Waystar adds agentic AI in move to 'autonomous' revenue cycle

Waystar to make revenue cycle autonomous

Waystar's ultimate vision is to use AI to make the revenue cycle "autonomous," Hawkins explained in the presentation at the conference.

The idea is to create a unified platform that connects the revenue cycle end-to-end using AI agents. Over 150 AI-trained models, to be exact, Hawkins explained. These models support the end-to-end approach from the front end of the revenue cycle, where AI can identify patients and their access to insurance coverage, to the most significant source of preventable denials because of manual errors and unstructured data, the midcycle, and to the back-end, where AI can clean claims for payer submission.

Unified data is also key to Waystar's journey to an autonomous revenue cycle. Hawkins touted the company's increase in data points over the past year, rising from 6 billion insurance transactions to about 7.5 billion in 2025.

These data points are also now combined with Iodine Software's data, which Waystar acquired late last year. Iodine boasts data on one in three hospital discharges, which provides Waystar with a large volume of proprietary data to train AI models, particularly on tasks such as prior authorization requests that require unstructured clinical data.

About 500 integrations with other health IT systems, including EHRs and practice management platforms, also contribute to this unified data system, Hawkins stated.

"I think this is game-changing, and I believe that this will prove very advantageous to Waystar over a longer period of time," he said. "The access to data, again, not siloed in lots of different locations, but centralized and curated, not on paper somewhere or on a publicly available resource site, but proprietary within our data set that will allow us to develop innovations and turn unified data into trusted intelligence to power the right AI at the right time and deploy it effectively."

'Autonomous' is the new RCM buzzword

Waystar has ambitious goals to make the revenue cycle more efficient through the use of unified AI agents. But it's not the only major revenue cycle management and healthcare payments vendor making autonomy part of their lexicon.

R1 RCM has made a significant investment in autonomous revenue cycle operations through its Phare Operating System. R1's answer to increasing complexity in revenue cycle management, the revenue operating system is powered by enterprise-grade AI to take a system-level approach to revenue cycle management. This approach contrasts with AI-powered point solutions that utilize the technology to address a specific revenue cycle pain point.

Many other vendors are also capitalizing on the capabilities unlocked by agentic AI, which is autonomous by nature. In other words, these AI agents can achieve complex, multistep goals with self-corrections. Meanwhile, generative AI and other types of AI technology require user prompts to function.

Healthcare providers are most familiar with autonomous coding platforms, which have been a primary use case for autonomous technology in healthcare. However, vendors are increasingly becoming more ambitious as AI technology matures, linking revenue cycle functions through agentic AI.

But the revenue cycle is not quite autonomous, yet.

"Any organization that says that they have an autonomous revenue cycle or that they have a full agentic suite is probably not at the front of the front line actually seeing what's happening," Chris Murray, managing director at Huron Consulting Group, told RevCyle Management. "This is where rubber hits the road, and it's a lot more challenging than all those releases."

Vendors and providers are still building the foundation for end-to-end revenue cycle management that leverages AI capabilities, including robust AI governance structures and data. That being said, industry leaders like Murray see autonomy in the near future.

"It's an exciting time and something we need to working towards," he said.

Jacqueline LaPointe is a graduate of Brandeis University and King's College London. She has been writing about healthcare finance and revenue cycle management since 2016.