As we wrap up another year and get ready for 2026 to begin, it is once again time for everyone’s favorite annual tradition of Health IT Predictions! We reached out to our incredible Healthcare IT Today Community to get their insights on what will happen in the coming year, and boy, did they deliver. We, in fact, got so many responses to our prompt this year that we have had to narrow them down to just the best and most interesting. Check out the community’s predictions down below and be sure to follow along as we share more 2026 Health IT Predictions!
Check out our community’s Healthcare AI Tools predictions:
Colin Banas, Chief Medical Officer at DrFirst
Ambient AI for clinical documentation is already delivering remarkable results, as evidenced by a study that found physicians at a large academic health system reported a 21% reduction in burnout in under three months. But easing documentation burden is just the beginning. In 2026, expect to see AI connecting prescribers, pharmacies, and payers to eliminate the phone tag and faxes that frustrate providers and complicate prior authorizations, so prescriptions arrive at the pharmacy ready to fill, and patients can start therapy faster.
Adam Oskowitz, Vascular Surgeon at the University of California San Francisco, and Co-Founder of Doctronic
By the end of 2026, AI will be authorized to legally prescribe medications in at least three U.S. states, starting with narrow formularies and clear guardrails for safety, documentation, and oversight. These early regulatory pathways will become templates for broader national adoption. A new wave of digital health hardware companies will move beyond diagnostics and monitoring. In 2026, several will begin delivering elements of primary care directly, pairing at-home devices with AI-driven clinical services to close gaps in access, accelerate triage, and reduce pressure on traditional care settings.
Zahiah (Zee Zee) Gueddar, Senior Director, Commercial Strategy at IQVIA Clinical Trial Financial Suite
By 2026, we may see sponsors increasingly bringing core clinical trial financial management functions in-house, not simply to cut costs, but to gain greater agility, control, and strategic insight. This will be done by pairing advanced AI with deep domain expertise, creating a model where technology drives speed and accuracy while human oversight ensures quality and informed decision-making. The results will be smoother operational execution, stronger site relationships, and ultimately contribute to a more efficient trial environment that better supports patients throughout their journey.
Matt Hanauer, Ph.D, Senior Director, Data Science at MedeAnalytics
In 2026, healthcare organizations will shift from broad, generic deployment of point solutions to AI-powered personalized targeting. As point solutions become increasingly expensive, organizations will use predictive analytics to identify which specific members will benefit most from each intervention, based on their historical and projected ROI. This personalized approach ensures resources are directed only to members likely to see meaningful outcomes, maximizing both clinical impact and financial efficiency.
Amy Cheetham, Partner at Costanoa Ventures
In 2026, a generalist AI diagnostic assistant will match or beat specialist physicians across 20+ conditions. We’re talking about systems that can interpret imaging, lab results, patient history, and clinical notes to provide differential diagnoses and treatment recommendations. The rapid adoption we’re seeing from providers suggests the infrastructure and trust are building toward this capability. AI-native healthcare startups are already gaining real traction.
Healthcare is one of the key places where AI can have a real impact on the world’s data, and much of that is images, which AI is particularly well-suited to process. Providers are reporting usage rates as high as 90% for some AI tools, particularly ambient documentation. Healthcare is also replete with old legacy systems of record (e.g., Epic), and that makes AI even more attractive as it can sit on top of these old systems and reduce manual effort without requiring complete replacement.
Tathagata Dasgupta, Founder and President at 4D Path
AI in pathology and oncology has long been applied primarily to productivity, streamlining workflows and reducing errors, but we’re entering a new ‘creative’ era where physics-informed AI extracts actionable knowledge directly from tumor images, revealing hidden patterns in how cancers behave and which patients may benefit from treatment. Digital-only biomarkers now appear in prospective trials as pre-specified endpoints, and AI-derived signals from H&E slides may soon rival traditional lab assays.
By 2026, I expect trials to show digital-only biomarkers influencing treatment selection alongside, or even ahead of, conventional tests. These models are beginning to uncover mechanisms of resistance that may not be detectable with existing assays, identifying escape circuits that let tumors evade the immune system. This kind of mechanistic insight, from routine biopsy images without extra tissue or specialized testing, marks a threshold moment: AI not just for efficiency, but for discovery.
Daniel Hallenbeck, Vice President of Strategy and Strategic Partnerships at Acentra Health
In 2026, Medicaid programs will shift from AI pilots to embedding AI in targeted, lower-risk workflows that help staff work faster and with better information. AI will assist caseworkers and assessors by researching complex cases, summarizing documents, and surfacing relevant history, always with a human in the lead oversight.
States will also expand secure AI-powered chat for 24/7 member and worker guidance, easing call center strain while maintaining strict limits on what the AI can answer. Behind the scenes, AI will accelerate system modernization by converting legacy documentation, generating test scripts, and strengthening auditability.
To implement these capabilities safely, states will rely on the NIST AI Risk Management Framework and Medicaid-specific efforts like the Safe AI in Medicaid Alliance (SAMA) for shared guardrails, risk tiers, and confidence in responsible adoption.
