Photo: Solskin/Getty Images
Executives told MobiHealthNews that they anticipate AI increasingly acting as a curator, personalizing healthcare and surfacing insights that can make clinical, operational and administrative workflows more seamless in 2026. However, careful consideration is needed now in how AI is developed and deployed to ensure positive outcomes in the future.
Here is Part 2 of healthcare leaders' predictions on where AI will make the biggest impact in 2026:
Claire Rudolph, cofounder and head of product at WellTheory
This past year, AI has done a great job at taking care of administrative tasks for clinicians and patients alike – transcribing and summarizing appointments, sifting through symptom logs to glean insights, surfacing early signals of flare-ups and connecting patients with relevant resources. AI handles the busywork, which allows practitioners to focus on delivering care and patients to focus on their healing journey.
At the same time, we are at a fork in the road with AI: It can bury us in endless, low-quality content and generic advice, or it can help us finally differentiate signal from noise. Next year, the opportunity is to move from volume to clarity. Patients don't need more information; they are already oversaturated. They need a personalized, focused approach to healing.
I see AI evolving into a curator rather than a creator. Its job shouldn't be to generate more emails or pile on generic recommendations that require the patient to do the heavy lifting. For someone navigating fatigue or pain, sifting through a mountain of suggestions to figure out which ones are worth pursuing often leads to overwhelm and inaction. AI needs to prune the excess – sifting through the many variables of a patient's life to find the one or two insights that actually matter. If we get this right, AI creates the quiet space necessary for effective care. If we get it wrong, we’re just adding to the noise.
Inbar Blum, director of planning and development in the growth division of the Israel Innovation Authority
Looking ahead to 2026, AI’s growth will expand on infrastructure and regulation. Governments and health systems are expected to introduce regulatory sandboxes, datasets and standards that will allow safe use of AI at scale. With better data access and clearer approval processes, hospitals will increasingly rely on AI for diagnostics, logistics and community care, while the healthcare workforce evolves into roles that manage, interpret and validate these systems.
Matt Cybulsky, managing director of healthcare at Catalant
How AI addresses labor shortages in healthcare is one that comes to mind for 2026, including the fact that how labor is scaled in healthcare is forever changed. The key in 2026 will be moving from simple staff augmentation to broader AI application, aligning real technological innovation with current operational models.
Not long ago, while at Oracle CloudWorld, I was informed that there is a real desire for systems to always know "who is closest to the patient." Literally, this makes sense, but it is also a profound statement when we think of this figuratively. Who's closest to the patient, with AI, will be innovations that invite participation from patients who welcome it.
In 2025, the hope of agentic AI became a regular talking point: To achieve autonomous agents, data must be available and ready. Cleaning and organizing data will become a higher priority for healthcare organizations as they seek solutions with truly agentic capabilities. How organizations think about their data, its accessibility and its structure is a demand imperative for 2026.
Ambient listening has changed healthcare and will continue to do so into 2026 and beyond. Ever since Alexa began exploring healthcare use cases, there has been great excitement about the possibilities. Products like Suki and Abridge create massive time savings, improve accuracy and enhance experiences (not to mention administrative burdens and concerns). Perhaps ambience marks the pivot in healthcare away from a dominance of screens to something more integrated?
2026 might be the year of wellness and longevity. With AI's ability to learn from patients' histories, advances in imaging that forecast wellbeing and health, and the possibility of connecting consumer-patients across multiple platforms for care and intervention, I'm hopeful of seeing real strides in this vertical for public health, personal health and innovative breadth in understanding populations and needs.
John Beck, senior vice president of strategy at Nextech
2026 will mark the start of a true adoption wave, with specialty practices doubling their use of AI capabilities in 2027 and doubling again in 2028. This is not a trend; it’s an exponential shift. The biggest transformation will come from AI that is fully integrated and workflow-native: charting, imaging, intake, communications, revenue cycle and patient engagement.
Passive AI that drafts text is helpful. But active AI that injects structured data and real-time insights into the chart is what fundamentally reshapes care delivery. The practices that win over the next three to five years will be the ones that operationalize AI as core infrastructure. AI is no longer an enhancement. It is the engine.
