In the U.S., administrative costs make up about 30% of total healthcare spending. This amounts to billions of dollars every year. Studies by groups like the American Medical Association (AMA) and McKinsey show that much of this spending comes from paperwork and manual processes needed to manage insurance claims, prior authorizations, referrals, and billing. Doctors spend twice as much time on paperwork as they do with patients. This extra work not only wastes time but also causes many healthcare workers to feel tired and stressed. Over 60% of U.S. doctors say they have at least one sign of burnout because of these issues.
When looking at prior authorizations alone, providers might spend up to two full workdays every week handling requests, sending documents, checking approvals, and following up with insurance companies. These delays often stop patient care, making it harder to provide quick diagnoses and treatments. For example, the American Heart Association says that 33% of doctors noticed bad effects on patients because of delays in prior authorizations.
Payer-facing AI phone calls are automated voice calls powered by artificial intelligence. They talk directly with health insurance companies for healthcare providers. Unlike older phone systems that make users press buttons and follow fixed menus, AI phone agents have natural conversations. They understand complicated questions, can handle multiple steps in a talk, and answer quickly. This makes the process more reliable and easier to use.
These AI systems use large language models or special language technology made just for healthcare tasks. They can handle requests like:
Compared to manual calling or old systems, AI calls can manage many conversations at once, switch to a human agent when needed, and connect with Electronic Health Records (EHRs), Enterprise Resource Planning (ERP) systems, and other healthcare software to share data and automate tasks.
Making calls to payers is often repetitive and takes a lot of time. AI phone agents can automate much of this work, saving staff time. Research from McKinsey says AI tools for prior authorization might cut the manual work by 50 to 75%. This means medical staff can spend more time helping patients instead of chasing paperwork.
For example, Baptist Health used an AI tool for prior authorizations that cut manual case reviews for imaging by almost half. This saved the work of about three full-time staff members. It also lowered costs and helped providers focus on patient care.
AI calls reduce mistakes that happen during manual data entry or by talking on the phone. These systems check payer rules and patient information in real time to make sure submissions are complete and correct. This lowers the chance of claim denials caused by errors or missing information. Research shows 45% of denial letters contain errors or missing instructions, which causes more delays and work.
Integrated with current systems and real-time dashboards, managers can see call results clearly and step in when people need to review details, keeping control and responsibility.
Delays in prior authorizations stop patients from getting needed treatments quickly. AI phone systems, like those from Rhyme and Availity, have been able to get first-time approvals within 90 seconds for 80% of cases. Quicker approvals help clinics reduce patient waiting times and improve satisfaction by making sure patients get tests, equipment, and treatments on time.
The American Medical Association says paperwork is a main cause of doctor burnout. Automating routine calls lowers stress and the need for extra work hours. For example, Baptist Health saved on overtime costs related to authorizations. Other tools, like HealthEdge’s AI member engagement solutions, help staff by making work easier and letting them focus on more important care tasks.
Healthcare work deals with very sensitive patient data. Strong security rules are needed to follow laws like HIPAA and get certifications such as SOC 2 Type 2 and ISO 27001. Leading AI healthcare companies like Bland AI, Synthpop, and Vogent follow strict rules to protect patient data while allowing smooth data exchange with payers.
Security helps build trust with providers and patients, which is important for using AI. Being clear about how AI works, protecting data privacy, and using safe system designs are key for healthcare workers to accept AI tools.
Using AI phone calls with automation tools gives more benefits. When payer communications connect to electronic health records (EHRs), appointment systems, billing software, and credentialing databases, healthcare groups get more complete solutions that cut down on broken manual tasks.
For example, AI tools from Synthpop can automate referrals, manage incoming faxes, check patient records for treatment needs, and convert talks into written notes to help submit claims that follow payer rules. Integration with ERP software like Bonafide smooths out order entry and claim handling, especially for areas like durable medical equipment (DME) and infusion treatment.
These AI workflows cut down on mistakes and allow real-time updates with detailed dashboards when monitoring operations. This helps managers find problems, ensure timely follow-ups, and use resources better.
