Health IT leaders across the country are sounding the alarm on a common theme: the pace of AI adoption is outrunning the governance, cybersecurity and workforce readiness needed to deploy it safely.
From CIOs and CISOs to chief AI officers and digital innovation leads, executives at organizations ranging from Stanford Health Care to UPMC to Memorial Sloan Kettering Cancer Center point to a widening gap between how fast AI capabilities are entering clinical workflows and how prepared health systems are to manage them.
Becker’s Healthcare asked healthcare IT, digital and marketing leaders to identify the most dangerous trend in health IT today. Their responses, featured below, surface recurring concerns: AI arriving through EHR platform updates rather than formal procurement review, automation bias eroding clinical judgment, expanding cyberattack surfaces, and the risk of mistaking technology deployment for true transformation. Here’s what they had to say.
Leaders quoted in this article are speaking at the Becker’s 11th Annual IT + Revenue Cycle Conference Sept. 14-17, 2026 in Chicago. Limited spots remain – register here!
Chris Carmody. CIO of UPMC (Philadelphia): The most dangerous trend in health IT is treating AI as a collection of projects rather than a strategic capability. Across the health IT and broader IT industries, we are seeing an explosion of AI use cases. While experimentation is important, it can be challenging to achieve meaningful organizational impact. At UPMC, we’re taking a deliberate approach. We’re building the foundation needed to scale AI responsibly by investing in leadership, governance, and enterprise adoption. Our vision is to create an environment where AI becomes part of how our teams work every day to improve care, reduce friction, and enhance the caregiver, patient, and member experiences. Success won’t come from having the most AI projects; it will come from executing a clear strategy for how AI can improve the way healthcare is delivered.
Judd Hollander, MD. Senior Vice President for Health Delivery Innovation and Chief Virtual Care Officer, Jefferson Health (Philadelphia): The AI arms race is the most dangerous trend. I fear that health systems will race to utilize AI to decrease denials and improve pre-authorization while payers will race to utilize AI to maintain denials and limit pre-authorization. Thus, we will all drive up healthcare costs reaching the exact same status quo we currently have with respect to details and pre-authorization. There may be some short-term winners and losers but the problem is not efficiency of these systems (which AI can help) but rather how these paradigms are leveraged to prevent payment for healthcare. We cannot simply make poorly designed systems more efficient. We must re-design the system.
Jeff Gautney. Senior Vice President and CIO at Rush Health (Chicago): The most dangerous trend in health IT is definitely not fully understanding and preparing for the impact on required cybersecurity capabilities of the Mythos/Glasswing developments this spring. This impacts everything – how we patch systems, what emerging attack vectors exist, how we think about our software partners, etc. Health systems need to consider who they are working with and how they are changing their development practices to take into account the impact of these capabilities.
Margaret Lozovatsky, MD. Chief Digital and Information Officer of Premier Health (Dayton, Ohio): The greatest threat in health is not the technology itself, it’s the temptation to move faster than our ability to govern, secure, and responsibly integrate it into care delivery. Innovation only creates value when it strengthens trust, improves patient outcomes, and enables our caregivers. Too often, organizations look to technology to solve challenges that are fundamentally rooted in people and process. Sustainable digital transformation requires equal focus on change management, workflow redesign, and workforce adoption because technology only succeeds when the people and processes around it evolve as well.
Dennis Leber, PhD. Senior Director and CISO at Erlanger Health (Chattanooga, Tenn.): In my view, the most dangerous trend in health IT is our rapidly increasing digital dependency without an equivalent investment in resilience. We are concentrating critical clinical workflows in interconnected platforms and third parties, creating the potential for one vendor failure or compromise to cascade across an entire healthcare ecosystem. At the same time, AI is giving adversaries greater speed, scale, and sophistication. As a healthcare CISO, my greatest concern is not simply the loss of data — it is the loss of operational capability. When technology fails, care can be delayed, clinical decisions are disrupted, and patient safety is placed at risk. Innovation must therefore be matched by tested recovery, dependable downtime procedures, accountable vendors, and the ability to continue delivering safe care when — not if — technology is disrupted.
Manuel Rodriguez. Chief Marketing, Experience and Consumer Officer at UCHealth (Denver): The most dangerous trend in health IT is allowing the pace of technology to outpace the needs of the people we’re trying to serve.
