Abstract:

Since the COVID-19 pandemic, the pace of the transformation of medical education has accelerated. During the pandemic-induced period of remote learning, medical educators were confronted with new pressures and opportunities to develop digital literacy and resilience. Consequently, many programs now feature hybrid digital learning environments in which Chatbots and virtual assistants handle routine student inquiries, high-fidelity simulation, and increasing AI leverage for curricular design and delivery. In short, AI has rapidly become the cornerstone of modern medical education, forever changing the medical education landscape, compelling medical educators to reconsider not just what we teach, but how and why we teach it.

In this evolving medical education ecosystem, some veteran faculty remain ignorant of the growing impact of AI on medical education, while others feel overwhelmed by these changes, lacking the training to harness AI tools responsibly. Faculty adoption of AI is slowed by uncertainty about best practices, particularly a lack of knowledge, limited time, unclear benefits, and discomfort with their new roles in AI-augmented learning environments. Institutional obstacles, ranging from inadequate infrastructure to poorly defined incentives, may compound these concerns.

Though survey data from medical educators consistently reveal widespread enthusiasm for AI’s potential, only a minority of medical school faculty are using AI daily for teaching, course design, and content delivery. Surveys and reviews reveal that although faculty confidence in AI has grown, most still report themselves as "novices" or "advanced beginners" and value formal training for effective use.

Our program has recently completed a strategic planning process during which we, like many other medical schools across the country, have committed to increasing the integration of AI throughout the curriculum. To achieve this strategic goal, we have committed to training faculty on AI literacy by developing AI literacy modules and hosting technology integration workshops.

This article examines how strategic professional development can empower faculty, especially those initially resistant or unfamiliar with technology to be leaders rather than late adopters. We envisage that the faculty development program will incorporate the following elements: Needs Assessment, Modular, Experiential Workshops, Champion-Led Communities, and Evaluation and Feedback. Drawing inspiration from Everett Rogers’s Diffusion of Innovations Theory and real-world best practices, the program will set out a roadmap for excellence in which we move beyond sporadic institution-led workshops to more program-focused sessions, led by peer faculty technology champions. Using a formal evaluation process to drive iterative improvement, we intend to move faculty past isolated AI experimentation towards meaningful, daily integration, supported by policies, training, and peer mentorship.

Keywords:

Artificial intelligence, training, faculty, education, quality, development, innovation.