Connor Landgraf, CEO and cofounder of Eko Health
In 2026, AI will play a larger role in creating continuity across encounters, ensuring that signals detected in one setting actually lead to action in another. We’ll see fewer missed diagnoses, fewer disconnected data points and more real accountability across the care continuum.
Dan Nardi, CEO of Reimagine Care
Looking to 2026, I predict we'll see AI integration become table stakes for healthcare delivery, particularly in specialties facing severe workforce shortages. We'll also see increased focus on AI's role in health equity – using these tools to extend quality care to underserved populations who historically had limited access to specialists. The real innovation will be in hybrid care models where AI and human expertise work seamlessly together.
Shannon West, chief strategy officer at Datavant
Looking ahead to 2026, we see an increased focus on embedding intelligence directly into clinical and operational workflows. The most forward-thinking organizations will break down traditional boundaries between payers, providers and life sciences companies, using shared data and embedded digitization and automation to accelerate insights and improve outcomes.
Ashley Rogers, chief product officer for Elation Health
Next year, I predict AI will move into a more proactive and predictive role, utilizing population health data to guide care teams on preventative intervention strategies and resource allocation before issues arise. This shift will redefine patient-provider interactions toward continuous, data-driven whole person management.
Ann Bilyew, president of WebMD Ignite
In 2026, the challenge won’t be generating more content. Instead, it will be ensuring that content is trusted, clinically aligned and delivered at precisely the right moment in the patient journey. The organizations that succeed will be those that can pair high-quality, evidence-based content with AI systems sophisticated enough to anticipate what patients need next and guide them toward appropriate care. AI won’t replace the human relationship in healthcare, but it will increasingly shape how, when and why patients engage with their providers.
Stephen Smith, cofounder and CEO of NOCD
AI is already starting to show real promise in healthcare, particularly in supporting provider-led care and automating the kinds of administrative tasks that have long weighed down clinicians.
This past year, we’ve seen strong adoption of ambient note-taking tools, which not only save time but also capture a much richer layer of clinical data. That data is starting to unlock new insights into care patterns, treatment effectiveness and patient needs.
Looking ahead, 2026 will likely be the year those insights move from observation to action. We’ll see AI begin to surface real-time clinical guidance, help tailor treatment plans and even predict when patients might need interventions before issues escalate. At the same time, the industry will keep a close eye on trust, bias and transparency.
Ahmed Elsayyad, cofounder and president of Ostro
I believe health systems consolidate dozens of point solutions into a few AI platforms with unified governance, audit and procurement.
I think there will be a wider use of models that combine text + imaging + vitals for early deterioration warnings and specialty decision support (still clinician-supervised).
Ambient scribing will expand beyond visits into procedures and inpatient rounds, generating coded data for quality and research.
I also think there will be formal CME/CE training on AI literacy and new roles, like AI safety officer, prompt librarian [and] model steward, will become common.
Joy Bhosai, CEO and founder of Pluto Health
Looking ahead to 2026, we’ll likely see even deeper collaboration between AI systems and clinical workflows, with technology augmenting care rather than having a conversation about how it will replace humans. Expect more solutions that automate administrative tasks and streamline patient triage.
Beyond functionality, the focus will increasingly be on usability, reliability and building trust, ensuring that clinicians feel confident in the recommendations AI provides and that patients experience safer, more efficient care.
Sanjay Doddamani, founder and CEO of Guidehealth
Looking to next year, AI will move from powering discrete interventions to supporting more longitudinal navigation. Integration into EHRs, health plan systems and care management operations will deepen. The organizations that align AI deployment with clinical governance and accountable workflows will see measurable improvement in outcomes and cost trends, while those that treat AI as an isolated tool will face limited impact.
Mudit Garg, CEO and founder of Qventus
In 2025, healthcare leaders are leaning in more and more; there’s an explicit desire to figure out exactly what they're going to do with AI rather than just discussing possibilities. Going forward, the focus needs to shift from simple task automation to full workflow transformation. To deliver real value for patients, staff and the system, we need to re-engineer entire processes, not just automate isolated tasks. That's where the meaningful ROI lives.
