The global market for artificial intelligence (AI) in healthcare is projected to reach approximately $701.79 billion by 2034, soaring from $37.09 billion in 2025. This growth reflects a robust compound annual growth rate (CAGR) of 38.64% over the period from 2025 to 2034.

The expansion of AI in healthcare can be attributed to its ability to improve diagnostic accuracy and speed, tailor treatment strategies, and enhance operational efficiency. These benefits culminate in improved patient outcomes while also lowering costs. AI empowers healthcare providers with tools for early diagnosis, rapid assessment, and optimized treatment plans, resulting in quicker care for both patients and hospitals. Furthermore, AI technologies streamline healthcare operations by automating routine tasks, improving workflow management, and optimizing resource distribution.

For example, in November 2025, InterSystems, a leader in data technology that supports over a billion health records globally, introduced the InterSystems HealthShare AI Assistant. This new generative AI tool is designed to help clinicians, case managers, and healthcare administrators access and analyze patient data swiftly and intuitively.

Key Insights from the AI in Healthcare Market:

- The software solution segment held the largest revenue share, exceeding 47% of the market in 2024.
- The robot-assisted surgery application dominated the market with over 14% revenue share in 2024.
- The machine learning technology segment claimed the highest market share, at over 36% in 2024.
- Healthcare companies were the leading end-users, accounting for more than 31% of the market's revenue share in 2024.
- North America led the global AI healthcare market, contributing to over 55% of the revenue in 2024.

Market Overview and Future Potential

AI technology represents a groundbreaking sector within computer science, poised to fundamentally change treatment methodologies and healthcare delivery. Tools powered by AI are deployed to diagnose illnesses, tailor personalized treatment plans, and aid medical professionals in making informed decisions. This innovation is crucial for advancing precision medicine, optimizing drug administration, enhancing health management for populations, and providing virtual health support. 

For instance, in May 2025, Danaher Corporation announced a partnership with AstraZeneca to innovate and commercialize new diagnostic tools aimed at helping clinicians identify patients who would benefit most from precision medicine.

Recent advancements in AI technology are set to transform various facets of healthcare, ushering in a future characterized by personalized, precise, predictive, and easily accessible care. Whether through incremental changes or more radical technological shifts, healthcare systems must navigate the evolving landscape to adapt effectively to these digital advancements.

For further insights, access the complete report on the AI in healthcare market here. 

This report offers in-depth analyses covering market size projections from $37.09 billion in 2025 to $701.79 billion by 2034, with a growth rate (CAGR) of 38.64%. It encompasses a variety of components, applications, technologies, and end-user sectors across regions including North America, Europe, Asia Pacific, Latin America, and the Middle East and Africa. Notable companies influencing this market include Microsoft, IBM, NVIDIA Corporation, Intel Corporation, and Medtronic, among others.

Healthcare AI Market Expected to Reach USD 701.79 Billion by 2034

A bright modern hospital ward bathed in warm morning sunlight. A doctor in scrubs studies a sleek tablet displaying a vibrant line chart shooting upward, labeled “USD 701.79 B by 2034.” In the softly lit background, a nurse checks a patient’s IV while medical monitors show subtle digital overlays, hinting at AI-driven diagnostics. The scene feels hopeful and earnest, celebrating the surge of AI in healthcare.

AI In Healthcare Market to Hit USD 701.79 Billion by 2034 - BioSpace

- The global AI in healthcare market is projected to reach $701.79 billion by 2034.  
- AI enhances diagnosis precision, treatment planning, and operational effectiveness, benefiting patient outcomes.  
- North America dominated the market in 2024, accounting for over 55% of revenue.  

The global AI in healthcare market size is expected to be hit around 701.79 billion by 2034, increasing from USD 37.09 billion in 2025, representing a healthy CAGR of 38.64% from 2025 to 2034.

The AI in healthcare market is increasing due to its capability to enhance precision and speed in diagnosis, targeted treatment plans, and increase operational effectiveness, which ultimately leads to better patient results and reduces costs. It offers various benefits such as early identification, quick diagnostics, and an efficient therapy plan, lower time and expenses for the patient and hospital, while getting quicker care. AI-driven technology streamlines medical care operations, enhancing patient care efficacy by automating administrative actions, enhancing workflow management, and optimizing resource allocation.

· For Instance, In November 2025, InterSystems, a creative data technology provider powering more than 1 billion health records worldwide, announced the launch of InterSystems HealthShare AI Assistant, a new generative AI capability designed to assist clinicians, case managers, and administrators in accessing and understanding patient information faster and more intuitively.

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AI In Healthcare Market Highlights:

⬥︎ Based on component, the software solution segment dominated the market with the largest revenue share of over 47% in 2024

⬥︎ Based on application, the robot-assisted surgery segment dominated the market in 2024 with the largest revenue share of over 14%.

⬥︎ Based on technology, the machine learning segment held the largest market share of over 36% in 2024.

⬥︎ Based on end use, healthcare companies dominated the market with the largest revenue share of over 31% in 2024.

⬥︎ North America AI in the healthcare industry dominated the global market and accounted for the largest revenue share of over 55% in 2024.

Market Overview and Industry Potential

AI-driven technology is a significant and disruptive area of computer science, with the latent to essentially transform the practice of treatment and the delivery of medical care. AI-driven technology is used to diagnose diseases, create advanced personalized treatment plans, and assist physicians with decision-making. It transforms targeted medicine, optimizes drug dosages, improves population health management, establishes policies, offers virtual health assistants, supports mental health care, enhances patient education, and influences patient-doctor trust.

⬥︎For Instance, In May 2025, Danaher Corporation, a global science and technology innovator, announced the launch of a partnership with AstraZeneca to develop and commercialize novel diagnostic tools and tests intended to help clinicians better determine which patients would most benefit from precision medicine treatments.

Recent advancement in AI-driven technology has the potential to revolutionize various aspects of medical care, allowing a future that is more personalized, exact, prognostic, and portable. An incremental adoption of novel technologies or radical adoption of these technological innovations, but the impact of such technologies and the digital renaissance they bring needs health systems to reflect how greatest they adapt to the shifting landscape of healthcare.

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Report Scope of AI In Healthcare Market

Report Coverage Details Market Size in 2025 USD 37.09 Billion Market Size by 2034 USD 701.79 Billion Growth Rate From 2025 to 2034 CAGR of 38.64% Base Year 2024 Forecast Period 2025-2034 Segments Covered Component, Application, Technology, End use, and Region Market Analysis (Terms Used) Value (US$ Million/Billion) or (Volume/Units) Regional scope North America; Europe; Asia Pacific; Latin America; MEA Key Companies Profiled Microsoft; IBM; NVIDIA Corporation; Intel Corporation; Itrex Group; GE Healthcare; Google; Medtronic; Oracle; Medidata; Merck; IQVIA

AI In Healthcare Market to Hit USD 701.79 Billion by 2034

The American Nurses Foundation is set to grant three $10,000 awards aimed at fostering nurse-led investigations into the integration of artificial intelligence (AI) within the nursing profession. 

These grants will support teams led by nurses who are interested in examining how AI can address challenges faced by healthcare professionals, ultimately aiming to develop innovative solutions that enhance nursing practices through technology.

This funding initiative is part of a broader effort to bolster leadership and innovation within the nursing field, particularly among nurses in the early stages of their careers. This endeavor not only provides financial backing for projects spearheaded by nurses but also emphasizes the importance of leadership development and collaborative learning among peers.

The financial resources for these grants are sourced from a partnership with Hippocratic AI, a global leader in generative AI. Hippocratic AI aims to mitigate the shortage of healthcare workers by automating routine tasks related to administration and communication.

