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 2 tomorrow and all our prediction posts looking to 2026.
Ryan Bosch, Chief Health and Informatics Officer, Acentra Health
LinkedIn: Ryan Bosch MD
As health systems adopt AI tools, their effectiveness will depend on strong data foundations and thoughtful integration into daily workflows. When clinicians trust the inputs and outputs, AI becomes a practical extension of the care team rather than a novelty or risk. With the right guardrails, AI’s predictive capabilities and real-time support have the potential to strengthen clinical care and operations, and ultimately, improve patient outcomes.
AI will also move deeper into clinical settings to close gaps in accessibility. Virtual health assistants and mental health support tools will help reach populations that have historically had limited access to physical and mental healthcare. The key to meaningful impact is not the technology itself, but the quality of the data and clinical oversight guiding it.
Donovan Campbell, CEO, Medbridge
LinkedIn: Donovan Campbell
If the last few years were marked by AI experimentation, 2026 will be the year AI matures. We’ll see it applied to more patient-facing functions in clinical settings, driven in part by growing patient comfort with AI tools. We anticipate clinicians will increasingly use AI to support care progression, coach patients in between live visits, and assist in decision-making for lower-acuity cases.
Mike Coen, Chief Product & Technology Officer, TeleTracking Technologies
LinkedIn: Michael Coen
AI is becoming a powerful catalyst for transforming hospital operations by turning real-time insights into coordinated automated action across the care journey. By intelligently streamlining task management, patient placement, and discharge workflows, it reduces administrative friction and keeps the right work happening at the right time. This orchestration will lighten the invisible burden on care teams, allowing clinicians and operational staff to focus more fully on direct patient care. The result is faster access to care, smoother patient flow, and improved outcomes driven by operations that actively support the care process.
Kevin Dawson, Chief Technology Innovation Officer, Los Angeles Network for Enhanced Services (LANES)
LinkedIn: Kevin Dawson
In 2026, we anticipate AI will be increasingly used for automating administrative tasks. For physicians, this will be demonstrated through the use of ambient clinical AI to transcribe and interact with EHR systems. We also expect human-machine interactions to become more context-specific, which holds promise for transforming how data is shared, accessed, and trusted among care providers across the healthcare ecosystem.
David Everson, Senior Director of Solutions Marketing, Laserfiche
LinkedIn: David Everson
Healthcare organizations will double down on digital transformation to meet the growing wave of compliance mandates, from price transparency and quality reporting to the new prior authorization rule. These regulations are reshaping how providers manage, document, and share information, pushing interoperability and automation to the top of every healthcare organization’s agenda.
To stay ahead, healthcare systems will increasingly integrate digital records across departments and implement AI-driven tools to automate compliance reporting and improve patient engagement. AI and process automation will not only streamline documentation and administrative workflows but also provide actionable insights into care quality and operational efficiency. As a result, organizations will be better positioned to measure outcomes, reduce staff burnout, and deliver a more transparent, patient-centered experience. The most forward-thinking healthcare providers will redefine what “connected care” means through intelligent, data-driven ecosystems built on trust, traceability, and measurable improvement.
Houda Hachad, Vice President of Clinical Operations, Aranscia
LinkedIn: Houda Hachad
In 2026, AI will become a true frontline partner in clinical care. It will analyze symptoms, vital signs, and risk indicators in real time, helping route patients to the right level of care before they ever enter the exam room. As digital intake expands, remote triage will finally scale, but only with strong clinical oversight to ensure algorithms don’t over-triage or miss critical cases.
Luke Hansen, MD, MHS, Chief Medical Officer, Arcadia
LinkedIn: Luke Hansen
AI will continue making steady progress across multiple clinical use cases in 2026, with the greatest near-term gains in tools that support clinical documentation and reduced administrative burden. While further development around true clinical decision support will continue behind the scenes, participants in the healthcare ecosystem are almost certain to see documentation support, including ambient listening technologies, in use. Administrative tasks, such as the expanding set of prior authorization workflows, assessing who qualifies for Medicaid, and administering new work requirements, are also poised for automation through AI adoption.
