Ethical Challenges of AI Adoption in Pharmacy Practice

Abstract

Artificial intelligence is increasingly being incorporated into medication management, clinical decision support, dispensing operations,  pharmacovigilance, patient counselling, and pharmaceutical supply systems. Despite these developments, existing ethical guidance largely addresses healthcare AI broadly and does not adequately reflect the interconnected responsibilities of pharmacists across the medication-use pathway. This study identifies a research gap in the absence of pharmacy-specific methods for assessing how ethical risks accumulate when AI recommendations move between prescribing, verification, dispensing, counselling, monitoring, and follow-up stages. It proposes a pathway-oriented ethical assessment framework centred on algorithmic fairness, patient autonomy, data governance, explainability, professional accountability, and continuous human oversight. The proposed investigation will evaluate AIsupported pharmacy decisions through simulated medication-use cases representing diverse demographic, clinical, linguistic, and socioeconomic conditions. Unlike studies that assess predictive accuracy alone, the framework treats ethical reliability as a multidimensional and context-dependent outcome. Particular attention is given to automation bias, responsibility diffusion, unequal system performance, confidentiality risks, and the erosion of pharmacistpatient trust. The study establishes a foundation for developing measurable governance standards that support responsible, equitable, and professionally accountable AI adoption in pharmacy practice