AI and other emerging technologies have extraordinary potential to transform healthcare, but there’s a risk that we begin pursuing innovation for the sake of innovation, rather than focusing on practical solutions to the very real problems patients and caregivers face every day.
The goal shouldn’t be to deploy the newest technology simply because we can. It should be to solve problems: make it easier for patients to access care, reduce friction, give caregivers time back, simplify processes and create a more connected and personalized experience.
For me, the measure of successful health IT isn’t how advanced the technology is. It’s whether patients and caregivers have a better experience because of it.
Melissa W. Sousa. Corporate Director of Data and AI Strategy at Emory Healthcare (Atlanta): The most dangerous trend in health IT isn’t AI itself. It’s the growing risk that we become overly dependent on it. When clinicians begin to trust AI recommendations without sufficient scrutiny, automation bias and confirmation bias can erode independent judgment and make it harder to detect errors. Most organizations focus on keeping humans in the loop, but we should also be thinking about how to intentionally keep some humans out of the loop often enough to preserve the skills needed to operate without AI. Healthcare must remain safe and resilient during outages, cyberattacks, and system failures. If clinicians no longer know how to perform critical tasks without AI assistance, we’ve created a new patient safety risk. The goal isn’t just to oversee AI. It’s to ensure our workforce retains the expertise, confidence, and critical thinking needed to challenge AI, recognize when it’s wrong, and continue delivering safe care when the technology isn’t available.
Omar Sangurima. Head of Program Management and Cyber Third-Party Risk at Memorial Sloan Kettering Cancer Center (New York City): The most dangerous trend in health IT is that artificial intelligence has stopped arriving through the front door.
Every governance apparatus a health system has built is designed to catch a purchase. Procurement review, security assessment, clinical validation, legal negotiation: all of it fires when someone decides to buy something. That model is now obsolete. The dominant EHR platforms are shipping AI directly into products health systems already run, with one vendor announcing more than 150 embedded AI features and another making ambient documentation available to its entire customer base at no additional cost. Those capabilities do not arrive as a purchase. They arrive as a release note.
Nothing in the standard governance stack fires on a release note. No purchase order, no security review, no validation study, no risk assessment. The capability is simply present inside a system that was approved years ago, under a contract negotiated for a product that no longer exists in the same form.
This is a seam failure, and seams are where accountability goes undefined. Security assumes clinical operations validated it. Clinical operations assumes IT reviewed it. IT assumes it came with the platform. Risk management hears about it after the event.
The patient absorbs the consequence, and the patient cannot opt out mid-treatment.
The AI I worry about in a health system is not the model that went through committee. It is the model that never needed to be.
John Gachago. Vice President of Digital Innovation at Parrish Healthcare (Titusville, Fla.): The most dangerous trend in health IT is the pursuit of AI at the speed of innovation rather than the speed of adoption. Technology can be implemented quickly, but trust, governance, and workflow transformation take time. Organizations that prioritize responsible adoption over rapid deployment will ultimately deliver the greatest value to patients, clinicians, and communities.
Nathan Winn. Vice President of AI Discovery and Innovation at Baylor Scott & White Health (Dallas): Honestly – I think it is adoption. Everyone is going to supercharge their application, tools, or platforms with AI features. There is a natural tendency that engineers and analysts have to adopt tools coming from well-intentioned places. The discipline of having a business case and truly understanding the technology setup (zero data retention, MCP, etc.) is going to require every analyst and engineer to be AI-savvy and examine solutions via the lens of technology, business, and security.
Carter Smith. Managing Director of Cone Health Ventures (Greensboro, N.C.): The most dangerous trend isn’t a technology, it’s the widening gap between how fast we’re deploying AI and how slowly we’re building the muscle to govern it.
Most health systems can tell you how many AI tools they’ve launched. Far fewer can tell you which ones are still performing the way they did on day one. Models drift, patient populations change, documentation patterns shift, but the monitoring to catch that rarely ships with the pilot.
The second-order risk is automation bias. Once a tool is embedded in a workflow, people stop questioning it. That’s how quiet degradation in model performance becomes a patient safety or compliance problem nobody sees coming.
