever they call home.

Brooklyn as a Setting and Symbol

Brooklyn is a fitting backdrop for these conversations. A city defined by generations of immigrants—scientists, healers and visionaries—stands as a beacon for what is possible when people are welcomed, not walled off. HIMSS is hosting its APAC meeting July 16-18 in Malaysia.

The HIMSS AI in Healthcare Forum brought together technologists, clinicians, ethicists and entrepreneurs. But more than that, it reminds participants of something timeless: when diverse minds come together, knowledge is not only shared—it is elevated. When human potential is honored without prejudice, the possibilities for better health are limitless.

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AI Is Not an Add-On—It Is the Infrastructure

One of the most powerful refrains in Lawry’s address was this: Artificial Intelligence (author’s definition – “augmented implementation”) is a general-purpose technology. Like electricity or the printing press, it doesn’t simply optimize existing processes—it refines them. It changes the sector’s (and perhaps society’s) operating system. It is not “intelligent,” it’s intelligence, [as John Nosta suggests].

In the health sector, AI must be treated not as a pilot project or a staffing replacement but as core infrastructure. It’s not a department, it’s a foundation. Lawry urged leaders to go beyond adoption cycles and recognize AI’s capacity to reshape systems, relationships and responsibilities. That shift requires not just technical integration but cultural transformation. It requires integration of clinical, operational and human resource functions.

“What Does This Mean for Me?”

Clinicians aren’t resisting AI—they’re seeking relevance. Their reflective question is: “What does this mean for me?” This question is surfacing across hospitals, clinics, and systems worldwide. Health professionals are not asking for more white papers or coding walkthroughs—they want to know if their judgment, autonomy, and voice will be protected.

His message was clear: Don’t ask clinicians to adopt. Invite them to co-design. Empower them to lead alongside technologists. That is how AI earns trust and ensures value.

Elevating the Workforce Through Upskilling

Referring to McKinsey forecasts, Lawry noted that up to one-third of clinical activity—primarily administrative—can be automated. But this is not about eliminating jobs. It’s about restoring the joy of practice and aligning people with purpose. If deployed wisely, AI can liberate talent from tasks that dull passion and delay patient care. The real challenge will be forging a bridge between aspirational and operational intent.

This is possible if health systems democratize AI knowledge. Upskilling cannot remain the domain of senior executives and IT teams. The professionals most affected by AI must also be those most prepared to use and question it with confidence.

Governance Is the Bedrock of Responsibility

Too many institutions speak about responsible AI but fail to structure it. As Lawry outlined and reflected in his Responsible AI Discussion Guide shared at the Forum, governance is not an aspiration. It is a requirement.

Lawry asks three key questions to test organizational readiness:

1. Has the institution formally adopted responsible AI principles, ratified by top leadership or the board?
2. Are those principles consistently applied to all AI projects and partnerships?
3. Are AI standards written into procurement practices?
   
   The health sector cannot afford partial answers. Most AI will arrive embedded within larger platforms—EHRs, diagnostics or billing systems. Governance alone is insufficient if the umbrella of its use doesn’t extend to vendors and embedded solutions. His cautionary guidance: policies without enforcement expose organizations to reputational and regulatory risk.

Judge AI by Outcomes, Not Headlines

It’s easy to get excited about the tech tools and early pilots. However, Lawry warned against evaluating success by the number of AI deployments. Actual value must be measured by mission alignment. That means, are outcomes improving? Are clinicians regaining time and focus? Are costs becoming more sustainable? Is ethical compliance being elevated? It is a nuts-and-bolts call-to-action.

Lawry urges organizations to treat AI not as a buzzword, but as a continuous improvement program. Like clinical quality, it requires constant evaluation and a clear connection to purpose.

Leadership Is the Deciding Factor

Perhaps the most lasting message from his keynote is that technology does not create transformation—leadership does. From boards to bedside, AI requires a mindset of clarity, courage, and consistency.

Leadership must:
– Understand what AI can—and cannot—do
– Create a culture where experimentation and transparency thrive
– Build governance, avoiding treating AI as a vendor offering

“AI value at scale is about leadership,” Lawry declared. “No algorithm, no matter how powerful, can substitute for moral clarity and institutional courage.”

A Gathering That Signals Momentum

This HIMSS AI in Healthcare Forum is a chance to compare notes and is a change-agent catalyst. It brought together visionaries and practitioners, policymakers and informaticists, engineers and ethicists. What unites them is the understanding that we are not waiting for the future—we are in it.

From HIMSS CEO Hal Wolf’s empowering opening remarks to Forum Master of Ceremonies and HIMSS Senior Director of the Personal Connected Health Alliance Rob Havasy and the powerful opening keynote by Tom Lawry, it is clear that this event is more than a “professional meeting” – it is an invitation to the possibilities of the age of AI in the health sector. But its success will not come from software, coding and flashing healthtech alone. It will arise from systems that put people at the center—patients, providers and the health ecosystem community.

AI Has No MRI: It’s All About Leadership

Tom Lawry offered more than a presentation—he provided a roadmap. One that begins not with technology but with trust. One that demands more than innovation—it requires intention.

The transformation ahead is not only technical. It is cultural, operational and profoundly human. The institutions that rise to the occasion will do much more than survive disruption. They will define the next era of healing.

AI is here. The question now is whether we are ready to use it and lead with it.

The post Why AI’s Future in the Health Sector Hinges on Leadership, Not Just Technology appeared first on Medika Life.

At the core of this transformation lies a new breed of companies—from patient engagement platforms and AI-powered diagnostics to cybersecurity solutions and social care integration—all focused on improving patient outcomes, enhancing institutional efficiency, and creating a more equitable health environment.

Over the past decade, many health provider systems have recognized that the key to improving health is not isolated solutions but integrating complementary technologies that enhance care delivery and operational performance. This shift in focus is evident in how providers and service companies are solving real-world problems, from improving workflows to using data analytics to enhance clinical decision-making and patient care.

Growth of the Health Innovation Pipeline

The health innovation pipeline has expanded significantly. The ecosystem has matured from focusing mainly on back-end technologies—such as EHR systems and clinical decision support tools—to encompassing forward-thinking solutions that put health professional effectiveness and patient experience at the center of the equation. Today, that pipeline includes:

1. Patient Experience Companies: These companies leverage digital health solutions such as smart hospital rooms, patient portals, and AI-powered scheduling tools to improve patient engagement and satisfaction. Companies like Vibe Health by eVideon demonstrate how patient experience can be enhanced with interactive technology, ensuring patients are informed and empowered to make decisions about their care.
2. Data-Driven Operational Improvements: Data analytics, artificial intelligence (AI), and machine learning enable health institutions to make informed decisions guided by curated information. Companies like CereCore and Tegria are at the forefront of transforming clinical operations and revenue cycle management through advanced data analytics, AI-driven insights, and cloud-based solutions. These tools help health systems optimize workflows, reduce administrative burdens, and enhance financial performance, all contributing to a more efficient system.
3. Patient Outcome-Focused Solutions: Improving patient outcomes must become the ultimate goal of health, and companies in this space are using innovative technologies to address social determinants of health (SDOH), chronic disease management, and real-time clinical decision support. Companies like Unite Us are addressing SDOH by connecting patients with community-based resources, ensuring that health providers can offer holistic care beyond medical treatment, including housing, food, and mental health services.

Health Innovation: From Reaction to Proactive

Historically, health systems often reacted to crises—whether a pandemic, financial strain, or workforce shortage—with patchwork solutions. Today, they are shifting from reactionary measures to proactive strategies. Companies seek transformational models and drive long-term sustainability through integration and automation.

For example, solutions from companies like Absolute Security and TigerConnect enable health institutions to proactively address cyber threats and disruptions in care and maintain system continuity despite unprecedented challenges. This level of preparedness and resilience enables health systems to focus on care delivery and data-driven patient management, ensuring that patient outcomes are improved and resources are optimally allocated.

Absolute Security: Ensuring Cyber Resilience in Health

As health systems become digitally interconnected, cybersecurity threats are escalating, particularly with the rise of ransomware and endpoint security breaches. Absolute Security addresses these vulnerabilities by embedding its patented Persistence Technology directly in the firmware of more than 600 million Windows devices, ensuring that security controls are maintained even when operating systems are compromised.

At HIMSS 2025, Absolute Security shared critical findings from telemetry data covering some million health PCs, highlighting a concerning 15 percent failure rate in security tests. These failures expose health organizations to increased risks and compliance issues. Absolute’s solutions offer unmatched resilience by enabling hospitals and clinics to recover devices to their original, fully operational state, regardless of whether cyber-attacks caused disruption, system crashes, or IT malfunctions.

Absolute can provide continuous protection and ensure quick recovery, which is particularly crucial for health organizations that rely on critical infrastructure. Their solutions keep security controls, applications, and operating systems up and running, providing secure access even in critical situations and ensuring that health teams can maintain focus on delivering patient care.

AvaSure: Revolutionizing Virtual Care with AI-Powered Technology

As hospitals and health systems continue to face mounting pressures to balance exceptional patient care with operational efficiency, AvaSure is stepping up with a game-changing solution.

 At HIMSS 2025, the company is launching its AI-powered Virtual Care Assistant, “Vicky,” developed in collaboration with Oracle Cloud Infrastructure (OCI) and NVIDIA. This cutting-edge technology bridges communication gaps, streamlines clinical workflows, and prioritizes urgent patient needs, improving patient care and operational efficiency. Vicky empowers healthcare teams to reduce response delays, alleviate clinician burdens, and improve patient outcomes. By integrating advanced AI into the care process, the AvaSure Virtual Care Assistant is a tool for streamlining tasks and a transformational solution reshaping how health providers operate and deliver care.

