How Can I Use AI to Automate Prior Authorization Calls? - 11 Tools

AI can automate the repetitive phone work behind prior authorization, including calling payers, navigating IVR menus, waiting on hold, checking whether authorization is required, retrieving status updates, documenting reference numbers, and scheduling the next follow-up.

Complex denials and clinical decisions should still move to qualified staff.

If you are asking how can I use AI to automate prior authorization calls, the most practical answer is to deploy a healthcare AI voice agent between your EHR or revenue cycle system and the payer phone line.

Instead of a staff member spending time dialing an insurer, entering member details, navigating phone menus, waiting for a representative, asking standardized questions, and typing the result back into the patient record, an AI agent can perform much of that administrative workflow.

Opportunity is significant. The American Medical Association reported in 2026 that physicians and their staff spend an average of 13 hours each week on prior authorization, while practices complete about 40 prior authorizations per physician per week.

Ninety-four percent of physicians surveyed said prior authorization contributes to burnout.

Goal is not to let AI decide whether a patient treatment is medically necessary.

Goal is to remove repetitive administrative calls from your staff workload while keeping people responsible for exceptions, clinical discussions, appeals, and peer-to-peer reviews.

11 Best AI Tools to Automate Prior Authorization Calls

Market includes both direct voice agents and broader prior authorization platforms.

Choose based on whether your actual bottleneck is payer phone calls, electronic submissions, clinical documentation, or the entire workflow.

The following are 11 strong platforms to evaluate in 2026.

This is not a claim that every product performs the same type of automation; their roles differ substantially.

1. Prosper AI

Best for: Direct payer calls for authorization initiation and follow-up.

Prosper prior authorization agent, Kate, is designed to call payers, determine whether authorization is required, initiate requests, track existing authorizations, navigate decision trees, speak with representatives, and return information to the EHR or system of record.

For organizations researching the top AI voice agents for prior authorization, Prosper deserves consideration because payer calling is a defined product use case rather than a generic voice-agent configuration.

2. Infinitus

Best for: High-volume payer follow-up and specialty healthcare workflows.

Infinitus provides voice AI agents for payer conversations involving prior authorization, benefit verification, appeals, claims, and related administrative work.

Its dedicated prior authorization solution focuses particularly on collecting PA requirements, status information, decisions, and updates for medications, procedures, and diagnostic tests.

3. SuperDial

Best for: Revenue cycle teams with heavy outbound payer call volume.

SuperDial focuses on automating outbound healthcare phone calls.

Its platform supports prior authorization, eligibility, claim follow-up, credentialing, and other payer interactions.

For authorization work, it can retrieve requirements and status updates and log call results into existing systems.

4. Orbit Healthcare

Best for: Combining voice, RPA, EDI, and electronic authorization workflows.

Orbit takes a broader workflow approach.

Its published process describes using AI voice agents to call payers to determine whether prior authorization is required, then using technologies including HL7, FHIR, EDI X12, and RPA to prepare, submit, monitor, and update authorization cases.

This is useful when calls are only one part of your authorization problem.

5. Spike

Best for: PT, OT, and SLP practices handling insurance administration.

Spike provides healthcare voice AI for back-office workflows including insurance verification, prior authorization, and claim status.

The platform is particularly positioned around therapy clinics and says its agents work with more than 1,000 payers.

6. Voice.ai

Best for: Configurable voice workflows for verification and PA follow-up.

Voice.ai offers a healthcare prior authorization workflow that covers eligibility, authorization status follow-up, missing-information intake, and exception routing.

It also supports sending denials, peer-to-peer needs, and complex situations to staff rather than trying to resolve everything autonomously.

7. IVA Evolve

Best for: Practices that want voice automation connected to EHR and billing tasks.

IVA Evolve healthcare agents support routine prior authorization calls and claims status follow-up alongside other practice communication.

Its broader model focuses on having the agent take an action after the conversation, such as updating an EHR, billing application, or workflow.

8. Telnyx

Best for: Organizations building a customized voice AI application.

Telnyx offers a pre-authorization support voice AI template designed primarily for incoming authorization status inquiries.

It can verify a caller, retrieve PA information using a webhook, explain statuses, and escalate clinical reviews or appeals.

This makes it relevant to payers and organizations building their own voice application rather than purchasing a completely managed provider-side calling solution.