The impact of this initiative is noteworthy, as nurses across all levels of experience are invited to apply for these microgrants. However, preference will be given to clinical nurses with a minimum of three to five years of experience who can collaborate with a senior nurse leader to implement strategies based on insights gained.

Key areas of focus for the proposals include examining how AI can be utilized prior to patient procedures, developing user-friendly AI tools for nurses, promoting AI usage in nursing practice, and addressing skepticism surrounding its integration.

Proposed projects must outline clear and feasible methods for implementation.

Graig Eastin, the executive director of the American Nurses Foundation, emphasized, “We seek submissions that not only envision possibilities but also demonstrate how nurse-led initiatives can revolutionize patient care and enhance community health.” Eastin looks forward to receiving innovative, insightful, and practical proposals that bridge the gap between ideas and impactful results.

Applications must be submitted by February 17, 2026, at 4 p.m. EST through the ANF online portal, with grant recipients expected to be announced in April.

The broader landscape shows that while 88% of healthcare systems have adopted some form of AI internally, only 18% possess a well-defined governance structure and a comprehensive AI strategy, as highlighted in an August report by the Healthcare Financial Management Association in conjunction with Eliciting Insights.

Despite the deployment of AI solutions in areas such as finance and clinical functions by 71% of respondents, governance remains an area needing improvement. The use of AI in healthcare continues to grow in popularity among physicians, according to a February survey conducted by the American Medical Association, although many practitioners continue to exercise caution due to ongoing concerns.

For those interested, the HIMSS AI & Cybersecurity Virtual Forum will take place on November 18, and attendees can register for free.

American Nurses Foundation to provide three $10,000 grants for AI research.

Three nurses in scrubs gathered in a sunlit conference room, each holding an oversized check for “$10,000 – American Nurses Foundation,” a laptop on the table displaying a colorful AI neural-network diagram, an American flag mounted on the wall, warm natural light pouring through large windows, hopeful expressions and a sense of innovation in the air.

American Nurses Foundation awarding three $10K grants for AI research - Healthcare Finance News

- The American Nurses Foundation is awarding three $10,000 grants for AI research in nursing.  
- Grants aim to advance nurse-led projects and enhance leadership for early-career nurses.  
- Applications are due by February 17, 2026, focusing on actionable AI solutions for healthcare.  

Successful applicants will explore the connection between AI and nursing.

The American Nurses Foundation will award three grants, each totaling $10,000, to applicants dedicated to advancing nurse-led research into artificial intelligence.

The grants will be awarded to nurse-led teams who can explore the connection between AI and nursing, and discover new solutions to issues impacting nurses using the technology.

The grants are designed as part of a larger initiative to strengthen nurse leadership and innovation with a focus on early-career nurses. In addition to funding nurse-led projects, the grant is intended to nurture transformation through leadership development and peer learning.

Funding for the grants comes from a partnership with global generative AI company Hippocratic AI, which has a goal to help the healthcare worker shortage by automating repetitive administrative and communication tasks.

WHAT'S THE IMPACT

Nurses at all career stages are encouraged to apply for these microgrants, but particular consideration will be given to clinical bedside nurses with at least three to five years of nursing experience, and the ability to partner with a C-suite nurse leader to apply any lessons learned.

Some of the priorities include exploring the use of AI agents and application before a patient procedure, nurse-friendly AI tools and interactions, and strategies to increase the use of AI in nursing, as well as reducing skepticism.

The proposals must also indicate clear and feasible implementation.

"We're seeking proposals that don't just imagine what might be possible but demonstrate how nurse-led solutions can transform patient care and improve the health of communities," said Graig Eastin, executive director of the American Nurses Foundation. "We look forward to receiving bold, thoughtful and actionable proposals that turn ideas into evidence, and evidence into impact."

All application responses are due Feb. 17, 2026, at 4 p.m. EST, via ANF’s online submission portal, and the notification of grantees is expected in April.

THE LARGER TREND

Eighty-eight percent of health systems are using artificial intelligence internally, but just 18% have a mature governance structure and fully formed AI strategy, according to an August report from the Healthcare Financial Management Association and market research company Eliciting Insights.

Governance is lacking despite the fact that 71% of survey respondents have identified and deployed pilot or full AI solutions in finance, revenue cycle management or clinical functional areas.

The use of artificial intelligence in healthcare is gaining popularity among physicians, found a February survey from the American Medical Association, though many remain guarded in their enthusiasm due to lingering concerns.

The HIMSS AI & Cybersecurity Virtual Forum is free to attend on Nov. 18. Learn more and register.





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Healthcare Finance News is a HIMSS Media publication. Jeff Lagasse is editor of Healthcare Finance News.Email: [email protected] Healthcare Finance News is a HIMSS Media publication.





American Nurses Foundation awarding three $10K grants for AI research

In his recent essay, Eric Reinhart articulates important concerns regarding the potential dangers of generative artificial intelligence (genAI) in the healthcare sector (What we lose when we surrender care to algorithms, November 9). I appreciate the inclusion of my viewpoint, and I maintain that “AI will be as ubiquitous in healthcare as the stethoscope.”

Reinhart accurately highlights the significant risks inherent in introducing new technologies within our profit-driven, time-limited healthcare system. However, a proper evaluation of genAI’s risks requires us to first recognize the unnecessary errors and fatalities that currently occur. We must consider whether this technology could exacerbate existing issues or enhance the safety of medical care.

In the United States, approximately 400,000 individuals lose their lives each year due to misdiagnosis, while another 250,000 die because of preventable medical errors. Patients with chronic conditions often have infrequent visits—typically every four to six months—without any assessment or adjustment to their treatment plans in between. As a result, conditions such as high blood pressure, uncontrolled blood sugar, and deteriorating chronic heart failure lead to hundreds of thousands of preventable heart attacks, strokes, cancers, and kidney failures annually.

This is where genAI can play a transformative role. It can provide patients with timely and accurate guidance while enabling physicians to receive alerts about potential warning signs, facilitating adjustments to medications before any irreversible damage occurs. Additionally, those experiencing mental health challenges can obtain support during critical times at night when their anxiety or depression intensifies, often leaving the emergency room as their only option.

Rather than viewing the future as a choice between clinicians and AI, we should embrace a collaborative approach that includes both. The synergy of dedicated healthcare professionals, empowered patients, and genAI has the potential to deliver safer, higher-quality, and more accessible care than any single element could achieve on its own.

Reinhart’s essay raises crucial points that warrant continued discussion. However, dismissing genAI will not shield patients; instead, it risks exacerbating current problems, ultimately putting them at greater risk. 

Dr. Robert Pearl  
Los Gatos, California

Dismissing generative AI in healthcare won't safeguard patients – it will endanger them.

A moody, dark hospital room at night: a lone doctor stands before an idle AI diagnostic console, its screen black and cables coiled like lifelines cut. Nearby, a patient on a bed struggles under an oxygen mask while the heart monitor’s green line sputters into red. Deep shadows swallow the corners, pierced only by the soft glow of an emergency exit sign, underscoring how refusing generative AI can endanger lives.

Rejecting generative AI in healthcare won’t protect patients – it will harm them | Letter - The Guardian

- Eric Reinhart's essay highlights risks of generative AI in profit-driven healthcare systems.  
- 400,000 deaths annually in the U.S. arise from misdiagnoses and preventable errors.  
- Generative AI can enhance patient care without replacing clinicians, improving overall healthcare quality.  

Eric Reinhart’s essay raises thoughtful concerns about the risks of generative artificial intelligence (genAI) in healthcare (What we lose when we surrender care to algorithms, 9 November). I appreciate that my perspective was included, and I stand by my belief that “AI will be as common in healthcare as the stethoscope”.

Reinhart rightly points out that there are serious risks in deploying new technologies in our profit-driven, time-constrained healthcare system. But to judge the risks of genAI accurately, we need to first acknowledge the unnecessary errors and deaths that occur today. And then we must ask whether this technology will make those problems worse or make medical care safer.