Beyond these functions, AI will continue to mature across triage, patient engagement, virtual health assistants, and mental health. These applications hold enormous promise, but clinician comfort, patient expectations, and broader cultural acceptance will shape their advancement. This is less a one-year leap and more a generational shift, with 2026 marking another step forward in a long trajectory of refinement.
Beyond 2026, increasingly sophisticated models are being trained on large, diverse patient populations, allowing AI to surface, in real time, what an individual patient in the exam room is most likely to benefit from. This has the potential to significantly improve diagnostic accuracy and overall clinical decision-making.
Dr. Shannon Housh, EdD, MBA, MHA, LCC, Director of Consulting Services, CenTrak and Leapfrog Certified Coach
LinkedIn: Dr. Shannon Housh, EdD, MBA, MHA, LCC
I expect a significant uptick in major health systems adopting Real-Time Location Systems (RTLS) as core infrastructure in 2026. By core infrastructure, I mean RTLS that’s fully integrated with the EHR, nurse call, environmental controls, security, and scheduling systems. Once embedded at this level, AI will take on a larger role in monitoring patient movement, turnover sequences, environmental triggers, and automated equipment redeployment. These capabilities will enable near–real-time load balancing, reducing ED and inpatient bottlenecks by more than 40%, increasing OR utilization to approximately 85% predictability, and driving lost equipment rates toward zero. AI-assisted assignments will become more common, equipment will be easier to locate (saving valuable time), and burnout metrics are expected to improve significantly. These aspects will reduce the burden of administrative tasks on the clinicians, returning time to direct care and boosting patient outcomes, human connection, and staff retention.
Lucienne Marie Ide, M.D., PH.D., Founder and Chief Executive Officer, Rimidi
LinkedIn: Lucienne Ide
In 2026, AI’s focus in healthcare will go from experimental pilots to practical, scalable deployments. While AI’s impact on administrative and back office work scales up, quickly becoming standard practice, we will see a more meaningful adoption of AI-enabled tools into clinical workflows. Success is contingent on AI’s ability to make data actionable at the point of care, seamlessly integrating into EHR systems to improve efficiency and outcomes without adding to clinicians’ workloads all while managing and mitigating risk and privacy concerns. The move toward responsible, practical AI will call for human oversight of processes, auditable performance, and continuous bias monitoring.
Dr. Nele Jessel, Chief Medical Officer, athenahealth
LinkedIn: Nele Jessel, MD
In 2025, AI has made significant strides and for many clinicians, it has proven to be a helpful tool that can accelerate workflows, ease daily administrative burden, and improve operational efficiency. In 2026, we will see AI advance past this use case into a technology that will transform care delivery. AI will help clinicians cut through the noise and move beyond administrative tasks to truly support patient care. Clinicians and staff will come to see AI as an assistant that can help them see the full picture by surfacing relevant information and identifying patterns that humans can’t easily see to ensure there are no oversights. With AI acting as a second mind, it will transition from artificial to augmented intelligence, quietly supporting the clinician experience by reducing friction for both clinicians and patients, and care delivery will improve.
Simon Kos, Chief Medical Officer, Heidi
LinkedIn: Simon Kos
With appetite for paid AI scribes most evident in the US geography, hospital segment, and physician role, the market features AI companies narrowly targeting this opportunity. This places a bottleneck on scale and learning through broad based adoption. 2026 will see AI scribes with the largest volumes creating far better out-of-the-box personalization for specialty groups, and use will broaden beyond physicians to clinicians of all types. This includes nursing and allied health, and health adjacent verticals like dental, disability services, and social services. This broad adoption will shift the dominant paradigm of data entry from mouse and keyboard to voice by default.
