Healthcare Providers’ Perceptions of How Artificial Intelligence Influences Provider-Patient Relationships in Saudi Arabian Hospitals: A Qualitative Study

Abstract

Background: Artificial intelligence (AI) is increasingly getting integrated into healthcare, with numerous promising benefits, including operation efficiency, decision support, and workflow optimization. However, its impact on provider–patient relationships remains unclear, particularly in Saudi tertiary hospitals where cultural norms, hierarchical structures, and patient expectations shape clinical interactions. Understanding healthcare providers’ perceptions is crucial to guide ethical, patient-centered AI implementation.

Purpose: This study aimed to explore healthcare providers’ perceptions of how AI affects provider–patient relationships in selected tertiary hospitals in Saudi Arabia.

Methods: A qualitative descriptive design was employed. Fifteen healthcare providers, including physicians, nurses, allied health professionals, and clinical technologists, were purposively recruited from tertiary hospitals. Data were collected through semi-structured interviews guided by three principal questions on AI use, interactions with patients, and ethical or practical concerns. Interviews were audio-recorded, transcribed verbatim, and analyzed using thematic analysis, following a structured coding and data reduction process.

Results: Four major themes emerged: (1) shifting dynamics of communication, where ai facilitated information delivery but sometimes disrupted interpersonal interaction; (2) trust and professional credibility, highlighting concerns about patients over-relying on ai and potential conflicts with clinician judgment; (3) balancing efficiency with human connection, emphasizing the need to preserve empathy despite AI-driven workflow improvements; and (4) transparency, accountability, and ethical concerns, including responsibility for AI-guided decisions, patient disclosure, and algorithmic bias. Participants underscored the importance of institutional policies, training, and governance to ensure AI complements rather than undermines relational care.

Conclusion and Recommendations: AI offers benefits for efficiency and clinical support but introduces relational and ethical challenges. Implementation should prioritize transparency, clinician training, patient communication, and equitable, context-sensitive governance. Future studies should examine long-term impacts on provider–patient relationships and patient outcomes.