It is a well-understood fact that the world of healthcare has an incredibly high burnout and turnover rate. A 2023 study from the CDC found that the burnout rate increased to 46% and the turnover rate increased to 44%. As such, it is vital that we do everything we can to make working in healthcare a better experience. It’s impossible to talk about all of healthcare at once, so today we are going to narrow our focus down to optimizing revenue cycle workflows.
We reached out to our brilliant Healthcare IT Today Community to ask — how are health IT solutions and AI being used to optimize end-to-end revenue cycle workflows, from patient access through final payment? Below are their responses.
Troy Wasilefsky, Chief Customer Officer at Greenway Health
Health IT and AI are transforming revenue cycle management in waves—first through automation that reduced administrative burden, and now through agentic AI that not only assists staff but actively performs key tasks, accelerating workflows and improving financial outcomes. At the same time, the industry is shifting from fragmented point solutions to more unified, AI-powered platforms that can manage the full revenue cycle end to end.
The next transformation goes further, embedding revenue cycle capabilities directly into the patient and physician journey. Instead of operating after the fact, these functions increasingly run in real time—alongside scheduling, patient engagement, and even within the clinical encounter. The result is a faster, smarter RCM model that is more tightly integrated with care delivery.
Karly Rowe, President and Provider at Inovalon
Healthcare organizations are at an inflection point. Administrative burden is rising, margins are tightening, and revenue cycle teams are being asked to do more with less. AI is no longer a future capability. It is becoming foundational to how revenue cycle operations function.
Across the end-to-end revenue cycle, from patient access and eligibility verification through charge capture, claims submission, and payment, AI is helping reduce manual work, accelerate timelines, and prevent avoidable errors. More advanced, agentic AI can anticipate payer requirements, identify missing or inconsistent data before submission, flag denial risk, and generate appeal documentation, all while keeping clinicians and revenue cycle teams in control.
The reality is that no individual or team can keep pace with the growing complexity of payer rules, regulatory requirements, and documentation standards. When AI is informed by data that spans clinical workflows, billing systems, and payer interactions, organizations can move from reactive revenue cycle management to a more predictive and proactive model. That shift is where the greatest financial and operational gains are being realized.
The organizations seeing the strongest results are not simply automating tasks. They are embedding AI directly into workflows to support better decision-making. When deployed thoughtfully, AI enables revenue cycle and clinical teams to spend less time navigating administrative friction and more time focusing on accuracy, outcomes, and patient experience. The future of revenue cycle is not fully automated. It is intelligently assisted.
Merideth Wilson, Financial Health General Manager at TruBridge
Health IT solutions and AI are transforming revenue cycle management from reactive to predictive. By applying proprietary data and decades of payer insight, providers can identify and stop deniable claims before they are created. This upfront alignment of patient access, coding, and payer requirements helps prevent $50–$60 per claim in costly rework and accelerates final payment.
Chris Gervais, Chief Technology Officer at CodaMetrix
AI is optimizing the revenue cycle by moving high-quality decisions earlier in the workflow, closer to where clinical care is documented. When coding is both automated and reliable enough to support straight-to-bill submission, it reduces downstream friction, rework, and denials. That shift doesn’t just improve efficiency, it creates a more predictable and scalable financial performance model for our healthcare systems.
Cassandra Skinner, Value Realization Partner at Xsolis
Health IT and AI are increasingly translating the complexity of the patient lifecycle into a clear narrative that surfaces opportunity and process gaps. The real potential lies in removing siloes across the care continuum — creating end-to-end transparency supports patient advocacy post-discharge and enables more effective decision-making between payers and providers.
Patty Hayward, General Manager of Healthcare and Life Sciences at Talkdesk
Health systems are moving beyond optimizing individual revenue cycle steps and instead orchestrating the entire journey from patient access to final payment. AI is enabling real-time decisions across scheduling, authorization, documentation, and collections, reducing friction and preventing revenue leakage before it occurs. The organizations winning today are treating the revenue cycle as a coordinated experience, not a back-office function.
Ted Ferrin, SVP, Payments Innovation at Zelis
AI is helping organizations see where revenue is at risk early enough to act on it. The issue for many providers is not a lack of data, but that too much of it sits in disconnected workflows across patient access, claims, and payment. When Health IT and AI bring those signals together, revenue cycle teams can identify friction sooner, prioritize the areas that need attention most, and take action before problems result in denials, payment delays, avoidable rework, or lost cash flow.
That is the value of end-to-end optimization. It is not automation for its own sake. It is about giving revenue cycle teams the visibility they need to focus limited staff resources on what matters and to move from reactive problem-solving to proactive decision-making. From eligibility and authorization through reimbursement and final payment, better, unified insights help organizations reduce blind spots, accelerate payment, and improve financial performance.
