Predictions from our experts last year on this subject looking ahead to 2025 said it would be formative and they were not wrong. We saw AI in clinical settings scale, stabilize, and reshape workflows. The year was defined by rapid adoption, cautious optimism, and a growing push for governance and trust. According to Elsevier’s 2025 Clinician of the Future Report, usage of AI tools is increasing dramatically among clinicians, with 76% having used an AI tool. So where will we go from here?
Not surprisingly on this subject we received an overwhelming amount of response from our experts. Look for part 1 and all our prediction posts looking to 2026.
Heather Bassett, M.D., Chief Medical Officer, Xsolis
LinkedIn: Heather Bassett
In 2026, AI in clinical settings will move beyond efficiency to empathy. The real progress will come from tools designed with safety, validation, and human connection at their core. As technology becomes more integrated into care delivery, our challenge, and opportunity, is to ensure AI strengthens the clinician–patient relationship rather than jeopardizing it or degrading trust. The next wave of innovation will be defined not by how smart our systems are, but by how thoughtfully they support the people who use them.
Danielle Bergman, MSN, APRN, FNP-BC, AVP Clinical Development, Lightbeam Health Solutions
LinkedIn: Danielle Bergman, MSN, APRN, FNP-BC
From working closely with physicians, care managers, and care teams, it’s clear that AI only works when it fits into clinical workflows. The tools that gain traction are the ones that support real patient care, ease administrative burden, and reduce after-hours documentation, without adding complexity. To scale in healthcare, AI has to be intuitive, explainable, and almost invisible in the background.
Dr. Kathryn Boger, Chief Clinical Officer and Co-Founder, InStride Health
LinkedIn: Kathryn Boger, Ph.D., ABPP
In 2026, AI will continue threading itself into behavioral health, and the bar will rise sharply for what counts as meaningful innovation. Patients, families, and clinicians will become increasingly selective, choosing tools that actually improve care rather than add noise. The organizations that pull ahead won’t be the ones chasing novelty. They’ll be the ones using AI in clinically sound, ethically grounded ways that genuinely improve treatment. AI overseen by licensed humans in the loop, supervised, compliant, and aligned with established clinical standards, won’t just be a differentiator; it will be a strategic advantage for those who do it right.
Steven Buslovich, MD, CMD, Chief Medical Officer, Senior Care, PointClickCare
LinkedIn: Steven Buslovich, MD, CMD, MSHCPM
In 2026, AI will become a core part of clinical practice as providers work to manage growing acuity and increasingly complex medication needs. AI-supported medication reconciliation, deprescribing workflows, and digital MAR systems will help reduce adverse drug events and provide clinicians with more complete, timely information. Predictive analytics and real-time clinical data will also support higher-quality documentation, stronger care coordination, and more reliable outcomes across skilled nursing and assisted living communities as these settings take on a larger role in value-based care.
Sean Cassidy, CEO and Co-Founder, Lucem Health
LinkedIn: Sean Cassidy
During 2026, provider organizations will see clear progress in how care teams use AI to support clinical performance. For example, platforms that analyze existing EHR data and surface patients who may benefit from further clinical evaluation can enhance existing screening protocols and help teams move individuals into timely care with greater consistency. This blend of automation and workflow fit can improve outcomes and strengthen clinical and financial results without adding new burden to clinicians.
Betsy Castillo, RN, VP of Clinical Data Abstraction, Carta Healthcare
LinkedIn: Betsy Castillo
AI is beginning to show real promise in clinical settings by taking on the routine tasks that slow providers down. From supporting diagnosis and triage to handling administrative work and engaging patients through virtual assistants, these tools are helping clinicians focus more on care delivery. The next frontier is extending that support into areas like mental health, where AI can offer timely guidance and connect patients to the right resources faster.
Todd Doze, CEO, Janus Health
LinkedIn: Todd Doze
In 2026, AI in clinical settings will shift from point solutions to deeply embedded tools that enhance diagnosis, triage, and patient engagement in real time. The biggest gains will come from reducing cognitive and administrative load so clinicians can focus more fully on patient care. As virtual assistants and mental health AI mature, we’ll see a meaningful lift in both clinical accuracy and patient outcomes.
Rom Eizenberg, Chief Growth Officer, Kontakt.io
LinkedIn: Rom Eizenberg
Clinicians in the center: ambient AI will continue to grow its footprint providing little ROI to health systems but strong returns to providers and better experiences for clinicians at large, helping to reduce burnout. Interfaces between ambient and workflow software like AI orchestration will create the first ROI-promising use cases for ambient technology.