In the United States, 400,000 people die each year from misdiagnoses. Another 250,000 die from preventable medical errors. People with chronic diseases (lifelong conditions that affect them daily) are often seen only once every four to six months, with no evaluation or treatment modifications in between. Over time, blood pressure remains elevated, blood sugar levels stay uncontrolled and chronic heart failure worsens. The result: hundreds of thousands of avoidable heart attacks, strokes, cancers and kidney failures each year.

GenAI can help. Patients can receive timely, reliable guidance, while physicians can be alerted to early warning signs and adjust medications before irreversible harm happens. Likewise, individuals with mental health conditions can access support at night when anxiety or depression worsens and the only option is the emergency room.

Instead of replacing physicians, genAI can fill the gaps when clinicians are unavailable. Rather than framing the future as either/or (ie clinicians or AI) it should be both/and. The combination of dedicated clinicians, empowered patients and genAI will lead to safer, higher-quality and more accessible care than any of the three can achieve alone.

Reinhart’s essay raises important questions, and we should keep discussing them. But rejecting genAI won’t protect patients. It will harm them by allowing today’s problems to become worse.

Dr Robert Pearl

Los Gatos, California

Rejecting generative AI in healthcare won’t protect patients – it will harm them

Two companies from SymphonyAI are merging to introduce GW RhythmX, an innovative platform that utilizes artificial intelligence to offer personalized care by integrating data from clinical, financial, payer, and social sources.

According to SymphonyAI Group, GW RhythmX will harness the power of AI to generate insights aimed at enhancing the operations of healthcare systems and improving patient outcomes.

Deepthi Bathina, founder of RhythmX AI, will take the helm as CEO of the newly unified company, while Michael O’Neil, the founder and CEO of Get Well, will serve as vice chair.

The significance of this merger is profound. Both RhythmX AI, a generative AI platform focused on supporting physicians and healthcare systems, and Get Well, known for its patient engagement tools, collectively cater to 150 health systems and have a reach of 85 million patients, including eight million veterans.

SymphonyAI Group has stated that the new precision care AI platform will integrate healthcare data from over ten different sources. This ambitious project aims to combine electronic health record data with clinical policies, guidelines, financial considerations, and social determinants to enhance clinical outcomes for patients, streamline workflows for healthcare providers, and improve financial performance for health organizations.

Launched in 2023, RhythmX AI’s platform is designed to be agnostic to electronic health records (EHR), allowing it to deliver over 300,000 personalized treatment recommendations and optimize coding and billing processes. Its analytics capabilities have been instrumental in predicting disease progression and uncovering previously undiagnosed conditions in patients.

As Dr. Romesh Wadhwani, chairman of the group, noted, the merger of these companies is pivotal for providing the necessary resources, technology, and scalability to empower health systems to excel in an era defined by patient-centered, AI-driven precision care.

In a larger context, SymphonyAI Group's acquisition of Get Well took place in 2024, with the goal of employing predictive and generative AI technologies to enhance the experiences of patient engagement. The collaboration has reportedly led to a reduction in hospital readmissions by over 65% while also generating new revenue opportunities and boosting patient satisfaction levels.

Earlier in the year, Get Well unveiled Opal, an AI assistant designed to support patients post-discharge, leveraging the technology from RhythmX. This AI assistant has helped notable clients, including Adventist Healthcare, Ascension, UMass Memorial, BayCare, and LifeBridge Health, by allowing them to monitor discharge progress, automate post-discharge check-ins, and ensure adherence to care plans while addressing potential obstacles such as transportation issues.

O'Neil expressed that joining SymphonyAI Group has accelerated Get Well’s access to vital data, technology, and talent, thereby maximizing the potential of generative AI to reduce challenges faced by patients, empower caregivers, and provide added value to healthcare systems throughout the entirety of the care continuum.

RhythmX AI has also formed partnerships with reputable tech firms, recently aligning with Microsoft to enhance clinical AI capabilities within Dragon Copilot.

In summary, Bathina emphasized the transformative potential of this unified approach, stating that by consolidating healthcare data into a singular actionable intelligence platform, they are redefining medical practices. This initiative is designed to allow clinicians to concentrate on crucial tasks, enhance patient interactions, and support health systems in achieving superior operational and financial outcomes. 

The HIMSS AI & Cybersecurity Virtual Forum is set to occur on November 18 and is free to attend, inviting interested participants to learn more and register. 

Andrea Fox is a senior editor at Healthcare IT News.

Get Well and RhythmX AI combine patient engagement with precision medicine.

A sunlit, modern clinic room bathed in warm natural light, where an adult patient and a physician in a white coat lean over a curved digital table displaying interactive health charts, a glowing DNA helix, and personalized medication icons. Prominently placed on the table are the Get Well logo and the RhythmX AI logo, connected by a vibrant ribbon of data. In the background, a sleek heart-rate monitor and wall-mounted tablets show dynamic patient-engagement modules, evoking a hopeful, collaborative precision-medicine future.

Get Well and RhythmX AI merge patient engagement and precision medicine - Healthcare IT News

- SymphonyAI companies unite to launch GW RhythmX, an AI-driven personalized care platform.  
- RhythmX AI and Get Well serve 150 health systems and 85 million patients collectively.  
- The platform integrates clinical, financial, and social data to enhance patient outcomes and operations.

The two SymphonyAI companies are combining to launch GW RhythmX, an artificial intelligence-driven personalized care platform that unites clinical, financial, payer and social data.

GW RhythmX will leverage artificial intelligence to surface insights that can improve health system operations and patient outcomes, according to SymphonyAI Group.

RhythmX AI founder Deepthi Bathina will lead the combined company as its chief executive officer, while Michael O’Neil, Get Well founder and CEO, will become vice chair.

WHY IT MATTERS

RhythmX AI, a generative-AI-based platform for physicians and health systems, and patient engagement platform Get Well, together serve 150 health systems and 85 million patients, including eight million veterans, according to an announcement on Tuesday.

Building a precision care AI platform will unite healthcare data across more than 10 sources, SymphonyAI Group said. It is expected to combine electronic health record data and clinical policies and clinical guidelines with financial, payer and social data in order to improve outcomes for patients and clinicians and financial performance for health systems.

RhythmX AI's platform, which launched in 2023, is EHR-agnostic. The company stated that it has delivered more than 300,000 uniquely personalized treatment recommendations and optimized coding and billing. Analytics have predicted disease progression and identified evidence of undiagnosed patient conditions.

The combined company brings the needed resources, technology and scale together to enable health systems to "thrive in the new era of patient-centric, AI-powered precision care," Dr. Romesh Wadhwani, the group's chairman, said in a statement.

THE LARGER TREND

SymphonyAI Group acquired Get Well in 2024 with the intention of using predictive and generative AI technology to enhance patient engagement experiences. Get Well has helped its customers reduce hospital readmissions by more than 65%, capture new revenue and improve patient satisfaction, the group said in a statement.

Earlier this year, Get Well launched Opal, an AI patient assistant for post-discharge support, by leveraging RhythmX technology.

The AI assistant enabled customers, including Adventist Healthcare, Ascension, UMass Memorial, BayCare and LifeBridge Health, to track real-time discharge progress and automate post-discharge check-ins, improve care plan adherence and help address discharge delays, such as transportation issues.

"Joining SAIGroup has accelerated Get Well’s access to data, technology and talent to unleash the power of genAI and agentic AI on reducing friction for patients, empowering caregivers and delivering more value for health systems at every point in the care continuum," O'Neil said in a statement at the time.

RhythmX AI has also partnered with other tech companies, most recently with Microsoft, to improve clinical AI capabilities in Dragon Copilot.