Craig Limoli, CEO, Wellsheet
LinkedIn: Craig Limoli
In 2026, clinicians will get the pleasure of being just clinicians again, AI agents will allow clinicians to check notes at the door. AI will help guide clinical pathways by giving clinicians visibility into the most effective path forward with access to the patient’s entire chart and answer questions quickly so more of their time can be spent on clinical judgement. Health systems will need to make sure they have safety protocols in place and a human in the loop approach ensuring patients’ needs are met.
William H. Morris, MD, MBA, Chief Medical Officer, Ambience Healthcare
LinkedIn: William H. Morris, MD, MBA
Ambient listening helped clinicians in 2025, but alone it’s not sufficient for the demands ahead. Health systems now need true ambient intelligence. These are systems that relieve not just documentation burden, but overall cognitive burden. They prepare clinicians before a visit. They enable clinicians to fully engage with and support their patients using the latest clinical guidelines. They also handle critical administrative and revenue cycle work after encounters that clinicians have historically absorbed. High reliability, accuracy, and auditability will be the defining opportunities, and they will separate the leading platforms from the rest.
Bilal Muhsin, EVP and President of Connected Care, Becton, Dickinson & Co.
LinkedIn: Bilal Muhsin
In the past, medical devices were narrowly focused tools, engineered to excel at one function. Today, I’m seeing a transformation, devices are easier to use and increasingly deployed across diverse care settings. This shift is making a tremendous impact on patient care and simplifying clinicians’ workflows.
What excites me most is how medical devices are now connected to larger networked systems, enabling real-time data capture and analysis. This improved connectivity makes devices smarter, whether by notifying clinicians of patient deterioration or automating workflows to improve patient safety.
My vision for 2026 is to continue to move beyond basic data transfer, toward building intelligent platforms that turn raw information into knowledge that clinicians can use immediately. With BD Incada, our new cloud-based platform powered by AI, we can transform data from BD devices into information that helps clinicians make faster, more informed decisions. Combined with innovations like BD Pyxis Pro, which delivers smarter, more secure medication storage at the point of care, we’re enabling hospitals to quickly access critical information on medication management and inventory levels, to support improved medication safety.
Generative AI, once experimental, is now delivering real-world scalable applications that save time and reveal insights from massive datasets. These advancements will help clinicians move from reactive to predictive care, improving patient engagement, safety, and outcomes. Ultimately, AI in clinical settings is about empowering providers to deliver smarter, safer, and more proactive care.
Lindsay Oberleitner, Ph.D., LP, Head of Clinical Strategy, SimplePractice
LinkedIn: Lindsay Oberleitner, Ph.D., LP
We keep debating whether AI belongs in mental health care, but that debate is moot at this point as patients are using AI tools to process their feelings (whether therapists approve or not). In 2026, clinicians need to stop only treating AI as a threat to avoid and start treating it as a reality to address and manage. That means creating space in sessions to discuss what patients are doing with these tools, and helping them use AI safely, effectively, and with appropriate limits. When acknowledged, rather than ignored, AI can become a legitimate part of the treatment process, but only if clinicians are willing to engage with it.
Morris Panner, President, Intelerad
LinkedIn: Morris Panner
AI embedded in radiology workflows will redefine productivity and diagnostics
By 2026, AI in medical imaging will no longer exist as a collection of isolated use cases. It will be embedded directly into core radiology workflows as an orchestrated, auditable layer of daily operations. This shift will be driven by emerging regulations, evolving reimbursement models, and sustained financial pressure on health systems to increase productivity without sacrificing quality.
The next phase of AI adoption will be defined by governance. Health systems will prioritize standardized model management, continuous bias monitoring, and clearly defined human oversight to ensure performance gains do not compromise diagnostic integrity or patient trust. AI will increasingly manage study prioritization and routing based on acuity, complexity, and clinical context.
This level of orchestration will enable providers to address shrinking margins by improving report turnaround times, reducing unnecessary repeat studies, and supporting consistent diagnostic accuracy at scale.
