At this point, it’s impossible to deny: Healthcare is being transformed by the introduction and mass adoption of powerful AI technologies. Just a few years after the launch of generative AI, the leading ambient AI platform now supports more than a million weekly clinical encounters in the U.S. alone. By comparison, it took the electronic health record decades to achieve similar penetration.
If 2024 was the year of proof-of-concept and 2025 was the year of early adoption and scale, 2026 is shaping up to be something different — a year defined by normalization. AI in healthcare won’t fade into the background, but it will shift into something more permanent: expected infrastructure and simply part of how work gets done.
Below are 10 predictions from clinical and executive health system leaders, researchers shaping the next phase of the field, and respected analysts, describing how the AI conversation will change in 2026.
1. Point solutions will give way to integrated AI platforms that become the foundation of healthcare infrastructure
The era of one-off AI tools is ending. The next year is about consolidation — fewer vendors, more value, and a shift from “tool-per-task” solutions to platforms clinicians don’t have to think about because they’re just there, running beneath the surface.
“We’ll move from point solutions that solve individual problems to platforms that support many use cases,” said Terri Couts, Senior Vice President and Chief Digital Officer at Sharp HealthCare. “Right now, you might have one vendor for coding help, another for ambient documentation, another for referrals or denials management. That’s not sustainable.”
The pattern echoes a broader truth about technology adoption: Once a tool becomes expected, it stops being a shiny new feature and becomes part of the infrastructure. AI is following that arc. What felt cutting-edge in 2023 — ambient documentation, real-time summarization — will feel like table stakes in 2026.
Zachary Lipton, CTO and Co-Founder of ambient AI platform Abridge, sees convergence as unavoidable. “Healthcare has long been the land of a thousand point solutions, and I think that structure is going to begin to collapse in 2026,” he said. The winners, he believes, will be those who make five or more core capabilities work seamlessly as a single fabric.
Joon Lee, MD, CEO of Emory Healthcare, describes the shift as generational. Today’s new physicians “won’t bolt AI onto existing workflows — they’ll build workflows around AI from the start,” he said. AI will raise clinicians’ baselines.
Jeffrey Ferranti, MD, MS, Chief Digital Officer of Duke Health, predicted the same: “Generative systems will move from pilot projects to daily use,” he said. Success will hinge on platforms that unify ambient intelligence, enterprise data, payer logic and clinical context.
In 2026, platforms — not point tools — become the backbone of clinical infrastructure.
2. Clinical decision support will evolve beyond search with contextual awareness
For years, clinical decision support has been trapped in a frustrating middle zone: better than searching guidelines manually, worse than talking to a specialist. In 2026, leaders expect CDS to leap forward into something closer to a true real-time assistant — aware of the patient’s chart, the live conversation, payer rules and the relevant literature.
“This is the year CDS evolves past glamorized search,” said Mr. Lipton. “Next-generation CDS will reason jointly over medical literature, the patient’s record and current visit context, helping clinicians apply knowledge, not just retrieve it.”
This transition mirrors the evolution from transcription to intelligence generation. What once felt transformative — eliminating the human transcription step — now feels primitive compared to systems that identify medication errors, clarify care plans, tee up orders and support diagnostic reasoning.
Leaders are already seeing these superpower-like capabilities in action. At Hartford HealthCare, an AI solution for foundational imaging detection expands the impact of clinicians’ own expertise. “AI is improving decision support for medical imaging data, decreasing time from diagnosis to treatment,” said Hartford HealthCare President and CEO Jeffrey Flaks. He expects AI to “increasingly improve care coordination,” elevating the clinical encounter rather than interrupting it in 2026.
Allegheny Health Network President and CEO Mark Sevco anticipates the proliferation of real-time risk predictions and precision treatment suggestions, especially as CDS capabilities integrate more tightly with ambient capture.
The leap from assisting search to assisting reasoning may be one of the most meaningful clinical inflection points of 2026.
3. Primary care will get specialist insight — especially in rural and underserved communities
A growing number of leaders believe one of AI’s most impactful applications will be expanding specialist-level insight to primary care — especially in rural and underserved communities where access to cardiology, endocrinology, rheumatology and other specialties is severely limited.
Numerous reports and pieces of academic research highlight the care disparities, but one that summarizes the challenge well is The Commonwealth Fund’s The State of Primary Care in the United States (November 2025), which states, “nearly all rural counties are considered health professional shortage areas,” specifically citing “a lack of specialists.”