CereCore: Bridging Clinical and IT Divides

As health systems digitalize, improving clinicians’ EHR (Electronic Health Record) usability remains a central focus. CereCore, the IT arm of HCA Health, has been instrumental in bridging the gap between clinical and IT teams. At HIMSS 2025, CereCore showcased its approach to resolving long-standing EHR challenges by improving back-end IT support through peer-to-peer pairings and data analytics.

CereCore solutions streamline workflows, enhance system usability, and resolve real-time EHR issues, reducing downtime and increasing productivity. Their expertise spans some of the most prominent EHR systems, including Epic, Meditech, and Oracle Health (Cerner). CereCore provides comprehensive IT help desk services, cybersecurity, cloud transitions, and revenue cycle management support.

This company is helping health systems overcome some of the most pressing technology challenges by improving clinical and IT staff collaboration. For the people who are the frontline of healing, CereCore offers clinicians and patients a seamless and more efficient care experience.

TigerConnect: Streamlining Emergency Care Coordination

One of the most urgent needs in health today is improving information exchange between emergency medical services (EMS) and emergency departments (EDs). Traditional communication tools, such as radios and pagers, result in slow response. At HIMSS 2025, TigerConnect introduced its Pre-Hospital and Transfer solutions to streamline emergency care workflows and improve patient throughput.

TigerConnect Pre-Hospital solution enables EMS teams to send patient information to the ED on the way to the hospital. This helps teams to rally and prepare to transition from ambulance to in-patient care coordination. Their Transfer solution digitizes the process of patient transfers, reducing the number of manual phone calls and minimizing delays.

By leveraging real-time communication and automation, TigerConnect improves emergency care efficiency, reduces time-to-treatment, and enhances clinical decision-making. As health continues to adopt digital tools, TigerConnect solutions will play an integral role in improving care delivery across the emergency spectrum.

Tegria: Guiding Digital Transformation

As health systems evolve, guidance is essential for implementing new technologies. Tegria, with its team of 1,500 professionals, is playing a key role in helping health organizations navigate digital transformation and operational improvements – providing sector-specific depth, operational experience across hundreds of health systems, and much-needed objective counsel and hospital networks to make critical IT infrastructure investment decisions.

Founded by Providence, one of the largest non-profit health systems in the U.S., Tegria offers expertise in IT optimization, revenue cycle management, and cloud-based solutions. The company supports 650 health organizations across North America and Europe, helping them adopt emerging technologies that drive efficiencies, reduce costs, and improve care quality.

Tegria partnership with health organizations empowers them to embrace digital tools while improving their financial sustainability and clinical outcomes. The company’s continued value and success are reflected in its #1 rank as a leading health IT Consulting Service and a top performer in Clinical Optimization and Application Hosting by KLAS Research, the noted health IT data and insights enterprise.

TruBridge: Enhancing Community Health

As the health system evolves, small and community-based hospitals are increasingly challenged to keep their heads above water while adopting new technologies. TruBridge, formerly CPSI, solves these challenges by offering integrated EHR technology and revenue cycle management (RCM) solutions for community hospitals and clinics.

At HIMSS 2025, TruBridge highlighted how its solutions help health providers optimize claims processing, improve reimbursement cycles, and reduce claim denials. Additionally, TruBridge supports Social Determinants of Health (SDOH) data integration, enabling health providers to address barriers to care like food insecurity and transportation issues, particularly common in rural and underserved populations.

“It’s critical that all Americans have access to high-quality healthcare. Sparta Community Hospital and Artesia General Hospital lead by example through strategic SDOH data collection to identify and address community needs. Their presentation at HIMSS ‘25 revealed lessons learned and best practices for other leaders on the path to improved healthcare access and outcomes. These facilities demonstrate strong community commitment, and we are honored to work alongside them to help solve SDOH challenges and keep care local,” said Wes Cronkite, Chief Technology and Innovation Officer at TruBridge.

TruBridge solutions help hospitals remain operationally efficient while improving the quality of care for their communities. This ensures that hospitals remain viable and continue serving their populations effectively.

Unite Us: Integrating Social Care into Health

In an increasingly connected world, health providers recognize the critical importance of addressing social determinants of health (SDOH), such as housing, food insecurity, and transportation. Unite Us is integrating social care into health systems, creating cross-sector partnerships to ensure that patients receive holistic care that includes both medical and social support.

Through its platform, Unite Us connects health organizations with community-based organizations, creating a seamless referral process that allows providers to track and manage patient progress across medical and social services. Their closed-loop referral system ensures that patients receive the care they need, whether it be housing support or mental health services.

By addressing the root causes of health disparities, Unite Us enables health systems to provide more comprehensive care, improving health outcomes and reducing costs.

Vibe Health by eVideon: Transforming Patient Engagement

Vibe Health by eVideon demonstrates how smart hospital rooms equipped with interactive technology transform patients’ experiences of care. Their solutions, such as smart TVs, digital whiteboards, and bedside tablets, empower patients to take a more active role in their care while reducing the burden on clinicians.

“At HIMSS, we shared how Nebraska Medicine uses Vibe Health by eVideon’s smart hospital room solutions to enhance patient engagement and improve clinical efficiency. Technologies like interactive Smart TVs, digital whiteboards, and digital door signs help us streamline communication and improve the patient experience. Our discussion explored how technology drives meaningful improvements in both efficiency and outcomes. HIMSS provides a valuable space to connect with peers, exchange ideas, and explore innovative solutions that drive meaningful change across the industry,” share colleagues Ron Carson, Executive Director of Enterprise Applications, and Calli Sibilia, Program Manager – Innovation Design Unit at Nebraska Medicine.

Hospitals like Nebraska Medicine have integrated Vibe Health solutions to streamline communication and care coordination. Their interactive platforms give patients real-time access to care plans, educational materials, and appointment reminders, ensuring they are always informed. This digital-first approach enhances patient satisfaction and improves clinical efficiency by reducing time spent on manual updates.

Vibe Health creates a more efficient and effective health system by providing hospitals with cutting-edge tools to enhance the patient and floor-staff experience.

Bringing It All Together: A Holistic Approach to Health Information

The most promising aspect of the current health innovation landscape is that companies are beginning to address not just one aspect of the health journey but the entire continuum—from pre-hospital to post-care.

Companies like TruBridge are improving care for underserved populations by addressing the administrative burden and ensuring that small and rural hospitals can thrive. Vibe Health by eVideon transforms the patient experience by integrating interactive digital platforms into hospital rooms. At the same time, Unite Us ensures that social determinants of health are addressed at the patient’s first point of contact. Tegria is helping hospitals optimize their operations to ensure these innovations can be scaled effectively.

This approach helps break down the silos that have traditionally existed in health—where care delivery, operational management, and patient engagement are often managed separately. By unifying these elements, health innovators provide solutions that enhance patient outcomes, streamline operations, and improve the health experience.

A Future-Focused System

The health landscape is becoming ever more digital- and data-driven; expect an increasing number of companies that can create synergies across various technologies, pushing boundaries in areas like personalized medicine, predictive analytics, and patient-centered care. The focus will continue to shift toward providing patients with proper care at the right time—whether through real-time monitoring, telehealth consultations, or personalized digital health experiences.

The strength of the health innovation system today is rooted in its collaborative nature, where varied technologies come together to create an efficient, patient-centric, and resilient health environment. The companies speaking, presenting, and networking at HIMSS are improving the quality of care and patient outcomes and addressing clinical and social factors. As this ecosystem evolves, it paves the way for a connected, proactive, and equitable health system where innovation opens the path to positive change for patients and providers.

The post Strength of the Health Innovation System: Growth, Evolution, and the Path Forward appeared first on Medika Life.

These 20 people are not just theorizing about the whizzbang of hot technology but rolling up their sleeves and demonstrating its value in real-world settings—to improve diagnostic care, access information that can inform treatment, address health inequities, and ensure the financial sustainability of health provider systems that operate on razor-thin margins. Their collective work offers a blueprint for leveraging AI responsibly and (hopefully) ethically, from streamlining hospital operations and enhancing clinical decision-making to revolutionizing drug discovery.

The current AI evolution presents both opportunities and challenges. Health systems face increasing demands, including rising patient expectations and staffing shortages. Implementing AI and large language models (LLMs) can address these concerns by enabling faster and more accurate treatment plans, automating administrative burdens, and personalizing patient care. However, realizing AI’s full potential requires thoughtful application, ethical considerations, and a commitment to addressing disparities.

These 20 champion AI’s practical application, guiding health systems toward innovation without losing sight of humankind’s well-being. They exemplify how AI can enhance rather than replace human expertise—an essential message as we continue to adapt to this rapidly evolving landscape. By following their work, health-sector leaders and innovators can gain invaluable insights into deploying AI for meaningful impact.

Trailblazers Redefining Health Innovation

While many thinkers will wow you with the future possibilities of these technologies, the 20 on this roster demonstrate transformative influence on the future of diagnostics, operational efficiency, and personalized care while emphasizing responsible, ethical implementation. From academia to industry, they provide vital insights and direction into leveraging AI for better health outcomes. Their work underscores AI’s ability to augment human expertise, providing a roadmap for health systems to innovate without losing sight of patient-centric care. Thanks to them and the others appearing on our Medika Life 2023 and 2024 list, we define AI as “augmented implementation” and not artificial intelligence.

How were they selected? They are public-facing, sharing their thoughts in articles, books, keynotes, classroom talks, research papers, and conferences. They willingly share their knowledge with others on their social media platforms. They spark ideas and challenge our current thinking, and these behaviors make them invaluable to the future application of information and its human health impact. Each person appears in hyperlinks so that readers can explore the depth of their contributions and, whenever possible, follow them on their social media platforms.