Provider groups seeing the most value are the ones using AI to turn digital workflows into clearer priorities, faster decisions, and more targeted action, not just adding another layer of technology. Where teams still need to hunt across systems to understand why payment is delayed or where revenue is leaking, the revenue cycle is still disconnected. The more teams can unify their data and payments, the more intelligent and simplified their workflows can become. The goal is faster, clearer, more connected decision-making that helps protect margin and reduce administrative friction.
Brandi Meyers, Vice President, EHR and RCM at Healthcare IT Leaders
We’re seeing a meaningful shift where AI is no longer being layered on top of revenue cycle workflows but is embedded directly within EHR platforms like Epic and Oracle Health. That integration matters because it brings intelligence into the natural workflow, whether it’s improving coverage accuracy at scheduling, guiding documentation for coding, or predicting denials before claims are submitted. The real impact isn’t just automation, it’s reducing friction across the entire lifecycle by making smarter decisions at the point of work.
Sashi Padarthy, Head of Strategy and Growth – Health Systems Business at Cognizant
AI has stopped being a departmental tool and has become the connective tissue of the entire revenue cycle. At patient access, AI is automating eligibility verification, predicting prior authorization requirements, and flagging documentation gaps before a patient ever leaves the building. Mid-cycle, natural language processing tools are reading clinical documentation in real time and surfacing coding opportunities that human reviewers would catch days later. On the back end, predictive denial management is protecting revenue before claims go out the door rather than chasing it after the fact.
Across our client base, our data shows that denials are almost evenly distributed across the front-end, mid-cycle, and back-end of the revenue cycle, which proves exactly why AI needs to operate across the entire continuum and not just solve one piece of the problem.
The organizations pulling ahead are not just implementing AI tools. They are fundamentally redesigning workflows around them, and that is where the real return on investment lives. Think about how the financial services industry transformed fraud detection. They did not just add fraud alerts at the point of transaction. They rebuilt their entire data infrastructure around real-time intelligence. Healthcare revenue cycle is at that same inflection point right now.
Ryne Natzke, Chief Commercial Officer and General Manager at TrustCommerce, a RevSpring Company
Health IT solutions and AI are helping transform the revenue cycle by connecting workflows into a more unified, personalized experience from the first search online for a doctor through final payment. This includes setting clearer cost expectations before care, supporting digital payment options, and ensuring payments are accurately tracked and reconciled.
Healthcare doesn’t have a demographic, and everyone is a patient, so it’s critically important to make sure you are providing the right information, at the right time, and using the right communication method to create a seamless experience while also minimizing your costs. Without AI and digital solutions, this would be impossible to do at any sort of scale, and it’s exciting to see this new technology drive better financial outcomes and a better patient experience.
John Waters, Director, Revenue Cycle Product at CliniComp
Organizations need analytical solutions that allow for big-picture visibility on financial performance KPIs and maximizing revenue. The differentiation comes with an ability to pre-emptively identify problems before they arise via the data and have the drill-down capability to address them before they negatively impact an organization’s financial health.
Robbie Hughes, Chief Product Officer at Health Catalyst
There’s a lot of momentum around applying AI in the revenue cycle, but most of it is still happening at the task level rather than the system level. Organizations are using AI to automate parts of patient access, coding, and billing, but the real opportunity is designing and connecting those workflows end to end.
When AI is applied at the system level, it helps reduce administrative friction, improve data handoffs, and prevent downstream issues like denials before they occur. The organizations seeing meaningful results are the ones using AI to align workflows, data, and decisions across the full revenue cycle—treating AI as part of the operating system— rather than optimizing individual steps in isolation.
Matt Seefeld, CEO at MedEvolve
Health IT and AI are being applied across the entire revenue cycle, but most solutions today are still optimizing tasks rather than reducing the number of interactions it takes to get paid. That’s the core issue.
The revenue cycle is not a single workflow. It is a series of “touches” across patient access, coding, billing, and payer follow-up. Every touch introduces cost, delay, and risk. AI is improving specific steps—automating eligibility checks, prioritizing work queues, and identifying denial risk—but it often does not complete the loop. It accelerates a touch, but doesn’t eliminate the need for the next one. That’s why organizations are seeing a disconnect. Denials continue to rise, yet many are ultimately overturned. The outcome is payment, but only after multiple interactions, rework, and follow-up.
Operational benchmark data shows that as much as half of revenue cycle work may be tied to touches that do not change the financial outcome, and the majority of open claims often do not require action at all in a given moment. The next phase of AI is not about doing more work faster. It’s about reducing the number of touches required across the entire workflow and closing the loop from patient access through final payment.
Such great insights here! Huge thank you to everyone who took the time out of their day to submit a quote to us! And thank you to all of you for taking the time out of your day to read this article! We could not do this without all of your support.
How do you think health IT solutions and AI are being used to optimize end-to-end revenue cycle workflows, from patient access through final payment? Let us know over on social media, we’d love to hear from all of you!
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About Dr. Rohin Rameswarapu