Executive Summary
AI in revenue cycle management is no longer a distant idea. As financial pressures grow and denials continue to strain provider organizations, revenue cycle leaders are beginning to see AI as a practical tool for improving efficiency, accuracy, and revenue performance.
To understand how AI is being viewed and used today, Inovalon surveyed more than 400 revenue cycle leaders across hospital, ambulatory, and post-acute settings. The findings reveal a market that is optimistic, but still cautious. While 53% of revenue cycle leaders are optimistic about AI in revenue cycle software, adoption remains uneven across care settings.
Hospitals are moving fastest, with 27% reporting AI implementation in revenue cycle software, compared with 8% of ambulatory and 4% of post-acute organizations. At the same time, generative AI use is already more common, with two in three acute and ambulatory leaders using tools like OpenAI’s ChatGPT at work.
This white paper explores where revenue cycle leaders see the greatest promise for AI in revenue cycle management, what concerns are slowing adoption, and how organizations are beginning to turn early use cases into measurable operational gains.
Inside, you’ll learn:
- How revenue cycle leaders’ expectations for AI have evolved from general automation to end-to-end workflow support.
- Why formal AI adoption remains limited, even as early users report gains in efficiency, accuracy, and cash flow.
- How generative AI use is outpacing formal RCM adoption and shaping leaders’ views of what AI can do.
