Nurse-led digital triage and health literacy navigation: redefining the front door of public health in the artificial intelligence era.

Artificial intelligence (AI)-driven digital triage is fast becoming the front door of public health systems worldwide. As algorithms take over symptom assessment and risk stratification, however, nurses risk being reduced to validators of machine output, and patients with limited health literacy risk being left behind. This perspective argues that nurses should not merely adapt to AI triage but redefine their role as "health literacy navigators," positioned between algorithmic risk stratification and the patient who must act on it. We outline four functions that define the role: interpretation (translating AI output into language patients can use), empathy (understood as emotional calibration rather than reassurance), calibration (using clinical judgment to verify, challenge, or override algorithmic recommendations), and referral (guiding patients through the complex pathways that follow triage). The aim is a form of coevolution in which AI handles data-intensive stratification and nurses take on meaning-intensive navigation. Realizing this vision requires changes in nursing education, institutional policy, and AI system design. Embedding health literacy navigation in the digital triage workflow lets public health systems capture the efficiency AI offers without losing the relational core of nursing, strengthening resilience by ensuring that technological efficiency does not come at the expense of relational safety and health equity.