Educating pharmacists for an artificial intelligence augmented profession: A narrative review of curricular and accreditation imperatives.
Journal:
Research in social & administrative pharmacy : RSAP
Published Date:
Jul 23, 2026
Abstract
Generative artificial intelligence (AI) moved from novelty to clinical infrastructure within a single Doctor of Pharmacy program, yet pharmacy curricula and the accreditation standards that govern them have not uniformly caught up. Written from a Canadian vantage point, this narrative review synthesizes international peer-reviewed literature and grey-literature guidance from the International Pharmaceutical Federation, World Health Organization, UNESCO, and national accreditors in Canada, the United States, the United Kingdom, Australia, and New Zealand. Rather than presenting a flat catalogue of competencies, we propose a four-tier hierarchy that makes explicit which AI competencies pharmacy owns and which it shares: general competencies (foundational AI literacy and the applied skills that follow from it, which in steady state belong upstream of pharmacy education); interprofessional competencies (AI governance, ethics, equity, and regulatory awareness, shared across the health professions); pharmacy-specific competencies (clinical AI applications in pharmacy workflows, pharmaceutical sciences AI, and AI-augmented pharmacokinetics and model-informed precision dosing); and role-specific specialization. Because current students entered pharmacy programmes without K-12 or undergraduate AI preparation, faculties must carry the general and interprofessional layers transitionally, a five to ten year window in which faculty development, not curriculum design, is the binding constraint. Six pedagogical principles and five accreditation levers are synthesized, with CCAPP Standard 20 and its international counterparts named as the single highest-leverage accreditation instrument. Whether pharmacy remains the medication-therapy expert profession depends on whether graduates are the clinicians most literate in AI assisted pharmacotherapy and, most distinctively, in model-informed precision dosing, where the profession's claim is strongest.
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