Healthcare’s administrative burden is not a documentation problem, it is a workflow problem.
Over the past year, healthcare organizations have widely adopted generative AI for an array of documentation-related activities such as drafting appeal letters, producing patient-friendly summaries, and even assisting with administrative writing. While these tools have improved how information is created, they do little to address the underlying issue: a fragmented, manual, and procedurally complex administrative system that consumes time, delays care, and exhausts clinical and operational staff. From prior authorizations and decision-making to reimbursement and follow-up, healthcare workflows remain burdened by steps that require coordination, tracking, and escalation. This is work that extends far beyond writing text.
An Administrative Crisis the Industry Can No Longer Ignore
When administrative workflows remain fragmented and manual, the burden does not stay abstract, it compounds across the workforce. The consequences of workflow-driven inefficiency are now visible in staffing shortages, escalating workloads, and measurable clinician burnout. What begins as a failure to automate end-to-end processes ultimately manifests as time lost to prior authorizations, delayed patient access, and unsustainable operational strain across health systems.
This gap is growing as workforce shortages intensify. The National Center for Health Workforce Analysis projected that between 2023 and 2038, there will be a large shortage of licensed practical and vocational nurses (LPNs). By 2028, the supply will only meet about 83% of the demand, while that number will decrease heavily to only 70% by 2038. Not to mention that the administrative procedures in clinical practice are actively slowing their efficiency, as around 80% of clinicians in the recent survey of the American Academy of Allergy, Asthma & Immunology reportalways experiencing delays in access to prescription medications and biologics. Furthermore, within the same report, over 80% of them believed PAs interfered with chronic treatment, and over 96% thought that PAs somewhat or significantly negatively affected clinical outcomes. Overall, they all express the burden of PA on their practices as high (26%) or extremely high (71%).
Behind these numbers are patient access teams, case managers, and revenue cycle staff with ever-increasing workloads. They manage eligibility checks, benefits verification, documentation alignment, authorization follow-up, and denial management. If AI can only make the writing part of this work more efficient, the overall burden hardly changes.
Enter Agentic Systems: From Assistance to Automation
Agentic systems are the game-changers healthcare desperately needs. Unlike generative tools that output text, these AI-driven agents handle end-to-end workflows with intelligence and autonomy. They pull data from disparate sources, apply payer-specific rules, verify details, submit through portals, monitor progress, escalate issues, and log everything for audits, all without human intervention.
Think of it as upgrading from a typewriter to a full-fledged executive assistant. A generative tool might draft an appeal letter; an agentic system identifies the denial reason, gathers supporting documents (like lab results and medical histories), packages the appeal, routes it correctly, follows up automatically, and updates the EHR. One creates information; the other drives results.
Interoperability as the New Competitive Advantage
Agentic systems offer something generative AI can’t: the ability to move across healthcare’s disconnected technologies. They can pull data from EHRs, payer portals, lab systems, and internal databases, then act on it to complete entire workflows.
This matters because interoperability is no longer optional. TEFCA, CMS rules, and state mandates now require not just data exchange, but actionable, traceable information flow, something traditional RPA or text-generating tools can’t deliver.
By bridging systems that don’t talk to each other, agentic systems finally solve healthcare’s “last mile” problem, eliminating the manual re-entry, portal hopping, and record matching that slow everything down.
The result is faster decisions, fewer denials, and a smoother patient experience. As pressures mount, the ability to orchestrate workflows across fragmented systems won’t just be a compliance box; it will be a core strategic advantage.
A Patient-First Ethical Imperative
Beyond efficiency, agentic systems champion ethics and equity. In an age of AI skepticism, their transparent, auditable nature builds trust, every decision traceable to data, mitigating biases that plague opaque generative models. For underserved populations, this means faster access: no more disproportionate delays for low-income patients navigating complex payer rules. It’s about justice, ensuring AI doesn’t just speed up the status quo but dismantles barriers to care.
Operational Benefits for Health Systems
Agentic systems relieve administrative pressures where they are most costly and most disruptive. They take less time to conduct repetitive activities, free up time for clinicians to work on complex cases and patient communication, and ensure accuracy and completeness of payer submissions. They also help organizations scale without having to add staff proportionately.
Health systems are dealing with rising costs, increasing patient volumes, and an insufficient labor pool. Tools that merely produce content cannot resolve these structural issues; only systems that are designed to perform multiple procedures simultaneously can.
A Vision for Collaborative, System-Wide Adoption
The shift to agentic systems is already here. Organizations that move now will gain measurable advantages in operational efficiency, approval rates, and staff retention. Early wins are already showing what this looks like in practice. .
In Catalonia, the public health system deployed an agentic assistant called ALMA to bring evidence-based clinical guidance into day-to-day clinician workflows. The results were striking: 65% of users integrated it into routine work, with a 98% user satisfaction rate. The program scaled across primary care and is now positioned for expansion into additional services.
Beyond administrative workflows, agentic systems are also transforming clinical trial execution. Tempus deployed its TIME program which is an AI-powered network that orchestrates trial matching, site activation, and patient enrollment across distributed care settings. The system analyzes clinical data to identify potentially eligible patients, then coordinates across multiple agents: patient pre-screening algorithms surface matches, clinical nurses review eligibility, and site activation workflows trigger in parallel with patient outreach. The TIME network has already driven measurable impact at scale: TriHealth Cancer Institute reported a 64% annual increase in patients enrolled in clinical trials, with Tempus TIME driving 95% of that growth. This agentic orchestration has addressed one of healthcare’s most complex coordination challenges of getting the right patients into the right trials at the right time.
The opportunity is clear. The question isn’t whether to adopt agentic automation, but how soon can you begin. Start here:
- Identify your high-volume, error-prone workflows (prior authorization, benefit verification, denial management)
- Assess where manual work is creating bottlenecks
- Look for vendors with proven interoperability, real-world deployment data, and transparent human-in-the-loop protocols
- Pilot with a defined scope and measurable metrics
If healthcare embraces this next phase with coordination and intention, we can build an administrative ecosystem that finally keeps pace with clinical innovation, one that restores operational capacity, reduces avoidable delays, and ultimately strengthens the patient experience. This is the opportunity ahead: a move from isolated efficiencies to system-level transformation, powered by automation that can actually do the work.
About Benjamin Easton
Benjamin Easton is the Co-Founder and CTO of Develop Health. He builds software infrastructure that improves communication between healthcare providers and insurers, with a focus on reducing clinician burden and improving patient access to medications. He was recognized by Forbes in its 30 Under 30 list (2022) and he has a long track record of building health-focused products and startups.
