According to the Mercer Future of the US Healthcare Industry, Healthcare Labor Market Projections by 2028, it expects a shortage of about 100,000 critical health care workers by 2028. The Association of American Medical Colleges (AAMC) projects a shortage of up to 124,000 physicians by 2034.The American Hospital Association estimates that the US will need to hire at least 200,000 nurses a year to meet rising demands. The question is no longer will AI take the professional’s job, but how can we use AI to fill the future voids we are predicting. AI-powered automation can enable staff to spend less time on routine administrative work and shift their attention to areas where they add more value, like direct care and patient-facing activities.
In 2025 AI became a front line solution to healthcare workforce shortages and challenges. Will we continue to invest in AI innovation that will help us in our biggest future challenge? We asked our experts what progress they think we will see in 2026. Here is what they had to say.
And check out all our prediction posts looking to 2026.
Daniel Blumenthal, Vice President of Strategy, MDClone
LinkedIn: Daniel Blumenthal
When AI is designed to amplify clinical expertise, it becomes a force multiplier for an overextended workforce. Giving healthcare workers the ability to quickly uncover patterns and validate decisions empowers them to deliver better care, and to do so more efficiently and with more confidence than before.
Fawad Butt, CEO and Co-founder, Penguin Ai
LinkedIn: Fawad Butt
Seventy-five (75%) percent of healthcare’s $1 trillion in administrative waste comes from just ten processes, with prior authorization, claims denial & appeals being two of the largest culprits. Operators have too many tasks and too little bandwidth. If organizations can lay the right data foundation, AI can truly remove those burdens so clinical review staff can focus on patients, not paperwork. Real progress is made when technology gives people back the time and energy they need to do the work only humans can do.
Betsy Castillo, RN, VP of Clinical Data Abstraction, Carta Healthcare
LinkedIn: Betsy Castillo
AI is starting to play a bigger role in tackling workforce challenges across healthcare. From automating routine data abstraction to easing the burden of quality reporting, organizations are finding ways to redirect staff time toward higher‑value work, such as taking care of patients or using data to improve quality. The real opportunity lies in using AI to stabilize operations and reduce burnout, while still maintaining the accuracy and trust that providers and regulators demand.
Jason Considine, President, Experian Health
LinkedIn: Jason Considine
The vision for 2026 is clear: Organizations must leverage technology to move beyond AI awareness to the seamless integration of AI in our daily workflows, ensuring that we empower staff rather than distract them with new complexities. For large-scale AI adoption, organizations must trust the technology, and we as vendors have to think critically about how to infuse it into provider workflows with transparency and without creating additional challenges. When humans and technology work together, we can simplify healthcare for all.
Noel Felipe, SVP and Revenue Cycle Practice Leader, Firstsource
LinkedIn: Noel Felipe
AI as a Frontline Stabilizer for Revenue Under Payer Mix Shifts
As payer mixes continue to shift toward higher-deductible and self-pay populations, health systems will increasingly rely on AI to strengthen front-end financial processes without expanding labor-intensive workflows. AI-enabled agents embedded in digital access points will help standardize coverage verification, estimate patient responsibility, and guide patients toward appropriate financing options in real time. These capabilities will reduce avoidable denials and bad debt, while giving patient access teams the support they need to manage rising financial complexity. In 2026, leaders will view these AI-driven workflows as essential elements of cash-flow stability and workforce efficiency rather than discretionary innovation.
Pietro Ferrara, Senior Vice President Margin and Operational Intelligence, The Craneware Group
LinkedIn: Pietro Ferrara
Hospital leaders are beginning to wrap their heads around the operational and financial benefits of AI, spurred by the imperative to find efficiencies and reduce costs. Administrators are rapidly evaluating how to integrate AI to alleviate staffing shortages by automating repetitive administrative tasks, enabling staff to focus on higher-value work and helping to reduce professional burnout. In addition, AI will become a critical tool for right-sizing staffing levels to fluctuating patient volumes due to its ability to rapidly synthesize and analyze real-time data.
