Same automation pressure, divergent outlooks: human resource development deficits associated with the stagnant employment outlook for Korean pharmacists in the age of Artificial Intelligence

Artificial intelligence (AI) and automation are reshaping the health workforce, yet projected employment differs across professions. The 2025–2035 qualitative job outlook published by the Korea Employment Information Service categorizes occupations using mean annual employment changes from its 2023–2033 quantitative projection. These changes are +2.7% for nurses, +1.9% for physicians and dentists, +1.7% for radiological technologists, +1.6% for Korean medicine doctors, +1.5% for clinical laboratory technologists, and +0.5% for pharmacists. Pharmacists alone among these seven professions are categorized as maintaining their current employment level, a downgrade from the previous edition. The outlook lists AI-driven automation as a decreasing factor for nurses, radiological technologists, and clinical laboratory technologists as well, although their projected growth remains positive. This narrative review combines policy and document analysis, an analysis of the national health insurance fee schedule effective 1 September 2026, and a comparison of pharmacy curricula to examine institutional characteristics that may help explain this divergence. Three interrelated features of pharmacist human resource development (HRD) are identified. First, 257 of 281 community pharmacy billing codes (91.5%) are dispensing fees tiered by days’ supply; medication counseling is the sole explicitly cognitive service among the six pharmacy fee categories. Second, professional development infrastructure was established later than for physicians and nurses, and a national specialist pathway for community practice is planned but not yet operational. Third, the extension of pharmacy education to six years substantially expanded experiential training, while school-based preparation remains limited in the curricula examined. No objective comparison of the outcomes of four- and six-year graduates was identified in this review. These features may help explain the divergence but have not been shown to cause the employment projection. An HRD agenda linking professional development, remunerated services, community specialization, and AI competencies is proposed.