What's Happening?
A recent survey by the Healthcare Financial Management Association (HFMA) and AKASA reveals that 80% of health systems in the U.S. are exploring, piloting, or implementing generative AI tools for revenue
cycle management (RCM) as of 2025. This marks a significant increase from 58% in 2023. The survey, which included responses from 519 chief financial officers and revenue cycle leaders, highlights the growing interest in AI to improve coding accuracy and revenue capture. However, many health systems face operational barriers such as cost constraints, integration challenges, and a lack of clear return on investment. Smaller health systems, in particular, struggle with limited IT capacity and competing priorities, which hinder their ability to adopt AI solutions effectively.
Why It's Important?
The adoption of AI in healthcare RCM is crucial as it promises to enhance documentation accuracy, compliance, and revenue integrity. Health systems are under financial pressure due to inflation, regulatory changes, and workforce shortages, making efficient revenue management essential. AI tools can help identify missed reimbursement opportunities and improve clinical documentation, potentially reducing the estimated 8.49% of revenue at risk due to documentation errors. This technological shift could lead to better financial outcomes for health systems, allowing them to reinvest in infrastructure and innovation. However, the initial investment and integration challenges remain significant hurdles, particularly for smaller systems.
What's Next?
As health systems continue to adopt AI for RCM, the focus will likely shift towards overcoming integration and cost barriers. Health tech vendors are encouraged to provide standards-based integrations to ease the adoption process. The success of AI in RCM could lead to broader applications in other healthcare operations, such as pre-authorization processes and coding reviews. Health systems may also explore partnerships with tech companies to leverage AI for more comprehensive solutions. The ongoing development of AI tools tailored to healthcare needs will be critical in ensuring sustainable adoption and maximizing the benefits of this technology.