Jenn Geetter, Partner, McDermott Will & Schulte
LinkedIn: Jennifer Geetter
AI tools will continue to shape and reshape how health care professionals take care of patients. The number of AI tools that effectively improve the patient experience and patient outcomes, help to better manage health care spending (in part by facilitating prevention), and minimize the on-going challenges of provider burnout will continue to increase. This is a two-sided sword, however. IT professionals will likely be asked to vet more technologies, more quickly and will need to take affirmative steps to create a constructive pipeline of technologies to pilot to avoid deluge-by-pilot. The so-called “human in the loop” safeguard only acts as one when the humans in the loop understand how to use the technology, what it does well, and what it doesn’t do well, and have clear clinical guidelines on how to use the tool. This takes time, training and practice. The on-going uncertainty about the respective roles of states and the federal government to set responsible AI policy may add twists and turns to adoption and developers and deployers will need to consider best practices absent consensus on the role of regulation. Clinicians will continue to look to certain AI tools as critical time savers to avoid tasks that diminish the job satisfaction and to look at certain AI tools with deep wariness for what they mean for the workforce. All of this means that the trend line for AI adoption is likely to be directionally upwards but with lots of fits and starts obscured in this trend.
Susan Grant, Chief Clinical Officer, symplr
LinkedIn: Susan Grant, DNP, RN, NEA-BC, FAAN
In 2026, we’ll finally start to ease the pressure on the people doing the hands-on, patient-facing work. Smarter staffing tools will help us shift from being reactive every shift to planning ahead and being more proactive. That shift will make a noticeable difference in how supported nurses feel. I also expect more nurses to be more visible and involved in technology decisions, because we can’t build the future of care without the people delivering it. Perhaps most importantly, we’ll see organizations invest in developing nurses at every stage of their careers, not just to keep them, but to help them grow and advance. When we do that well, the entire system becomes stronger.
Jan Grimm, CEO, Savista
LinkedIn: Jan T. Grimm
Workforce Challenges Will Inspire Innovation
The healthcare labor shortage presents an opportunity for creative leadership and strategic innovation. Revenue cycle leaders can enhance productivity through strategic outsourcing and flexible hybrid models. The future belongs to organizations that embrace bold solutions and transform workforce challenges into competitive advantages, maximizing the specialized human expertise with tools and operational support to drive efficiency.
Luke Hansen, MD, MHS, Chief Medical Officer, Arcadia
LinkedIn: Luke Hansen
In 2026, AI will continue to expand its role in administrative automation, but it won’t replace clinicians. We’re still multiple innovation cycles away from technology that could meaningfully serve as a substitute for the healthcare workforce. The near-term opportunity is to use AI to reduce administrative burden and redirect that time toward better experiences for patients and the clinicians who care for them.
A good example is ambient clinical documentation. Its adoption curve looks like other early-stage technologies, some organizations are enthusiastic, others are cautious, and the technology itself is still evolving. Despite the hype, ambient tools today operate closer to advanced transcription than true clinical documentation support. There’s still important work ahead before they deliver on their full promise.
Patty Hayward, General Manager of Healthcare and Life Sciences, Talkdesk
LinkedIn: Patty Hayward
In 2026, we’ll stop treating the healthcare contact center as a cost center we tolerate and start recognizing it as the experience engine patients meet first. AI won’t only backfill staffing shortages; we will see it start to change how front-line work happens. The winners will be the health systems that understand this: AI isn’t here to dehumanize the contact center, it’s here to make it a place worth working, and a place patients want to call.
Carol Howard, Vice President of Innovation and Adoption, Janus Health
LinkedIn: Carol Howard
In a healthcare landscape marked by burnout and ongoing staffing challenges, providers will increasingly adopt AI to improve efficiency across the revenue cycle, allowing teams to focus on more meaningful work. Revenue cycle management lends itself naturally to automation, given its reliance on repeatable tasks, data-heavy analysis, and rules-based decisions. When intelligent automation is combined with operational insight, health systems simplify workflows, make better use of resources, and enhance staff productivity and satisfaction.