The answer isn’t to slow down. It’s to insist that every deployment comes with a named owner, a performance baseline, and a kill switch. If a tool can’t clear that bar, it isn’t ready for production.
Karl Hightower. Vice President and Chief Data and Analytics Officer, Stanford (Calif.) Health Care and School of Medicine: AI for the sake of AI without articulation of true value creation.
Charity Dorazio. CIO of Adventist HealthCare (Gaithersburg, Md.): One of the most dangerous trends in Health IT today is the invisible integration of AI into clinical workflows. This can occur when vendors enable new AI features without informing customers or when staff adopt AI tools independently. AI that is not properly evaluated, monitored, and governed can create significant risks, including data exposure, gaps in oversight, and the inability to implement effective monitoring and control processes.
Bob Berbeco. CIO of Mahaska Health (Oskaloosa, Iowa): The most dangerous trend in healthcare IT is the rush to layer more technology, especially AI, into workflows and data foundations that are not ready for it. Organizations that chase innovation without first addressing data quality, interoperability, cybersecurity, governance, and workflow design don’t create value faster. They create complexity and additional risk at an accelerated rate.
AI makes this risk especially acute. Once it’s embedded in a trusted clinical workflow, people may give its recommendations more credibility than earned. That’s what concerns me, not whether healthcare adopts AI fast enough, but whether we hold onto human judgment, accountability, and trust as we do it.
Andie Romaniuk. Senior Director of Information Management Applications at Ann & Robert H. Lurie Children’s Hospital (Chicago): The most dangerous trend in health IT is treating technology as the solution. Technology is an enabler. Sustainable change happens when people, processes, and ownership come together to create measurable value. We’ve reached a point where deploying technology is often the easy part. The harder leadership challenge is rethinking how work gets done, eliminating unnecessary complexity, and creating the operational commitment needed to drive lasting change.
As organizations race to adopt AI, I believe we’re often asking the wrong question. Instead of asking, “How do we implement AI?” we should be asking, “What work no longer needs to exist?” The organizations that will lead the future of healthcare won’t be those with the most technology. They will be the ones that use technology to empower teams, reduce friction, create capacity, and improve outcomes for patients, families, caregivers and the organization alike. Transformation doesn’t happen when technology goes live. It happens when people see themselves in the solution, embrace new ways of working, and experience the value firsthand. Ultimately, the goal isn’t to implement more technology. The goal is to create more time for care.
Christine Baran. Regional IT Director, MaineHealth (Westbrook): The most dangerous trend in health IT is not artificial intelligence itself, but the inconsistency of its adoption. Today, one provider may use AI to enhance clinical decision-making while another may not use it at all, despite having access to the same technology. Unlike the move to electronic health records, which established a common standard of practice, AI remains largely optional and often exists outside formal clinical workflows. As a result, healthcare risks creating significant variability in care delivery before clear best practices, governance models, and standards are established. The challenge is not whether AI will become part of healthcare, but how quickly we can ensure it is used safely, consistently, and equitably.
Shannon Becker. Vice President, of IT – Clinical & Revenue Cycle Systems at Sentara (Virginia Beach, Va.): The danger is not AI itself. The danger is believing technology can compensate for fragmented care models, inconsistent workflows, and a lack of operational discipline.
Healthcare organizations are rapidly layering AI, automation, and point solutions onto environments already burdened by excessive customization and unnecessary complexity. When we automate a broken process, we do not fix it; we allow the problem to move faster, scale further, and become harder to see.
That creates real consequences. Clinicians become overwhelmed by technology that was intended to help them. Patients fall through the gaps between disconnected teams. Organizations struggle to adopt meaningful innovation because every new capability must navigate years of accumulated variation. And as financial, access, and staffing pressures intensify, we lose the capacity to respond quickly.
Our responsibility as health IT leaders is not simply to deliver what is requested. It is to help determine whether we are solving the right problem. That means simplifying before automating, standardizing wherever possible, designing care around teams rather than individual providers, and ensuring technology measurably improves access, safety, efficiency, and the human experience of care.
AI will amplify whatever foundation we give it. If the foundation is fragmented, AI will accelerate fragmentation. If the foundation is thoughtful, standardized, and clinically grounded, it can genuinely transform healthcare.