ON THE RECORD

"With our companies coming together as one, we have the opportunity to forever change the way medicine is practiced," Bathina said in a statement. "By orchestrating all of healthcare's data into one platform of actionable intelligence, we're helping clinicians focus on what matters most, giving patients a more connected experience and enabling health systems to achieve new levels of operational and financial performance."

The HIMSS AI & Cybersecurity Virtual Forum is free to attend on Nov. 18. Learn more and register.

Andrea Fox is senior editor of Healthcare IT News.

Email: [email protected]

Healthcare IT News is a HIMSS Media publication.

Get Well and RhythmX AI merge patient engagement and precision medicine

The use of Artificial Intelligence in healthcare is expanding rapidly nationwide, enabling medical professionals to detect conditions like sepsis and conduct neurological studies with enhanced precision. As advancements in AI continue to emerge, hospitals are discovering diverse applications for this technology. Dr. Akshay Sayal from NBC News provides insights from Cleveland, Ohio, on November 13, 2025.

The impact of AI on healthcare is reshaping the industry nationwide.

Sunlit modern hospital ward: a physician reviews a sleek tablet showing a 3D heart model overlaid with a subtle neural-network motif; a nurse fits a wearable vital-sign sensor on an adult patient’s arm; warm natural daylight floods the white walls and potted plants, evoking AI-powered healthcare transformation.

How AI is transforming healthcare across the country - NBC News

- AI is increasingly utilized in healthcare to detect sepsis and aid neurological research.  
- Hospitals are expanding the range of AI applications in patient care and diagnostics.  
- Innovations in AI are transforming medical practices and improving healthcare outcomes nationwide.  

Artificial Intelligence is being implemented in more and more healthcare settings across the country, helping doctors spot sepsis or perform neurological research. As AI innovations grow, hospitals are seeing a wider range of uses for the technology. NBC News' Dr. Akshay Sayal reports from Cleveland, Ohio. Nov. 13, 2025

How AI is transforming healthcare across the country

Across the nation, healthcare facilities are increasingly integrating Artificial Intelligence to enhance patient care and clinical research. This technology is proving vital in assisting physicians with tasks such as identifying sepsis and conducting neurological studies. As advancements in AI continue to evolve, the applications of this technology within hospitals are expanding significantly. Dr. Akshay Sayal of NBC News provides insights from Cleveland, Ohio, on these developments.

The impact of AI on healthcare nationwide.

A bright, sunlit hospital corridor with large windows flooding the space with warm natural light. In the foreground, a physician in a white coat and a nurse stand side by side, peering at a sleek, wall-mounted touchscreen displaying vivid AI-analyzed medical scans with colorful annotated overlays and predictive health metrics. Their faces show hopeful engagement. In the background, an autonomous smart cart glides quietly down the hall, delivering supplies—symbolizing AI’s seamless support in modern healthcare.

- AI is increasingly aiding doctors in detecting sepsis and conducting neurological research.  
- Healthcare settings across the country are adopting AI for various supportive roles.  
- Innovations in AI are expanding its applications in hospitals and patient care.

As lawmakers return to Washington, D.C. amid the ongoing government shutdown, the situation remains critical. This shutdown, extending for 43 days, marks the longest in U.S. history. A vote on a funding bill could take place as soon as this afternoon; however, division among Democrats complicates efforts. They are demanding an extension of enhanced Affordable Care Act tax credits, a key issue for many. Without progress on this front, healthcare subsidies may expire at the year's end, leading to increased out-of-pocket costs for millions.

In Pennsylvania, attention is also on the state budget, with both chambers of the state legislature reconvening today. A voting session looms for an over $50 billion spending bill, which is now more than four months overdue. Lawmakers are expected to address budget bills in hopes of resolving this stalemate that has delayed funding crucial for counties, schools, nonprofits, and various services.

Meanwhile, in Lancaster County, negotiations continue between a local college and its union, although they're yet to reach an agreement after seven hours of discussions last night. Both parties are set to meet again tomorrow to further their talks.

Weather-wise, the day is starting off cloudy, with the sun reportedly starting to peek through. A warm front is moving through the Susquehanna Valley, promising some partial clearing this afternoon. Currently, temperatures are milder compared to yesterday, with readings at 35 degrees in Lebanon, 41 in York, and 39 in Carlisle. While breezy conditions persist, gusts won't be as intense as they were previously, with daytime highs expected to reach around 52 degrees. Tonight, temperatures will settle around 40, leading into tomorrow's partly sunny forecast with highs in the lower 50s.

On the transportation front, an accident on I-283 southbound in Harrisburg has caused significant delays, leading to approximately a mile-long backup near the airport. Commuters should expect heavy traffic and plan for extra travel time.

In downtown York, preparations are underway for the arrival of the city's Christmas tree, a generous donation from local residents Donald and Sally Reichert. The tree is set to be cut down shortly and is expected to reach its destination by around 9:00 AM today, signaling the approaching holiday season. The weather for this event aligns with a high of 52 degrees, making for a pleasant morning. Looking ahead, a chance of showers is forecasted for Sunday, followed by a cooler trend early next week.

Pennsylvania legislator plans to introduce a bill regulating AI in the healthcare sector.

A brightly lit legislative chamber in the Pennsylvania State Capitol, sunlight streaming through tall windows. A suited state lawmaker stands at a podium draped with the Pennsylvania flag, holding a folder stamped “AI Healthcare Bill.” Behind him, a large digital screen displays a glowing caduceus woven with circuit patterns. In the foreground, a doctor in scrubs watches attentively, symbolizing the new push to regulate AI in healthcare.

Pa. lawmaker to propose bill that regulates AI in healthcare - WGAL

- Pennsylvania lawmaker plans to propose a bill regulating AI in healthcare.  
- Government shutdown continues for 43 days, longest in U.S. history.  
- State legislature nearing a vote on over $50 billion spending bill.