20 Voices of Influence Shaping AI in Health

Regina Barzilay, PhD

Dr. Barzilay, an MIT professor and MacArthur Fellow, is revolutionizing oncology and drug discovery through AI. Her pioneering work in machine learning has led to breakthroughs in early cancer detection, particularly in breast cancer screening. As co-founder and AI faculty lead of the MIT Jameel Clinic and the AI Cures initiative, she’s spearheading efforts to deploy AI models for cancer risk prediction in hospitals around the globe and accelerate drug development for infectious diseases. Dr. Barzilay’s work in oncology and drug discovery is paving the way for screening policies and new treatments.

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Anthony Chang, MD, MBA, MPH, MS

Dr. Anthony Chang, a pediatric cardiologist and founder of AIMed, is a driving force in AI education for health professionals. His book Intelligence-Based Medicine has become a cornerstone text. Dr. Chang’s recent work focuses on developing AI-powered predictive models for pediatric cardiac care and implementing AI solutions to enhance hospital operational efficiency. His annual AIMed conference has become a global platform for sharing cutting-edge AI health innovation.

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Karen DeSalvo, MD, MPH

Google Chief Health Officer DeSalvo leads initiatives that leverage AI and big data to address critical public health challenges and promote health equity. Her work includes developing AI-driven tools for early disease detection in underserved communities and creating platforms that provide real-time health data analytics for policymakers. Dr. DeSalvo’s leadership in responsible AI use ensures that Google’s health technologies prioritize patient privacy and ethical considerations.

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Pamela Davis, MD, PhD

Dr. Davis is a distinguished researcher at Case Western Reserve School of Medicine specializing in AI-driven diagnostics and clinical applications. After 13 years as the Dean of the School of Medicine, she returned to the faculty. Her work centers on predictive algorithms for early disease detection and improved treatment planning. But Dr. Davis is an anomaly to this roster. She has no social media handles and her many published works are not curated carefully. Yet, tracking her contributions shows her depth and national influence on the future of AI in practice. With numerous published studies on AI’s transformative role in health, Dr. Davis continues to shape the future of diagnostic pathways.

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David Feinberg, MD, MBA

As Chair of Oracle Health, Feinberg champions using AI and cloud-based technologies to improve health outcomes. He focuses on predictive analytics and data-driven tools that enhance clinical decision-making and streamline hospital operations. His leadership drives innovation in health technology integration. Dr. Feinberg is widely recognized for his transformative leadership as CEO of Geisinger Health, where he pioneered initiatives in population health, precision medicine, and value-based care. His expertise in integrating technology with health-care delivery continues to drive innovation, making digital tools more accessible and impactful for providers and patients.

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John Halamka, MD, MS

John Halamka, President of the Mayo Clinic Platform, is a trailblazer in AI-driven health solutions, leveraging data and technology to transform patient care. Co-author of The Digital Reconstruction of Healthcare, Halamka is a leading voice on digital transformation, interoperability, and the ethical use of AI in medicine. His work at the Mayo Clinic focuses on developing scalable digital platforms and AI models to advance diagnostics, remote monitoring, and personalized medicine. With a background spanning emergency medicine, informatics, and policy, Halamka’s insights continue to guide health systems toward a more connected, efficient, and data-driven future.

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Taha Kass-Hout, MD, MS

Dr. Taha Kass-Hout, General Manager of Amazon Health AI, is a pioneer in leveraging artificial intelligence to drive advancements in healthcare delivery. With a background in clinical practice, public health, and digital innovation, he leads initiatives that harness AI for improved diagnostics, care management, and population health outcomes. Previously, as the first FDA Chief Health Informatics Officer, he championed data-driven approaches to public health. His leadership at Amazon drives scalable, data-driven health models that integrate machine learning with real-world applications, positioning him as a key influencer in the future of AI in health.

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Isaac Kohane, MD, PhD

Dr. Kohane, Chair of the Department of Biomedical Informatics at Harvard Medical School and co-author of The AI Revolution in Medicine: GPT-4 and Beyond, is a leading authority on the intersection of AI and clinical care. His research focuses on using machine learning for precision medicine and improving electronic health records. Dr. Kohane has been instrumental in developing AI models that enhance diagnostic accuracy and patient outcomes. His recent work explores the potential of LLMs, such as ChatGPT, in clinical decision-making and patient engagement.

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Daniel Kraft, MD

Dr. Daniel Kraft is the founder of Exponential Medicine and a visionary in personalized medicine approaches. He’s an inventor, a former F-16 flight surgeon, and always ready to champion others’ bold ideas. Dr. Kraft explores how AI can transform health delivery and disease prevention. Dr. Kraft’s recent initiatives focus on AI-powered tools for early diagnosis and patient engagement. His next chapter includes the very successful NextMed Health and the evolution of Exponential Medicine. NextMed Health 2025 will be held in San Diego on March 30 and April 2, 2025.

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Tom Lawry

Tom Lawry, soon to be the author of his highly anticipated new book Health Care Nation: The Future Is Calling, and It’s Better Than You Think, may redefine the intersection of technology and patient care. Already renowned as the author of Hacking Healthcare, Lawry has built a reputation as a leading AI strategist who advises organizations on integrating cutting-edge AI solutions to boost operational efficiency. His former role at Microsoft as Director for AI for Health and Life Sciences, Director of Worldwide Health, and Director of Organizational Performance for the company’s first health incubator cements his standing as a trailblazer in health innovation. He’s almost always a keynote favorite at conferences such as HLTH and HIMSS.

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Fei-Fei Li, PhD

Dr. Fei-Fei Li is a strong advocate for diversity and inclusion in AI, emphasizing ethical considerations and societal impact. She co-founded AI4ALL, a nonprofit dedicated to increasing diversity in artificial intelligence, and has played a pivotal role in shaping policies for responsible AI development. Her leadership continues to influence the global AI landscape, bridging technology with human values.

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Vivian Lee, MD, PhD, MBA

Dr. Lee, author of The Long Fix, is a pioneering health tech executive driving data-driven health transformation. Her recent work includes developing AI-powered platforms for value-based care models and implementing predictive analytics to reduce hospital readmissions. Dr. Lee’s initiatives as former president at Verily Life Sciences focused on leveraging AI to optimize care delivery across diverse populations.

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Peter Lee, PhD

As Corporate Vice President of Microsoft Health, Dr. Peter Lee spearheads initiatives that apply AI to solve complex health-sector challenges. His recent projects include developing AI models for precision medicine and creating cloud-based solutions for health data interoperability. In his role, Dr. Lee seeks to solve complex health-sector challenges by integrating cutting-edge technology with practical healthcare applications.

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John Nosta

John Nosta has earned his place as a top influence in the AI landscape—particularly in discussions surrounding ChatGPT and large language models—due to his visionary insights and ability to demystify complex technological innovations. His thought leadership bridges the gap between cutting-edge AI research and practical, real-world applications, making the transformative potential of these tools accessible to a broad audience. By articulating AI’s promise and ethical challenges, Nosta fosters a balanced dialogue that drives the industry forward. His forward-thinking perspective and engaging commentary not only illuminate the evolving impact of AI on various sectors but also inspire both startups and established companies to reimagine the future of technology. Nosta has an upcoming book that is expected to drop sometime in fall 2025.

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Ziad Obermeyer, MD

Ziad Obermeyer, MD, is the Blue Cross of California Distinguished Associate Professor of Health Policy and Management at the UC Berkeley School of Public Health, researching the intersection of machine learning, medicine and health policy. His work has exposed biases in clinical algorithms and highlighted disparities in care delivery. As a co-founder of Nightingale Open Science, he promotes data transparency and collaboration to advance medical AI. His contributions are reshaping predictive analytics and decision-making in healthcare. Before his full-time career in emergency medicine, he consulted pharmaceutical and global health clients at McKinsey & Co. in New Jersey, Geneva, and Tokyo.

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Neal Patel, MD, MPH

As the Chief Information Officer for Health IT at Vanderbilt University Medical Center (VUMC), Dr. Patel leads the integration of advanced technologies into health delivery. With more than two decades of experience in HIT, Patel has been instrumental in computerized physician order entry systems and electronic health records to enhance clinical and quality processes. He focuses on translating VUMC goals into informatics strategies, optimizing patient care, and improving safety and services across the care continuum. Dr. Patel’s work underscores the transformative potential of AI and LLMs in the provider system.

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Kyu Rhee, MD, MPP

As Senior Vice President at CVS Health, Rhee leads initiatives that leverage AI for health equity and personalized care. His recent projects include implementing AI-driven health risk assessments in underserved communities and developing machine learning models to predict medication adherence. Through his leadership, CVS has deployed AI-powered virtual care solutions expanding access to preventive services and helping to close care gaps while improving outcomes for diverse patient populations.

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Nigam Shah, MBBS, PhD

Dr. Shah, a professor at Stanford University, specializes in applying AI to clinical workflows and electronic health records. His recent work includes developing AI models for real-time clinical decision support and creating algorithms to identify patients for clinical trials. He has published extensively in peer-reviewed journals on machine learning applications in healthcare and co-authored chapters in Artificial Intelligence in Medicine. Shah also leads Stanford’s Center for Biomedical Informatics Research, advancing research on AI’s role in population health and precision medicine.

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Eric Topol, MD

Dr. Eric Topol is not just “a” trailblazer in digital medicine. He will likely be among those acknowledged singular voices bridging the possible with the practical. His groundbreaking work has consistently pushed the boundaries of health innovation. Dr. Topol redefined patient empowerment with his seminal book The Patient Will See You Now. He transformed the traditional healthcare model, advocating for a future where technology facilitates personalized, proactive care. As the author of Deep Medicine, he continues to champion the integration of AI in health, exploring its potential to revolutionize patient care. Dr. Topol’s visionary contributions and commitment to merging clinical expertise with cutting-edge technology have established him as a guiding voice at the intersection of care and innovation, making him a standout influencer in AI applications.