Garrett Olin. CIO of Shasta Community Health Center (Redding, Calif.): I think the most dangerous trend in HIT is the speed and growth of AI at the potential expense of cybersecurity. The industry is definitely a target for ransomware or other data breaches, and as the speed of use and growth of AI, organizations may surpass their cybersecurity capabilities in the pursuit of AI.
Susan Goodson. Senior Vice President and Chief Digital Information Officer, Lurie Children’s (Chicago): The most dangerous trend in Health IT is taking our eye off the ball. I see cyber risk rising, AI accelerating expectations, and tighter margins leaving little room for wasted effort. There is so much temptation to chase every new capability or respond to every urgent demand. The most successful organizations are focused on the fundamentals: resilient operations, secure and trustworthy data, strong governance, and deploying technology that has impact for our patients and our employees.
Gregory Bryant. Director, North Texas Medical Center (Gainesville): I think the dependence on AI could be both the most dangerous and a useful tool. Several health systems and health system vendors have gone all-in with AI. But we have to consider whether the governance is in place and what the true value-add (beyond just financial metrics) is for the organization. I do think AI is a game changer; I just feel we are moving too quickly in some areas.
Nonku Kunene Adumetey. Director of Population Health Data Analytics at ChristianaCare Health System (Newark, Del.): The most dangerous trend in health IT is the rapid adoption of AI without equally strong governance, transparency and accountability. When organizations implement tools without validating the data, monitoring for bias or integrating insights into clinical and operational workflows, they risk scaling inaccurate decisions rather than improving care. The real opportunity is not simply to adopt more technology, but to ensure it produces trusted, actionable insights that improve outcomes, reduce disparities and support the people delivering care.
Ryan Kenney. Vice President of Strategy Enablement at Nebraska Medicine (Omaha): The most dangerous trend is mistaking technology adoption for transformation. AI and automation are advancing faster than most health systems are redesigning the work around them. If we simply add new technology to old workflows, we risk creating more complexity instead of more capacity. The winners will be the organizations that use technology as a catalyst to fundamentally rethink how care and work are delivered.
Andrew Cooper. Chief Digital and Access Officer at NCH (Naples, Fla.): The most dangerous trend is complexity disguised as innovation. We’re going to see an explosion of AI and digital tools, but if we’re not disciplined about how we deploy them, we’ll simply create more noise for clinicians and patients. The technology must make healthcare simpler, not add another layer of complexity. And the infrastructure and process must be in place to support the technology.
Neil Bahroos. Former Chief Research Informatics Officer: The most dangerous trend in health IT is designing and deploying technology for the bedside without truly building it around the bedside team. We risk drowning clinicians in high-tech solutions that add administrative noise rather than relieving cognitive burden. When AI and digital tools are rolled out as top-down compliance measures rather than supportive team-enablers, they accelerate clinician burnout and drive talent away. The health systems that will win are those leveraging tech not to replace or micromanage bedside staff, but to automate operational friction — giving nurses, doctors, and care teams time back for meaningful patient care.
Artimisha Curl. Director of Inclusion, Diversity, Equity & Belonging at El Camino Health Mountain View and Los Gatos (Calif.): For me, the most dangerous trend in health IT is not the technology itself. It is how quickly we are moving to adopt new technology without always slowing down long enough to ask who it is actually serving, who may be left out, and what inequities we may be unintentionally carrying forward.
We have to remember that technology is built from data, and data is built from people and systems. If those systems have historically had gaps, bias, or inequities in them, technology can absolutely reproduce those same issues, just at a much larger scale.
That is what concerns me most.
We can have the most advanced AI, predictive analytics, digital tools, and automation in the world, but if we are not looking at those tools through an equity lens, we can actually create greater barriers for the very communities we are trying to serve.
For me, the questions have to remain very human: Who benefits from this? Who could be harmed? Who is missing from the data? Who was not at the table when this was designed?
I believe innovation and equity have to move together. We cannot automate our way out of inequity if inequity is embedded in what we are automating.
At the end of the day, health IT should not just make healthcare faster or more efficient. It should help us make healthcare more accessible, more equitable, and ultimately more human.
Drew Smith. Chief Data and AI Officer at ChristianaCare Health System (Newark, Del.): Interesting question for sure and a lot of possible choices. And truthfully, I could have a different answer on a given day depend on what’s in focus in the organization, or developing in the tech world.
