UF Health Partners with R1 to Deploy AI-Powered Revenue Cycle Platform

UF Health is working with R1 to deploy an AI-native revenue cycle model using Phare OS, combining agent-driven workflows with human oversight.
UF Health has partnered with healthcare revenue management company R1 to deploy an AI-native operating model for revenue cycle management (RCM), the companies announced September 9.
The collaboration will use R1’s Phare OS platform and its R37 Innovation Lab to support revenue cycle operations across the University of Florida Health system. UF Health’s network includes 11 hospitals and hundreds of physician practices and outpatient locations across Florida.
The initiative comes as healthcare providers increasingly apply AI to administrative and financial workflows. AI has already moved into areas such as claims processing, denial management and revenue recovery, with providers looking to automate work that remains labor-intensive.
Our recent look at AI in healthcare revenue cycle operations found that specialized AI systems are being used for tasks such as eligibility verification and denial management, with human review retained for higher-risk cases.
R1 Brings Phare OS Into Academic Health System
At the center of the UF Health collaboration is Phare OS, which R1 launched in 2025 as a platform intended to connect workflows across the revenue cycle rather than address individual processes in isolation.
R1 said Phare OS is built on three core components: its Data Platform, Payer Atlas and Phare Intelligence. The company said Payer Atlas has more than 1,500 payer connections and processes more than 600 million payer transactions annually.
The platform was live across provider organizations representing more than $76 billion in net patient revenue as of 06/18, according to R1. The company has continued expanding Phare OS through capabilities covering areas including denials management and prior authorization.
R1 said engineers from R37 will work directly with UF Health teams. The model combines agent-driven workflows with human governance, allowing staff to oversee AI-supported processes rather than removing human involvement from the revenue cycle.
That approach reflects a broader shift toward AI systems that execute defined administrative workflows while retaining human oversight. Healthcare technology company TELCOR, for example, has also incorporated AI for prior authorizations, appeals, payer follow-up and document processing with human oversight.
Focus on Operational and Financial Performance
UF Health CFO Geoff Gardner said the health system selected R1 because of its combination of revenue cycle expertise and AI capabilities.
“We chose to collaborate with R1 because of its ability to pair 20 years of deep revenue cycle expertise with advanced AI capabilities for revenue management,” Gardner said in the announcement.
The collaboration is intended to identify opportunities to improve operational efficiency and financial performance while supporting UF Health’s workforce.
R1 CEO Joe Flanagan said the companies were working to reshape the revenue cycle around AI, automation and operational expertise. He described the UF Health engagement as a technology-first collaboration focused on outcomes and designed to allow clinicians to spend more time on patient care.
The focus on financial operations follows a wider healthcare AI trend. Hospitals and health systems have increasingly deployed AI to identify billing discrepancies, recover revenue and automate administrative work as financial pressures persist across the sector.
For R1, the UF Health engagement extends Phare OS into a large academic health system and gives its R37 team a direct operating environment for applying AI across the revenue cycle. The company said the collaboration is intended to support continuous optimization while maintaining human governance over the technology.
Key Takeaways
- UF Health partners with R1 to implement an AI-native revenue cycle management model.
- Utilize R1's Phare OS platform for enhanced revenue cycle operations across UF Health's network.
- Leverage AI to automate labor-intensive tasks like claims processing and denial management.
- Retain human oversight for complex cases while using AI for efficiency in administrative workflows.
- Adopt specialized AI systems for tasks such as eligibility verification within healthcare revenue cycles.