Healthcare groups using AI also get benefits like:
Costs from inefficient administrative work in U.S. healthcare are very high. The average yearly spending per person was about $15,074 in 2024, with 15-30% of this for administrative tasks. Groups like the American Hospital Association and McKinsey say wider use of AI might save the system up to $360 billion every year by cutting manual work and speeding up tasks.
Automating payer calls helps with staff shortages at over 65% of hospitals and health systems, where paying workers takes up more than half of the expenses. AI handles many calls that busy staff face, lowers patient no-shows by sending reminders, improves follow-ups after hospital stays to cut readmissions, and makes payment collections easier.
For both healthcare payers and providers, AI phone agents with automation can lower costs, speed patient care, reduce staff burnout, and improve care quality. Better administrative processes also improve how payers and providers work together, as seen in AI tools that make communication in prior authorization smoother and clearer.
Even with clear benefits, AI tools for payer communication face some challenges. The 2025 Healthcare Consumer Study by HealthEdge found that only 21% of patients have used AI tools from health plans, though 64% are open to trying them. Many people worry about data privacy, security, and the accuracy of AI information. To ease these concerns, healthcare groups and AI makers need to explain how AI works, promise to follow rules, and ensure data is kept safe.
Also, using AI needs to cause as little disruption as possible to current clinical work. Providers like AI tools that fit inside their existing EHR systems, like Epic, so staff don’t have to learn new systems or stop using familiar ones. This ease encourages provider support and wider use.
Several companies lead the creation of AI phone tools made for healthcare:
These companies show growing moves toward more automated and efficient healthcare administration in the U.S.
Medical practice managers, owners, and IT staff who handle efficiency should consider payer-facing AI phone calls and workflow automation. These tools change costly, time-consuming manual work and can make communication between providers and payers faster, smoother, and more accurate — which helps both patients and providers.
Payer-Facing AI Phone Calls use AI to manage phone interactions with health insurers, automating tasks like verifying eligibility, prior authorizations, claim status checks, denied claims appeals, credentialing, and provider management, mostly via outbound calls with some inbound capabilities.
Healthcare AI agents offer dynamic, natural conversations with lower latency and higher reliability, integrating securely with EHRs and allowing seamless fallback to human agents, unlike rigid, menu-driven traditional IVR systems which have limited adaptability and user experience.
Most platforms hold HIPAA and SOC 2 Type 2 certifications, with some also possessing ISO 27001 and GDPR compliance, ensuring strong data privacy and security in managing sensitive healthcare information.
Processes commonly automated include eligibility and benefits verification, prior authorization requests, appointment scheduling, claim status updates, medication management, referral intake, billing inquiries, and managing denied claim appeals.
AI agents reduce administrative burden by automating repetitive tasks, improving data accuracy, expediting patient access to care, integrating with existing healthcare and ERP systems, and providing real-time analytic dashboards for performance monitoring.
They use proprietary or fine-tuned large language models and in-house language models to enable human-like, low-latency voice interactions, with capabilities to break conversations into sub-prompts and support advanced IVR navigation and human handoffs.
AI platforms integrate with EHRs, ERP, order management, prescription platforms, and insurance databases via APIs or low-code/no-code dashboards, allowing seamless data exchange and automation of complex workflows within healthcare operations.
Features include scheduling and tracking calls, custom call flow configuration through low-code UIs, real-time call result viewing, post-call automation, human agent fallback, and dashboards for monitoring and optimizing call performance.
Notable providers include Bland AI, Infinitus Systems, Nanonets Health, SuperDial, Synthpop, Vogent, Avaamo, Deepgram, Delfino AI, and Prosper AI, each offering specialized AI-driven automation for payer and patient communications.
AI agents automate key RCM processes like claim status updates, eligibility checks, prior authorizations, and denials management by communicating with payers, generating summaries, alerting humans when necessary, and integrating with multiple EHR platforms for accuracy and speed.
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