Michelle Hilburn, MSN, RN, CPHQ, CPPS, AVP of Quality, Compliance & Standards at Vastian
By 2026, AI will not be just a tool for innovation but a primary workforce staffing strategy. Use of AI will become essential in healthcare to offset workforce gaps caused by Baby Boomers retiring, deepening burnout, and increasing nurse vacancy rates as a result of academic programs limiting class sizes due to teacher shortages. AI will be necessary to reclaim clinical time and decrease inefficiencies around documentation requirements and ED boarding caused by discharge gridlock.
Edmund Jackson, Co-Founder and CEO at UnityAI
Next year, AI in healthcare will move from broad experimentation to real operational integration. In 2025, we finally saw AI handle the ‘last-mile’ work that has strained healthcare for decades, like outreach, scheduling, coordination, and managing day-to-day variability. In 2026, buyers will expect the ability to fit into real workflows, and the hype will fade for tools that can’t deliver. As it relates to jobs, AI will reshape roles rather than eliminate them, automating the administrative load while people shift toward work that requires judgment and human connection. The organizations that embed AI into their operating fabric instead of treating it as an add-on will look meaningfully different by the end of the year.
Ece Kalvaci, Software Engineer at Lindus Health
As agentic AI becomes more deeply embedded in clinical trial operations, its role will evolve from experimental to essential, not as a replacement for human oversight and expertise, but as an engine for efficiency that seamlessly coordinates complex workflows across clinical, data, and operational teams. The focus will increasingly shift toward transparency, auditability, and governance, which are all critical foundations for the next generation of successful clinical trials.
Craig Limoli, CEO at Wellsheet
AI agents will increasingly play a supportive but essential role in healthcare delivery. More than ever, AI will serve as the invisible infrastructure managing background tasks, drafting summaries, sending reminders, and surfacing insights. Early feedback from clinicians already using AI agents is clear: those who don’t adapt to this new way of working risk burnout, falling behind, and compromising patient care. 2026 is the year agents will automate away much of the repetitive and mundane work that burdens clinical teams and interrupts patient care.
Angel Mena, Chief Medical Officer at symplr
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.
David Minkin, President and General Manager, epocrates at athenahealth
In 2026, the defining divider won’t be who deploys AI. It’ll be who delivers trustworthy AI at clinical speed. Clinicians are working under extraordinary cognitive load, and they will no longer tolerate tools that hallucinate, obscure their logic, or add steps. The winners will combine real-time intelligence with real human editorial oversight, building systems that are transparent, traceable, and tuned to how clinicians actually work. By 2026, organizations that pair AI precision with accountable professional judgment will cut through noise, curb burnout, and re-center clinicians on meaningful patient care.
Michael Monovoukas, Co-Founder and CEO at AcuityMD
Next year, AI will redefine how MedTech proves value to healthcare systems. In 2026, AI won’t just accelerate product innovation. It will reshape how MedTech companies demonstrate clinical and financial value. On-demand analytics will instantly quantify treatment impact, helping manufacturers prove outcomes for both clinicians and CFOs. Rather than relying on retrospective studies or data, AI-driven models will provide evidence on demand. For forward-thinking MedTech companies, this will mean faster adoption, confidence that they’re aligned to a buyer’s distinct needs, and a competitive edge built on transparency and measurable results.
Kumar Dharmarajan, Co-Founder and Chief Medical Officer at World Class Health
In 2026, healthcare IT will do much more than support documenting care; it will help guide decisions, surface risk earlier, and align patients with the most appropriate treatments. With CMS advancing transparency, prior authorization reform, and clearer expectations for outcomes, analytics increasingly powered by AI to detect patterns clinicians can’t easily see will influence which procedures are delivered, where, and with what expected results. High-cost specialties such as orthopedics, spine, cardiac, and bariatrics will lead the shift as employers and payers prioritize Centers of Excellence that can prove outcomes and price reliability with real-world data, not reputation alone.
For Healthcare IT leaders, EHR-integrated appropriateness tools, AI-assisted clinical navigation, longitudinal data pipelines, and routine patient-reported outcome capture will move from pilots to core infrastructure. The systems that win in 2026 and beyond will be those that use AI to make high-value decisions easier, more consistent, and transparently measured.
Greg Samios, CEO at Wolters Kluwer Health
Clinical-grade generative AI (GenAI) can be a trusted copilot when embedded in daily workflows, rigorously validated, protected by guardrails, and infused with expert-in-the-loop oversight. Looking ahead to 2026, the ecosystem will continue to witness GenAI’s ability to automate documentation, synthesize clinical notes, surface care gaps, and streamline clinician-patient communications at scale.
As shadow AI continues to be more prevalent, clinicians should only use purpose-built GenAI systems that are trained on expert-validated evidence, transparent with source citations, and capable of tailored recommendations. GenAI will provide an increase in staff efficiency and care quality, but we must preserve safety and clinician-patient relationships by reframing workflows that elevate GenAI from a tool to a partner, keeping humanity at the center of care.
Thank you so much to everyone who took the time out of their day to submit a prediction to us, and thank you to all of you for taking the time to read this article! We could not do this without all of your support. What do you think will happen for Healthcare AI Tools in 2026? Let us know on social media. We’d love to hear from all of you!
Be sure to check out all of Healthcare IT Today’s Healthcare AI Tools content and our other 2026 Health IT Predictions.
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