Agentic AI and the Race to a Touchless Revenue Cycle
McKinsey & Company
Healthcare providers continue to face considerable financial and operational headwinds, including reimbursement pressures and higher labor and supply costs. In response, health systems and care delivery providers are looking to improve cost and performance while maintaining access, improve clinical staff and patient experience and deliver high-quality, timely and effective care.
Why the Future of the Revenue Cycle Is Predictive, Not Reactive
Medical Economics
In 2026, the health care industry reached a financial breaking point. A 2024 MGMA Stat poll found that 60% of medical group leaders reported an increase in claim denial rates compared to the previous year. While most health systems treat claim denials as an unavoidable cost of doing business, the reality is more clinical: The costliest mistake in medical billing happens before a claim is ever submitted.
Agentic AI Evolution Begins to Pave Way for Autonomous Revenue Cycle
TechTarget
Artificial intelligence is already a staple for revenue cycle leaders, but emerging capabilities through agentic AI could bring automation to a whole new level: autonomous revenue cycle. Autonomous revenue cycle brings together AI, machine learning and robotic process automation to handle end-to-end processes with very limited human intervention. More vendors are touting autonomous capabilities, with some going as far as to signal autonomous end-to-end revenue cycle management.
Revenue Cycle Denials Intelligence Market (2026 – 2036)
Future Market Insights
The revenue cycle denials intelligence market was valued at USD 2.1 billion in 2025 and is projected to reach USD 2.4 billion in 2026, reflecting a CAGR of 12.5%. Continued investment is expected to drive market expansion to USD 7.8 billion by 2036, as healthcare providers adopt advanced intelligence solutions to counter increasingly automated payer claim denials and preserve collection performance.