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Hal Wolf, III, FHIMSS

Harold (Hal) Wolf is the president and CEO of HIMSS, a global advisor and thought leader supporting the transformation of the health ecosystem through information and technology. If health-related smart technologies such as AI, ChatGPT, GenAI, and LLMs have a central home to discuss policies and implementation, it is HIMSS. Hal shepherds the world’s health information management community. While his staff advance science and policy, championing implementation throughout the ecosystem. Wolf and HIMSS are where theory meets action. Wolf is far more than a leader of a global society of import; he is the community’s ambassador to NGOs, governments, and industry.

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The Rise of Generative AI in Digital Health: Key Insights from Galen Growth

Beyond tracking the 20 listed in the year’s people to watch and the previous two years, following the Galen Growth executive briefing Generative AI in Digital Health – Hype or Reality? The report is a must-read for AI, ChatGPT, and LLM professionals. It reveals how nearly 4,000 digital health ventures leverage AI, with 2% focused on generative AI. Notably, 27% of these applications enhance health management, and over 330 AI-driven ventures have partnered with health systems in the past five years. This report offers critical insights into AI’s growing impact on digital health innovation.

Acknowledgments

I thank my Medika Life colleagues, including Drs. Robert Turner, Jeff Livingston, Hesham A. Hassaballa, Patricia Farrell, and Michael Hunter, whose commitment to public health information inspire. I am also grateful to the many sector professionals I engage at events such as CNS Summit, DHAI, HIMSS, HITLAB, HLTH, and ViVE—people who generously share perspectives and contribute invaluable recommendations. A shout-out to Christina Raish, our new associate editor at Medika Life, for her support in making this feature possible.

Special recognition goes to those who have appeared on past Medika Life lists and remain engaged in advancing health and well-being. Their commitment to meaningful change is commendable to individuals and the planet. These trailblazers continue to push boundaries, demonstrating an unwavering dedication to improving lives.

Since the dawn of civilization, humanity has been awed and challenged by technological progress—from the mastery of fire to artificial intelligence. Each era, from the Stone Age to the Iron Age and now the Information and Cognitive Age, has demanded careful consideration of how best to harness innovation. Today, as we navigate the era of “thinking” technologies, one truth remains unchanged: the power of human insight, courage, and empathy must guide progress.

—Gil Bashe, Editor-in-Chief, Medika.Life

Remember to Follow the Voices of Influence from our 2023 and 2024 Rosters:

Spot a broken link, typo, forgotten degree, or name misspelled?

Oops! Apologies! While care has been taken in compiling this list and adding social media links, things go wrong: a name is misspelled, a link is broken, or an incorrect social media handle is listed. Please do get in touch to address typos, amendments, or omissions by reaching gil.bashe@medika.life.

Thanks in advance and be healthy!

The post 20 People Who are Transforming the Health Ecosystem Through Practical Paths to Apply AI – 2025 Roster appeared first on Medika Life.

In this exclusive conversation, I join Hal Wolf, President and CEO of HIMSS, to explore HIMSS’s evolving role in fostering collaboration between hospitals, startups, and policymakers. With the health-ecosystem landscape tracking the early days of a new administration, uncertainties remain—ranging from regulatory shifts to funding allocations. Yet, as Wolf underscores, HIMSS remains steadfast in advancing health equity, supporting digital transformation, and offering actionable strategies that improve care delivery.

This conversation occurs between ViVE in Nashville and HIMSS in Las Vegas—two health gatherings that bring innovators, policymakers, and industry leaders together. While ViVE spotlights digital health startups, investment trends, and edgy sparks, HIMSS serves as the broader convening ground for professionals shaping the future of health information and technology. HIMSS is where the work happens—the “Davos” of health information.

Wolf outlines key issues such as integrating artificial intelligence in hospital systems, the role of primary care in driving better patient outcomes, and how organizations must balance innovation with financial realities. At HIMSS, essential dialogue between established institutions and emerging disruptors has never been more crucial.

Join us as we delve into the forces shaping the health system’s future—where technology, policy, and leadership converge to improve patient outcomes and system-wide efficiency.

Medika Life Editor Gil Bashe: In examining hospital systems, we focus on how information flows within our industry and who has access to it. We still have a lot to learn. These are the first few weeks of the new administration, and we don’t know how things will unfold, how the Senate Committees will approach these discussions, or how actions will be implemented. Will we rely on Executive Orders? If that’s the case, we know where to focus our attention. You’re a remarkable ambassador for the discipline and the sector, and certainly for HIMSS, a professional association, trade association, and global NGO.

People come to HIMSS with tremendous optimism, hoping to gain insights that will make them more effective. I prefer to focus on current developments and HIMSS priorities rather than just reacting to them; that’s a different conversation. I’ll also note that the administration’s conversation around health access, cost, and priorities is still in motion.

HIMSS CEO Hal Wolf: We don’t know enough to discuss new policies and their potential outcomes. One challenge will be securing funding. While we know things will be different, we don’t know where the policies will land. Still, we know that HIMSS is dedicated to its vision and mission statements as they fundamentally relate to realizing the full health potential of every human everywhere.

We are dedicated to health equity and will stay dedicated to it. Our collaboration with governments and NGOs worldwide and our fundamental principles will not change, nor should they! We’ll work with our principles within the context of whatever comes out of the White House.

We worked well with the previous Trump administration and collaborated effectively with ONC and HHS on various initiatives. We look forward to advancing the HIMSS mission within the established parameters.

Bashe: HIMSS is far more than an annual mammoth gathering; it’s a professional society that covers the full spectrum of health information and technology – from cybersecurity to economics to professional development and government policies. Unlike other popular meetings that primarily focus on networking, HIMSS is where professionals from around the globe come to set objectives, strategies, and operational priorities. It’s 30,000 feet and 3,000 in scope.

Wolf: This morning at 6:00 a.m., I had an interesting conversation with the CEO of a successful start-up that is getting distribution now and beginning to roll. At HIMSS, we see the merging of different worlds.

We have our core population, core members of the health ecosystem– hospitals, clinics, health operations, nurse practitioners, CMIOS, CIOS, physician leaders, and administrators. This group represents a significant portion of the HIMSS membership, which includes over 120,000 members.  

On the other hand, we have the entire global app ecosystem that drives innovation and introduces new ideas. As you know, many of these ideas and innovations are driven by personal experiences. A family member encountered a situation, and they tried to solve it. Or have worked in the industry, identified a gap, and pursued it.

They often have a long list of improvements to address, and, often, they aren’t performing well financially. Their reimbursement processes are a little murky, and this uncertainty might increase in 2025.

How much time do they have to integrate innovations that don’t directly impact their outcomes, quality, access or bottom line? Because everything’s being looked at in that piece.

We need to understand that the situation changes as the market evolves. What is the critical point where innovation intersects with standard operating procedures, and what does it look like? How can information from one area influence the other? We must determine how to identify the good and the bad and how to present them to the market.

What happens at the global conference? What happens in chapter meetings? What happens in the papers that are submitted? What happens in the insights? Much of this depends on how these elements connect.

Bashe: Many diverse health information communities come together yearly at HIMSS. You have consistently made this gathering relevant. This year, a new startup section called Emerge addresses a critical need within the HIMSS community. You just started with the story about a startup enterprise. Could you share some important and innovative aspects that will be highlighted at this year’s gathering?

Wolf: That’s a pressing question, so I’ll divide it into multiple parts because it’s challenging.

We’re part of the industry, so let’s return to your original premises to find the answer. You mentioned “competing,” which refers to people competing against each other. However, you also have specific points of interest to consider.

The benefit engine can determine how much money you’ll receive in reimbursement for a particular service. However, if you’re on the insurance or payer side, the configuration may depend on whether it’s for North America or a Ministry of Health. Here, the goal is to anticipate the costs incurred in treating a patient. This perspective aligns with an actuarial professional trying to understand and guide the process forward.

I’ve observed hospital systems are starting to integrate AI functionalities, but currently, only 5 to 7% are using it effectively, from an operational standpoint,

For example, when someone walks to the front desk and says their right arm is hurting, the staff collects the information by typing it into a form. They ask a couple of questions, such as “Who’s your primary care doctor? Who’s your insurance company? Are you on managed care? Is this new? What other ailments do you have? What other prescriptions do you have?” They must ask those questions if they don’t have that information readily available. That data feeds into new algorithms on the AI side.

In the background, AI analyzes the information and makes predictive models about how long this person would be in the hospital, what resources they will consume, and how much revenue it will generate. It’s occurring in the background, without the front desk staff being aware of AI’s calculations; meanwhile, the administrator is beginning to recognize the impact of these advancements. The inbound process begins with appropriate testing, questioning, and, if necessary, into a bed.

Meanwhile, the hospital administrator or the system managing the situation assesses the resources the patient will need, whether they will need a specialist and whether the specialist will be available when needed. By the time an exam takes place, they can inform the patient about what to expect in the next 24 to 48 hours, whether they will be staying at the hospital or going home. This preparation and communication represent the positive aspects of the process.  

The dark side is that the hospital engine in the background might say, “We’re not going to get a lot of money out of this. This is not a good use of our beds/time. If we maximize profits, we should send this person on and see what the next person will bring because our algorithm told us that five people would come in with congestive heart failure, and we do make money on that.”

The person writing this down may never realize what is happening; they won’t know that the system will indicate that the hospital is full, even though there might be capacity. Instead, they will tell the person to go down the street to Acme Community Hospital, which can take care of them, explaining that their system lacks resources. That is a dark coin flip to what could happen.

Bashe: Many hospital networks are acquiring primary care practices as feeder systems in their facilities. For example, if a patient is told, “You need to do a cardiac stress test. Do you have a cardiologist?” and they respond with “No?” the primary care provider can then say, “Why don’t you let me arrange that for you.” The primary care satellite site is closing the loop on a fragmented system. While the hospital system benefits economically from the service, patients benefit, and the primary care satellite site serves as a conduit for care.

