Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Jul 17, 2026
Date Accepted: Sep 2, 2026
Beyond AI Literacy: Understanding Healthcare Workforce AI Enablement in the Generative AI Era
ABSTRACT
The rapid diffusion of generative artificial intelligence (AI) is transforming healthcare delivery, education, administration, and research. In response, healthcare organizations have invested heavily in AI literacy initiatives and workforce development programs. Existing frameworks primarily focus on whether healthcare professionals understand AI and whether they can engage with AI effectively. However, healthcare practice increasingly reveals that individuals with similar levels of AI literacy and AI engagement often contribute very differently to AI-enabled work and organizational adoption. Some professionals primarily use AI to improve their own work, whereas others facilitate AI adoption, coordinate stakeholders, and integrate AI into routine practice. This observation suggests that current perspectives may overlook an important dimension of workforce AI enablement. In this viewpoint, we argue that AI literacy and AI engagement alone provide an incomplete explanation of how healthcare organizations realize the benefits of AI. Drawing upon literature from AI literacy, fluency theory, human–AI interaction, innovation diffusion, implementation science, and healthcare workforce development, we propose the Healthcare Workforce AI Enablement Matrix (HWAEM). HWAEM conceptualizes workforce AI enablement through two complementary capabilities: AI Fluency and AI Harnessing. AI Fluency refers to the capability to engage with AI effectively, appropriately, and responsibly across professional contexts, whereas AI Harnessing refers to the capability to identify opportunities for AI-enabled improvement, mobilize stakeholders, facilitate adoption, and integrate AI into collective work practices. The interaction of these capabilities generates four workforce profiles: AI Novices, AI Practitioners, AI Facilitators, and AI Leaders. We illustrate how these profiles manifest in healthcare practice and discuss implications for workforce development and AI implementation. HWAEM offers a new perspective for understanding healthcare workforce preparedness in the generative AI era and provides a foundation for future empirical research.
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