Dr. Aaron Galaznik, Chief Medical Officer, MDClone
LinkedIn: Aaron Galaznik
In clinical trials and pharma, AI’s greatest impact comes from turning fragmented real-world data into structured, actionable insight. When paired with governed, high-fidelity synthetic data, researchers can explore patient populations, assess feasibility, and model outcomes without the long delays of traditional data access. This shortens development cycles and strengthens evidence generation across the entire pipeline.
Virginia Halsey, Senior Vice President, Strategy and Product Management, FDB (First Databank, Inc.)
LinkedIn: Virginia Halsey
In 2026, clinically grounded AI agents will expand clinical decision support by being purpose-built to help care teams complete specific jobs to be done within the care process. Using patient information—including insights captured only in notes—and real-time clinical context, these agents will guide and automate tasks such as drafting prescriptions from notes or preparing essential checks for pharmacy verification, while clinicians retain final oversight. The result will be smoother, more efficient workflows that help teams accomplish essential work with less effort.
Gary Hamilton, CEO, InteliChart
LinkedIn: Gary Hamilton
In 2026, AI will shift from being a support tool to an active partner in care. Intelligent systems will flag early warning signs, guide triage, and help close the gaps that often delay treatment or follow-up. When designed with empathy and purpose, these tools will not only boost efficiency but also improve outcomes and strengthen the trust between patients and their care teams.
Jason Harber, Head of Inpatient Flow Business, LeanTaaS
LinkedIn: Jason Harber
In 2026, hospitals should brace for a level of emergency department (ED) pressure that will eclipse what we’re already experiencing today. The unwinding of Medicaid eligibility and broader financial policy changes are poised to push millions more patients out of coverage, and when that happens, the ED becomes the unavoidable front door. We’re already watching the consequences unfold: rising acuity, hours-long waits for beds, patients receiving inpatient-level care in hallways, and rural facilities once again struggling to transfer their sickest cases. These stressors are not temporary. They will accelerate. And the ED will continue to serve as the clearest pressure test of whether a system is operationally prepared for the volume, variability, and complexity coming its way. Organizations that continue to rely on reactive decision-making will find themselves overwhelmed more frequently and for longer stretches of time.
The defining shift in 2026 will be how health systems respond operationally. The organizations positioned to weather this next wave are those that treat patient flow as an interconnected network rather than a series of isolated decisions. That means predicting when ED volumes will spike, aligning staffing and diagnostic resources in advance, and creating more consistent, earlier discharge patterns to avoid the “weekday gridlock” that so many teams experience. The old model, reacting in real time, relying on manual huddles, and hunting for information across systems, cannot keep pace with the level of variability hospitals now face daily. Leaders will need to adopt a more proactive, AI-enabled, systems-engineering mindset, one that anticipates bottlenecks hours or days before they occur and prioritizes throughput with the same discipline used in other high-stakes, high-complexity industries.
Finally, 2026 will force hospitals to think more creatively about care pathways. As EDs absorb more uninsured patients and as inpatient units remain full, systems will need to diversify how and where care is delivered. Alternative pathways, short-stay units, transitional care spaces, virtual support, and expanded community partnerships, will become essential for routing patients to the most appropriate setting without defaulting to a high-acuity bed. Health systems with both urban and rural sites will increasingly seek ways to balance load across facilities, leveraging regional assets more intentionally rather than allowing one flagship hospital to carry the full burden. The year ahead will reward organizations that act with urgency, rethink long-standing processes, and build durable operating models capable of absorbing the volatility that is now a permanent reality for hospital emergency departments.
Dr. Paige Kilian, SVP, Chief Medical Officer, Inovalon
LinkedIn: Paige Kilian
In 2026, agentic AI will advance efforts to tackle healthcare’s most stubborn administrative burdens, such as prior authorization, a clinician-draining process that too often delays patient care. Ideally, agentic AI will help to expedite approvals in areas like identifying “gold-card” physicians whose documentation consistently aligns with health plan standards and fast tracking those cases, while routing complex or ambiguous documentation for human review.
It will require a real culture shift to accept that AI will make some decisions without human intervention, so it’s crucial for experts to be involved in curating these algorithms to set the rules these agents follow and regularly audit their application. AI won’t make every decision, and it shouldn’t, but it will intelligently handle much of the regulatory complexity that overwhelms clinicians today so they can focus on patient care rather than manage a deluge of regulatory obligations. The real value of agentic AI is its ability to surface where human input is absolutely necessary and allow clinicians to focus their time on decisions that genuinely require their expertise.
Dr. Laura Kohlhagen, Chief Medical Officer for Sunrise, Altera Digital Health
LinkedIn: Laura Kohlhagen, MD, MBA
In 2026, AI in clinical settings will evolve from pilot projects to enterprise-wide deployments. Ambient documentation, predictive insights and automated clinical workflows will finally reduce cognitive load rather than add to it, allowing physicians to practice medicine with greater clarity and fewer distractions. The organizations that integrate AI seamlessly into the EHR will set the new standard for safety, efficiency and patient experience.