I’m always thinking about the benefits of technology in enhancing the hospital and primary care systems. Imagine a doctor saying, “You know, you’ll have many questions. I will be here to help you frame your thinking around those questions. Our system has an LLM model. Let’s call it Dr. Hal. You can ask Dr. Hal every question regarding your congestive heart failure or prostate cancer. Dr. Hal is the composite wisdom of all the experts in our system and is here to address your questions.”

The creative aspect of our discipline, combined with information, is becoming a superpower. We use data to guide our supply chain resourcing and leverage information to promptly provide patients with confidence and comfort. We ensure greater access to accurate information vetted by the system, so patients do not depend solely on Dr. Google.

Wolf: The actual value of AI is knowledge management. It allows a very broad and capable synthesis of vast amounts of data and information that no human can keep up with. For example, in the 1970s, clinicians had access to three to four journals, where editors picked what was important enough to be published. These journals had to be printed and mailed out, resulting in about 400 peer-reviewed articles per year reaching healthcare professionals. If you read one a day, you could keep up. Today, more than 10,000 articles will be published this year alone. All that information, knowledge management, and sharing will occur collaboratively, and there is no way for anyone to synthesize all that.

AI plays a crucial role in operational and clinical decision support by turning information into knowledge, with recommendations that lead to changes in operations, suggestions, and care.

In clinical care, pharmacy, or whatever path you’re on, these recommendations are communicated back to physicians with an explanation of why they are a recommendation and the source of that information.

I think part of the maturity that we’re seeing, and you’ll see at HIMSS 2025, is the evolution of AI since our session three years ago. Back then, we held a session titled, “What is AI, and what does it mean?” The panel discussed its potential application in healthcare, and at that time, chat had just been introduced, and people were starting to look at it. Some people were on stage calling for a six-month hiatus before we allowed anything to go forward.

Last year, we saw glimpses of initial uses of AI being deployed operationally, albeit only in a few hospital systems. But it was beginning to happen, and we knew that AI was in the background of devices or operational considerations. Where would the benefit engines come from? The algorithms were starting to be built, and we had a particular point of looking out for biases. We started talking about biases within AI and realized that no matter what you do, there will always be some biases. It’s unavoidable. What was the source information for AI, and how do I ensure I utilize it to the best of my ability?

You’ll see the presentation of how people are using it on a scale. What are examples of its success, and what are some of its limitations? Numerous applications are set to emerge. You’re going to see them on the floor, where people are using components of AI in the background to produce better products that are more efficient and can guide operations as well as at-home care, and all those pieces are being brought forward. The common link between it and your point is on the information side of the house. How good is the starting information, and how broad does it go? Where is the opportunity from a linking standpoint?

To achieve this, a private-public partnership is essential. If you’re looking at algorithms and information that utilize global data that gets turned into global information, it has an impact. Most healthcare systems around the globe are publicly held. They’re not privately held. The United States is an aberration due to its vast amounts of privately held institutions versus publicly held ones.

Bashe:  Are you seeing more of that regarding the technology being used proactively?

Wolf: Yes, and that’s a good thing. We’ve always wanted to see that proper reimbursement takes place and proper services rendered. Many things in a system can get missed, but not an overwhelming amount.  If hospital systems perform well, they typically operate on a 2 percent to three percent margin, but many run at a loss, making proper reimbursements difficult. Large actuarial departments played a key role in the past, with various organizations providing revenue support, which was a huge thing even 15 years ago. However, over time, those efforts began to converge.

The real opportunity lies beneath the surface. It must coincide with an understanding of the care that was delivered. Right next to that benefit realization is the value proposition. What was the quality of what was rendered? Was the care appropriately given? Did we miss something in the diagnosis?

Bashe: One of the things that I worry about is not New York City or Los Angeles. Medical centers such as Mount Sinai, NYU Langone, Weil-Cornell, Columbia Presbyterian, and Memorial Sloan Kettering, much like their counterparts in Boston, Chicago, and the Bay area, provide excellent care. However, in rural America, someone can live three hours from a tertiary care center.

Your approach of using information to improve the care of almost 29 percent of the US population applies, I think, to other nations where people live far from centers of excellence. What are your thoughts about devices, wearables, remote patient monitoring and information, and protecting the information from your standpoint?

Wolf:  Wearables and home monitoring have transformed patient engagement, making health data more immediate and actionable. It’s fascinating. My wife and I compare our Oura daily. How did you sleep? How’s your heart rhythm? We’re finding the features and working through them. She lives anonymously. We are very engaged in our health. How far did we walk? What was our heart rate? Let’s do the 6-minute walk today and see. Were you snoring last night?

All of that is going on, and that’s an engagement level. The information flows from me to my ring, and then my ring says, do you want to share it with Apple? I said yes, and my wife said no; she didn’t want it to flow to another company. Apple will know how well I sleep – I don’t worry about it. If they want to dive into it, there is a profile about me and my general health. They could also derive that from the stuff I buy and the credit card information. That’s always been the case.

If you remember, back in the 1980s, we were already using demographic data with Donnelly overlays. I worked for Time Warner in the early 1990s when Time magazines were delivered to your door. The Time magazine that arrived at your next-door neighbor was different from yours—not the content, but the cover and the ads in the back. You may have gotten an ad for a sports car, and your neighbor may have gotten one for a minivan.

It was specifically designed based on the Donnelly reports, which provided insights about the household. We’re starting to shape recommendations at the personal level of the care an individual should receive.

Why wouldn’t a physician or a clinician want every piece of information on this Oura ring to be included in a patient’s profile? This information would help complete the picture needed to utilize sophisticated knowledge management systems, tapping into tens of thousands of research papers and combining that data with the person’s unique health details. The richer that information becomes, the more accurate it becomes, the more mistakes it makes, the more positively it helps the next person.

Bashe: Often, when I speak to doctors and nurses in the health system, we talk about the Electronic Medical Record (EMR). They’re candid: “We have an EMR system—it’s not perfect, we know that, and it’s getting better and better.” Yet, they often say, “Did you read that patient’s EMR data?” and then they’ll say, “I don’t have time to read the EMR.” While best practices come from committees, you play a unique role as an advisor to corporations. You’re the sounding board for major corporations, whether AWS, Epic, Microsoft, or Oracle. I’m sure they will listen to you because you’re the voice of the global community.

Wolf: We don’t have a dog in the race against them as a competitor.

Bashe: As a not-for-profit society that operates at a global NGO level, when you look at your role and the challenges you face, how does HIMSS address constant sector transformation? HIMSS and its members are constantly evolving because you represent applied information. The system is getting more interesting and more creative.

Look at the challenges that HIMSS owns and represents and your mission, which is obviously to improve access to care. As the organization’s leader, you’re clear and committed to this role, but you’ve seen difficulties implementing cultural or systemic changes.

What’s your guidance for the community? Please don’t take out a ruler and slap people on their hands. You’re obviously about supporting the system’s evolution, making it better. Can you share insights on how you’re filtering down best practices within this evolving landscape? How do you reflect on these challenges that arise and guide systems to understand that care is delivered to the front lines and is not always in hospitals? It’s specialists or primary care—physicians in their little offices worldwide.

Wolf: This is precisely what we discuss daily at HIMSS, and it’s central to our global work. Let’s walk through our view of the ecosystem and how we influence what you just related to because it’s our core.

Hospital systems – or, more importantly, governments worldwide – including our own, recognize their fundamental responsibility to care for their populations. Let’s set the United States aside for a second.

Ministries of Health in countries around the world are accountable for the well-being of their citizens. We’ll talk about citizens for a minute. The people living within their country want a healthy population, which improves the economy. They’re smart enough to know that a healthier population, or one cared for, efficiently reduces the constant increase in costs within healthcare systems. No one is looking to save money; instead, the goal is to slow the escalating costs of healthcare systems, which seem to rise every year.  

Information is the driver behind everything, but to your point, the combination of people, processes, and technology shapes the outcome. Technology is rarely an issue here; the challenge lies in implementing and changing culture. The pandemic forced a significant global cultural change, and while it may seem that it’s deeply in our rear-view mirror, its impact is still felt. Telemedicine, the idea of using information, and the idea of remote care to alleviate the pressures on the front line became a standard feature, and people recognize that.

We see the impact in our relationships with organizations like the WHO in Europe. Take Romania, for example, where we just signed an agreement to help them develop a strategic plan to deliver digital health transformation. HIMSS is focused on four major points.

1. First is digital health transformation.
2. Second is the deployment and utilization of AI as a tool.
3. Third is cyber security to protect that information and ensure that it works for the betterment of their ecosystem with less hassle.
4. Fourth is workforce development, which trains people to understand these tools before they can utilize them to their fullest extent.

Those are our four main areas. When we think about digital health transformation, we start with the HIMSS maturity models from five to seven years ago.

Back then, our maturity models were a checklist of technology. Do you have that technology? Are you wired? That used to be the baseline, what we now consider table stakes. It’s not table stakes anymore.

We’ve transformed our maturity models to reflect quality, access, correctness, and fundamental value. How are you using the information? How does it improve the flow?

From an IT standpoint, we began looking at our maturity models like a stack. It starts with the information layer. What does the infrastructure look like? How is it laid out? How does your data need to be laid out? Where does the electronic medical record go on top of that? How do those two pieces feed into each other? How do you utilize the radiology and the pictures that are in there? How does that flow? What’s your analytical layer? How does this work?

Where are you getting your information, and how are you handling your analytics? How does that tie itself back into the infrastructure? How does that information flow from your reporting back into your EMR and the data layer? How does that data layer tie in when discussing the imaging ecosystem? What’s your continuity of care, the CCMM? How does it flow across the board to ensure you’re not dropping a patient?

We’ve created a stack of maturity models that form the foundation of how information flows from the patient across hospitals, clinics, and homes, wherever the case is provided, to ensure you can keep up with them. And we present these maturity models not just as a technology checklist. Anyone can do that—it’s not meaningless—but anyone can do that. The true focus is on how you use these technologies.