9. Develop Health

Best for: Multi-channel medication authorization automation.

Develop Health takes a wider approach than voice alone.

Its prior authorization model combines real-time benefit information, electronic PA channels, FHIR, fax, AI-powered payer outreach, and human escalation.

Its own guidance correctly highlights an important reality: no single phone, fax, portal, or electronic channel reaches every payer workflow.

10. Notable

Best for: Automated authorization work queues and payer portal workflows.

Notable’s authorization product focuses on determining whether authorization is required, extracting information from the EHR, submitting authorizations through payer portals, and bringing status information back into the EHR.

It is more relevant when your bottleneck is portal work than when you specifically need an autonomous payer-calling bot.

11. Infinx

Best for: Organizations wanting automation combined with human authorization support.

Infinx Patient Access Plus uses AI, payer integrations, workflow automation, and human-in-the-loop services to manage prior authorizations.

This makes it worth evaluating when you need a broader operating model rather than voice AI alone.

What Does AI Prior Authorization Call Automation Actually Do?

Voice agent performs the administrative parts of a payer call while exchanging structured information with your existing healthcare systems.

A well-designed AI workflow can start when a new authorization case appears in EHR, practice management platform, or RCM work queue.

Agent can retrieve approved data such as the patient member ID, payer, provider NPI, CPT or HCPCS code, diagnosis information, service date, and authorization request number.

It can then:

Call the payer automatically.
Navigate IVR menus using speech and keypad inputs.
Verify patient and provider information.
Ask whether prior authorization is required.
Request the current authorization status.
Capture approval or reference numbers.
Identify missing information.
Record the payer representative’s response.
Generate a structured call summary.
Update your work queue or EHR.
Schedule another follow-up when the request remains pending.
Escalate exceptions to a human authorization specialist.

Platforms such as Prosper AI, Infinitus, SuperDial, and Orbit advertise voice-based payer workflows for prior authorization.

Where AI Helps Most in Prior Authorization Calls

Start with predictable, repetitive calls rather than trying to automate every authorization scenario at once.

Safest and highest-value use cases are administrative.

Prior Authorization Requirement Checks

AI calls the payer and asks whether a given service, procedure, medication, or CPT code requires authorization.

Result can be recorded before staff spend time preparing a submission that may not be necessary.

Authorization Status Follow-Up

After submission, the agent calls the payer and asks whether the case is approved, pending, denied, or waiting for additional documentation.

This is one of the strongest applications for AI agents that handle prior authorization calls because the conversation follows a relatively predictable structure.

Missing Information Checks

Agent can identify whether the payer needs clinical notes, supporting documents, additional coding details, or another action before processing the request.

It should then assign that requirement to the appropriate person instead of inventing or supplying clinical information itself.

Approval Detail Capture

When approved, the AI can collect the authorization number, approved service, effective dates, number of visits, limitations, and payer reference information.

Those details can be written directly into the authorization record.

Automated Follow-Up Scheduling

If the payer says, “Call again in three business days,” workflow can create the next task instead of relying on an employee to remember.

How to Build an AI Prior Authorization Call Workflow

Strongest architecture connects the AI voice layer to your case data before the call and writes verified results back afterward.

A practical workflow looks like this:

EHR/RCM → Authorization Queue → AI Voice Agent → Payer → Structured Result → Validation → EHR/RCM

Step 1: Identify the Right Cases

Start with routine authorization requirement checks and status inquiries.

Avoid starting your pilot with complicated appeals, peer-to-peer reviews, experimental treatments, or cases requiring nuanced clinical interpretation.

Step 2: Give the Agent Only Required Data

Pull the minimum information needed for the call from your source system.

Examples include:

Patient name
Member ID
Date of birth
Payer
Provider name
NPI
CPT/HCPCS code
Diagnosis code when necessary
Authorization number
Requested service date

Do not provide unrelated patient information simply because it exists in the EHR.

Step 3: Build Payer-Specific Call Logic

Different payers use different IVR structures, authentication questions, terminology, and workflows.

Automation therefore needs defined conversation paths rather than one vague prompt telling an LLM to “handle the prior authorization.”