Pennsylvania lawmaker to propose bill that regulates AI in healthcare

IT IS 656. TIME FOR WGAL NEWS EIGHT TO GO. WE’RE ALL HERE TO HELP YOU START YOUR DAY. AND WE DO BEGIN WITH THE ONGOING GOVERNMENT SHUTDOWN AS HOUSE LAWMAKERS ARE MAKING THEIR WAY BACK TO WASHINGTON, D.C., THE GOVERNMENT HAS BEEN SHUT DOWN FOR 43 DAYS, THE LONGEST SHUTDOWN IN AMERICAN HISTORY. THE U.S. HOUSE COULD VOTE AS EARLY AS THIS AFTERNOON ON A FUNDING BILL. DEMOCRATS, THOUGH, ARE SPLIT ON THE BILL IN THE HOUSE BECAUSE THEY SAY IT DOES NOT ADDRESS THEIR TOP DEMAND, WHICH IS AN EXTENSION OF ENHANCED AFFORDABLE CARE ACT TAX CREDITS. SO WITHOUT ANY ACTION ON THAT. SUBSIDIES FOR HEALTH CARE WILL EXPIRE AT THE END OF THE YEAR AND RAISE OUT OF POCKET COST FOR INSURANCE FOR MILLIONS OF PEOPLE. LET’S TALK ABOUT THE STATE BUDGET AS WELL IN HARRISBURG. BOTH CHAMBERS OF THE STATE LEGISLATURE WILL BE BACK IN SESSION TODAY, AS LAWMAKERS ARE NEARING A VOTE ON A SPENDING BILL OF OVER $50 BILLION. THE STATE BUDGET NOW MORE THAN FOUR MONTHS OVERDUE. THIS IS A LIVE LOOK FROM THE STATE CAPITOL IN HARRISBURG, WHERE SENATE LAWMAKERS RETURNED LAST NIGHT FOR COMMITTEE MEETINGS TO ADVANCE BUDGET RELATED BILLS. BOTH CHAMBERS ARE EXPECTED TO TAKE UP BUDGET BILLS TODAY TO TRY TO END THIS IMPASSE, WHICH HAS BEEN HOLDING UP BILLIONS OF DOLLARS IN FUNDING FOR COUNTIES, SCHOOLS, NONPROFITS AND OTHER SERVICES. GOOD MORNING. I’M GABRIEL THOMAS, LIVE HERE AT THE HAT CAMPUS IN LANCASTER COUNTY, AND AFTER SEVEN HOURS OF NEGOTIATION LAST NIGHT, A REPRESENTATIVE FROM THE UNION SAYS THEY HAVEN’T REACHED AN AGREEMENT WITH THE COLLEGE, BUT THEY ARE MOVING IN THE RIGHT DIRECTION. NOW, THE COLLEGE AND THE UNION ARE SUPPOSED TO CONTINUE NEGOTIATIONS TOMORROW AT 2:00, AND WE’LL CONTINUE TO KEEP YOU UPDATED ON WHAT COMES OUT OF THAT. GOOD MORNING. WE’RE TAKING A LIVE LOOK OVER LANCASTER. IT’S A CLOUDY START TO THE DAY, THE SUN JUST PEEKING OVER THE HORIZON. THERE WE HAVE A WARM FRONT TRYING TO MOVE THROUGH THE SUSQUEHANNA VALLEY. SO AS THAT FRONT PASSES, WE SHOULD SEE SOME BREAKS IN THE CLOUDS THIS AFTERNOON. RIGHT NOW, THOUGH, IT IS DRY, IT’S QUIET, AND IT’S NOT AS COLD AS IT WAS YESTERDAY MORNING. 35 LEBANON, 41 DEGREES IN YORK, 39 DEGREES IN CARLISLE. AND WE ALSO DON’T HAVE THE STRONG WINDS THAT WE HAD YESTERDAY. NOW IT WILL STILL BE BREEZY. DON’T GET ME WRONG, I THINK 10 TO 20 MILE PER HOUR WINDS, BUT WE WON’T HAVE THOSE GUSTS UP TO 40MPH AND IT WON’T FEEL LIKE THE 30S. TODAY’S HIGH IS 52 DEGREES. MIX OF CLOUDS AND SUNSHINE. LATER TONIGHT WE DROP DOWN TO 40 WITH PARTIAL CLEARING AND TOMORROW LOOKS PARTLY SUNNY AND BREEZY. SHOULD BE A DRY DAY FOR US WITH HIGHS IN THE LOW 50S. WE’LL SEE ON THE TEN DAY WHEN HIGHS GET INTO THE UPPER 50S COMING UP. GOOD MORNING SUSQUEHANNA VALLEY. WE ARE TRACKING THAT ACCIDENT ON I-283 SOUTHBOUND IN HARRISBURG IN DAUPHIN COUNTY NEAR EXIT ONE, WHICH IS CAUSING A PRETTY DECENT BACKUP THIS MORNING. THAT’S THE MAIN ACCIDENT THAT WE’VE BEEN TRACKING HERE IN THE LAST PROBABLY 15 MINUTES OR SO, AND TAKING A LOOK AT OUR PENNDOT CAMERA IN THAT PARTICULAR SPOT, AGAIN, RIGHT NEAR HARRISBURG INTERNATIONAL AIRPORT, WE ARE SEEING A SIGNIFICANT AMOUNT OF TRAFFIC THAT’S BACKED UP, PROBABLY ABOUT A GOOD MILE OR SO. THEY ARE GETTING AROUND THAT ACCIDENT, ABOUT ONE LANE OF TRAFFIC OR SO, BUT AGAIN, A DECENT BACKUP FOR YOU TO BE AWARE OF THAT IS GOING BACK ALMOST TO THE TWO 8383 INTERCHANGE. SO BE AWARE OF THAT AS YOU HEAD OUT THE DOOR THIS MORNING. GIVE YOURSELF A LITTLE BIT OF EXTRA TIME SO YOU DON’T GET CAUGHT UP IN THAT TRAFFIC. TAKING A LIVE LOOK RIGHT NOW IN CONTINENTAL SQUARE IN DOWNTOWN YORK. THAT IS WHERE THE CITY’S CHRISTMAS TREE WILL BE ARRIVING IN JUST A FEW HOURS. THIS TREE WAS DONATED FROM DONALD AND SALLY REICHERT FROM SPRINGETTSBURY TOWNSHIP. IT’S ACTUALLY GOING TO BE CUT DOWN FROM THEIR PROPERTY IN ABOUT 15 MINUTES, AND THEN IT WILL MAKE THE JOURNEY TO DOWNTOWN YORK. IT SHOULD BE ARRIVING THERE, THE CITY SAYS AROUND 9:00 THIS MORNING. IF YOU HAPPEN TO BE IN THE AREA AND I HAVE TO GET MY CHRISTMAS TREE LIGHTING CEREMONY FORECAST ALL DUSTED OFF FOR YOU, BECAUSE BOY, THAT TIME IS COMING UP THE CORNER FAST. 52 DEGREES IS OUR HIGH TODAY. NOT AS COLD, NOT AS WINDY AS YESTERDAY. STILL A LITTLE BREEZY TOMORROW. EVEN BRISK ON FRIDAY. OUR NEXT CHANCE OF SHOWERS IS SUNDAY, FOLLOWED BY A COOLDOWN EARLY NEXT WEEK. I

Pa. lawmaker to propose bill that regulates AI in healthcare

Director Sonny Taite reveals how HealthX is funding, assessing, and implementing digital and AI solutions throughout New Zealand’s healthcare system.

Te Whatu Ora Health New Zealand has initiated a technology innovation program aimed at delivering digital and AI solutions to healthcare professionals on a monthly basis.

In September, the organization unveiled HealthX, led by Sonny Taite, who serves as Te Whatu Ora's national Chief Information Security Officer (CISO) and is temporarily appointed as the acting director of innovation and AI.

Over the next six months, leading up to February 2026, HealthX will lay out its foundational structure, bringing together a core team along with clinical advisors and frontline champions. The initiative focuses on identifying digital tools designed to relieve workforce strain, improve healthcare accessibility, and boost overall clinical efficiency.

This developmental phase will concentrate on gaining trust and building momentum with healthcare providers while conducting real-world tests of various tools. Following this, HealthX will assess which technologies warrant further development.

HealthX's inaugural activity involves a pilot program featuring AI scribe technology in the emergency department at Hawke’s Bay.

In a conversation with Healthcare IT News, Taite articulated the essential criteria for projects under the HealthX banner:

- Delivering positive impacts on health objectives
- Potential for scalability across multiple locations and regions
- Addressing high-priority areas, including workforce challenges, access disparities, and clinical inefficiencies

"Each project will need tailored support for scaling," he noted. "Our initial project, the AI scribe in the emergency department, is not yet integrated with other systems, which allowed for a rapid rollout."

Budgeting and focus areas

HealthX is leveraging funding from Te Whatu Ora's capability uplift budget. Last year, resources initially designated for data, digital capabilities, and innovations—such as the stalled Hira project—were redirected to support frontline services and stabilize healthcare payrolls.

The program has not established a fixed annual expenditure target. Taite mentioned that the monthly rollout of initiatives naturally limits overall spending in the program’s first year.

As it outlines its future plans, HealthX is also examining potential advancements in cardiology, radiology, and dermatology, as confirmed by Taite.

"We are particularly interested in the development of virtual hospital concepts, including virtual emergency departments, virtual wards, and hospital-at-home models," he added. New Zealand continues to explore and integrate virtual care solutions post-2020 pandemic, most recently launching a 24/7 online general practice service in July to mitigate emergency department strain and trialing a hospital-at-home initiative in Gisborne last year.