Annie Lambert, PharmD, BCSCP, Clinical Program Manager for Compliance Solutions for Clinical Surveillance & Compliance, Wolters Kluwer Health
LinkedIn: Annie Lambert, PharmD, BCSCP
In 2026, compounding pharmacies will remain in the spotlight, driven by demand for GLP-1 medications and heightened regulatory scrutiny as state boards move beyond basic implementation of USP standards. Compliance programs will mature, shifting from manual tasks to intelligent, integrated oversight, using AI-powered platforms to automate monitoring and documentation while connecting vendor systems. However, in-person checks and balances will remain essential to ensure accountability and quality. The Designated Person’s role will evolve into a strategic leadership position that balances advanced automation with hands-on validation to ensure safety and trust in a rapidly changing landscape.
S.V. Mahadevan, CMO and co-founder, Fold Health
LinkedIn: S. V. (Maha) Mahadevan, MD
In the coming year, AI adoption in clinical settings will come down to trust. The most trusted clinical AI won’t be the model with the best answers, it’ll be the one that reliably completes the next step in the right system, with transparent guardrails and human sign-off. AI will move from ‘insights on a screen’ to execution inside clinical workflows, agents that draft orders, coordinate follow-ups, and prepare the team, with clinicians approving the final move. The biggest winners will be provider organizations that redesign care teams around AI-assisted ops, not just add new AI tools.
Theresa Meadows, CIO in Residence, symplr
LinkedIn: Theresa Meadows
AI will continue to be the number one topic for CIOs, but the healthcare systems that truly benefit from it will be the ones that treat governance and data readiness as non-negotiables. Healthcare leaders are increasingly drawn to the potential value AI can bring, yet this technology only creates value when they’re built on clean data, standardized processes, and a strong operational foundation. Too many health systems are still falling into the trap of “adding AI” to messy, fragmented workflows, which only amplifies risk and dissatisfaction. The systems that succeed will be those that slow down long enough to fix what’s broken, establish clear governance models around AI, and create unified data structures that allow AI to safely and meaningfully transform clinical and operational workflows.
Angel Mena, MD, Chief Medical Officer, symplr
LinkedIn: Angel J. Mena, MD
In 2026, we’ll be focused on raising the next generation of digitally enabled physicians, clinicians who are not only skilled in the art of medicine but fully equipped to operate in an increasingly digital healthcare ecosystem.
This past year’s boom in AI tools has shown tremendous promise in reducing administrative burden at a time when clinicians are already spending nearly 88 minutes per day on administrative tasks. As these technologies continue to expand, proper training and digital fluency will become even more essential. AI must be woven into how we train, coach, and support clinicians.
Miriam Paramore, CEO and Founder, RxUtility
LinkedIn: Miriam Paramore
The Rise of the AI Healthcare Assistant
Prediction: Every constituent in healthcare is going to launch an AI assistant capability of some kind in 2026.
There will be a conversational AI assistant like ChatGPT for your health plan, for your doctor and for your pharmacy. The industry has to rewire its focus toward consumers, and conversational AI chatbots are tools that can help. These assistants will help consumers better understand and navigate their healthcare choices, including costs. Once these systems are fully integrated with strong LLMs, consumers will be able to ask the AI assistant how much a medication costs and instantly see all price options. This is not possible today, and AI will help bring the answers to our phones with ease.
Nancy Pratt, Senior Vice President, Product Management, CliniComp
LinkedIn: Nancy Pratt
Clinical AI is already out of its pilot phase and in use for diagnostic support, virtual triage, patient engagement, documentation and even basic mental health interventions. Hospitals that commit now to embedding validated tools in their care pathways will see marked improvement in time-to-diagnosis and other process metrics. Ultimately, it will mean more efficiencies in patient care and hopefully faster access to care.
David B. Snow, Jr., Chairman & CEO, Cedar Gate Technologies
LinkedIn: David Snow
In 2026, the pace of AI innovation in healthcare will shift from acceleration to intentional refinement, driven directly by payers, providers, and self-funded entities demanding tools that meet real-world operational, clinical and regulatory requirements. Rather than accepting rushed capabilities, these organizations will insist on AI that is developed safely, reliably, and transparently, and that empowers clinical quality and economic performance. This market pressure will redefine success, no longer focusing on speed-to-release, but instead on the proven impact of the technology.