This aligns with frontline reality: a five-minute wait for a specialist can feel like one problem; a five-month wait is a different kind of barrier entirely. Embedding specialist-level expertise into primary care workflows may be the only scalable way to bridge that gap.
Emory’s Dr. Lee sees AI as a natural extension of the patient journey. Patients don’t want to parse which elements of their care are machine-generated or human-generated — they want consistency. “If we can put all of that together in a seamlessly integrated manner…that’s the goal,” he said.
4. AI will show increased ROI for value-based care models by reducing readmissions, predicting complications and personalizing care
The value proposition for AI is shifting from time savings to clinical return. Celebrations for less pajama time will give way to more attention on the urgent need for AI that drives better patient outcomes and, in doing so, strengthen performance under value-based care models. Leaders will raise the bar in 2026, calling for clearer evidence that AI improves readmission rates, complication detection, chronic disease management and personalization of care plans.
“ROI will move beyond financial metrics to also include measures for quality, safety, efficiency and experience,” said Hartford’s Mr. Flaks. “Imagine clinicians spending 30% more time with patients because AI handles the administrative burden.”
Mr. Lipton noted that as ambient AI matures, it will increasingly support the downstream activities that ultimately shape health systems’ financial health — things like risk adjustment, code concordance and prior-authorization logic. Even modest gains, he said, could remove “single-digit to tens of billions” of dollars of waste from the U.S. health system.
Mac Boyter, Senior Research Director at healthcare consulting firm KLAS, said systems are moving “from pilot stage to actual productivity,” and that CFOs want clearer causality between AI and downstream value. Are risk scores improving? Are readmission rates declining? Are clinical outcomes more consistent, with quality scores improving?
Duke’s Dr. Ferranti argued for standardization, saying 2026 is the year to implement “Impact Cards” — clear, consistent metrics that track ambient AI’s effect on clinician retention, time saved, documentation quality, patient outcomes and performance against quality benchmarks.
5. AI governance will move from backroom checkbox to strategic engine
If there is a place where leaders speak with near unanimity, it’s governance. An area once treated like infection control — important and steady, but quiet — is about to become urgent and visible.
“AI governance needs to move from reactive to proactive,” said KLAS’s Mr. Boyter. He described a shift from simple intake processes to comprehensive oversight of drift, risk, transparency and adverse AI events. “That’s a major tonal shift,” Mr. Boyter said.
Oversight bodies like state health departments, accrediting agencies, and federal regulators are beginning to push requirements that emphasize safety, outcomes and accountability over mere compliance. This external environment may be one more reason health systems adjust their governance resources in the year ahead. For context, only 16% of health systems had an enterprise-wide governance strategy; by 2025, the average IT budget allocation to governance hovered around 4%.
In 2026, governance emerges as a strategic discipline — clinical, operational and cultural.
6. Revenue cycle efficiency will increase as AI fixes thrash upstream
Denials have long been one of healthcare’s most expensive and demoralizing forms of waste. Leaders believe AI will begin correcting this upstream by generating more defensible coding, ensuring medical necessity alignment, and resolving prior authorization barriers before they trigger a fight.
“Ambient listening through AI will create structured notes that will also assist with coding, clinician orders and cross walk to insurance coverage plans providing real time prior authorization approvals,” said AHN’s Mr. Sevco.
Daniel Greenleaf, CEO at Duly Health and Care, predicts change even more starkly: “I believe that spend comes down by half,” he said of revenue cycle management. “The tools are going to be so sophisticated that we’re all going to agree that, ‘This doesn’t need a prior authorization. This shouldn’t be denied.'” Mr. Greenleaf added that as AI automates the predictable, offshore labor models built around high-volume administrative work will lose relevance.
Muhammad Siddiqui, Chief Digital and Innovation Officer of Richmond, Ind.-based Reid Health, highlighted improvements in problem-code concordance and risk adjustment as early signs of what 2026 may bring.
2026 may be the year denials begin to shrink — not because payers and providers suddenly agree, but because of fewer reasons to disagree in the first place.
7. The “context layer” of AI will drive much more robust patient care
Ambient AI solved documentation. The next shift is solving piecemeal context: combining EHR data, payer requirements, health-system-specific knowledge, medical literature and conversational reasoning into one layer.