Although it’s been [more than] a week since UGM, my current answer would center around the volume and generally high quality of AI solutions native to the EMR. And the trend I’d call out is the trend to “turn it on first” and sort out the expected value, the adaptation needs of the caregiver and the process second. I think rightfully folks are inspired by what a given AI tool can do, and they are overwhelmed by the need to govern this insane volume of potential solutions. So, it seems strategic intent and change management have been forgotten.
Penny Kyte. Senior Vice President of Technology Enabled Care at Ballad Health (Johnson City, Tenn.): The most dangerous trend in health IT is also its most innovative: AI, and increasingly, agentic AI. We are still so early in AI implementation that building a truly robust ambient AI capability requires stitching together inputs from multiple vendors — and it will remain that way until health systems mature enough to develop their own AI products.
The dangers of AI implementation carry several downstream effects:
Duplication and misalignment. Layering multiple AI products from different vendors creates the risk of duplicated effort and misaligned outputs, which ultimately compromises response quality and coordination.
Expanded cybersecurity exposure. Every AI implementation widens the attack surface, opening health systems to new and unfamiliar risks on top of the threats they already face.
Automation bias. As clinicians grow reliant on these tools, there is a real danger of over-trusting their output. Human oversight remains essential and preserving it takes deliberate effort.
Workforce erosion. As AI tools are implemented and positions are eliminated, organizations risk cutting roles that should have been retained — or using AI to justify eliminating jobs when the tool is not yet capable of fully replacing the human work behind them.
Michelle Mello, JD, PhD. Professor of Health Policy, Department of Health Policy, Stanford (Calif.) University School of Medicine: Adopting AI tools on the basis of sales pitches, without a governance process that digs deeper into performance claims and examines how local workflow and the constraints facing the humans-in-the-loop might impact real-world outcomes.
Rob Sumter, PhD. Executive Vice President and Market COO of Ascension Illinois:
1. Cyberattacks: As healthcare becomes more reliant on technology, the frequency of cyberattacks will likely increase. We are increasingly dependent on cloud vendors, EHR platforms, clearinghouses, medical-device manufacturers, and other third parties. Based on my experience, a compromise of just one critical vendor can have a significant impact across the entire organization.
2. The rapid deployment of AI technologies. The old saying, “Garbage in, Garbage out,” can certainly come true with AI because bad data can be broadcast across many organizations, not just one.
Hetal Rupani. Senior Director of Business Intelligence and Analytics at Johns Hopkins Medicine (Baltimore): One of the most dangerous trends in health IT is the assumption that technology adoption equals transformation. It doesn’t.
The real risk is deploying tools faster than organizations can operationalize them — without the workforce training and upskilling, workflow redesign, governance, and accountability needed to turn technology into value. In healthcare, successful digital transformation is not measured by implementation alone; it is measured by whether technology improves care delivery, reduces burden on clinicians, and drives better patient outcomes.
A second risk is the blurred line between what EHR vendors enable and what health systems must own. EHR platforms are foundational, but the responsibility for making technology scalable, usable, and clinically meaningful sits with health systems. When that distinction is not clear, organizations can end up with expensive systems that are technically live but operationally underperforming.
At the end of the day, the most dangerous trend is not innovation itself — it is innovation without adoption, alignment, and measurable impact.
DeAnne Boegli. Public Information Officer, Communications and Marketing Manager, UnityPoint Health – Meriter (Wis.): In my view, one of the biggest risks emerging in health IT is that patients increasingly view “Dr. Google” and AI-powered health tools as being just as credible as their primary care provider. While these technologies can be valuable starting points, they cannot replace the expertise, context, and relationship that come from a trusted healthcare professional.
This shift reinforces the critical role healthcare organizations play in helping people find accurate, evidence-based information. Patients want answers quickly, and we need to meet them where they are by providing trusted resources that are easy to find and understand.
As healthcare marketers, we have an opportunity to turn this trend into an advantage. By embracing new technologies and using them to amplify credible clinical expertise, we can build confidence in our providers, strengthen trust in our health systems, and help patients make more informed decisions about their care.