How do you ensure that the relationship between the patient and pharmacy utilization, as well as the benefit realization, is maintained? And how does all this tie together?

Whether it’s community service, a hospital system, or a home, what we’ve created in those stacks is a blueprint that any hospital system, country, or large-scale region can use to identify the technology needed and deploy it for its maximum benefit. 

People do assessments in hospital systems. For HIMSS members in the United States, these assessments are part of the membership, allowing them unlimited access to evaluate their systems. They can conduct these assessments online, check their status, and aim for levels 6 and 7, which is when all those benefits kick in. That’s when we do our validations.

We also do white papers, thought leadership, and HIMSS events, panels and educational programs. More than 300 academic programs are coming up at HIMSS in 2025, with more than 150 offering CE credits.

But these experiences are all based on the output, what worked, and what didn’t work. As you know, learning from others’ mistakes is just as valuable as learning from their successes. Some of the most impactful lessons come from those who try something, fail, and then fix it.

That’s where HIMSS and advisory services come in. We’re presenting the aggregated global knowledge of what’s working and what isn’t.

Most ecosystems don’t work the same way the United States does because most don’t have the same amount of money invested in it. We draw from many healthcare systems- from the U.S., to Romania, Italy, Germany, Singapore, Indonesia, Malaysia and Australia. We learn from all these countries, bring it together in our membership, and figure out what we have learned. How does it impact the models? We do these reviews in a constant session. That’s how we make the society work.

Bashe: It’s a brilliant use of human capital and composite wisdom. As we’re gearing toward the end of our conversation, I wanted to ask you about the Emerge Innovation Experience– this is a first-time gathering, but the concept of start-ups at HIMSS is nothing new. What’s different now is that you’ve recognized that start-ups are a unique culture with unique needs. You’ve assembled a cohort of leaders dedicated to helping these start-ups succeed. What are your expectations from Emerge?

Wolf: First, I’m very interested in the outcome of Emerge. This is the first time that we’re going to try to bring that mesh point I mentioned earlier, where innovations meet operations. They’ve chosen some excellent examples of what can come forward. I think it’s got the right practicality and innovative forethought. From what I’ve heard from people involved in it and talking to people on the committee, I’ve listened to everything from “Wow! This is fantastic and very innovative!” to “It could have been stronger.”

If I talk to heavy innovator startups, they reply that it doesn’t go far enough and could be really “wow.” Meanwhile, those focused on operations often reply that it’s “really pushing the edge.” What that tells me is that it’s in the right mesh point.

What I’m curious to see is how it is received. Many smart people have been working on it, focusing on what will have the biggest impact on operations and be ready for prime time tomorrow, especially in areas like AI utilization and operational impact. What is one step beyond? We also have an incubator ecosystem there.

The Emerge Innovation Experience will be unique, and I look forward to that outcome.

Bashe: I always value your candor.

Wolf: Sometimes, I can get criticized for it, but I believe in absolute transparency. The beautiful part about thought leadership is that we share these thoughts, which makes HIMSS thrive. Transparency is a strength in a positive society. If we’re not transparent with each other, we can’t advance. My grandfather taught me a long time ago that the three most essential phrases in business are “I don’t know, I’ll find out, and I’ll get back to you.” “I don’t know” is critically important.

What’s beautiful about healthcare is that you learn something new every day. It’s impossible to be in the health sector without learning something new every day unless you don’t ask a single question, read nothing, or stay in a room and shut the door.  

Just today, I learned something about HIMSS. I didn’t know because I was asking about a process. A question was raised, and I followed the thread through the organization and found one I’d never seen before, which was exciting.

I appreciate the philosophical and real questions you’re asking. We’re excited about HIMSS 2025 and the learning opportunities it will offer. It’s also about the big picture of what’s happening globally. We call it the Global Conference because it brings together Ministries of Health and NGOs worldwide. It all comes together. This is our largest membership meeting, and we’re thrilled that there’s at least a 35% increase in people signing up for HIMSS membership compared to last year.

Bashe: I’ll be attending this year. As always, thank you for the in-depth exchange. *****

In this insightful conversation, Hal Wolf, President and CEO of HIMSS, explores the critical forces shaping the sector’s future. As industry and governments navigate a rapidly evolving policy landscape under a new administration’s eyes, hospital systems, startups and policymakers must adapt to changing regulations, funding challenges, and digital transformation. Wolf highlights HIMSS’ role as a global leader in uniting a diverse ecosystem to advance health equity, interoperability, and patient-centered care.

A key theme of the discussion is how data and AI are transforming payer, provider and product innovation operations – how information can improve people’s lives. Wolf explains how AI-driven predictive models are integrated to optimize patient care and resource allocation. However, he also warns of ethical concerns—such as the potential for financial-driven decision-making that could prioritize revenue over patient needs. HIMSS plays a vital role in ensuring there is a balance between digital health innovation aligns with quality care and equitable access.

As digital tools, AI, and large language models (LLMs) become more integrated into healthcare, Wolf and Bashe discuss how these advancements can empower providers and patient-enhancing decision-making, improving operational efficiency and offering trusted, system-vetted health information.

As HIMSS prepares for its annual global conference, Wolf emphasizes its role in shaping industry priorities. HIMSS is not just an event; it’s a society that defines strategies, policies, and innovations that drive the future of health. With an expanding ecosystem of startups and industry veterans, HIMSS remains a pivotal force in bridging technology, policy and patient care.

The post The Future of Health Information and Innovation: A Conversation with HIMSS CEO Hal Wolf appeared first on Medika Life.

For too long, “AI” has been the abbreviation for “artificial intelligence.”  Reject that label!  It’s not only limiting – it’s incorrect.  The information gathered and parsed comes from real-world sources – patients, payers, product innovators, policymakers, and providers.  It is composite data, once called “big data,” sliced and diced through machine learning and then applied to good, sometimes life-sustaining use.  It’s time we acknowledge how “AI” has become a practical source for talent and organizational enhancement.

Health Enters the Age of “Augmented Implementation”

Here’s a dive into 10 transformative examples of how “AI” enables people to tap into their significant potential to heal and accelerate care delivery.  Change is always hard, even when the advantages appear evident, as it requires revamping processes and policies.  However, as innovation theorist, AI philosopher and Nosta Lab Founder John Nosta reflects: “Culture crushes innovation.” 

Nosta shares with Medika Life readers: “AI, particularly through large language models (LLMs), is revolutionizing healthcare by fostering ‘learner-centricity.’ This approach places physicians, patients, and healthcare systems at the center of a dynamic, personalized learning process. LLMs provide tailored, context-specific knowledge, enabling real-time insights and deeper understanding. Whether it’s a clinician refining diagnostic skills or a patient comprehending treatment options, LLMs create a collaborative learning ecosystem. This synergy enhances the healthcare experience, empowering all participants through shared knowledge and continuous growth.”

The culture of medicine is storied and slow-moving. Still, these 10 approaches to weaving AI into the health system are piquing people’s priorities and enthusiasm for greater use. The wave of universal acceptance is underway.

1. Revolutionizing Patient-Clinician Interaction

Ambient Listening Technologies (ALTs) are modernizing how clinicians transcribe medical documents – by capturing, recording, managing, and analyzing audio data from the patient exam room. AI transcription tools like the Nuance Dragon Ambient eXperience (DAX) from Microsoft streamline recording tasks that once consumed chunks of a clinician’s day. AI-driven transcription systems record and summarize patient-clinician conversations, enabling providers to focus on patients rather than documentation. The plus for doctors is reduced admin time; for patients, it provides the benefit of ensuring their provider has real-time notes for follow-up care delivery.

2. AI-Enhanced Diagnostics are Challenging the Future of Illness

Technologies like DeepMind AlphaFold provide unprecedented insights into protein structure prediction, accelerating drug discovery and enhancing diagnostic tools for diseases like Alzheimer’s and certain cancers. Anyone tracking the field of AI-empowered diagnostics would do well to keep a close eye on innovation in this space.  The 2024 Chemistry Nobel Prize was awarded to John Jumper, PhD, and Demis Hassabis, PhD, at Google DeepMind in London for developing this game-changing AI tool for predicting protein structures.  The Galien Foundation Prix Galien is often called the Nobel Prize of the Life Science industry.  Viz.ai, a pioneer in AI-powered disease detection and intelligent care coordination, received the 2024 Prix Galien USA Award for its Viz HCM™ (Hypertrophic Cardiomyopathy) module.  Keep an eye on these companies and their advances.

Rob Havasy, HIMSS Senior Director of Informatics Strategy, representing one of the most influence professional communities – the leaders from health institutions and governments worldwide – offered this exclusive comment to Medika Life:

“AI has been part of many radiology workflows for years, but data from our HIMSS Market Insights surveys show one of the fastest growing applications right now is ambient AI and other AI tools to relieve some of clinicians’ documentation burden. These tools either help clinicians capture information from a visit or streamline patient-provider communications by creating discharge instructions or helping to manage overflowing inboxes.”

3. Accelerating Drug Discovery and Clinical Trials

AI is catalyzing innovation in drug development, a process that traditionally spans over a decade. Platforms like Hong Kong-headquartered Insilico Medicine and companies like Exscientia are applying machine learning to design drug molecules faster than ever. Meanwhile, decentralized trials are becoming more accessible through collaborative pathways set by organizations such as the Decentralized Trials & Research Alliance (DTRA), a central gathering point for regulators and industry leaders to shift the conversation from theoretical to operational regarding implementation.

Dr. Amir Kalali and Craig Lipset, pioneers in clinical trial innovation, champion this collaborative model that draws in biopharma-sector leaders, CROs, and FDA and EMA regulators. The DTRA Co-Chairs have long advocated that decentralized clinical trials (DCTs) supported by AI tools broaden access and reduce biases. These collaborations demonstrate how AI unlocks new efficiencies and enables more inclusive participation, particularly among underrepresented populations.