As AI progresses from an interpretation tool to a foundational component of sustainable diagnostic operations, its impact will extend beyond efficiency alone. Its success will be measured by improved experiences for radiologists, care teams, and patients, while strengthening clinical performance and long-term client success across the imaging enterprise.
Marc Samuels, CEO, ADVI Health
LinkedIn: Marc Samuels
AI in clinical care is no longer a future aspiration, but a present-day reality, driven by its immense potential to improve outcomes, cut costs, and solve workforce shortages. Moving into 2026, while regulatory hurdles will continue to persist, notably the CMS’s refusal to reimburse software as a direct clinical expense, the industry will forge ahead, supported by initiatives like the FDA’s AI Scientific Review Pilot, to further integrate AI across diagnostics, administrative tasks, and drug development. This rapid adoption, however, will intensify the focus on critical guardrails to maintain patient privacy and actively mitigate bias within AI models, ensuring equitable care for all patients.
Scott R. Schell, MD, PhD, MBA, Chief Medical Officer, Cognizant
LinkedIn: Scott Schell
The near-term productivity lift will come less from diagnosis and more from documentation and workflow improvements. Ambient scribes, smart scheduling, and denial-prevention tools are already reclaiming hours for clinicians and support staff. In life sciences, generative systems now draft clinical protocols, summarize literature, and flag pharmacovigilance signals. Individually, each task may seem small, yet together they return time, attention, and morale. The best systems disappear into workflow. They make existing infrastructure breathe again. The real advance is when the workday feels lighter and the care feels closer.
Evan Steele, CEO, rater 8
LinkedIn: Evan Steele
Today, much of patient sentiment lives in online reviews, portal messages, and social channels that staff struggle to evaluate consistently and holistically. In 2026, AI will aggregate these insights, detect recurring themes, and bring attention to patterns that may otherwise be missed, such as communication gaps or poor bedside manner. Acting on patient sentiment to adjust scheduling, clarify billing, or improve communication, and informing patients of these changes, makes them feel heard.
Additionally, rather than relying on a survey sent days after an appointment, AI will identify moments during the care journey when patients are most apt to share input and will prompt them with short, timely questions. This approach encourages higher response rates and fosters more meaningful participation from patients. In 2026, AI will play a central role in strengthening patient engagement by making feedback easier to share, more relevant, and more likely to drive action. This increases patient trust and encourages ongoing involvement in their care.
Pete Stetson, Chief Medical Information Officer, TigerConnect
LinkedIn: Pete Stetson
AI-Driven Orchestration in Smart Hospitals Will Reduce Clinicians’ “Middleware Role”
Today’s healthcare system is fraught with friction, which puts immense strains on both the delivery and experience of care for patients, caregivers, and clinicians. Too often, clinicians serve as the “middleware” to bridge disconnected systems, devices and processes. Having to remember status updates, chase information, handle patient needs outside of clinical care and repeat the same messages to multiple colleagues drives inefficiency and clinician burnout. Communication tools alone cannot alleviate this burden effectively and in 2026, AI-driven orchestration will rise to fill that critical gap.
Hospitals need an intelligence layer to organize, route, and seamlessly connect the work in the background. AI will absorb that “middleware burden” and smart orchestration engines will interpret context, recognize stalled workflows, surface the right data at the right time, and automatically escalate when needed. With this shift, the focus will transition from point solutions to intelligent ecosystems that deliver outcomes-based workflows. As these orchestrated systems evolve, clinicians will be empowered to work more efficiently, leading to measurable improvements in efficiency, a reduction in errors, and decreased time spent by nurses on non-clinical tasks.
Julia Strandberg, Chief Business Leader, Connected Care, Philips
LinkedIn: Julia Strandberg
In 2026, AI will orchestrate care across the end-to-end patient journey: In 2026, the real breakthrough in clinical AI won’t be from the arrival of new tools and solutions, it will come from unifying the ones already in place.
Hospitals today are burdened by fragmented clinical workflows and siloed data, forcing clinicians to manually piece together information when their focus should be on delivering care to patients. These inefficiencies slow diagnosis, complicate triage, and add friction to every step of the patient journey.