In contrast to the frenzied pace of AI development, Cedar Gate’s clients are telling us that they want a more responsible, methodical, and purposeful AI approach, tools that include the appropriate safeguards and transparency, with thoughtful and actionable design that empowers priority use cases and accuracy that builds trust among patients and care providers. Speed to market should not be our ultimate goal with healthcare AI, because being 90% right still leaves way too much room for error, and errors can be life and death in this field. Pressure from healthcare organizations and consumers in 2026 will ensure that the primary focal points in developing and deploying these technologies are safety, accuracy, and efficacy for better patient outcomes.
Alex Sommer, Vice President of State Government Affairs, Avalon Healthcare Solutions
LinkedIn: Alex Sommer
In clinical settings, artificial intelligence must be embedded within rigorous policy frameworks to ensure that human-led diagnosis, triage, and care-engagement remain central, and administrative gains don’t come at the expense of trust or transparency. As providers adopt virtual assistants, mental-health bots, and other AI-driven tools, the real opportunity lies in governance models that make these innovations both ethically robust and operationally scalable.
Nick Sterling, MD, Chief Medical Informatics Officer, Vital
LinkedIn: Nicholas Sterling, M.D., Ph.D.
By 2026, health systems will increasingly rely on intelligent platforms to ensure that care gaps are closed proactively, beginning with incidental findings. Agentic systems will replace static ‘Swiss cheese’ approaches for patient safety and facilitate detection, risk stratification, follow-up coordination, transforming long-standing gaps in care into opportunities to intervene and improve patient health. What were once major sources of missed care opportunities and malpractice risk will become the targets of proactive systems that identify early warning signs and orchestrate the appropriate interventions.
Karen Thomas, Vice President, Clinical Solutions, CorVel
LinkedIn: Karen Thomas
Workers’ compensation will undergo a fundamental transformation in 2026, shifting from reactive claims handling to proactive risk identification powered by AI-driven early intervention. This evolution represents the industry’s most significant opportunity since managed care emerged, with success measured not merely by claims processed but by injuries prevented and lives improved.
The critical window for intervention lies within the first 30 days following an injury. Early identification and targeted clinical support yield lower costs and faster resolution.
This transformation isn’t about replacing healthcare professionals with algorithms. Instead, it’s about empowering nurses and clinicians with AI-enhanced capabilities. While artificial intelligence handles complex data analysis, healthcare providers can focus on what they do best: delivering compassionate patient care.
To succeed in this new paradigm, organizations must invest in integrated platforms that seamlessly connect claims data with medical records, train staff to collaborate effectively with AI tools, build strategic partnerships with providers who understand early intervention protocols, and develop metrics that prioritize prevention over simple claims closure. Companies that master this balance between advanced technology and human-centered care will achieve dramatic improvements in both clinical outcomes and financial performance.
Salvatore Viscomi, MD, CEO & Co-Founder, Carna Health
LinkedIn: Salvatore Giovanni Viscomi, MD
The future of digital health is being shaped by the integration of diagnostics and AI to develop analytics to drive earlier diagnosis, predict risk of progression and indicate timely treatment interventions. As the healthcare ecosystem becomes increasingly connected, data insights from wearable technologies, mobile health applications, remote monitoring devices and electronic health records are converging to create a more comprehensive picture of patient well-being. Within this digital framework, AI-driven models can identify subtle changes in patients and alert care teams of potential disease indicators long before symptoms appear.
This is especially critical for conditions where symptoms don’t become apparent until later stages, such as chronic kidney disease (CKD), where early detection can mean the difference between lifestyle changes to prevent progression requiring dialysis. By harnessing predictive technologies, clinicians can access integrated insights drawn from blood and urine tests, medical history and lifestyle data, all in real time. These advanced models detect patterns that the human eye may miss, enabling physicians to shift from reactive treatments to proactive, preventive care.
This combination of real-time data and physician expertise will foster a continuous care model, extending beyond care settings into the patient’s everyday life. Future success depends on collaboration across the healthcare ecosystem to drive rapid, ethical advancement of AI. When technology innovators, clinicians, policymakers and healthcare leaders unite around a shared vision, these tools can be harnessed to deliver smarter, more equitable care and significantly improve patient outcomes.
Julie Wood, MD, MPH, FAAFP, Senior Medical Director, Clinician Engagement, Linus Health
LinkedIn: Julie Wood, MD, MPH
In 2026, AI will help clinicians strengthen everyday care by introducing timely, relevant and actionable insights into routine workflows rather than adding new burdens. For example, tools that can surface early signals of cognitive, functional, or behavioral change will give primary care teams the opportunity to intervene sooner, support shared decision-making, and guide patients to the right resources. As a family physician, I value AI that enhances clinical judgment and supports whole-person care by helping teams recognize change early and respond with confidence.