Gerrit von Wenckstern, Director of Marketing, University of Texas Medical Branch: Gerrit von Wenckstern, Director of Marketing, University of Texas Medical Branch (Galveston): From my perspective, one of the most significant pitfalls in health IT today is the tendency to view AI as an overarching strategy instead of a supportive tool.
Many healthcare systems are racing to adopt automation and digital agents, often motivated by the pressure to keep pace with industry trends. While these advancements offer remarkable potential to streamline operations and ease administrative loads, we face a real risk of becoming so preoccupied with implementation that we overlook the human experience we aim to enhance.
The core of healthcare resides in deeply personal and vulnerable moments. Our initial insights indicate that although consumers value convenience, they remain cautious about relying on AI for needs that demand empathy, clinical trust, and complex understanding. A patient might find value in an AI-driven scheduling tool, but when it comes to their long-term health and quality of life, they need the assurance that a dedicated professional is truly listening.
Ultimately, the threat isn’t the technology itself, but rather the overestimation of where it can substitute for human connection. Success won’t be defined by the sheer volume of AI an organization deploys; it will belong to those who use these tools to eliminate friction and empower caregivers, thereby creating more space for meaningful, person-to-person engagement.
In our industry, fundamentally human challenges still require fundamentally human responses.
Babatope Olanloye. IT Director, Pioneers Medical Center (Meeker, Colo.): The most dangerous trend in health IT is the speed at which emerging technologies, particularly AI, are being adopted without equally mature governance, cybersecurity, and data protection frameworks. Generative, ambient, and agentic AI offer tremendous opportunities, but connecting these technologies to clinical workflows and sensitive health data without clearly understanding access, data use, third-party risk, and human oversight can create vulnerabilities faster than organizations can manage them. Innovation should absolutely move forward, but in healthcare, speed cannot come at the expense of patient safety, privacy, or operational resilience.
Mackenzie Schild. Vice President, Data and Artificial Intelligence, Centerstone (Springfield, Mo.): The most dangerous trend in health IT from my seat is the growing gap between how quickly we are creating new data and technology and how effectively organizations and providers can absorb it. AI, ambient documentation, connected devices and digital workflows are generating enormous amounts of information, putting more pressure on infrastructure, costs, governance, privacy and security. Provider adoption is also a real concern. If clinicians do not understand or trust these tools, or if the tools add complexity to their work, they will not use them consistently. We risk building a more advanced healthcare system without providers trusting it enough to use it.
Ray Lowe. Senior Vice President and CIO of AltaMed (Los Angeles): The most dangerous trend in Health IT today is not AI itself, but the rush to deploy AI without trusted data, governance, cybersecurity, and a clear business case. AI is only as good as the data behind it, and without strong data stewardship, organizations risk automating bad decisions at scale. Every AI investment should begin with a defined business case, measurable KPIs, controlled pilots, and ongoing monitoring of tokenization and consumption costs to ensure value is realized and sustainable.
At the same time, healthcare faces unprecedented cyber exposure. Every cloud platform, AI model, connected device, vendor integration, and data exchange increases the attack surface. Cybercriminals are now leveraging AI to accelerate phishing, identify vulnerabilities, and automate attacks faster than organizations can respond. The risk is no longer limited to data breaches. A successful cyberattack can disrupt patient care, compromise operations, impact revenue, and erode patient trust. The organizations that will lead in the next decade will not be those that deploy the most AI, but those that combine trusted data, disciplined governance, measurable outcomes, cost transparency, and cyber resilience to deliver secure, responsible innovation.
Rachel Papka. Chief Innovation Officer of SDMI Steinberg Diagnostic: Healthcare organizations are under enormous pressure to improve access, reduce costs, address workforce shortages, and improve the patient experience. That makes AI incredibly attractive. But the danger comes when we start asking, “Where can we put AI?” instead of, “What problem are we trying to solve, and how can AI support our team members in solving it?”
At the Becker's 11th Annual IT + Revenue Cycle Conference: The Future of AI & Digital Health, taking place September 14–17 in Chicago, healthcare executives and digital leaders from across the country will come together to explore how AI, interoperability, cybersecurity, and revenue cycle innovation are transforming care delivery, strengthening financial performance, and driving the next era of digital health. Apply for complimentary registration now.
