Claim denials have been going up steadily over the past few years. According to BDO, about 60% of medical groups in the United States say they have more claim denials each year. Healthcare providers spend close to $20 billion every year trying to fix these denied claims. The problem is even bigger because around 82% of these denials could be avoided or fixed early, before they turn into bigger issues.
Denied claims stop cash from coming in and make extra work for staff. People have to manually review and follow up on denials, taking time away from patient care and other important tasks. The number of denials is growing faster than staff can handle, which causes hold-ups in the revenue cycle. That is why better denial management is very important for healthcare administrators and IT teams.
Agentic AI means smart computer systems that can do difficult jobs without much human help. In healthcare revenue management, these AI systems do many time-consuming steps. These include finding denied claims, figuring out why they were denied, deciding which ones to handle first, and making appeals automatically.
John Landy, CTO of FinThrive, says that agentic AI fits well with the denial appeal process. Denials need careful checking of rejection codes, medical documents, and payer rules. AI can handle all of this in a systematic way. It not only studies denial trends but can also send appeal requests right when a claim is denied. This cuts down the work for revenue cycle teams a lot.
Waystar’s AltitudeAI is an example of agentic AI used for denial management. Users of AltitudeAI have seen a 40% rise in claims being overturned. They also cut the time to handle appeals from 38 hours down to just 2 hours for medium-sized health systems. This shows a shift from slow manual work to a faster and more effective way that improves money flow.
Managing denials by hand takes a lot of effort. Staff must go through many denial notices, understand complicated payer rules, check medical information, prepare appeal papers, and track appeal progress. All this work takes a lot of time.
Agentic AI makes these tasks easier by:
By using these automated steps, healthcare workers can spend less time on routine tasks and more on cases that need human decisions. Waystar says its AI platform saves about 13 full-time employee hours per medium-sized institution. This lets staff focus more on important priorities like patient care.
The main goal of managing denials is to get paid for claims quickly. Higher overturn rates mean more denied claims get approved later, which helps bring in more money.
Agentic AI helps with:
Early users of AI systems like AltitudeAI report up to 40% higher overturn rates compared to manual methods. This means more claims get paid faster without repeated appeals or long waits. It helps healthcare practices stay financially stable.
Issues with prior authorization and coding errors cause many claim denials. Agentic AI helps by automating prior authorization. It collects needed clinical data, checks payer documents, submits requests, and watches for approval in real-time. This cuts down on delays caused by manual reviews and phone calls.
For coding errors, AI looks at clinical documents linked to denied claims. It spots when claims were coded correctly or not. If there are errors, AI makes tailored appeal letters with reasons. This cuts paperwork for staff.
BDO research shows about 82% of denials can be avoided, many due to prior authorization and coding mistakes. Using AI to fix these reduces denial frequency and increases clean claim submissions.
AI is changing how revenue cycle management works by automating workflows. Platforms like Jitterbit’s agentic AI combine smart apps, AI agents, and data tools to link processes together.
For healthcare administrators, this means:
Research shows these automation tools can improve workflow efficiency by up to 50%. For healthcare providers, this means faster payments, less administrative work, and better patient satisfaction due to fewer billing errors and quicker answers.
Denied claims and billing issues often confuse and frustrate patients. AI agents not only help with internal denial management but also improve how patients get financial information by:
Judson Ivy, CEO of Ensemble Health Partners, says AI agents in patient contact centers increase the rate of questions being answered right the first time. This lowers the number of follow-up calls and helps patients trust their provider more.
Interest in AI for revenue cycle management is growing fast. A 2025 Healthcare CFO Outlook Survey shows:
This quick growth is due to more claim denials, complex payer rules, fewer staff, and more regulations.
Industry experts say agentic AI might automate up to 80% of revenue cycle tasks soon. This includes denial management, prior authorizations, checking patient eligibility, and processing claims. AI agents may also communicate and learn from each other across systems, leading to fully automated company-wide processes.
Medical practice administrators, owners, and IT managers thinking about AI for denial management should consider:
Working with well-known AI providers that offer support and help with change management can reduce risks and speed up the benefits.
Agentic AI technology is becoming important for healthcare revenue cycles in the United States. By automating denial management and appeals, it greatly lowers manual workloads, raises the number of overturned denied claims, and makes revenue cycle processes more efficient. When combined with full workflow automation and better patient financial communication, AI is changing how healthcare providers handle their financial tasks.
For medical practices facing more denials and heavy administrative loads, using agentic AI can be a good way to improve financial results, simplify operations, and spend more time on patient care instead of paperwork.
Agentic AI refers to autonomous AI systems capable of performing complex tasks without human intervention. In RCM, it automates and improves processes like claims management, prior authorization, denial management, patient eligibility checks, and financial communications to enhance efficiency, accuracy, and reduce administrative burden.
AI agents can cut administrative tasks by automating repetitive workflows. According to a Salesforce survey, agentic AI can reduce administrative workload by 30% for doctors, 39% for nurses, and 28% for administrative staff by taking over tasks like claims processing and prior authorizations.
Agentic AI automates verification by extracting data from insurance cards, EHRs, and payer systems using natural language processing and APIs. This real-time verification minimizes eligibility errors, reduces denials, accelerates revenue cycles, and smooths billing and collections.
The technology autonomously collects clinical data, reviews payer policies, completes submission forms, and tracks requests. It identifies potential approval issues proactively, reducing delays, administrative workload, and enabling cleaner claims with minimal human input.
Agentic AI analyzes denial codes, identifies error patterns, prioritizes high-impact denials, and automates the appeals process from initial denial to resubmission. This reduces manual work, scales appeals operations, and increases denial overturn rates.
Claims management involves parsing complex payer contracts and rules. Agentic AI learns payer requirements, automates claim assembly, predicts payment likelihood, and adjusts processes accordingly, significantly reducing errors and approval times.
AI agents handle routine billing inquiries, provide personalized billing explanations, process payments, and offer multilingual support. They increase one-touch resolution rates while escalating issues to humans when needed, thus enhancing patient experience and operational efficiency.
Agentic AI improves workflow orchestration by enabling AI agents to communicate and learn from each other across systems, accelerating processes, reducing errors, and improving coordination across revenue cycle functions.
Agentic AI tackles labor-intensive tasks such as manual eligibility verification, prior authorization bottlenecks, rising claim denial rates, complex claims processing, and patient communication inefficiencies, all exacerbated by staffing shortages and administrative overload.
Beyond early adoption, agentic AI promises scalable, enterprise-wide deployment with faster market delivery. Its orchestration capability allows expansion into diverse healthcare administrative tasks, revolutionizing revenue cycles with continuous learning, automation, and improved financial outcomes.
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