Artificial intelligence is no longer experimental in healthcare finance. AI in revenue cycle management is already reshaping how organizations code, bill, and collect, turning slow, manual tasks into precise, data-driven workflows. GeBBS Healthcare Solutions is one of the companies leading this shift, using AI for healthcare RCM to help providers protect margins, reduce denials, and maintain compliance while easing pressure on staff.
Below are six key ways AI is revolutionizing RCM today.
1. Autonomous coding and AI-powered claims processing
GeBBS’s autonomous coding within its iCode Workflow platform uses AI in medical coding to turn provider documentation into accurate medical codes with minimal human intervention. This automated medical coding tool helps deliver 96–98% coding accuracy and improve chart turnaround times by 45–55%, while cutting coding costs by up to 35%.
By pairing autonomous coding with AI-powered claims processing, organizations speed clean claim submission, reduce rework, and move closer to same-day billing.
2. Predictive denial analytics and smarter prevention
High denial rates drain cash flow and staff bandwidth. GeBBS’s AI-Powered RCM solutions use LLM-driven machine learning to scan claims before submission, identify patterns that typically trigger denials, and flag high-risk encounters for review.
This proactive approach supports RCM automation that minimizes revenue leakage instead of reacting to it weeks later.
3. End-to-end RCM workflow automation and status checks
RCM workflow automation is where AI and robotic process automoation (RPA) work together. GeBBS’s RPA bots automate routine work such as payment posting, adjustments, write-offs, and even claims follow-up. In one case, bots reduced posting time per claim from three minutes to 50 seconds and increased daily volume from 320 to around 2,000 claims, with 98% accuracy.
These same capabilities can automate claims status checks across payer portals, eliminating hours of manual logins and updates, and giving teams more time for high-value AR resolution.
4. Real-time RCM insights dashboards for healthcare leaders
In its recent guidance on How to Use AI in RCM to keep your revenue flowing, GeBBS highlights the importance of real-time visibility across denials, cash flow, and work queues.
AI-driven analytics power real-time RCM insights dashboards for healthcare leaders, consolidating data from coding, billing, and AR systems into one view.
5. Smarter patient financial engagement
AI in Revenue Cycle Management is also changing the patient experience. GeBBS’s AI-driven tools support automated payment reminders, tailored outreach, and data-backed payment plan recommendations that reflect a patient’s ability to pay.
6. Scalable operations with less burnout
Manual, repetitive work increases errors and drives burnout. GeBBS’s AI and RPA take over low-value tasks such as data entry, basic coding, and routine claim follow-up, so teams can focus on complex cases and strategic projects.
This shift improves accuracy, stabilizes staffing needs, and creates a more resilient operating model that can scale without adding equivalent headcount.
Why AI-Powered RCM Now
Taken together, autonomous coding, AI-powered claims processing, predictive denial analytics, RCM workflow automation, real-time analytics, and patient-centric engagement, AI for healthcare RCM is becoming essential infrastructure, not a “nice to have.” GeBBS Healthcare Solutions, as a leading technology-enabled RCM partner, is using these iCodeOne capabilities to help organizations protect revenue, lower costs, and future-proof their revenue cycle.
For healthcare leaders, the message is clear: embracing AI-powered RCM solutions today is the fastest path to more accurate billing, faster cash flow, and a healthier, more sustainable RCM operation.