AI scribe implementation

Currently, HealthX's primary focus is on the rollout of AI scribes throughout New Zealand’s emergency departments. The Ministry of Health has acquired licenses for approximately 1,000 public emergency department doctors and staff to utilize these AI tools. "Our clinicians have expressed significant interest in AI scribes to help alleviate administrative and documentation burdens," Taite revealed.

In Hawke’s Bay, clinicians reported an average time savings of 11 minutes per consultation, reducing post-shift documentation from 40 minutes to 20 minutes, enhancing the likelihood of staff finishing their shifts on time. "This decrease in cognitive load and burnout is a significant advantage of employing AI scribes," Taite explained.

HealthX anticipates that around 70% of emergency department clinicians nationwide will be utilizing AI scribes by the end of the year.

The National Artificial Intelligence and Algorithm Expert Advisory Group at Te Whatu Ora currently endorses four AI scribe tools for New Zealand's public health system: Heidi, iMedX, T-Pro, and IntelliTek, provided by international vendors. Additionally, several other ambient AI scribe technologies are currently under review, according to Taite.

The direction of Te Whatu Ora's technology innovation division's upcoming digital and AI initiatives.

Natural sunlight streams through floor-to-ceiling windows into a sleek health innovation lab. An adult tech leader in scrubs leans over a large interactive touchscreen table displaying a digital AI roadmap overlaid on a neural-network blueprint. A brass compass and stethoscope rest on the table’s edge. A New Zealand flag hangs on the wall.

What's guiding Te Whatu Ora's tech innovation arm's next digital, AI steps - Healthcare IT News

- Te Whatu Ora launched HealthX to implement digital and AI solutions in healthcare.  
- The program's focus includes easing workforce pressures and improving clinical efficiency.  
- HealthX's first initiative is AI scribes, expected to be used by 70% of EDs.  

Director Sonny Taite lifts the curtain on how HealthX funds, tests, and scales digital and AI tools across New Zealand's health system.

Te Whatu Ora Health New Zealand has launched a technology innovation programme that reportedly aims to roll out digital and AI-driven solutions to clinicians each month.

In September, the organisation announced its newest programme, HealthX. At its helm is Sonny Taite, Te Whatu Ora's national CISO, who has been seconded as acting director of innovation and AI.

Over the six months to February 2026, the programme will establish its structure – comprising a core team, a group of clinical advisors, and frontline clinical champions – and explore digital tools aimed at easing workforce pressures, improving access to care, and increasing clinical efficiency.

This period will focus on building momentum and trust with clinicians while testing tools in real settings. HealthX will then prioritise which technologies to take forward after this initial phase.

Minimum criteria

HealthX's first major activity to date is an AI scribe pilot in the Hawke’s Bay emergency department.

In an interview with Healthcare IT News, Taite outlined the minimum criteria for a HealthX project:

positively impacting health targets;

scaling to multiple locations and regions; and

focused on high-priority areas, such as workforce pressures, access inequities, and clinical inefficiencies.

"Each initiative will require different support to scale," he said. "Our first initiative, AI scribe in the ED, is not integrated into other systems, which helped us deploy quickly."

Lean funding, target areas

According to Taite, HealthX taps funding from Te Whatu Ora's capability uplift budget. Last year, funding previously allocated for data and digital capability and innovations, including the stalled Hira project, was redirected to frontline services and healthcare payroll stabilisation.

The tech innovation programme has not set an annual target spend. Taite said the monthly cadence of initiatives creates a "natural constraint" that limits overall expenditure in the first year.

As it plans out its upcoming pipeline, HealthX is also assessing opportunities in cardiology, radiology, and dermatology, Taite confirmed.

"The concept of a virtual hospital, including models such as virtual ED, virtual wards, and hospital-at-home care, is an area we're watching closely," he added. New Zealand has continued to test and adopt virtual care models in the years following the 2020 global pandemic. Most recently, in July, it launched a 24/7 online general practice service to ease pressure on EDs, and Te Whatu Ora in Gisborne trialled a hospital-at-home concept last year.

On AI scribes

For now, HealthX is focused on implementing AI scribes across New Zealand EDs. The Ministry of Health has purchased licenses for the use of AI scribes by about 1,000 public ED doctors and staff. "There's been a lot of demand from our own clinicians to bring in AI scribes to help reduce clinical administration and documentation workloads," Taite shared.

In Hawke’s Bay, clinicians reported saving an average of 11 minutes per consultation, and after-shift documentation time fell from 40 minutes to 20 minutes, enabling staff to finish on time. "That reduction in cognitive load and burnout is a real benefit of AI scribes," Taite added.

HealthX expects around 70% of ED clinicians nationwide to be using AI scribes by year-end.

The National Artificial Intelligence and Algorithm Expert Advisory Group at Te Whatu Ora currently endorses four AI scribes for use in New Zealand's public health system, namely Heidi, iMedX, T-Pro, and IntelliTek, all from international vendors. A number of other ambient AI scribe tools are currently under review, Taite said.

What's guiding Te Whatu Ora's tech innovation arm's next digital, AI steps

Akram Hossain, MBA, A-CSPO®, CBAP

The integration of artificial intelligence in healthcare is entering a transformative stage. Where once the focus was primarily on research pilots and isolated experiments, stakeholders such as hospitals, medical device manufacturers, insurance companies, and digital health startups are now shifting towards ownership of AI technology. Instead of merely testing algorithms, these entities are actively developing, purchasing, and managing AI solutions with a heightened sense of responsibility. This evolution has important implications for regulatory compliance, patient outcomes, and the adaptation of the healthcare system to accommodate algorithms that function as products in their own right.

With AI being treated as a standalone product, the role of the product owner becomes increasingly crucial. Within agile or scrum environments, product owners are responsible for feature prioritization, managing backlogs, resolving trade-offs, and ensuring alignment of development efforts with business goals. In larger corporations, there may be various product owners focused on different types of products, including data-driven and technical offerings. In a startup context, however, one product owner often takes on multiple roles, encompassing responsibilities such as product management, business analysis, or even acting as scrum master. Through my experiences in both environments, I have witnessed significant variations in product ownership, each presenting its own set of challenges influenced by stakeholders, regulatory demands, scope, and investment levels.

In the realm of healthcare AI, product owners encounter distinct hurdles. They must guarantee access to clean data for training purposes, navigate vendor selection, balance clinical and commercial metrics, and continuously refine product performance. Beyond functionality, product owners are accountable for ensuring seamless integration into clinical workflows, scalability, and adaptability as data continues to evolve.

From my professional experiences with both clinical and operational stakeholders, I have observed that poorly sequenced features during the implementation of electronic health records (EHR), electronic practice management (EPM), or enterprise resource planning (ERP) systems can adversely affect clinical practices and patient outcomes. Healthcare AI products must navigate a complex web of regulatory and governance standards, such as HIPAA and FDA approval. It is crucial for product owners to meet business demands while prioritizing safety, validation, and compliance during early discovery phases, requirement gathering, and backlog refinement.

Regulatory Aspects of AI in Medical Devices

Compared to the drug development process, which frequently utilizes AI during early discovery, medical devices are confronted with immediate regulatory challenges. The FDA has provided guidance on treating software, including AI tools, as medical devices. A significant challenge arises from the fact that, unlike traditional medical products, an AI solution can evolve post-deployment. Regulators must determine whether updates necessitate re-approval, how to monitor ongoing safety, and what standards of transparency should apply.

Incidents have already highlighted these complexities. For instance, the FDA approved IDx-DR in 2021—an AI system for autonomously detecting diabetic retinopathy. While this was a groundbreaking step, it also underscored the difficulties in establishing accountability when an AI operates independently. Recently, Epic incorporated generative AI within its EHR to create clinical notes. This innovation led hospitals to assemble internal oversight boards due to the still-unfolding regulatory framework. This integration raises questions about the degree of trust that healthcare professionals can place in AI-generated outputs, given the implications for patient care.