Dr. Shannon Housh, EdD, MBA, MHA, LCC, Director of Consulting Services, CenTrak and Leapfrog Certified Coach
LinkedIn: Dr. Shannon Housh, EdD, MBA, MHA, LCC
AI-supported RTLS will be expected by new & current staff
When new hires interview at a hospital, most expect that the health system is already leveraging technology such as Real-Time Location System (RTLS), especially for staff duress solutions. These rising expectations from both new and current staff will drive hospitals, globally, to implement system-wide RTLS deployments with AI-support in 2026, staff duress and asset tracking being the typical starting points. Prioritizing safety is non-negotiable. As RTLS becomes standard practice in 2026, with a significant push for the increased use of staff duress solutions, AI integrations will take on a larger role. These tools will enhance actionable reporting, heat-mapping, and basic predictive insights that help address equipment shortages, overused ORs, ED flow bottlenecks, cost savings, and duress situations. With continuous monitoring powered by AI, I anticipate meaningful operational gains: a 10–15% improvement in equipment utilization, a 12% reduction in lost or missing mobile medical equipment, and an 8% improvement in ED wait times.
Evan Huang, Chief Technical Officer, Lightbeam Health Solutions
LinkedIn: Evan H.
Ambient listening tools powered by generative AI are rapidly becoming foundational to addressing workforce strain, with early clinical evidence showing meaningful impact on documentation burden and burnout. In a large JAMA Network Open study, Mass General Brigham saw a 21.2% absolute reduction in burnout at 84 days, while Emory Healthcare reported a 30.7% increase in documentation-related well-being at 60 days. A Yale-led multicenter trial similarly found burnout prevalence fall from 51.9% to 38.8% after just 30 days of AI scribe use, reflecting a substantial reduction in the odds of burnout. In 2026, these tools will evolve beyond passive documentation capture to become real-time clinical co-pilots, helping systems counteract staffing shortages, reduce cognitive load, and enable clinicians to work more efficiently at the top of their license.
Ankit Jain, Founder and CEO, Infinitus
LinkedIn: Ankit Jain
AI agents will be critical in 2026 as resource-starved providers free up thousands of virtual hours.
- We have a generation of healthcare leadership that approaches roadblocks with a lens of scarcity. Instead, these leaders who are searching for resources to help with workload should be using agentic to inspire them to think in abundance.
- Abundance v. scarcity…what could you do if you had an abundance of labor? Agentic solutions make this theoretical question a reality.
Sandra Johnson, SVP of Client Services, CliniComp
LinkedIn: Sandra Johnson, CDH-E
Over the next year, AI will become a true workforce multiplier in healthcare, automating administrative tasks, reducing documentation load, and triaging routine requests so clinicians can focus on patient care. AI will give clinicians back meaningful time and ease the burnout that drives turnover. Health systems that embed AI directly at the point of care, supported by clinician trust, workflow alignment, and responsible governance, will see the greatest gains in retention and long-term workforce resilience.
Samantha Keating, MBA, Healthcare Product Marketing Manager, FDB
LinkedIn: Samantha (Sweeney) Keating, MBA
AI will continue to help reduce some of the operational burdens that contribute to nursing workforce burnout by automating administrative tasks, such as delivering essential patient education. Quickly accessing simple, personalized medication information at the bedside can cut down the time nurses spend searching for resources and increase the time they spend with patients. As these capabilities develop, AI will enhance communication, support nurse well-being, and improve the overall care experience.
Simon Kos, Chief Medical Officer, Heidi
LinkedIn: Simon Kos
As AI tools continue to bring about undeniable relief to physicians, more doctors will experiment independently, using unsanctioned or “shadow” AI for note-taking, patient summaries, and more. Already, a large chunk of physicians are using generative AI in clinical work, often without formal approval or oversight. According to a recent survey published by email security provider Paubox, 62% of healthcare IT and compliance leaders have observed staff experimenting with ChatGPT or similar tools even though they’re unsanctioned, and 72% surveyed believe employees assume tools like Microsoft Copilot automatically support HIPAA compliance. 2026 will bring a reckoning: health systems will need to balance innovation with governance, giving staff safe, compliant tools rather than forcing them to improvise or forcing them to work with tools that they don’t enjoy using.
