Attitudes Towards AI in Healthcare Among University of Hail Health Sciences Students: A Qualitative Exploration

Abstract

Background: The adoption of Artificial Intelligence (AI) in healthcare continues to grow, promising more accurate diagnoses, greater efficiency and fewer human errors. Despite this trend, a critical gap remains in understanding how healthcare students-who represent the future workforce-perceive and accept these emerging technologies, including issues related to ethics, data security and the potential impact on patient care, particularly within the context of Saudi Arabia’s rapidly evolving healthcare sector. Objective: This study explores how health sciences students at the University of Hail view the integration of AI in clinical contexts, focusing on their willingness to adopt such tools-referred to as their “acceptance level”-and on how ethical and privacy concerns shape their attitudes. Methods: A qualitative case study design was adopted. Semi-structured individual interviews were conducted via Zoom from June to August 2024 with 18 participants, recruited from diverse health sciences programs (medicine, nursing, pharmacy, dentistry, public health and health informatics). The interview guide addressed students’ understanding of AI, perceived benefits and challenges, ethical considerations and the potential effects on their future professional roles. Data were analyzed using Braun and Clarke’s six-phase thematic analysis framework. Trustworthiness was ensured via member checking, an audit trail and reflexive journaling. Results: Participants generally recognized AI’s capacity to enhance efficiency and precision in healthcare tasks. Most conveyed optimism about the technology’s benefits, emphasizing improvements in workload management and diagnostic accuracy. Nevertheless, concerns about data privacy and over-reliance on algorithms emerged as major reservations, particularly given students’ limited clinical experience. Ethical considerations ranged from protecting patient confidentiality to ensuring that AI complements, rather than displaces, clinicians. Several interviewees also expressed a desire for AI-focused training in their academic curriculum. Conclusion: Health sciences students at the University of Hail anticipate AI’s transformative potential in healthcare but remain cautious about privacy breaches and diminished human oversight. These findings highlight the necessity for targeted education that addresses technical, ethical and practical challenges. By adopting a measured approach to AI implementation, future healthcare professionals may be equipped to leverage technology while maintaining high standards of patient care.

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