Throughout 2026, we will see AI break down these barriers. It will automate routine documentation, streamline administrative tasks, enhance triage workflows, and support remote bedside monitoring. Equally important, AI will synthesize and interpret data from disparate systems, transforming disconnected inputs into clear, actionable insights at the point of care.
By reducing administrative burden and enabling smarter, faster clinical decisions, AI will serve as the connective tissue across the care continuum, helping clinicians reclaim time, reduce complexity, and deliver a more seamless, coordinated experience for every patient.
Sundar Subramanian, CEO, Zyter/TruCare
LinkedIn: Sundar Subramanian
Explainable AI Becomes a Clinical Imperative, Shifting Care From Recommendations to Reasoned Workflows
The most important clinical AI breakthrough in 2026 won’t be accuracy. It will be explainability built directly into daily workflows.
AI systems will not only generate alerts or recommendations; they will display their confidence levels, the evidence behind each output, and how their reasoning aligns with established clinical pathways.
When AI behaves less like a calculator and more like a collaborator, learning from physician feedback and adapting in real time, override rates collapse and confidence soars.
This shift transforms AI from a second opinion into a true member of the care team.
In 2026, understanding the AI will matter as much as the result it produces. That is how we usher in an era of truly collaborative, intelligent medicine.
Jim Szyperski, CEO, Acuity Behavioral Health
LinkedIn: Jim Szyperski
In clinical behavioral healthcare settings like inpatient psychiatry, the patient experience is predominantly driven by the care they receive from nursing staff, who in my experience are simply extraordinary, dedicated, empathetic and caring. Unfortunately, there are not enough of them and the rates of attrition, either from burnout or plain old retirement are high. And they are not being replaced fast enough forcing the use of technicians and others to fill needed roles in the absence.
Access to behavioral healthcare is poor today and just growing poorer due to:
- Closure of rural facilities, the exit or planned exit of many facilities from behavioral healthcare, and the scarcity of trained psychiatrists and behavioral healthcare providers.
- An acute shortage of psychiatrists, psychiatric nurses, and trained clinical staff.
- A national shortage of inpatient beds.
- Emergency departments overrun with patients, with up to 15-20% being there for psychiatric reasons
For all the above reasons, there is a screaming case for technology to provide care for these patients and to give the clinical staff the most asset of all, their time. More time to care for patients with time freed up from administrative tasks or looking for data they do not have access to so they can make better clinical decisions in their patient care.
Jordan Taradash, CEO, PeopleOne Health
LinkedIn: Jordan Taradash
AI will hone in on its purpose(s) in healthcare. After years of hype and widespread exploration, 2026 will be the year AI shifts from broad experimentation to targeted impact. Its greatest use will come from automating administrative work to free up clinicians’ time to focus on patients, while improving both virtual and in-person care with guidance and clinical decision support throughout the care journey.
Greg Tietjen, CEO, Revalia Bio
LinkedIn: Greg Tietjen
Next-gen safety: Toxicology specific Human Data Trials will identify human-specific adverse responses early, cutting clinical attrition due to toxicity by a significant margin.
Mechanistic risk mapping: Integrated molecular and cellular profiling of human tissues will uncover target-specific liabilities invisible in animal models.
Human-first go/no-go decisions: Human Data Trials will allow pharma partners to terminate non-viable assets earlier based on human relevance metrics.
Xavier Trilla, Venture Associate, Silicon Foundry
LinkedIn: Xavier Trilla
As AI gains agency, our interaction with technology may paradoxically diminish. We’ll move from commanding systems to collaborating with them, where intent, not input, drives action. As machines better understand context and anticipate needs, interaction will become faster and more fluid. Interfaces will simplify and fade, with voice, automation, and ambient cues replacing clicks, keyboards, and screens. Even as technology becomes more deeply embedded in our world, our engagement with it will feel lighter, more natural, and hands-off.