The healthcare AI landscape is crowded with buzzwords, but one term is rapidly separating the future leaders from the legacy players: Agentic AI. Here’s what it actually means and why it matters for your practice.

If you’ve sat through recent healthcare technology presentations, you’ve likely heard vendors promise their AI will “revolutionize” your practice. Yet most clinicians using today’s AI tools—whether it’s a scribe AI solution or other ambient documentation platforms—still find themselves spending hours on administrative tasks.

Why? Because there’s a fundamental difference between AI that assists and AI that acts.

The Evolution: From Scribe to Agent

Traditional AI scribe tools have delivered incremental improvements to clinical documentation. These solutions listen to patient encounters, generate notes, and suggest coding—but they stop there. The clinician still needs to review, edit, approve, and then manually trigger every downstream action.

Think about your current workflow with an AI scribe:

  • The AI captures your patient conversation
  • It drafts a note for your review
  • You edit and approve the documentation
  • Then you manually order labs
  • Separately submit prior authorizations
  • Remember to schedule follow-ups
  • Chase down referral statuses
  • Close care gaps one by one

Each step requires human intervention. The AI assists, but it doesn’t execute.

Enter Agentic AI: The Autonomous Difference

Agentic AI represents a quantum leap beyond traditional scribe AI capabilities. Instead of just capturing and suggesting, agentic systems autonomously plan, reason, and execute complete workflows across your entire practice operations.

Here’s the critical distinction: While other ambient documentation platforms operate as sophisticated assistants or “copilots,” agentic AI functions as an autonomous workforce that can:

  • Execute tasks end-to-end without constant human intervention
  • Make contextual decisions based on clinical protocols and practice preferences
  • Orchestrate complex workflows across multiple systems and stakeholders
  • Maintain persistent state to follow up on tasks over days or weeks
  • Self-correct and adapt when encountering new scenarios

Think of it this way: You’re not getting software that helps your team. You’re getting a digital care team extension that never calls in sick, works 24/7, and gets more accurate over time.

The Three Levels of Healthcare AI: Where Does Your Solution Fit?

Level 1: Assistant AI

Promise: Finds patterns in data and predicts outcomes
Reality: Alerts and flags issues but never acts independently
Limitation: Only works well with lots of clean data

Example: Basic clinical decision support systems that highlight potential drug interactions

Level 2: Copilot AI (Including Most AI Scribe Solutions)

Promise: Synthesizes information and drafts outputs, reducing manual effort
Reality: Helps draft or summarize but always needs a human to complete the job
Limitation: Always requires human intervention to finish the work

Example: Current generation ambient documentation tools that generate encounter notes but require manual review and downstream action

Level 3: Agentic AI

Promise: Executes tasks autonomously while maintaining expert oversight
Reality: Independently completes multi-step workflows with built-in safety checkpoints
Limitation: Can run independently and go off track without proper guardrails checkpoints

Example: AI agents that not only document the encounter but also automatically submit prior authorizations, schedule follow-ups, close care gaps, and update problem lists—all while maintaining appropriate clinical oversight.

The Technical Architecture Behind True Agentic AI

What enables this leap from assistance to autonomy? True agentic AI requires three fundamental components that most scribe AI solutions lack:

1. Multi-Agent Orchestration

Instead of a single AI model trying to do everything, agentic systems deploy specialized agents that work together:

  • Documentation agents for clinical notes
  • Coding agents for billing compliance
  • Care coordination agents for follow-ups
  • Network agents for referral management

These agents communicate and hand off tasks seamlessly, like a well-coordinated clinical team.

2. Persistent State Management

Unlike traditional AI scribe tools that process each encounter in isolation, agentic systems maintain context across time. They remember that Mrs. Johnson needs her mammogram scheduled, that Dr. Smith prefers certain referral patterns, and that your practice always orders specific lab panels for diabetes management.

3. Autonomous Decision-Making with Guardrails

The system can make routine decisions independently—submitting straightforward prior authorizations, scheduling standard follow-ups, ordering protocol-based labs—while escalating complex cases to human experts.

Real-World Impact: From Hours to Minutes

Consider a typical Medicare Annual Wellness Visit. With traditional scribe AI:

  • AI documents the 45-minute encounter
  • You review and edit the note (5-10 minutes)
  • You manually identify care gaps (10 minutes)
  • You create orders and referrals (15 minutes)
  • Your staff follows up on each item over the next weeks

Total provider time saved: Maybe 15-20 minutes on documentation

With Agentic AI:

  • AI documents the encounter
  • Automatically identifies and prioritizes care gaps
  • Submits qualifying prior authorizations
  • Schedules appropriate follow-ups
  • Sends referrals with all required documentation
  • Tracks completion and follows up automatically
  • Alerts you only for items requiring clinical judgment

Total provider time saved: 35-40 minutes per visit, plus countless hours of staff follow-up time

Making the Shift: From Concept to Reality

The difference between assistive and agentic AI isn’t theoretical—it’s measurable in hours reclaimed, errors prevented, and workflows automated. Healthcare organizations implementing true agentic AI are seeing transformative results: 3-4 hours saved per provider daily, 40-60% reduction in medication errors, and 30-50% reduction in prior authorization denials.

But understanding the concept is just the beginning. In part two of this series, we’ll dive deep into specific workflows—pre-visit preparation that saves 6-11 minutes per patient, medication refills that execute in 12 seconds instead of 5 minutes, prior authorizations that auto-submit when criteria are met—and show you exactly how agentic AI transforms each process. We’ll also address the critical questions of safety, oversight, and implementation that every healthcare leader needs to consider.

For now, the key insight is this: The evolution from scribe AI to agentic AI represents a fundamental shift in healthcare technology. We’re moving from tools that help document care to systems that help deliver it. The practices that recognize and act on this distinction today will be the ones leading healthcare transformation tomorrow.

The Bottom Line: Actions Speak Louder Than Assistance

The healthcare AI market is noisy, with vendors claiming revolutionary capabilities. But when you strip away the marketing language, most solutions—remain stuck in the assistive paradigm. They’re sophisticated helpers, but helpers nonetheless.

Agentic AI represents a fundamental shift in how we think about healthcare automation. It’s not about building better assistants; it’s about creating autonomous systems that execute complete workflows while maintaining clinical oversight and safety.

The math is compelling. According to real-world implementations, agentic AI delivers 3-4 hours of time savings per provider per day:

  • Pre-visit preparation: 6-11 minutes saved per patient
  • During the visit: 40-45 minutes saved through real-time note creation and task execution
  • Post-visit administration: 115-170 minutes saved on refills, prior authorizations, and coding
  • Care continuity: 35-40 minutes saved per patient on gap management and follow-ups
  • Network interactions: 15-40 minutes saved on referral tracking and closure

These aren’t theoretical projections, they’re measured results from practices using autonomous AI agents. When you multiply these savings across 20-25 patients per day, the impact transforms practice operations.

But this isn’t just about ROI. It’s about transforming how healthcare is delivered. When administrative tasks become autonomous, clinicians can focus on what matters: patient relationships, complex medical decision-making, and preventive care.

As you evaluate AI solutions for your practice, remember this distinction: Most AI suggests. Onpoint Iris Medical Agentic AI acts.

The question isn’t whether AI will transform healthcare—it’s whether you’ll still be manually executing on AI suggestions while your competitors have digital care teams handling the work autonomously, 24/7, with ever-increasing accuracy.

Ready to explore how agentic AI can transform your practice operations? The shift from assistance to autonomy is already underway. Make sure you’re not left managing the suggestions while others are leveraging the execution. Fill out this form below to get connect with our market leadership team.

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