The AI Colleague: Reimagining Interprofessional Collaboration and Education in Medicine

Area of Science:

• Medical Education
• Artificial Intelligence in Healthcare
• Interprofessional Collaboration

Background:

• Artificial intelligence (AI) is increasingly integrated into clinical workflows, moving beyond decision support to actively shape diagnostics, triage, and documentation.
• Current educational approaches often frame AI as a tool for individual clinicians, overlooking its impact on interprofessional team dynamics.
• This perspective fails to address how AI fundamentally alters team cognition, communication, and accountability.

Purpose of the Study:

• To introduce the concept of AI-expanded interprofessional collaboration (AI-IPC) and propose a framework for AI-expanded interprofessional education (AI-IPE).
• To argue that AI literacy alone is insufficient, advocating for training in coordinating human-AI-human interactions within clinical settings.
• To provide a practical, theory-aligned approach for educating healthcare teams on integrating AI as a collaborative participant.

Main Methods:

• Building on interprofessional education (IPE) theory, situated learning, and distributed cognition.
• Developing an AI-IPE approach focused on clarifying AI's role, defining AI-specific subcompetencies within IPE frameworks, and evaluating team behaviors.
• Utilizing the Interprofessional Education Collaborative (IPEC)-aligned evaluation scaffold with practical learning activities and assessment strategies.

Main Results:

• Proposed AI-IPE framework includes clarifying AI's boundary conditions, mapping AI subcompetencies, and evaluating team-level performance.
• An IPEC-aligned scaffold with concrete learning activities and assessment approaches is presented.
• Implementation requires digital infrastructure, institutional governance, and educators skilled in AI, workflow design, and IPE facilitation.

Conclusions:

• AI integration necessitates a shift from individual tool use to AI-expanded interprofessional collaboration.
• Effective AI-IPE requires training teams for critical engagement with AI, including verification and overriding AI contributions when necessary.
• Educational strategies must adapt to prepare healthcare teams for the evolving demands of collaboration in an AI-integrated environment.