Itzik Levy, CEO, vcita
LinkedIn: Itzik Levy
As staffing shortages persist, healthcare organizations must rethink how work gets done. AI offers a sustainable path forward by automating routine administrative tasks that traditionally drain staff time and energy, contributing to burnout. This isn’t about replacing people. It’s about giving clinicians intelligent assistants that handle scheduling, documentation, follow-ups, and first-line patient inquiries, so that teams can finally focus on providing meaningful human care. This shift not only reduces burnout but also stabilizes operations when hiring lags. AI operates as a dependable virtual colleague, ensuring continuity, consistency, and support, something every patient demands and every care team needs more than ever.
Jackie Mattingly, Senior Director of Consulting Services, Clearwater
LinkedIn: Jackie Mattingly
Healthcare might not see the mass layoffs some predicted and instead, AI adoption will accelerate as leaders look for ways to ease documentation burden and keep clinicians focused on patient care. But as AI becomes embedded into EHRs, RCM, and clinical decision-support tools, it will also expand the attack surface, especially with adversaries already using AI for phishing and credential theft. In 2026, the real differentiator will be whether organizations apply the same rigor to AI governance that OCR expects for HIPAA risk analysis. The winners will be those who balance productivity gains with disciplined security controls and model oversight.
Cabul Mehta, Industry Principal, Healthcare and Life Sciences, Presidio
LinkedIn: Cabul Mehta
AI will become a frontline strategy to reducing clinician burnout in 2026: Navigating modern care delivery with outdated systems and inefficient technology is directly correlated to clinician burnout, with 95% of healthcare professionals claiming that outdated tech contributes to rising stress levels and even drives some to use unsanctioned tools. In 2026, organizations that bring AI into everyday workflows to streamline admin heavy tasks including documentation, scheduling, and billing will give clinicians more time to focus on patient care, reducing the risk of burnout.
Steve Mok, PharmD, MBA, BCPS, BCIDP, Manager of Pharmacy Services and Fellowship Director for Clinical Surveillance and Compliance, Wolters Kluwer Health
LinkedIn: Steve Mok, PharmD, MBA, BCPS, BCIDP
Pop culture examples like The Pitt and Nurse Jackie portray a glimpse of the world of drug diversion, but in reality, diversion impacts thousands of healthcare workers, and the even larger number of patients they serve. More troubling, a recent survey showed as many as 2/3 of healthcare leaders lack confidence in their diversion prevention programs. With thousands of record reviews required to deduce suspicious patterns, AI-backed solutions quickly become a necessity for organizations looking to take a proactive and holistic approach to patient and staff safety. As hospitals look to ramp up their AI investments in 2026, drug diversion is a low hanging fruit where timely, automated deduction and pattern recognition can quickly enable teams to reduce harm to patients and staff.
Ali Morin, Chief Nursing Informatics Officer, symplr
LinkedIn: Allison Morin MSN, RN, NI-BC
In 2026, organizations must focus on building clinical trust in AI as a tool that strengthens and supports workflows. As AI becomes more integrated into care delivery, addressing fears and setting clear expectations will be critical to ensure it adds value for nurses and clinicians rather than creating new challenges and steps in their processes. With 85% of clinicians wanting a voice in technology decisions, involving them early and maintaining engagement after implementation will be essential. By showcasing real-world results and reinforcing that AI is designed to ease burdens, not replace human judgment, we can help nurses navigate workforce shortages while preserving the human connection at the heart of patient care.
Dan Nardi, CEO, Reimagine Care
LinkedIn: Dan Nardi
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. The real opportunity with AI isn’t eliminating roles; it’s enabling clinicians to practice at the top of their license.
Take oncology as an example. We have a massive shortage of oncologists in this country, yet they’re spending significant time on routine cases that follow established treatment protocols. With AI-powered platforms like ours, we can handle a large volume of these traditional cases, managing symptoms, monitoring treatment response, coordinating care, answering patient questions. This frees oncologists to focus on the complex cases that truly require their specialized expertise: rare cancers, treatment-resistant cases, clinical trial decisions, and end-of-life care conversations.