As AI-enabled medical devices continue to evolve at a rapid pace, it is imperative for MedTech companies to formulate specialized teams dedicated to ensuring regulatory compliance for their products. Collaboration between compliance and product teams can facilitate adherence to both regulatory and quality standards. From my observations, successful teams implement formal change management processes and are adept at pivoting when circumstances shift unexpectedly. This approach acts as a safeguard against regulatory scrutiny and auditing.

Finding the Right Balance Between Innovation and Equity

AI technologies hold remarkable promise for expediting diagnostics, personalizing treatments, and expanding access to care. However, the inherent opacity of some algorithms can inadvertently perpetuate disparities, as demonstrated by risk assessment tools that fail to accurately reflect the health needs of minority populations due to biased data. The scaling of these AI products magnifies their potential impact.

Consequently, strong governance and ownership models are essential. Collaborations among product owners, compliance teams, and regulators are necessary to promote fairness and transparency without obstructing innovation. Many hospitals are now establishing AI governance boards to evaluate prospective products before adoption and monitor their usage and effectiveness post-implementation.

Product owners can enhance the sustainability of AI features by carefully prioritizing them while also managing clinical risks. Establishing frameworks that implement stricter oversight for features directly affecting clinical outcomes, while applying lighter scrutiny for operational enhancements, can be effective. Maintaining transparency with clinical stakeholders about how algorithms function and the data sets utilized is vital for fostering trust, while communication should avoid overwhelming technical jargon to keep stakeholders engaged.

Currently, major technology firms are establishing benchmarks in the clinical and MedTech AI sectors, with innovative startups forming strategic partnerships with healthcare and pharmaceutical giants. To achieve scalability in this dynamic environment, it is crucial for these companies to adopt practices and frameworks from regulated industries. Success hinges not solely on AI advancements but equally on a commitment to governance, compliance measures, and accountability. For product leaders, this represents a new era of innovation within the product lifecycle, marked by a willingness to embrace uncertainty and recognize AI as a continuously evolving product rather than just an additional feature.

About Akram Hossain

Md Akram Hossain is a seasoned leader in business analysis and product management, boasting over nine years of experience directing enterprise-wide digital transformation initiatives within healthcare and technology sectors. As an MBA holder, Advanced Certified Scrum Product Owner, and Certified Business Analysis Professional, Akram specializes in EPM, ERP, and EHR systems, with expertise across platforms such as Anaplan, Workday, SAP, and Epic. He has a proven history of defining product strategies and roadmaps, leveraging design thinking methodologies, enhancing workflows, and driving operational efficiency through Agile and Scrum practices.

The Emergence of AI Product Owners: Managing Responsibility in Healthcare Technology

A midshot of a professional AI product owner standing in a sunlit hospital office, reviewing a tablet that displays dynamic healthcare dashboards—patient vitals, treatment pathways, and a subtle circuit-brain icon woven into the data streams. Warm natural light from a large window highlights her focused expression. On the sleek desk in front of her, a stethoscope and medical clipboard sit beside a small digital balance scale overlay, symbolizing accountability. In the softly blurred background, clinical monitors and a row of medical file cabinets evoke a healthcare setting without artificial blue AI tones.

The Rise of the AI Product Owner: Navigating Accountability in Healthcare Technology - HIT Consultant

- AI in healthcare transitions from experimentation to ownership, impacting regulation and patient outcomes.  
- Product owners must manage datasets, compliance, and integration into clinical workflows effectively.  
- Governance is crucial; AI tools can innovate but may exacerbate existing inequities in healthcare.  

Akram Hossain, MBA, A-CSPO®, CBAP

Artificial intelligence in healthcare is moving into a new phase. What was once dominated by research pilots and one-off experiments is now becoming a matter of ownership. Hospitals, medical device firms, insurers, and digital health startups are no longer just testing algorithms. They are building, buying, and maintaining AI products with real accountability. This shift has significant consequences for regulation and for patient outcomes, and it raises questions about how the healthcare system adapts to a landscape where algorithms are as much products as medical devices.

When AI becomes a product, the role of the product owner becomes central. In agile or scrum teams, product owners sequence features, prioritize backlogs, handle tradeoffs, and align development with business objectives. In larger organizations, there may be multiple product owners specializing in data products, business products, or technical products. In startups, however, the product owner often wears multiple hats, acting as product manager, business analyst, or even scrum master. I have personally worked in both these settings and have seen how product ownership can vary significantly, with unique challenges for each based on stakeholders, regulation, scope, and dollar investments involved.

For AI in healthcare, product owners face unique challenges. They must ensure clean datasets for training, manage vendor selections, balance commercial and clinical metrics, and constantly iterate on performance. Beyond functionality, they are accountable for how the product integrates into clinical workflows, whether it scales, and how it adapts as data evolves.

What I have seen in my career while working with both operational and clinical stakeholders is that errors in sequencing features when you are implementing a new EHR, EPM, or ERP system in healthcare can have direct clinical and patient outcome consequences. In comparison to consumer AI products, healthcare AI products must also adhere to various regulatory and governance standards like HIPAA, FDA clearance, etc,. and ensure that the iterations in the models don’t break or overlook any of those standards. So, it’s important for product owners to balance the demand of the business while still ensuring safety, validation, and compliance checks early on in discovery, requirement elicitation, and backlog refinement sessions.

AI in Medical Devices and Regulation

Unlike drug R&D, which often relies on AI in early discovery, medical devices present a more immediate set of regulatory challenges. The FDA has issued guidance on software as a medical device, including AI-based tools. The challenge is that, unlike a pill or implant, an AI product may evolve after it is deployed. Regulators must decide whether updates require re-approval, how to evaluate ongoing safety, and what transparency standards should apply.

Examples already illustrate these tensions. In 2021, the FDA cleared IDx-DR, an AI tool that autonomously detects diabetic retinopathy. It was groundbreaking but also exposed gaps in defining accountability when AI acts independently. More recently, Epic integrated generative AI into its EHR system to draft clinical notes, prompting hospitals to form internal oversight boards since regulatory frameworks are still emerging. While this is an exciting integration for sure, especially considering the volumes in busy care-site settings, it still begs the question of how much trust physicians or clinicians in inpatient or outpatient settings can have in the quality of the EHR AI outputs, considering patient outcomes are at stake.

We all see that AI-enabled medical devices evolve continuously. It’s more important than ever for Medtech organizations to establish separate teams to ensure regulatory readiness of the products they are building. They can have compliance and product teams work together to ensure both regulatory and quality adherence. From my experience, I have seen successful teams enable formal change control processes, as well as know when to and how to pivot if things do not go as planned. This can help Medtech organizations have an additional shield against regulation and auditing authorities.

Balancing Innovation, Equity, and Accountability

AI tools have the potential to accelerate diagnosis, personalize treatment, and make care more accessible. But opaque algorithms can also reinforce inequities, as seen in risk scoring systems that underestimate the health needs of Black patients due to biased cost data. When these models scale as products, their impact multiplies.

That is why governance and ownership structures are critical. Product owners, compliance teams, and regulators must work together to ensure fairness and transparency without stifling innovation. Hospitals are already setting up AI governance boards to evaluate products before adoption and monitor their performance after deployment.

Product Owners can establish sustainability for AI features by prioritizing those alongside managing clinical risk. There can be frameworks established where features involving clinical outcomes face tighter scrutiny before approval, while those for enhancing operational workflow can have lighter checks in place. Transparency with clinical stakeholders to explain how algorithms work, and what datasets are being used is important to gain trust while also ensuring abstraction in conversations so that the stakeholders are not lost in technical details.

