Healthcare

AI for Healthcare

The friction between payers, your staff, and your records.

INDUSTRYSenior Care LivingAI Agent LayerCloses coordination gaps across your operationsRecordsERP, EHR anddata sourcesSchedulingShifts, tasks andworkflowsBillingFinance, AR andrevenue cycles
01. Why AI Matters

Why AI Matters Here

Healthcare operating margins held near 1% for most of 2025. Administration accounts for roughly 25% of total US healthcare costs, and the staff who manage billing, prior authorization, and patient access are retiring faster than organizations can replace them. There is no reliable backfill pipeline for those roles.

The highest-return AI use cases in healthcare are operational, not clinical. Prior authorization, denial management, scheduling, and eligibility verification are high-volume, rule-based processes. AI agents handle that volume without touching your clinical workflows or replacing systems your staff already use.

02. Operational Challenges

Where Staff Time Goes

Prior Authorization Processing

Patient access staff check payer portals, compile documentation, and track submission status manually. A single request can take four to six staff touchpoints to resolve.

Claims Denial Management

Denial staff log into multiple payer portals, identify reason codes, and rebuild resubmission packages for each appeal. Backlogs grow faster than available staff hours allow.

Eligibility Verification

Coverage changes between scheduling and intake. Verifying it requires cross-referencing payer systems that do not connect to your EHR automatically.

Scheduling Coordination

No-shows create gaps that schedulers fill by contacting waiting patients one at a time. Proactive outreach at volume requires staff capacity that most scheduling teams do not have.

03. Qualification

Who This Is For

Good FitNot a Good Fit
Your revenue cycle or patient access teams handle high volumes of prior authorizations, claims, or eligibility requests daily.You are mid-implementation of a new EHR and cannot commit staff to a parallel pilot.
Your billing and patient access roles are under staffing pressure and open positions are not being filled.You expect AI to replace clinical judgment or manage patient-facing care decisions.
You have documented workflows and defined business rules for at least one revenue cycle process.Your administrative processes are not yet standardized across locations or departments.
You are ready to pilot one process in your live environment before committing to anything further.You need a full enterprise rollout within 60 days with no phased approach.
04. AI Applications

Where AI Agents Work

Revenue Cycle

  • Prior authorization agent: Submits requests, monitors payer portals, and escalates exceptions for staff review.
  • Denial management agent: Identifies reason codes, retrieves EHR documentation, and prepares resubmission packages for staff approval.

Patient Access

  • Eligibility verification agent: Confirms coverage at scheduling and at intake, flagging discrepancies before the visit occurs.
  • Scheduling agent: Identifies cancellation slots and contacts waitlist patients to fill gaps without requiring staff to initiate each outreach.

Clinical Operations

  • Referral tracking agent: Monitors outbound referral status and alerts care coordinators when an external provider has not responded within the defined window.

Compliance and Coding

  • Coding audit agent: Reviews encounter documentation for ICD-10 and CPT accuracy before billing submission and flags errors for coder review.
05. Results

What Changes With AI

Prior Authorization Processing

Before: Patient access staff spend 12 to 16 minutes per authorization on portal submissions, documentation, and status tracking. High-volume specialties handle 40 to 80 requests per staff member per day.

After: The AI agent handles submission and monitoring for standard requests. Staff manage exceptions only, and turnaround drops from 3 to 5 days to same-day.

Claims Denial Management

Before: Each denial appeal takes 20 to 40 minutes to prepare across multiple payer portals, with staff rebuilding each case from scratch.

After: The agent prepares the resubmission package for staff to approve. Resolution time drops approximately 60%.

Figures shown are representative of outcomes in comparable implementations.

06. Agent Screens

What the agents look like

Representative screens showing how AI agents surface data and present decisions to your staff. Click any card to see the full view.

Revenue Cycle

Denial Management

Denial reason codes identified and resubmission packages prepared for staff approval.

Revenue Cycle

Prior Authorization

Authorization requests submitted, payer portals monitored, and exceptions escalated for staff review.

Patient Access

Voice AI Scheduling

Cancellation slots filled by contacting waitlist patients automatically without staff initiating each outreach.

07. Engagement

How an Engagement Begins

Phase 1: AI Foundation Training (1 to 2 weeks)

Your billing, patient access, and operations staff complete AI Foundation Training before any solution is proposed. They identify use cases from inside their own workflows, which builds internal demand before implementation begins.

Phase 2: AI Readiness Assessment (2 to 3 weeks)

Tayana evaluates your EHR integrations, payer portal connections, and workflow documentation to confirm which processes are ready to automate. You receive a written recommendation with a prioritized scope.

Phase 3: Pilot Deployment (6 to 8 weeks)

One process, one AI agent, in your live environment with your actual data. Investment starts from $10,000. You evaluate the outcome before any further commitment.

08. Questions

Common Questions

How long does it take to deploy a healthcare revenue cycle AI agent?

A focused pilot on one process typically goes live within 6 to 8 weeks. Prior authorization and denial management are the most common starting points.

Can AI agents work alongside our existing EHR without replacing it?

Yes. The AI agent connects to your EHR and payer portals via API and works alongside your current systems. Nothing in your EHR changes.

What does a healthcare AI pilot cost?

Investment starts from $10,000 for a single-process deployment. Scope and complexity determine the final investment.

Is AI in healthcare administration HIPAA compliant?

Tayana addresses HIPAA requirements at the architecture level before any agent goes into production. Data handling, access controls, and audit logging are built in from the start.

Which healthcare administrative processes produce the fastest ROI from AI?

Prior authorization, denial management, and eligibility verification consistently show measurable outcomes within 90 days. These processes are high-volume and rule-based, which makes them well-suited for automation.

Can AI address healthcare administrative staffing shortages?

AI agents handle high-volume repetitive tasks, allowing your current staff to focus on exceptions and complex cases. This extends team capacity without requiring additional headcount.

What happens if an AI agent makes an error in a prior authorization submission?

The agent flags exceptions for human review before submission. Human oversight is built into the workflow at every point your process requires it.

How is Tayana different from a healthcare AI software vendor?

Tayana is a consulting firm. We design AI agents using your existing systems as the foundation. You pay for a working solution built on what you already have, not a new platform.

Ready to Take the Next Step

Book a thirty-minute call. We will confirm whether your situation is a fit and what the right starting point is, whether that is the AI Adoption Accelerator, a readiness assessment, or a direct pilot.

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Agent screen