America’s healthcare system is fighting battles on several fronts: surging patient needs across specialties, an aging clinical workforce, and escalating provider burnout. Projections indicate a shortfall exceeding three million healthcare workers by 2026. This is supported by a 2023 McKinsey study, which found that 40% of inpatient registered nurses were planning to leave their positions. At the same time, nearly 60% of oncologists cite burnout as one of the primary reasons they may seek earlier retirement, only exacerbating an already staggering gap in care, as nearly 32 million Americans live in counties without locally available cancer care. Similar patterns have emerged across specialties, with fewer radiologists graduating.
The implications extend far beyond access—capacity limitations drive up costs, limit patients’ access to potentially lifesaving clinical trials, compromise care quality, and strain the entire healthcare ecosystem. This is a societal issue and one that requires immediate attention.
When we look deeper into these signs of dissatisfaction, a clearer picture emerges. Physicians spend more than 35% of their time on non-patient-facing tasks. Registered Nurses (RNs) continue to cite the need for more manageable workloads as a key factor in their decision to remain in or leave their positions. Their administrative burdens will only grow as new diseases emerge, the population ages, and cancer rates rise.
To date, few technologies have had a beneficial impact on clinician productivity and work burden. However, today’s AI technologies stand ready to deliver the same efficiencies found in drug discovery to fundamentally transform healthcare delivery capacity. Incremental efficiency gains and amplifying clinicians’ capabilities may not sound revolutionary at first glance, but those new AI advancements will be able to resolve this capacity crisis and ensure high-quality physician-led and patient-centric care.
AI Agents: Extending Clinical Teams to Drive Patient-Centric Care
The most frequent concern physicians express, especially those in oncology, is how to alleviate the burden on clinicians. How can you cut back on the tasks that take them away from direct patient care? In these same discussions, I hear about the tremendous advancements the industry is making and how AI has begun to reshape the foundation of healthcare. These rapidly advancing AI solutions are already addressing mission-critical capacity issues and will create an entirely new foundation of data and intelligence. That foundation will consist of domain-tuned and specific Large Language Models (LLMs) with and without transparent reasoning combined with agentic AI.
AI agents are available to prepare data and an array of traditionally administrative or non-performed tasks that, in turn, will be used by other agents and agents deployed as assistants to care providers. From intake processes to discharge instructions and patient follow-up, AI agents can offload these repetitive yet crucial steps in the patient journey.
In oncology, where every day matters for so many, the ability to spend more time with patients and speed up clinical trials can be life-changing. Imagine walking into an oncology clinic and seeing each of the doctors and nurses actively engaged with patients, providing guidance and personal treatment support, while AI agents quietly manage routine tasks in the background.
Consider a clinical trial where AI predicts which participants are at risk of dropping out and recommends interventions to improve retention. Or imagine the profound impact these agents can have when they are used to offload even higher-level tasks behind the scenes. Employing a kind of corporate-like hierarchy, AI agents can each have a distinct domain specialty, with higher-level supervisor agents keeping tabs on specialists. An example of this would be to design a “transaction agent” to specifically look at molecular diagnostic reports, extract the critical biomarker information, and then format it into a usable condition. A higher-level “supervisor agent” would oversee that particular agent to make sure they do their work correctly.
These scenarios are no longer hypothetical—they are becoming a reality that will shape a more patient-centric future.
AI as a Strategic Imperative: Empowering Clinicians and Accelerating Innovation
Solving the healthcare capacity crisis requires more than just technology. It demands collaboration between domain experts, clinicians, technologists, and researchers to ensure that AI solutions align with real-world needs.
As AI continues to advance at an unprecedented pace, these collaborations will be essential to unlocking the full potential of AI agents. They are not a replacement for the knowledge, experience, intuition, and empathy that clinicians bring to patient care. Instead, they can empower clinical teams. By reducing administrative burdens and enhancing decision-making, AI agents hold the promise of bringing balance to the clinician’s workload, freeing them up to spend more time doing the most important work…the work that initially drew them to healthcare—caring for patients.
Most healthcare providers now view AI adoption as a strategic imperative. By investing in AI solutions that optimize workflows and augment human expertise, healthcare systems and research institutions can reduce burnout, improve retention, and accelerate the pace of medical innovation. The foundations for this transformation are being put into place now. Based on the progress made in the last 12 months alone, we anticipate substantial advances quarter over quarter in the coming three years.
The future of healthcare isn’t about technology for the sake of technology. It’s about prioritizing patient care and bringing life-saving therapies to market faster. AI agents are here, and it’s exciting to be part of harnessing this amazing technology to make healthcare more accessible for everyone.
About Jeff Elton, Ph.D.
Jeff Elton, Ph.D., is Vice Chairman of ConcertAI, an AI SaaS solutions company providing research and patient-centric solutions for life sciences innovators and the world’s leading providers. Prior to ConcertAI, Jeff was Managing Director, Accenture Strategy/Patient Health; Global Chief Operating Officer and SVP Strategy at Novartis Institutes of BioMedical Research, Inc.; and partner at McKinsey & Company. He is also a founding board member and senior advisor to several early-stage companies. Jeff is currently a board member of the Massachusetts Biotechnology Council. He is the co-author of the widely cited book, Healthcare Disrupted (Wiley, 2016). Jeff has a Ph.D. and M.B.A. from The University of Chicago.