4. Predictive Analytics for Patient Safety

Predictive analytics powered by AI is transforming patient safety in hospitals. For example, Qventus predicts and mitigates perioperative complications. At the same time, companies like Stasis Labs, Current Health, and Vytrac provide real-time in-patient and at-home monitoring, sending vital sign data to nurses and doctors so they know their patient status and triage care.  Amy Abernathy, MD, PhD, has served in several high-profile roles that cut across the health ecosystem, from Principal Deputy Commissioner at the Food and Drug Administration (FDA) and is now Co-Founder of Highlander Health, a bold new organization advancing clinical research and patient care through learning labs, investments, and philanthropy, comments: “AI is transforming how we approach patient safety by intervening in a proactive measure rather than a reactive one.”

5. Addressing Mental Health Needs with AI

Mental health care is becoming more accessible with AI-driven platforms such as Woebot Health and Wysa. These companies are using AI to provide scalable, CBT-based support for conditions like anxiety and depression, often meeting the needs of underserved populations without ready access to mental health services. Another approach led by GrayMatters Health enables mental health professionals to address PTSD through neuromodulation – an FDA-approved for-use approach designed through years of data aggregation.  Noted digital health pioneer, inventor, and  Founder and Curator for NextMed Health, Daniel Kraft, MD, notes: “AI-powered mental health tools are filling the gaps in traditional care delivery, providing immediate, accessible, and empathetic support when people need it most.”

6. Driving Precision Medicine

Precision medicine, enabled by AI, is bringing targeted therapies into sharper focus. Collaborating with Roche, Foundation Medicine uses genomic profiling to guide cancer treatments. Similarly, Tempus leverages AI to connect molecular and clinical data, accelerating therapeutic breakthroughs. The combination of high tech with high science has enabled scientists with support from private equity and academic institutions worldwide to create companies at the vanguard of the discipline in the UK Golden Triangle, Southeast Asia, and the Cambridge/Boston innovation hub. LABIOTECH author Willow Shah-Neville wrote a concise report of 12 biotech unicorns rated in order of their valuations according to CB Insights. It is worth examining how these fast-moving innovators apply information technology to augment their scientific implementation.

7. Streamlining Hospital Operations

AI tools enhance hospital operations, optimize workflows, and improve patient outcomes. For instance, GE Healthcare Command Centers use predictive analytics to manage patient flow. Other companies, such as LeanTaaS, with its iQueue platform, improve operating room and infusion suite scheduling. Hyro is a much-watched hospital workflow optimizer with services that cut across administrative and clinical departments and add AI to Epic workflows, improving access to care. Edward Marx, a global healthcare consultant and former Cleveland Clinic CIO, emphasizes: “Operational AI is reshaping how hospitals function, eliminating inefficiencies and ensuring resources are used where they’re needed most.”

“Top Trends in Healthcare and Life Sciences” Microsoft video episode titled “The power of information to improve healthcare,” Gil Bashe, Chair of Global Health and Purpose at FINN Partners and Medika Life Editor-in-Chief, joins Tom Lawry, formerly National Director for Artificial Intelligence Health and Life Sciences at Microsoft and now Founder of the AI consultancy Second Century, talk about the opportunities and obstacles in health, AI, and the power of information.

8. Promoting Health Equity Through AI

Medtronic AI-enabled remote monitoring devices are helping bridge the care gap in underserved areas. Similarly, PathAI, in collaboration with Quest Diagnostics, is leveraging “machine learning to improve diagnostics in resource-limited settings, ensuring equitable access to healthcare.  Michelle Longmire, MD, a Stanford-trained dermatologist and founder and CEO of Medable, which offers the research-based biopharma industry an array of research tools with a unified platform, adds: “AI’s potential lies in its scalability, which can extend high-quality care to populations previously overlooked by traditional systems.”

9. Harnessing AI for Population Health

AI is transforming public health by integrating social determinants of health into predictive models. Companies like Epic Health Research Network and Innovaccer are helping health systems anticipate and address population health challenges more effectively. Michael Rosenblatt, MD, with his storied career as a scientist and teacher, having served as Chief Medical Officer at Merck and Flagship Pioneering and now as Co-Chair of the Galien Foundation, notes: “AI-driven insights empower health systems to deploy resources strategically, reducing disparities and improving outcomes across entire communities.”

10. Empowering Patients with Wearables and Digital Health Platforms

Wearables like the Apple Watch have popularized health tracking. Still, more specialized solutions, such as AliveCor and Biobeat are examples of advanced monitors delivering medical-grade heart data enabling patients to access, manage, and share their data and connect with their physicians. Additionally, platforms like the Belong.Life Dave AI focuses on cancer care by guiding patients with tailored recommendations, educational content, and peer support.  David E. Albert, MD, Oklahoma native, physician, inventor, and serial entrepreneur, is the founder of AliveCor and a long-time AI champion, says, “AI will play a role in reducing data into manageable and actionable information for clinical decision-making.”

Looking Forward: A Future Shaped by Collaboration

AI progress in health settings during the past five years illustrates what’s possible when technology meets the demands of patient care, equity, and innovation.  

Is “AI” still threatening and misunderstood?  Absolutely! The term “artificial intelligence” is a threatening misrepresentation of the idea that people will become secondary to machines processing vast amounts of data (largely) accurately and in a blink. However, technology is continuously called upon to automate repetitive tasks.  It does not alone transform people’s health or the fractured health ecosystem – instead, it’s the human desire to question, collaborate, and generate shared – augmented – wisdom that is core to implementation.  

“Driving measurable value at scale with AI is less about the right technology and more about the right leadership. Is there a sufficient level of AI understanding at all levels of the organization?  Is your culture change-ready or change-resistant,” reflects Tom Lawry, principal of Second Century.  Is AI part of your HR plan? In the end, AI success cannot be delegated. Leadership is the catalyst for unlocking its true potential. This requires vision, strategic alignment, and a commitment to empowering teams to innovate and execute with purpose.”

As more people dip their toes into the tech waters, comfort levels are increasing rapidly. Remember the 15-year time gap between Apple’s failed Newton and the early iPhones? Once the idea of a smartphone caught on, it became a personal must. According to a Pew Research Center Survey conducted May 19 to Sept. 5, 2023, 90% of US adults say they have a smartphone. Soon, AI will be ubiquitous in most health settings.

Say so long to artificial intelligence. Welcome to the age of Augmented Implementation!

The next five years promise even more significant advances, , a thirst to use information to accelerate decision-making, fueled by curiosity and collaborations across sectors and the drive to improve lives globally.

The post AI is Transforming Health Delivery: A Five-Year Reflection appeared first on Medika Life.

Technological advances, including AI, are like fire—destructive and essential. Our mastery of fire has been vital to industrial and technological progress, from smelting iron to the steam engine to sterilizing food and medical instruments.  But, unchecked, fire is a destructive, societal danger. Similarly, AI can be a force for positive change, but it requires a positive perspective and responsible use to avoid potential dangers and greater socio-economic disparities.

By tapping into AI’s potential, we can create a future where human ingenuity and machine learning work together to improve the well-being of people and the planet. For instance, AI can assist in medical diagnoses, climate change predictions, and disaster response, among other areas. But to make that possible, we will need the courage and curiosity to see AI as humanity’s partner rather than an unwelcomed competitor – to leverage its strengths to complement our own.

Language matters, so we might be better off and more equipped to apply smart technologies by thinking about AI not merely as “artificial intelligence but, at the same time, “augmented implementation.”  

AI is not theoretical. It’s already transforming drug research and discovery and patient care delivery. From the research bench to the patient bedside, augmented implementation accelerates the discovery of new drugs and optimizes clinical trials, assigning the right patients to the right protocol. In hospitals, AI enhances resource allocation, accelerates clinical decision-making, personalizes patient care, automates administrative tasks such as billing and scheduling follow-up appointments, and tracks supply-chain necessities to avoid drug shortages. These implementation advancements result in better patient outcomes, reduced health costs, and a more effective care delivery system.

So, what is the problem? It seems evident that embracing these information technologies can make us smarter and faster – even fail smarter and faster. We don’t even need to know coding.  Large language models (LLMs) with the proper prompts can generate code based on a natural language description of the desired functionality.  

Perhaps the problem isn’t the technology; it’s humanity.  While most believe that humanity will triumph over tech, people’s fears translate into “pump the breaks” reflexes. But go slow quickly also ensures guardrails are in place for its appropriate use.  These transformative informational technologies are happening; now it’s a question of protecting people’s privacy and well-being, using these platforms ethically and responsibly, and keeping our eye on the prize – people’s healthy lives and the planet’s sustainable future.

20 AI/ChatGPT/LLM Champions to Follow

Once again, selecting only 20 thoughtful pathfinders for this listing was a challenge. There are thousands of people writing, speaking, and commenting about AI. It remains a hot topic and is always trendy. This list is not an exclusive roster of people speaking about or explaining AI possibilities. Those that do appear are key voices of influence at the frontlines of AI, GenAI, ChatGPT and LLMs and are boldly guiding the health sector and other related industries to adapt to these technologies ethically and practically. There is no turning back! For that reason, it is important to follow their social posts, speeches, and writings. They are consultants, physicians, policymakers, teachers and theorists. What they say and write should inform opinions and directions. Follow them and get smarter faster or fail slowly.

On this list, you will notice several differences from our last roster. First, we begin with including an LLM model we have been tracking and recommend following closely. Dave AI was the topic of a previous Medika Life article and is a role model for those interested in the potential of LLM technology to augment the patient-care team’s abilities and desire to help and heal. Dave AI offers patients WAZE-AI-like information support.

We have also included an organizational policy leader to close the list—Hal Wolf, President and CEO of HIMSS. We have interviewed Hal before, and his global community, nearing 40,000 members, comprises health leaders and government representatives who are setting the parameters for how these smart technologies can be used wisely.

