Objectives: 

  1. Distinguish among a large language model, an AI agent, and an agentic AI system based on their capabilities and degree of autonomy.
  2. Identify how institutional knowledge, patient information, and tools enable AI agents to perform healthcare workflows.
  3. Interpret comparative evidence on clinician-alone, clinician-with-AI, and AI-alone performance when considering clinical implementation.
Session date: 
10/14/2026 - 7:20am to 8:20am CDT
Location: 
Hybrid (In-person and Virtual)
United States
See map: Google Maps
  • 1.00 AAPA Category 1 CME
  • 1.00 MOC: ABS Accredited CME
    • 1.00 ABS Self-Assessment
  • 1.00 MOC: ABS Lifelong Learning & Self-Assessment Points (Part II)
    This activity meets the ABS requirements for CME and self‐assessment credit toward Part 2 of the ABS MOC program.
  • 1.00 AMA PRA Category 1 Credit™
  • 1.00 ANCC Contact Hours
  • 1.00 University of Wisconsin–Madison Continuing Education Hours
    • 1.00 Approved for AMA PRA Category 1 Credit™
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Discloser List CME Internal Report
Presenter(s): 
Anai Kothari, MD