Step 4: Define Human Escalation Rules

Transfer or stop the automation when the conversation requires:

Clinical judgment
Peer-to-peer review
An appeal decision
Medical necessity discussion
Information not present in an approved source
Unexpected identity verification
Conflicting payer information
A patient safety concern

This boundary matters. A 2026 research benchmark examining complex healthcare workflows, including provider prior authorization, found that even the best evaluated AI-agent configuration completed only a minority of long-horizon tasks successfully.

That is a strong reason to use controlled automation rather than assume an AI agent can safely improvise across every authorization scenario.

Step 5: Write Structured Results Back

Do not leave useful information trapped inside a call recording or transcript.

Extract fields such as:

PA required: Yes/No
Authorization status
Authorization number
Effective dates
Missing documentation
Representative name
Call reference number
Follow-up date
Escalation reason

That turns voice AI into workflow automation rather than another communication channel employees must review manually.

How to Compare the Top Voice AI Healthcare Platforms for Prior Authorization

Do not choose a vendor because the demo voice sounds natural; evaluate whether it can reliably complete your real payer workflow.

When comparing the top voice AI healthcare platforms for prior authorization, ask each vendor to demonstrate your actual use case.

Evaluate:

Which payers can the system call?
Can it navigate payer IVRs?
Can it wait on hold?
Can it interact with human payer representatives?
Can it use DTMF when required?
Can it pull case information securely from your EHR?
Can it write structured results back?
Can it recognize when information is missing?
What happens when the payer contradicts existing records?
How does human escalation work?
Are calls and actions auditable?
Does the vendor execute a BAA when appropriate?
How is PHI stored and retained?
Can you control which fields the AI accesses?
How are failed calls retried?
Can you measure automation rate, accuracy, turnaround time, and escalations?

A polished conversational demo is less important than reliable task completion.

HIPAA and Compliance Requirements

Prior authorization automation handles sensitive patient information, so compliance and security need to be designed into the workflow before launch.

If a software vendor creates, receives, m/8aintains, or transmits PHI on behalf of a HIPAA-covered entity, HHS generally treats that vendor as a business associate, which means an appropriate business associate agreement is required.

Your implementation should also address access controls, encryption, audit logs, data retention, minimum-necessary access, authentication, incident handling, and subcontractors that may process PHI.

Call recording and automated-call disclosure requirements can also vary by jurisdiction and situation, so organizations should have their legal and compliance teams review the proposed calling workflow before deployment.

AI Voice Calls Will Not Replace Electronic Prior Authorization

Voice automation solves today’s phone bottleneck, but the future PA architecture will increasingly combine voice with APIs and electronic transactions.

CMS is pushing healthcare toward more standardized electronic prior authorization.

Under CMS-0057-F, impacted payers generally must implement Prior Authorization APIs beginning January 1, 2027. Those APIs must support requirements discovery, requests, responses, approval information, denial reasons, and requests for additional information for covered services subject to the rule.

That does not mean phone calls disappear in 2027.

Organizations will still encounter exceptions, payer variations, workflows outside the CMS rule, drug authorizations that are excluded from these particular API requirements, legacy systems, and cases requiring human interaction.

The better architecture therefore supports API + portal + fax + voice + human escalation, rather than betting on one communication channel.

Where Should I Start?

Automate one high-volume, low-clinical-risk call type first and measure it before expanding.

Start with authorization status checks.

Choose one payer group and one repeatable workflow. Document what your employee does from the moment a case enters the queue until the payer response is saved.

Then automate the predictable steps.

Track:

Calls attempted
Calls completed
Average handling time
Human interventions
Successful status retrievals
Incorrect results
Cases requiring rework
Time from submission to decision
Staff hours saved

Once accuracy and escalation behavior are stable, expand into authorization requirement checks, initiation, missing-information follow-up, and related workflows.

Do not begin by asking an AI agent to autonomously handle every denial and clinical conversation.

Final Thoughts – AI Agents that Handle Prior Authorization Calls

Strongest use of AI in prior authorization is not replacing healthcare judgment; it is removing repetitive administrative work between your staff, your systems, and payers.

For organizations asking how can I use AI to automate prior authorization calls, start with the calls employees repeat every day: determining whether authorization is required, checking pending status, collecting approval details, documenting results, and scheduling follow-up.

Use AI for predictable administrative work. Use structured integrations so results flow back into the EHR. Create strict escalation rules for clinical and unusual cases. Measure accuracy before increasing autonomy.