Acknowledgments

Special appreciation to Medika Life colleagues such as Drs. Robert Turner, Patricia Farrell, and Michael Hunter, who inspire and the many others from numerous circles I meet at meetings CNS Summit, DHAI, HIMSS, HITLAB, HLTH, and ViVE and who share their thoughts and contribute recommendations. Many who appeared on the initial list of global voices keep in touch and share news of sector colleagues who are in the thick of the conversation. Special acknowledgment to people who appeared on previous Medika Life lists and continue along the path to improve the well-being of people and the planet. These exemplary people are dedicated to improving people’s health and we applaud their efforts to make a difference.

Since the dawn of time, people have been in awe and fear about advances made in times marked by technologies—from fire to AI: the Stone Age, Iron Age, and now, today’s Information and Sustainability Age. Humanity must decide how best to deploy these transformative “thinking” technologies. The emphasis on objective and expansive (courageous) “thinking”—the human touch—remains constant.

Gil Bashe, Editor–in-Chief, Medika.Life

AI and ChatGPT Global Voices of Influence

Here is our Medika Life roster of 20 people to follow in alphabetical order—all-important voices to track and learn from in the coming years. We have included links to the social media platforms and bios wherever available.

Follow these Voices of Influence—they are accessible leaders who write and speak on the future of how AI, ChatGPT, GenAI, and LLMs will be essential to health system transformation and the future of care delivery.

Dave AI

Dave is the world’s first LLM conversational AI oncology mentor for cancer patients, bringing a new level of support for cancer patients and their families and trained on billions of unique data points and anonymized real-world patient journey information accumulated during eight years on the Belong Life platform. Learn how LLMs make a difference for patients and the care team, “Meet Dave” and see the practical possibilities and potential of LLMs.

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Anima Anandkumar, PhD

Anima Anandkumar is a Bren Professor at Caltech. Her work developing novel artificial intelligence algorithms enables and accelerates scientific applications of AI, including scientific simulations, weather forecasting, autonomous drone flights, and drug design. Anandkumar is a fellow of the ACM, IEEE, Schmidt Science, Guggenheim and Alfred. P. Sloan Foundations. 

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Brian Anderson, MD

Dr. Brian Anderson is the Chief Executive Officer and Co-Founder of the Coalition for Health AI (CHAI). He leads a national coalition developing technical standards and best practices for MLOps, including governance, testing, evaluation, and monitoring in Health AI Assurance Labs. Dr. Anderson led the Informatics and Network Medicine Division at Athenahealth, where he launched a new approach to clinical decision support leveraging machine learning models.

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Pascal Bornet

Pascal Bornet is an award-winning expert, author, keynote speaker, influencer, and thought leader in artificial intelligence. He has received multiple technology and artificial intelligence awards. Various research and consultancy firms rank him as one of the top 10 global experts in AI and Automation, and he was awarded Global Top Voice in Tech in 2019. He is the author of the best-seller and first reference book on Intelligent Automation.

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Lex Fridman, PhD

Lex Fridman, PhD, is a Russian-American computer scientist, podcaster, and artificial intelligence research scientist at the Massachusetts Institute of Technology on computer vision and autonomous vehicle systems, among other areas of specialty. Fridman also hosts the “Lex Fridman Podcast,” a popular podcast and YouTube series.

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Mo Gawdat, MBA

Mohammad “Mo” Gawdat is an Egyptian entrepreneur and writer. He is the former chief business officer for Google X and the author of the bestselling business books covering life and technology: Solve for Happy and Scary Smart – The Future of Artificial Intelligence and How You Can Save Our World. His premise is critical – “Humans design the algorithms that define the way that AI works, and the processed information reflects an imperfect world.”

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Aneesh Chopra, MPP

Aneesh Chopra is the Chief Strategy Officer of Arcadia, a health data platform that acquired CareJourney, the company he co-founded in 2014. Aneesh served as the first United States White House Chief Technology Officer during the Obama Administration and authored “Innovative State: How New Technologies Can Transform Government.‘ When it comes to policy and smart tech applications, he’s at the forefront of the conversation.

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Eric Horvitz, MD

Microsoft’s Chief Scientific Officer and an early AI champion for health and medicine going back many years, Dr. Eric Horvitz is among the founders and funders of Stanford’s 100-year longitudinal study of the impact of AI on Society. Dr. Horvitz is known for his contributions to AI theory and practice, with a focus on principles and applications of AI amidst the complexities of the open world.

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Andrej Karpathy, PhD

Andrej Karpathy was the senior director of AI at Tesla, where he led its computer vision team in the development of the Tesla Autopilot. He championed its neural network training, the science of “making it work, ” and deployment. His PhD focused on convolutional/recurrent neural networks and their applications in computer vision, natural language processing, and their intersection – his adviser was Fei-Fei Li at the Stanford Vision Lab, who also makes this list of 20 people to follow. He also did a stint at OpenAI.

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Tom Lawry

Tom Lawry is a leading AI transformation advisor to health and medical leaders globally, a top keynote speaker, and best-selling author of Hacking Healthcare – How AI and the Intelligent Health Revolution Will Reboot an Ailing System. Now the managing director of Second Century Tech, he is a former Microsoft leader who served as National Director for AI for Health and Life Sciences, Director of Worldwide Health, and Director of Organizational Performance for the company’s first health incubator. Prior to Microsoft, he was Senior Director at GE Healthcare, the founder of two venture-backed healthcare software companies, and a health-system executive.

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Fei-Fei Li, PhD

Dr. Fei-Fei Li is the inaugural Sequoia Professor in the Computer Science Department at Stanford University and Co-Director of Stanford’s Human-Centered AI Institute. She was the Director of Stanford’s AI Lab from 2013 to 2018 and mentored others appearing on this Medika Life Top 20 list of AI voices to follow.

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Berci Mesko, MD, PhD

Bertalan Meskó, PhD, is known as “The Medical Futurist” and the Director of The Medical Futurist Institute. He analyzes how science fiction technologies can become a reality in medicine and healthcare. Dr. Mesko’s writings are must-reads—he provides incredible practical knowledge on how AI will transform the health sector. He holds a PhD in genomics and is an Amazon Top 100 author. His book, “The Future of Medicine,” outlines his journey as a medical futurist.

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Allie K. Miller

Allie K. Miller was the Global Head of Machine Learning Business Development for Startups and Venture Capital at Amazon (AWS), advising the world’s top machine learning researchers, founders, and investors. She was the youngest-ever woman to build an artificial intelligence product at IBM, spearheading product development across computer vision, conversation, data, and regulation for thousands of companies. Allie continues to explore how this technology will impact workflow.

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Andrew Ng, PhD

Dr. Andrew Ng is a globally recognized leader in AI. He is the Founder of DeepLearning.AI, the Founder and CEO of Landing AI, the General Partner at AI Fund, the Chairman and Co-Founder of Coursera, and an Adjunct Professor at Stanford University’s Computer Science Department.

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John Nosta

John Nosta is a cutting-edge thinker and speaker in the world of technology, science, medicine, and innovation. He is globally recognized among the foremost voices constantly pushing the envelope on how AI and ChatGPT will transform health settings and workflow. Nosta is a nonstop power thinker (and contrarian) and has more than 500 articles published on innovation topics. His writings on Psychology Today chronicle “The Cognitive Age.” John is someone who challenges the status quo. As a creative thinker; he’s also been the spark behind several multi-billion health products improving and saving lives.

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Tam C. Nguyen

Tam Nguyen holds multiple appointments, including Associate Professor at Melbourne Medical School and Deputy Director of Research at St. Vincent’s Hospital Melbourne. He has more than 20 years of experience in clinical trials, health and medical research, and research management, including tertiary teaching hospitals, medical research institutes, and universities across Australia. He is applying smart technologies to learn and engage faster. He is the co-editor of the recent book Artificial Intelligence in Medicine (Springer).

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Ziad Obermeyer, MD

Ziad Obermeyer, MD, is the Blue Cross of California Distinguished Associate Professor of Health Policy and Management at the UC Berkeley School of Public Health, researching the intersection of machine learning, medicine and health policy. Before his full-time career in emergency medicine, he consulted pharmaceutical and global health clients at McKinsey & Co. in New Jersey, Geneva, and Tokyo.

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Brian Roemmele

Brian Roemmele is an author, scientist, researcher, analyst, connector, thinker, and doer. Brian became an early adopter of AI and neural networks and pioneered Prompt Engineering technologies and techniques to understand and extract information from AI platforms. He’s also a bit of a pop icon, and his works range from smart tech to how to apply Pokémon for customer acquisition.

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Stela Solar

Stela Solar is the Inaugural Director of Australia’s National AI Centre, hosted by CSIRO. The Centre’s mission is to accelerate positive AI adoption and innovation that benefits businesses and the community. Currently, Stela also serves as Co-chair of the Commonwealth AI Consortium.

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Harold (Hal) Wolf III

Harold (Hal) Wolf is the president and CEO of HIMSS, a global advisor and thought leader supporting the transformation of the health ecosystem through information and technology. If health-related smart technologies such as AI, ChatGPT, GenAI, and LLMs have a central home to discuss policies and implementation, it is HIMSS. Hal shepherds the world’s health information expert community, and his staff advances the science and policy championing implementation throughout the health ecosystem. Wolf and HIMSS are where theory meets action.

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Spot a broken link, typo, forgotten degree, or name misspelled?

Oops! Apologies! While care has been taken in compiling this list and adding social media links, things go wrong: a name is misspelled, a link is broken, or an incorrect social media handle is listed. Please do get in touch to address typos, amendments, or omissions by reaching gil.bashe@medika.life.

Thanks in advance and be healthy!

The post As AI and LLMs Supercharge Digital Health Possibilities – Here Are Medika’s Top 20 ’24 Influential Voices to Follow appeared first on Medika Life.