Today, big tech firms are setting standards and startups are driving innovation in the clinical and Medtech AI space while strategically partnering with Healthcare and Pharma giants. To ensure scalability in this area, these firms must embed practices and frameworks from regulated industries because success depends not just on AI innovation but on balancing it with governance, compliance guardrails, and accountability. For product leaders, it means entering a new phase of innovation in the product lifecycle, embracing uncertainty, and treating AI as a living and evolving product, not just another feature.

About Akram Hossain

Md Akram Hossain is an accomplished business analysis and product management leader with over nine years of experience leading enterprise-wide digital implementations across healthcare and technology. An MBA, Advanced Certified Scrum Product Owner, and Certified Business Analysis Professional, Akram specializes in EPM, ERP, and EHR systems, with deep expertise in platforms like Anaplan, Workday, SAP, and Epic. Akram has a proven track record of defining product strategy and roadmaps using design thinking concepts, optimizing workflows, and driving operational efficiency through Agile and Scrum methodologies.

The Rise of the AI Product Owner: Navigating Accountability in Healthcare Technology

A company's approach to adopting AI technologies can greatly impact its competitive standing. Chief Information Officers (CIOs) face the challenge of swiftly deploying AI from various providers while also grasping how users utilize these technologies to improve their experiences. A crucial part of this evolution involves designing interactions between AI agents (referred to as agent-to-agent or A2A interactions), which is becoming a notable trend as highlighted by recent announcements from leading tech firms.

Here’s an overview of significant developments and recommendations for healthcare CIOs to refine their strategies.

Google

Google Cloud has introduced Gemini Enterprise, a platform intended to consolidate all AI functionalities and simplify the creation of AI agents. This new offering, previously known as Agentspace, features a "no code" builder that allows users to develop AI agents without programming expertise. Additionally, the platform comes with a selection of pre-built Google AI agents and the ability to connect with various third-party applications.

Amazon

Amazon's Bedrock AgentCore is designed with a focus on foundational operations and security for enterprises. It provides a robust infrastructure to securely manage and operate production AI agents at scale.

Key features of the AgentCore platform include:

- **AgentCore Identity**: This feature enables agents to perform actions on behalf of users across different systems.
- **AgentCore Runtime**: A serverless environment that offers low-latency capabilities.
- **AgentCore Gateway**: Secure API access for AI agents is provided through this gateway.

Salesforce

Salesforce is integrating its products and partnerships into the Agentforce 360 initiative, which aims to showcase its ability to connect people, data, and systems through an intelligent and reliable framework.

The core elements of Agentforce 360 consist of:

- **Agentforce Builder**: A low-code/no-code platform for building and testing AI agents within a unified interface.
- **Agent Script**: A scripting tool designed to influence the behavior of AI agents, allowing for more responsive interactions based on specific scenarios.
- **Agentforce Voice**: Customized conversational voice agents that are designed for brand-specific interactions and integrate seamlessly with contact center systems.

CIO’s Perspective

Healthcare CIOs are looking for platforms that can manage various AI agent functionalities effectively. One application of A2A interactions could be in automating several hospital operations, including contact centers, physician workflows, and verifying patient insurance eligibility. This A2A process can streamline identifying patient eligibility, initiating appointment scheduling based on the patient's convenience, and producing relevant information summaries for physicians ahead of patient visits.

A2A automation could rely on Amazon's AgentCore, which provides a secure connection to numerous data sources and initiates API calls. The Salesforce agent can engage with patients, gather demographic and insurance details, and confirm service eligibility. Upon verification, this agent can set up appointments and interact with the Google Gemini agent, which access the EHR system to compile a patient’s medical history and prior appointments for the physician.

This example illustrates how integrating AI agents with various platforms can simplify intricate tasks.

Each AI platform strives to become the primary coordinator for advancing A2A automation across different systems. CIOs require secure and adaptable platforms that ensure seamless integration. The outcome of whether A2A agents will replace human roles in routine tasks, thereby allowing staff to concentrate on more valuable responsibilities, remains to be seen.

The Transformation of Healthcare IT by A2A AI Agents

Sunlit hospital command center with large windows casting warm daylight over a team of doctors and IT specialists gathered around sleek tablets; small, friendly wheeled AI assistant robots physically link polished server racks to patient monitors with glowing data strands, illustrating A2A AI agents seamlessly transforming healthcare IT.

How A2A AI Agents Are Transforming Healthcare IT - Forbes

- Google Cloud launched Gemini Enterprise to simplify AI agent creation without coding skills.  
- Amazon's Bedrock AgentCore focuses on secure infrastructure for managing AI agents at scale.  
- Salesforce's Agentforce 360 integrates people and systems through low-code environments and scripting languages.

the logo of AI Agent is displayed on a smartphone screen VCG via Getty Images

An organization’s AI adoption strategy will define its competitive edge. CIOs must manage the fast rollout of AI from multiple vendors and understand how users leverage it to enhance experiences. The next step is designing agent-to-agent (A2A) interactions—automating and connecting multiple AI agents—a trend reflected in recent major tech company announcements.

Below are key announcements and how healthcare CIOs should evaluate their strategy.

Google

Google Cloud has launched Gemini Enterprise. Google positions this platform as one that unifies all AI capabilities and provides ease in creating AI agents. The Gemini enterprise platform offers AI agent creation with a "no code" workbench, formerly called Agentspace, which supports users in developing AI agents without requiring coding skills. The platform also includes pre-built Google AI agents and connectivity to various third-party applications.

Amazon

Amazon’s Bedrock AgentCore serves as an enterprise platform focused on foundational operations and security. AgentCore is designed to provide the essential infrastructure for running and managing production AI agents securely and at scale.

The key components of the platform are:

AgentCore Identity enables agents to act on behalf of users across multiple systems.

AgentCore Runtime is a serverless, low-latency environment.

AgentCore Gateway provides secure API access for agents.

Salesforce

The company is aligning its products, platform, and partnerships under Agentforce 360, aiming to show customers that Salesforce connects people, data, and systems through an intelligent and trusted framework.

The main components of Agentforce 360 are:

Agentforce Builder is a low-code/no-code environment that enables the building and testing of agents within a single interface.

is a low-code/no-code environment that enables the building and testing of agents within a single interface. Agent Script is a scripting language designed to prompt the AI agent’s behavior, enabling more effective responses to if/then scenarios.

is a scripting language designed to prompt the AI agent’s behavior, enabling more effective responses to if/then scenarios. Agentforce Voice delivers conversational voice agents tailored to a brand and integrates with contact-center platforms.

CIO’s Point Of View

Healthcare CIOs seek a platform that enables them to manage all AI agent capabilities. One way to design an agent-to-agent (A2A) interaction is by automating hospital functions such as the contact center, physician workflows, and patient insurance eligibility checks. This A2A workflow identifies patient eligibility, triggers automated appointment scheduling based on patient convenience, and generates a summary of relevant information for physicians ahead of the visit.

A2A automation begins with Amazon AgentCore’s infrastructure, which powers complex automation by securely connecting to various data sources and triggering API actions. The Salesforce agent integrates with the contact center, interacts with the patient, collects demographic and insurance data, and determines eligibility for service. After verifying eligibility, the Salesforce agent schedules the appointment and contacts the Google Gemini agent, which makes an API call to the EHR system and compiles a summary of the patient’s medical history and past appointments for the physician.

This scenario shows how AI agents and platform integrations can streamline complex tasks.

Every AI platform competes to be the central coordinator for driving A2A automation across systems. CIOs demand secure, flexible platforms that integrate seamlessly. Whether A2A agents will replace humans in routine tasks and enable them to focus on higher-value work remains uncertain.

AI in healthcare News