Perception of Pharmacy Students on the Integration of AI in Clinical-Decision-Making

Abstract

Background: Artificial intelligence (AI) is transforming healthcare by enhancing clinical decision-making, drug discovery, and patient management. In pharmacy, AI improves diagnostic accuracy, reduces medication errors, and personalizes treatments. However, its integration depends on future pharmacists’ preparedness and perceptions, which remain underexplored. This study examines pharmacy students’ awareness, attitudes, and readiness toward AI adoption in clinical decision-making. This study aimed to assess pharmacy students’ awareness, perceptions, and attitudes toward AI in clinical decision-making and identify perceived benefits, challenges, and barriers to its integration. Methods: A cross-sectional survey was conducted among final-year pharmacy students in Iraq. The questionnaire covered demographics, AI knowledge, perceived benefits and challenges, and AI integration in education. Quantitative data were analyzed using descriptive statistics, Spearman correlation, and chi-square tests, while thematic analysis was applied to qualitative responses. Results: A total of 234 students participated, with 59.4% female and 77.8% aged 18–24 years. While 71.9% had prior AI exposure, only 14.5% had advanced AI knowledge. Though 51.1% viewed AI positively, 54.7% were uncertain about its role in clinical decision-making. AI’s key benefits included diagnostic accuracy (62.6%), time-saving (79.1%), and error reduction (61.5%), while major concerns involved job displacement (54.5%), lack of training (67.7%), and data reliability (38.4%). A positive correlation (p < 0.001) was found between AI knowledge and favorable attitudes, with students who had not attended AI-related workshops reporting higher self-perceived preparedness to integrate AI into future practice (p = 0.018). Conclusion: While students recognize AI’s potential, education gaps and practical limitations hinder adoption. Integrating AI training into pharmacy curricula and addressing ethical concerns are crucial to ensuring AI’s effective and balanced implementation in clinical practice.

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