“Ambient AI will become vastly more context-aware — providing value from the beginning to the end of the clinical encounter,” said Mr. Flaks. He envisions systems that prepare the chart before the visit, flag payer requirements mid-encounter, suggest orders, obtain prior authorizations, and generate patient-friendly summaries before the clinician leaves the room.
Mr. Sevco anticipates a similar capability. “It will help with revenue cycle operations, improving performance metrics and collections,” he said, but also with coding and clinical actionability.
The combination of what have traditionally been distinct data sets and domains into a single layer marks a significant improvement to clinicians and health systems. But don’t underestimate how the context layer of AI will translate to patient experience, leaders say.
Such intelligence stands to do more than eliminate friction before it reaches the patient — cutting out complexity, low-value time and administrative headaches that patients should never have had to manage in the first place. The combined layer of intelligence and insights also stands to enrich the time shared between patients and clinicians, with the latter able to see the former more holistically and clearly than they otherwise could.
8. Winning AI platforms will be increasingly transparent to secure trust from leaders and clinicians
Transparency becomes a defining competitive advantage in 2026. Clinicians have less and less patience for opaque systems, especially as AI moves deeper into clinical, operational and financial workflows.
“The clinicians are demanding to understand how AI makes decisions,” said Mr. Siddiqui at Reid Health. “What is the evidence base? How is this going to be embedded? How accurate is it?” He shared that his organization requires “11 pages” of AI and cybersecurity vetting before deployment. His prediction for 2026? “The black-box era will be over.”
At Sharp, Ms. Couts tied transparency to accountability: “When I click ‘accept,’ I’m accountable for everything the AI gives me.” In a world where clinicians remain responsible for outcomes, opacity is untenable.
Mr. Flaks believes transparent systems will command greater credibility, especially as patients expect clarity about how AI influences their care. He said the onus will be on AI technology that not only performs as expected, but “in a way that patients can understand and clinicians can trust.”
Transparent systems don’t just win trust — they win adoption.
9. Patients will begin to choose health systems that improve convenience, experience, access and trust with AI
As AI becomes more integrated in operations and clinical workflows, patients will begin to feel its presence in shorter waits, smoother access, clearer instructions and more attentive clinicians. Leaders expect all of these secondary benefits to start informing something powerful: patient choice.
Patients who have gotten used to navigating a slow, overcomplicated healthcare system don’t need to understand AI to feel a difference. When a system delivers care more smoothly, patients will notice — whether or not they know what solution is powering that improvement.
“Patients will choose where to receive their care based on how AI benefits them with improved access and convenience, and their confidence in the quality and safety of care,” said Mr. Flaks.
At AHN, Mr. Sevco anticipates AI to improve administrative flow and experience for patients, all while maintaining safety and engagement.
Mr. Boyter observed that when clinicians are more present — when they look at their patients rather than their keyboards — patients feel it immediately. 2026 will be a year when that benefit starts to become more of a movement, where patients differentiate the systems that are built with an intentional patient experience in mind and those that still ask them to endure the old way of doing things.
10. Healthcare avoids an “AI bubble” and “rightsizes” the market
Outside healthcare, debates about an AI bubble are common. Inside healthcare, expectations are different. Leaders see something closer to a “rightsizing” — a steadying of expectations and a clearer distinction between hype and durable value.
“AI rightsizing in 2026 will look like more of a subsummation as opposed to a deflation,” said Mr. Boyter. “This is not a dot-com bubble. These are real outcomes that we can actually point to that are having real impacts.”
Dr. Ferranti expects “scaled transformation,” as systems shift from discrete AI wins to portfolio-level management.
Ms. Couts noted earlier that AI will become “less of a buzzword” and more of a baseline — something clinicians expect, not something they marvel at. Here begins AI’s next chapter, marked by fewer hypotheticals or spectacle.
2026 may be the year AI stops surprising anyone — precisely because it is working for everyone.
If 2024 showed that AI could work in healthcare, and 2025 proved it could scale, 2026 will demonstrate something more fundamental: AI will become an integral part of how healthcare is delivered, governed, measured, financed and experienced — for clinicians, patients and health systems.
The question is no longer whether AI will reshape care, but how quickly, and how well health systems and their people manage the infrastructure under their feet.
