AI and automation are revolutionizing healthcare revenue cycle management (RCM), reducing inefficiencies, optimizing financial workflows, and enhancing the patient experience. Yet many health systems struggle to navigate the complexities of adoption due to limited financial and human resources or uncertainty over the potential value that these technologies can deliver.
It is important to understand that automation is a continuum, progressing from rules-based workflows to AI-driven predictive analytics, chatbots, and generative AI solutions. AI is already transforming key aspects of patient access and financial clearance, including scheduling, insurance benefit verification, and prior authorizations, as well as clinical documentation, coding, and management of denied claims, reducing administrative burdens and improving cash flow and revenue.
These represent just the tip of the iceberg when it comes to the potential of AI and automation to influence a healthcare organization’s overall financial stability, patient experience, and operational excellence. However, while AI holds immense promise for transforming RCM, a measured, pragmatic approach is required to ensure a sustainable impact on efficiency, financial outcomes, and care access and quality.
A Turbulent Landscape
The current healthcare financial landscape is best described as complex. Operating costs are rising while operating margins are declining. At the same time, insurance companies are implementing increasingly complex requirements designed to delay and deny payments to providers. These actions include increasing and more intricate prior authorization requirements that drive up claim denials and a push to embed advanced technology more deeply into the review process.
Another factor contributing to the rise in claim denial rates is the surge in pre- and post-payment audits by commercial and government insurers. According to an analysis by MDaudit, audit volume more than doubled between 2023 and 2024, and total at-risk dollars increased fivefold. This resulted in a sharp uptick in final denial dollars across professional (34%), hospital outpatient (84%), and hospital inpatient (148%) settings.
Along with the financial impacts, these trends contribute to already high administrative demands, which in turn increases the strain on an overburdened and more costly workforce that RCM leaders struggle to maintain amid an ongoing shortage. As a result, many healthcare leaders are exploring onshore, nearshore, and offshore outsourcing models to avoid staff burnout.
Moreover, many healthcare organizations lack the insights to identify and remediate systemic issues that undermine RCM. Approximately 55% of respondents to a recent AGS Health survey express a desire for enhanced analytics, and nearly half indicated that no automation had been implemented to support patient access functions, despite the growing adoption of that same technology by payer organizations.
Also at play are the inefficiencies created by outdated, time-consuming, and cost-intensive RCM processes. In addition to hindering timely access to care, these archaic processes contribute to revenue leakage and further weaken the bottom line.
The Transformative Power of AI and Automation
Navigating this tumultuous financial landscape calls for embracing a global, technology and AI enabled approach built on a seamless and cohesive RCM framework that accelerates the revenue cycle. For example, proactively identifying and addressing patient eligibility and coverage issues before they become denials improves revenue capture, while workforce shortages can be alleviated by supplementing internal staff with outsourced RCM experts.
Crucial to this framework are AI and automation, which are already having a transformative impact on healthcare RCM. This includes the broader adoption of AI and automation tools to support clinical staff with essential administrative tasks like documentation integrity, utilization management, prior authorizations, and clinical denial appeals. Another tactic is expanding the deployment and refinement of ambient technology at the point of care, which helps streamline operations, reduce costs, and improve patient experience and revenue outcomes.
The broader utilization of predictive analytics enables healthcare organizations to stay ahead of increasing payer denial trends by proactively preventing denials and prioritizing denials with the highest return on investment. Advances in AI will also drive increased adoption of tools like AI dialers that can manage calls with payers and gather complex information from payer representatives, streamlining tasks like denial overturns and authorization checks.
On the automation front, AI agents can handle labor-intensive tasks related to clinical and non-clinical appeals, such as drafting appeal packets that humans review before submission.
A side benefit of this growth in AI and automation will be increased patient satisfaction. At a time when patient expectations are evolving rapidly, integrating technology like AI and machine learning (ML) will enhance the patient experience. This includes self-pay technology and automation to educate patients on their financial responsibilities and provide simple, accessible payment options and plans. It is an approach that not only boosts patient satisfaction but also improves revenue collection.
Transforming RCM
AI and automation are reshaping the future of healthcare RCM, helping industry leaders adapt and innovate to overcome the internal and external forces threatening patient care and the bottom line. From workforce and revenue challenges, advanced AI and automation can close workforce, workflow, and revenue gaps while mitigating risks, easing administrative and staffing burdens, and lowering associated costs while streamlining RCM processes.