Our nurses are experiencing the same shift. Instead of routine check-in calls and basic symptom monitoring, they’re spending time on the patients who need more intensive support and clinical judgment. AI handles the volume; clinicians handle the complexity. The jobs that will evolve are those that involve repetitive, protocol-driven tasks. But we’re not eliminating healthcare workers, we’re dramatically expanding their capacity to deliver high-value care where it matters most. In a system facing critical workforce shortages, that’s not just efficiency, it’s necessity. The question isn’t whether AI will change healthcare jobs, but whether we’ll use it to address our access crisis while improving care quality. We believe the answer is yes.
David Pessis, Chief Product and Technology Officer, PointClickCare
LinkedIn: David Pessis
In 2026, AI will play a critical role in addressing the healthcare workforce crisis. As staffing shortages persist, AI will automate the most time-consuming administrative work, whether it be documentation, scheduling, compliance, or other tasks, and free clinical and operational teams to focus on care delivery. The organizations that succeed will use AI in this way to enhance, not replace, human expertise and build systems that reduce burnout, restore time for patient interaction, and empower caregivers to do their best work.
Misty Phillips, MLS(ASCP) MB, Technical Laboratory Educator, Thermo Fisher Scientific
LinkedIn: Misty Phillips, MLS(ASCP) MB
Looking ahead, AI and automation will lead to strong, visible laboratory leadership and overall workforce empowerment. AI will continue to redefine testing roles in laboratories, allowing investment in continuous education and reskilling of lab staff. We’re already seeing growing momentum around ensuring the sustainability of the workforce through fair pay, staffing standards and union representation. AI will enhance this momentum, giving professionals time to focus on leadership development and professional advancement, ultimately transforming the work environment for lab staff at all levels.
Hari Prasad, CEO, Yosi Health
LinkedIn: Hari Prasad
In 2026, AI will be moving from the pilot program stage to everyday workhorse. That will help reduce the most repetitive, burnout-inducing, administrative tasks for healthcare facilities. In practice, that means voice AI assistants handling large chunks of phone volume (estimates show roughly 60–65% of doctor appointments are still made by phone), automating insurance eligibility checks, and routing complex cases to humans with full context. The result: shorter hold times, fewer manual data entries, and more time for clinicians and front-desk staff to do higher-value work. Hiring pressure will ease because teams are no longer carrying the same volume of “low-value” administrative tasks. With clinical data collected and transferred securely into EMR’s by systems like Yosi, we expect the clinician burnout via clicks to be substantially reduce.
Clay Ritchey, CEO, Verato
LinkedIn: Clay Ritchey
The most effective use of AI will be to strengthen the healthcare workforce, enabling every role to practice at the top of their license. Across hospitals and health plans, staff burnout often stems from fragmented data and the constant need to verify or re-enter information. When accurate, connected identity data support AI, it can streamline those workflows and eliminate the manual data chasing that pulls clinicians away from patients and undermines efficiency. Trusted data, therefore, will become a genuine source of support for the people who deliver care every day.
Ram Sahasranam, co-founder, Fold Health
LinkedIn: Ram Sahasranam
The next stage of healthcare workforce transformation won’t come from producing even more intelligence, it will come from activating the intelligence we already have. In 2026, we’ll see the early formation of a new operational infrastructure built around AI-driven orchestration layers that connect data, workflows, and people into a single, coordinated system. These orchestration layers won’t just analyze information; they will move work. Routine but essential tasks, scheduling, benefits verification, prescription coordination, data handoffs between systems, paperwork management, and lab tracking, will increasingly be delegated to AI agents that execute reliably in the background. By absorbing the administrative load that currently overwhelms care teams, this new infrastructure will allow clinicians and staff to practice at the top of their license, reduce burnout, and create a more humane, sustainable model of care.
Scott R. Schell, MD, PhD, MBA, Chief Medical Officer, Cognizant
LinkedIn: Scott Schell
AI at scale demands new roles that unite clinical literacy, digital fluency, and ethical oversight: Clinical AI Product Owners who bridge service lines, compliance, and engineering; Healthcare Data Stewards fluent in interoperability and consent frameworks; Safety and Change Control Leads who manage lifecycle transparency for evolving systems; Workflow Engineers who design the handoffs between human and machine, ensuring that automation supports judgment rather than replaces it. Tomorrow’s leaders will speak both the language of science and the rhythm of care.
Ben Scharfe, EVP, Altera Digital Health
LinkedIn: Ben Scharfe CPA
In 2026, the conversation around AI in hospital operations will shift from simple task automation to the deployment of agentic AI at scale. Sophisticated AI agents will manage and participate in complex workflows, particularly in the back office, which is an area under intense financial and staffing pressure. We will see these systems participate in the prior authorization process, handling claims denials and optimizing patient scheduling.
Jonathan Shoemaker, CEO, ABOUT Healthcare
LinkedIn: Jonathan Shoemaker
In 2026, AI will become one of healthcare’s best teammates. By forecasting demand, rebalancing workloads across facilities, and handling the repetitive tasks that drain energy and time, intelligent systems will let clinicians focus on top-of-license care and meaningful patient moments. Less burnout, more purpose, that’s the real promise of AI for the healthcare workforce.
David B. Snow, Jr., Chairman & CEO, Cedar Gate Technologies, an IQVIA business
LinkedIn: David Snow
Market pressures are growing in healthcare, as evidenced in headlines about workforce shortages, physician burnout, and financial pressure on hospitals, as well as new CMS program mandates (like TEAM) and reimbursement cuts. Cybersecurity threats are also growing, with healthcare surpassing finance as the most-breached industry in 2024. Organizations that rely on data and application architecture from multiple vendors and sources will only see these pressures grow in 2026.
The market will turn to integrated end-to-end platforms as a means to combat these growing challenges, with the promise of providing clean, enriched data from which payers, providers, and employers can glean meaningful insights that translate into actionable steps for care teams to improve care and lower costs. An integrated platform that shares a single data lake minimizes the number of vendors, implementations, exposure points, and APIs required to collaborate effectively with teams within an organization and across systems for more effective and efficient care. It can also eliminate redundant work for already-strained care teams and mitigate the risk of errors, variations, or missed opportunities in care delivery.
Sundar Subramanian, CEO, Zyter/TruCare
LinkedIn: Sundar Subramanian
2026 is the Year Health Plans Move From “Black-Box AI” to “Glass-Box Decisions” and Surge Ahead of Providers
Providers jumped out early on AI with single-use-case tools such as ambient listening, medical documentation automation, and point-of-care assistants. Those were important proofs of concept, but they were primarily clinical micro-automations.
2026 is the year health plans pull ahead with population-level, system-level AI that spans claims, prior authorization, care management, risk adjustment, and quality workflows.
That acceleration will also force a major transparency shift. Members, regulators, and providers will expect ‘glass-box AI’ with clear explanations of how care decisions are made, what data informed them, and where humans intervene. Plans will increasingly need to produce explainability reports for key decisions, especially in prior auth and complex claims.
Transparent AI becomes the new compliance standard and the new competitive differentiator.
The health plans that win will be the ones that move from automation to accountability.
Jim Szyperski, CEO, Acuity Behavioral Health
LinkedIn: Jim Szyperski
Thoughtfully designed and implemented, AI and data-driven automation is and will be indispensable in behavioral healthcare for clinical decision support for trained staff. It is an extremely valuable tool to aggregate information that would otherwise take hours, days, weeks, to gather. IMO, it should be used solely to inform and suggest in clinical settings, and not to replace clinical decision making.
Stephen Vaccaro, President, HHAeXchange
LinkedIn: Stephen Vaccaro
Homecare will become increasingly smart and autonomous
As adoption of wearables, Internet-of-Things devices, robotics, and AI grows, homecare agencies will begin offloading more routine “monitor and assist” tasks to technology, so caregivers can focus on the human side of care. The robotics segment for homecare is already showing rapid momentum with assistive robots, fall-detection, and medication-management bots gaining traction. Agencies that invest in this “smart home + caregiver” model will gain a competitive edge with lower costs, higher quality, and scale.
Philipp von Gilsa, CEO and cofounder, Kontakt.io
LinkedIn: Philipp von Gilsa
Clinical workflows will move beyond note-taking automation, eliminating all bottom-of-license work across departments. Automating workflows based on location-triggers will be the tool to do so. And as these automations mature, hospitals will finally redirect thousands of wasted micro-tasks back into clinical capacity, easing burnout while improving both throughput and care quality.